Pattern of Blood Usage Estimate Blood1 Dr Neelam Dhingra Coordinator Blood Transfusion Safety WHO, Geneva Estimate Blood Requirements - Search for a Global Standard Pattern of Blood

1

Dr Neelam Dhingra

Coordinator

Blood Transfusion Safety

WHO, Geneva

Estimate BloodEstimate Blood

Requirements Requirements --

Search for aSearch for a

Global Standard Global Standard

Pattern of Blood Pattern of Blood UsageUsage

Developed countries

� complex medical and

surgical procedures

� cardiac, vascular,

neuro, transplant

� trauma care

� cancer chemotherapy

� haematological

malignancies

Developing countries

Limited diagnostic & treatment

facilities

� complications during

pregnancy and childbirth

� severe childhood anaemia,

often resulting from malaria

or malnutrition

� trauma

� conflict, disasters, violence,

road-traffic accidents

Emergency Trauma Care Emergency Trauma Care

� Worldwide, >100 million people sustain

injuries each year and >5 million die

from violence and injury

� RTAs are the 2nd leading cause of

death and a leading cause of serious

injury for both sexes aged 5–29

� Uncontrolled bleeding accounts for

>40% of trauma related deaths

� Capacity to provide safe blood

transfusion - essential component of

Emergency Trauma Care Systems to

minimize death and disability in injured

patients

Maternal MortalityMaternal MortalityMaternal Mortality

� Globally, >530 000 women die each year during pregnancy,

childbirth or in PP period – 99% of them in the developing world

� 14 countries had MMRs of at least 1000, of which 13 are in the

SSA, where the lifetime risk of maternal death is 1 in 73,

compared with 1 in 7300 in rich countries

� Severe bleeding during delivery or after childbirth: commonest

cause of MM, contributing up to 44% of maternal deaths in Africa,

31% in Asia and 21% in Latin America and the Caribbean

� In most developing countries 50-80% of supplied blood is used for

obstetrics emergencies

� Blood transfusion: one of the eight signal functions of

Comprehensive Emergency Obstetric Care (EmOC) facilities

Blood SupplyBlood Supply

� Role of blood transfusion services

� provide equitable access to safe blood/blood

products for all patients who need it

� adjust supply to actual needs

� Shortages

� various reasons (lack of donors or well organized

donor programme, ↑↑↑↑ safety measures,…)

� periodic or continuous

� crucial for patients when no alternative is available

Estimating Blood Requirements Estimating Blood Requirements

� Important for planning a national blood programme

� Needs based programme - to satisfy the needs of a

country's health care system, equitably and timely

(routine and emergency)

� No global standard for estimating countries' needs for

blood/blood products, and estimates have to be made

for each country and each region

� Plan blood collection and donor recruitment

systematically, to avoid an excess or a shortage

2

Variables affecting demand and supplyVariables affecting demand and supply

� Geography, population and epidemiology

� Level and rate of development of health care

system

� Prevention: e.g. anaemia, malaria

� Diagnosis: e.g. haemophilia

� Treatment: e.g. advanced medical and

surgical procedures

� Location and accessibility of health care facilities

Epi Profile

Pop Needs Pop Demands

Clinical Competence

Clinical

Demand Transfusion

Production

Demand and SupplyDemand and Supply

Country's Need for Blood and Blood Country's Need for Blood and Blood

Products Products

� Balance between demand and supply is

needed

� Minimize wastage

� Avoid blood shortages

� Ensure appropriate use

Estimating blood needsEstimating blood needs

Transfusion vol.45 Oct 2005 Supplement

GeoGeo--population related Factorspopulation related Factors

� Size of the country

� Geographical characteristics

� Population

� Size

� Demographics – age distribution, growth

� Density/distribution in regions

� Epidemiology of diseases in the patients' population

(dependence on blood/blood products)

� Disasters (natural or man-made)

� Level & rate of development of health care

� Accessibility of patients to health care

� Diagnostic and treatment facilities

� Preventive public health measures

� Water, electricity, communication and transportation

systems

� Hospitals

� Number and location

� Total no. of hospital beds

� No. of hospitals/beds for specialized complex care

� New hospitals/ ↑ hospital beds

Health Care System related ParametersHealth Care System related Parameters

3

� Development and effectiveness of BTS to provide

safe blood/blood products to support regular and

specific transfusion needs

� Number of blood centres and level of coordination

� Assessment of services in each centre

� blood collected, blood processing, storage and

transport capacity

� % of blood separated into components

� shelf-life of blood/blood components

BTS BTS related Parameters (1 of 2)related Parameters (1 of 2)

� Degree of component preparation tailored to real need

and resources of a country

� What % of blood should be separated into

components?

� What to do with the excess plasma?

� Options for Fractionation – Contract / In-country

� Hospital blood stock management / inventory control

� Future needs, including the feasibility of using recovered

plasma for fractionation

� Future need for apheresis and / or autologous programme

BTS BTS related Parameters (2 of 2)related Parameters (2 of 2)

Clinical Blood UsageClinical Blood Usage Parameters Parameters

� National guidelines on blood usage

� Size of hospital (s) and number of patients

� No. and kind of procedures, deliveries, anaemia pts

� Clinical competence and experience of staff

� Training for hospital and blood bank staff

� Annual blood usage review (past, present and future) -

hospitals, blood components

� Different types of components needed

NBS Total Losses 2005/06

>2.2million donors attending

13.14

2.02

2.23

0.27

0

2

4

6

8

10

12

14

16

18

20

Per

10

0 A

tte

nd

ee

s

Time-Expiring at

NBS

Complete Donations

Not Validated

Incomplete Bled

Donations

Attendees Not Bled

NBS Donations 2005/06

>2.2million donors attending

0

10

20

30

40

50

60

70

80

90

100

Pe

r 1

00

Att

en

de

es

Time-Expiring at

NBS

Complete Donations

Not Validated

Incomplete Bled

Donations

Attendees Not Bled

Issued Red Cell

Michael Bowden 2006 Michael Bowden 2006

Complete donations not validated = testing losses (i.e. repeat reactives for microbiological markers, abnormal test results in grouping) plus processing losses.

These figures do not include time-expiry/wastage in hospitals which was of the order of 2.2%in therelevant period.

UK National Blood Service: overall efficiencyUK National Blood Service: overall efficiency

Historical PerspectiveHistorical Perspective (1 of 2)(1 of 2)

Advance health care system

� Need for cellular blood products can be met if number of units

donated annually correspond to 5% of population

� If at least 3% of the population is regular blood donors

(average annual donation of 1.5 to 2 ), all needs for cellular

products can be satisfied

If health care is not fully operational

� Need for blood should not relate to size of the population but

to other factors reflecting quality and extent of health service

Management of Blood Transfusion Services, WHO, 1989

Joint study WHO/IFRCRCS(1986)

� Average donation per 1000 population

Industrialized countries: 52

Middle-income countries: 10

Low-income countries: 1

� Donation/hospital admission ratio was 0.44, 0.33 and

0.25

� 2% donor population may be sufficient

� Blood requirement per bed per year 10-30

(Super-speciality - 30, Speciality - 20, General -10)

Historical PerspectiveHistorical Perspective (2 of 2)(2 of 2)

4

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

HDI values

Nu

mb

er

of

do

na

tio

ns /

10

00

pop

ula

tio

n

75%

of global population

High HDILow HDI Medium HDI

Donations/1000 populationDonations/1000 population

35%

of global blood collection

A total of 73 countries have donation rate of <1%

(< 10 donations/1000 population)

Average 2.3Range 0.4 – 7.5



WHOWHO--BSI/GDBS 2007BSI/GDBS 2007

Method 1Method 1

Method 1: based on previous usage

� Assess the number of units of blood used in a specified

period in a defined geographical area or population

� Analyse previous blood usage and requests for blood to

give an approximate indication of whether the demand

for blood is constant, increasing or decreasing

Blood UsageBlood Usage

� 120 countries report that a total of 51,400 hospitals

perform blood transfusions, serving a population of

around 3.6 billion

� Only 25 % hospitals performing transfusions in

developing countries and 33% hospitals in transitional

countries have a transfusion committee to monitor

transfusion practices; as compared to 88% hospitals in

developed countries

Method 2Method 2

Method 2: based on acute hospital beds

� Suitable for countries with modern hospital services

� Calculate 6.7 units of blood per acute hospital bed

per year (WHO, 1971)

Hospital Beds Model

� # hospital beds may provide an estimate of blood use

� Limitations:

� growing trend to provide OPD treatment (reduced

relevance on # hospital beds as indicator of health

care)

� # hospital beds not dependent on size of population

(not an appropriate indicator for estimating and

forecasting future demand)

� hospital beds may be used for patients with complex

disorders with different levels of blood consumption

Method 3Method 3

Method 3: based on population

� Used to estimate the number of units of blood needed to

meet a country’s blood requirements over one year

� Calculation is based on 2% of population requiring blood

per year

� Can be used to calculate the blood requirements of

individual regions or districts within the country

5

Population Based Model

� Makes it possible to:

� compare between countries or regions of

similar size

� project the trend in requirements in terms

of population trends

� paint a picture of the national situation

Method 3Method 3

Example

� For a country with a population of 10 million,

calculate as follows:

� 10 000 000 x 2% = 200 000 units of blood per

year or approximately 3850 per week

� A minimum of 100 000 donors will be needed if

each donor gives blood at least twice per year

Selecting a method to estimate Selecting a method to estimate

blood requirementsblood requirements

� Method 1 is the most practical where there is a

constant supply of blood

� Methods 2 and 3 can be useful where no data are

available or new established blood centre

1

Health Statistics and Informatics 3 February 2010

The Global Burden of Disease approach to comparable international statistics

Gretchen Stevens

Health Statistics and Informatics Department

Health Statistics and Informatics

Overview

A brief introduction to the Global Burden of Disease project

Issues in preparing comparable cross-national statistics

1. Selecting indicators and metrics

2. Correcting for bias in available data

3. Estimating and communicating uncertainty


Global burden of Disease (GBD)

A standardized framework for integrating all available information on mortality, causes of death, individual health status, and condition-specific epidemiology to provide an overview of the levels of population health and the causes of loss of health

• Consistent, comprehensive descriptive epidemiology

• Common metric or summary measure


GBD Principles

Quantities of interest are total events or states at the population level

Best available data used to make estimates

Corrections for major known biases to improve cross-population comparability

Comprehensive set of disease and injury causes –nothing is left out in principle

No blanks in the tables, only wider uncertainty intervals

Internal consistency used as a tool to improve validity


Leading Causes of Mortality and Burden of Diseaseworld, 2004

%

Ischaemic heart disease 12.2

Cerebrovascular disease 9.7

Lower respiratory infections 7.1

COPD 5.1

Diarrhoeal diseases 3.7

HIV/AIDS 3.5

Tuberculosis 2.5

Lung cancer 2.3

Road traffic accidents 2.2

Prematurity, low birth weight 2.0

%

Lower respiratory infections 6.2

Diarrhoeal diseases 4.8

Depression 4.3

Ischaemic heart disease 4.1

HIV/AIDS 3.8

Cerebrovascular disease 3.1

Prematurity, low birth weight 2.9

Birth asphyxia, birth trauma 2.7

Road traffic accidents 2.7

Neonatal infections and other 2.7

Mortality DALYs


Overview

A brief introduction to the Global Burden of Disease project

Preparing comparable international statistics




2


Three types of health statistics

Unadjusted statistics:

Adjusted statistics:

Predicted statistics:

derived directly from primary data collection

corrected for known biases

predicted using a statistical model, includes both forecasts and "farcasts"


What is meant by comparable statistics?

Key elements:

Quantities of interest are estimated at the population level

Corrections for major known biases

Estimates are made for every population

Adjusted and predicted statistics can be used for national and international priority-setting


Three issues to consider when generating comparable statistics





Selecting health indicator and metrics

• Meaningful health indicator

• Data are available or collectable

• Disease and risk factor indicators are preferably comparable across diseases/risk factors


Inputs & processes Outputs Outcomes Impact

Data

collection

Indicator

domains

Improved

health outcomes

& equity

Social and financial

risk protection

Responsiveness

Efficiency

Fin

an

cin

g

Infrastructure;

ICT

Health

workforce

Supply chain

Information

Intervention

access &

services

readiness

Intervention

quality, safety

Coverage of

interventions

Prevalence risk

behaviours &

factorsGo

ve

rna

nce

Administrative sourcesFinancial tracking system; NHA

Databases and records: HR,

infrastructure, medicines etc.

Policy data

Facility assessments Population-based surveys

Coverage, health status, equity, risk protection, responsiveness

Clinical reporting systemsService readiness, quality, coverage, health status

Civil registration

Framework for monitoring health systems






3


Bias in height and weight reported over the telephone

NHANES – a national health examination survey –measures height and weight of a national sample

BRFSS – a telephone health survey – asks about height and weight for state samples

Comparing these data:

• Women underreport weight on the phone

• Men overreport height on the phone

Ezzati et al. predicted unbiased state rates of overweight and obesity using NHANES to correct BRFSS


Self-reported and corrected obesity

Source: Ezzati, 2006







Population-based hearing loss studies


The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health

Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted

lines on maps represent approximate border lines for which there may not yet be full agreement.

© WHO 2002. All rights reserved


Uncertainty in health estimates

Some sources of uncertainty:

• Input uncertainty (especially bias)

• Model uncertainty (functional form, covariates)

• Parameter uncertainty

Estimating uncertainty in a consistent way across diseases and risk factors has had limited success

Uncertainty is a major focus of the new round of estimates


Predicted hearing loss prevalence

Prevalence

of moderate hearing loss

(41+dB)

Age

Western Europe Eastern Europe

4


Summary

Choice of exposure metric may need to be flexible to meaningful and/or accommodate data availability• There is often a trade-off between data

quality and population-based data

Modeling approaches can correct for missing or biased data

Assessing and communicating uncertainty is a continuing challenge



Data

collection

Indicator

domains

Analysis

&

synthesisCommunication

& use

Improved

health outcomes

& equity


risk protection

Responsiveness

Efficiency

Fin

an

cin

g

Infrastructure;

ICT

Health

workforce

Supply chain

Information

Intervention

access &

services

readiness

Intervention

quality, safety

Coverage of

interventions

Prevalence risk

behaviours &

factors

Go

ve

rna

nce

Administrative sourcesFinancial tracking system; NHA

Databases and records: HR,

infrastructure, medicines etc.

Policy data

Facility assessments Population-based surveys

Coverage, health status, equity, risk protection,

responsiveness

Clinical reporting systemsService readiness, quality, coverage, health status

Civil registration

Data quality assessment; Estimates and projections; In-depth studies; Use of research results;

Assessment of progress and performance of health systems; evaluation

Targeted and comprehensive reporting; Regular country review processes; Global reporting

FrameworkM&E of health systems strengthening


Why calculate internationally comparable statistics?

Global health can be characterized by:

• Sparse, sometimes inconsistent data, especially where burden is highest

• Insufficient evidence-based priority-setting or evaluation

• Resource constraints

Researchers can use data and experiences from multiple settings to correct for biases in country data or to make estimates when they are not available



Indicator

domains

Improved

health outcomes

& equity


risk protection

Responsiveness

Efficiency

Fin

an

cin

g

Infrastructure;

ICT

Health

workforce

Supply chain

Information

Intervention

access &

services

readiness

Intervention

quality, safety

Coverage of

interventions

Prevalence risk

behaviours &

factorsGo

ve

rna

nce

FrameworkM&E of health systems strengthening

Health Statistics and Informatics Health Statistics and Informatics

World Health Organization 12 April, 2010

1

WHO Experts' Consultation on

Estimation of Blood Requirements03 February 2010

Geneva.

Dr Peter OlumeseGlobal Malaria ProgrammeWHO/HQ, Geneva

Requirements of Blood & Blood

Components for Management of Malaria

Requirements of Blood & Blood

Components for Management of Malaria

Requirements of blood for management of malaria. Expert Consultation, Geneva, 03 Feb 20102 |

Global malaria burdenGlobal malaria burden

� 4 species of human malaria parasites

– Plasmodium falciparum, P. vivax, P. malariae, P. ovale

– and few recent infections with the simiarn parasite P. knowlesi

� Estimated 243 (152-387) million malaria patients in 2008

� Estimated 863 (610-1212) thousand malaria deaths in 2008

� 90% of deaths and 85% of cases occur in Africa south of the Sahara -mainly among children under 5years of age


Clinical Disease and EpidemiologyClinical Disease and Epidemiology

� The nature of malaria clinical disease depends greatly on the background level of the acquired protective immunity, a factor which is the outcome of the pattern and intensity of malaria transmission in the area of residence.

� Where the transmission of malaria is “stable”,entomological inoculation rate [EIR] >10 per year), partial immunity to the clinical disease and to its severe manifestation is acquired early in childhood.

– severe manifestations mainly in the very young before acquisition of immunity

� In areas of "unstable" malaria, the rates of inoculation fluctuate greatly over seasons and years. Entomological inoculation rates are usually < 5 per year and often < 1 per year. This retards the acquisition of immunity.

– all age groups (adults and children alike), are at high risk of progression to severe malaria if untreated.


Malaria Control Technical Strategies

…..evidence-based actions

Malaria Control Technical Strategies

…..evidence-based actions

� Early diagnosis and prompt treatment with effective

medicines

� Insecticide-treated nets (ITNs), Indoor Residual Spraying

(IRS), and other vector-control methods

� Intermittent preventive treatment in pregnancy (IPTp)

� Emergency and epidemic preparedness and response

� Intermittent preventive treatment in infancy (IPTi)


Severe malariaSevere malaria

P. falciparum asexual parasitaemia and no other obvious cause of symptoms, the presence of one or more of the following clinical or laboratory features classifies the patient as severe malaria

� Clinical features: – impaired consciousness or unrousable coma– prostration, i.e. generalized weakness so that the patient is unable walk or sit up without assistance – multiple convulsions – more than two episodes in 24 h– deep breathing, respiratory distress (acidotic breathing)– circulatory collapse or shock, systolic blood pressure < 70 mm Hg in adults and < 50 mm Hg in children– clinical jaundice plus evidence of other vital organ dysfunction– Haemoglobinuria

– abnormal spontaneous bleeding (DIC)– pulmonary oedema (radiological)

� Laboratory findings:– hypoglycaemia (blood glucose < 2.2 mmol/l or < 40 mg/dl) – metabolic acidosis (plasma bicarbonate < 15 mmol/l)

– severe normocytic anaemia (Hb < 5 g/dl, packed cell volume < 15%)– Haemoglobinuria

– hyperparasitaemia (> 2%/100 000/µl in low intensity transmission areas or > 5% or 250 000/µl in areas of high stable malaria transmission intensity)

– hyperlactataemia (lactate > 5 mmol/l)– renal impairment (serum creatinine > 265 µmol/l).


Malaria AnaemiaMalaria Anaemia

� Anemia (hemoglobin level < 11 g/dL) remains one of the

most intractable public health problems in malaria-

endemic countries of Africa.

� and has serious consequences as severe anemia

(hemoglobin level < 5g/dL) is associated with an

increased risk of death


2


Severe Malaria AnaemiaSevere Malaria Anaemia

� Hemoglobin less than 5g/dl (PCV less than 15%)

� Features of anaemic heart failure (even if PCV is >15%)

� In the presence of P.falciparum parasiteamia


The burden of malarial anaemiaThe burden of malarial anaemia

� It affects more than half of all pregnant women and

children less than five years old

� Each year in children < 5 years…

– 1.4 - 5.7 million cases

– 190,000 - 974,000 deaths

– Case fatality rate of severe anaemia (13.4 - 17.2%)

– Highest mortality in infants


Management of

Severe Malaria

–Specific antimalarial treatment

–Adjunctive therapy and supportive care


Antimalarial treatment Antimalarial treatment

� Any of the following antimalarial medicines are

recommended

3

– Artesunate (i.v. or i.m)

– artemether (i.m.)

– artemotil (i.m)

– quinine (i.v. infusion or

i.m. injection).


Management of severe anaemiaManagement of severe anaemia

� The need for blood transfusion must be assessed with great care in each individual child. Not only packed cell volume or haemoglobin concentration, but also the density of parasitaemia and the clinical condition of the patient must be taken into account.

� In general, a packed cell volume of 12% or less, or a haemoglobin concentration of 4 g/dl or less, is an indication for blood transfusion, whatever the clinical condition of the child.

– transfusion (10 ml of packed cells or 20 ml of whole blood per kg of body weight).

� In children with less severe anaemia (i.e. packed cell volume 13–18%, Hb 4–6 g/dl), transfusion should be considered for high-risk patients with any one of the following clinical features:

– respiratory distress (acidosis); – impaired consciousness;

– hyperparasitaemia (>20%).

� The sicker the child the more rapidly the transfusion needs to be given.


Other indications for blood and blood

products


products

� Disseminated intravascular coagulation, complicated by

clinically significant bleeding, e.g. haematemesis or

melaena, occurs in fewer than 10% of patients.

– It is more common in non-immune patients with imported malaria in the temperate zone

� Treatment

– transfuse fresh blood, clotting factors or platelets as required.


3



products


products

� Hperparasitaemia– If parasitaemia exceeds 10% in severely ill patients, especially

those deteriorating after optimal chemotherapy, exchange transfusion with screened blood should be considered where facilities are available

– Exchange blood transfusion

– There have been many anecdotal reports and several series claiming benefit for exchange blood transfusion in severe malaria but no comparative trials.

– There is no consensus on whether it reduces mortality or how it might work, so there is no global recommendation on its us


Challenges of blood transfusionChallenges of blood transfusion

� Wastage

– Non availability of paediatric blood bags

– Use of whole blood in place of packed cells or other specific blood components (e.g platelets)

– Unnecessary transfusions

• Inadequate diagnostics facilities

• Blood storage facilities –proper blood bank facilities

15 |

Impact of the scale up malaria control measures in Africa

Impact of the scale up malaria control measures in Africa

SME/MP/WHO Surveillance, 2008

12 April 2010

Comparison of trend patterns of inpatient malaria cases and deaths, by year, all ages, 2000/1-2006/7. Eritrea,

Rwanda, Sao Tome and Principe, Zambia, and Zanzibar.

Rwanda

0

2000

4000

6000

8000

10000

12000

2000 2001 2002 2003 2004 2005 2006

Cases

0

20

40

60

80

100

120

140

Death

s

Inpatient cases

Inpatient deaths

Eritrea

Sao Tome and Principe Zambia Zanzibar

0

5000

10000

15000

20000

25000

2000 2001 2002 2003 2004 2005 2006 2007

Cases

0

50

100

150

200

250

300

350

400

450

Death

s

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2001 2002 2003 2004 2005 2006

0

50

100

150

200

250

300

350

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

2001 2002 2003 2004 2005 2006

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

0

2000

4000

6000

8000

10000

12000

2000 2001 2002 2003 2004 2005 2006 20070

50

100

150

200

250

300

350

400

450

12 April 2010

Figure 2a. Malaria and non-malaria in- and out-patient cases, children <5 years old, January to October 2001-2007, Rwanda. LLIN = long-lasting insecticidial nets, ACT = artemisinin-based

combination therapy medicines.

�

�

�

�

�

�

�

�

�

�

��

�

�2001 2002 2003 2004 2005 2006 200701000200030004000500060007000800090001000002000400060008000100001200014000

Malaria in-patient cases Malaria out-patient laboratory-confirmed cases

Year� Malaria in-patient cases� Malaria out-patient laboratory-confirmed cases

�

�

�

�

�

�

�

�

�

�

�

�

�

�

2001 2002 2003 2004 2005 2006 20070100020003000400050006000700080009000010000200003000040000500006000070000

Non-malaria in-patient cases Non-malaria out-patient casesYear� Non-malaria in-patient cases� Non-malaria out-patient cases

LLIN,

ACT

12 April 2010

Inpatient malaria cases

Inpatient malaria deaths

Outpatient slide

positivity rate (SPR)

Rainfall

Inpatient and outpatient indicators decline markedly, to low levels in 2006 and 2007, MRC research hospital and clinic, Fajara, Gambia

Source: Ceesay SJ et al. Changes in malaria indices between 1999 and 2007 in The Gambia: a retrospective analysis. Lancet 2008; 372:1545-54.

74% 100%

73%


4


Combined Approved Interventions and the ImpactCombined Approved Interventions and the Impact

Positivity

rate

Prevalence

rate

12 April 2010

Source: Ceesay SJ et al. Changes in malaria indices between 1999 and 2007 in The Gambia: a retrospective analysis. Lancet 2008; 372:1545-54.

Hemoglobin rises in 2005-2007 and blood transfusions in children

decrease to near zero in 2007, Sibanor, Gambia


ConclusionsConclusions

� The use of blood and blood products remains an essential component of the management of severe malaria

� Estimating the requirement remains a challenge especially now in the light of the reducing burden of malaria due to rapid scale up of malaria control interventions

� Urgent need to optimise the use of blood and blood products especially in very young children with severe malaria anemia.


Thank You


1

WHO Experts' Consultation on Estimation of Blood RequirementsGeneva Feb 3-5, 20101 |

Requirements of blood &

blood components in

maternity care

Matthews MathaiDepartment of Making Pregnancy Safer

Requirements of blood &

blood components in

maternity care

Matthews MathaiDepartment of Making Pregnancy Safer


OutlineOutline

� When are blood and blood components used in maternity

care?

� How often are blood and blood components required?

� What are the challenges in estimating requirements?


Common indicationsCommon indications

� To correct hypovolemia resulting from acute haemorrhage

– Antepartum and postpartum haemorrhage

– Ruptured ectopic pregnancy, uterine rupture and other genital lacerations

– Post abortion

� To treat severe anaemia

– With cardiac failure

– Before or during surgery


Other indicationsOther indications

� In newborns

– Top up transfusions in preterm infants

– As part of treatment of sepsis

– For hypovolemia resulting from trauma

– Exchange transfusion

� To correct coagulation failure

– Placental abruption

– Retained products

– Sepsis

– Amniotic fluid embolism


OutlineOutline


care?




WHO analysis of causes of maternal death: a systematic review

Lancet 367: 1066-1074, 2006


2


WH

O a

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a s

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: 1

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We need to have a

strategic approach to achieve our

goals

WHO analysis of causes of maternal death: a systematic reviewLancet 367: 1066-1074, 2006


2.1%

(0.0-5.9)

7.7%

(0.0-15.1)

11.6%

(0.0-13.0)

9.7%

(6.3-12.6)

Sepsis

16.1%

(6.7-24.3)

25.7%

(7.9-52.4)

9.1%

(2.0-34.3)

9.1%

(3.9-21.9)

Hypertension

13.4%

(4.7-34.6)

20.8%

(1.1-46.9)

30.8%

(5.9-48.5)

33.9%

(13.3-43.6)

Haemorrhage

282311777160894508Maternal deaths

510118Data sets

Developed

countries

LACAsiaAfrica




33%334552001MC W Africa

19%695922001Zimbabwe

28%7293491998Zambia

10%15031212002, 2003South Africa

23%529761988Tanzania

22%690872002Senegal

30%845852000Egypt

16%5101431997DR Congo

HaemorrhageMMRMaternal deathsYearCountry


Estimated blood transfusion requirements Estimated blood transfusion requirements

Number per 1000 deliveries

� Antepartum haemorrhage 7.26

� Postpartum haemorrhage 12.5

� Puerperal sepsis 8.0

Estimated global resources needed to attain universal coverage of maternal and newborn health services

• B Johns, K Sigurnbjörnsdottir, H Fogstad, J Zupan, M Mathai, T T-T Edejer

• Bull WHO 2007; 85: 256-263


WHO Global Surveys on Maternal and

Perinatal Health

WHO Global Surveys on Maternal and

Perinatal Health

� Facility based survey conducted between 2004 and 2008

� 24 countries in Latin America, Africa and Asia

� Analysed mode of delivery, maternal and perinatal

outcomes

� Varying caesarean delivery rates between and within

regions and countries


WHO Global Survey on Maternal and

Perinatal Health


Perinatal Health

Blood transfused in 1.58% of births

� Spontaneous vaginal delivery 1940/205303 (0.94)

� Operative vaginal delivery 198/7287 (2.72)

� Antepartum CS - no indications 14/1826 (0.77)

� Intrapartum CS - no indications 26/1063 (2.45)

� Antepartum CS with indications 887/26876 (3.3)

� Intrapartum CS with indications 1467/43815 (3.35)


3



Perinatal Health


Perinatal Health

Near miss study in LAC (n=97095 births)

� Vaginal bleeding 22 in every 1000 births

� Blood transfusion 13.8 in every 1000 births


Source: Macro International Inc, 2010. MEASURE DHS STATcompiler. http://www.measuredhs.com, February 2 2010.

Delivery complication: Excessive bleeding% of live births in the last five years with excessive bleeding by region

34.4

17.5

13.2

3.8

7.3

16.4 17.2

10.7

18.4

7.2 7.4 6.8

22.3

5.4

25.7 25.1

7.4

32

28.3

34.6

0

5

10

15

20

25

30

35

40

Chad 1

996-9

7

Tanzania

1996

Zam

bia

1996

Egypt

1995

Jord

an 1

997

Turk

ey 1

998

Yem

en 1

997

Bangla

desh 1

99

9-2

000

Bangla

desh 1

99

6-9

7

Indonesia

1997

Indonesia

1994

Phili

ppin

es 1

998

Bolivia

1998

Bra

zil

1996

Colo

mbia

1995

Dom

inic

an

Republic 1

996

Guate

mala

1998-

99

Guate

mala

1995

Nic

ara

gua 1

998

Peru

1996

Sub-Saharan Africa North Africa/West

Asia/Europe

South & Southeast Asia Latin America & Caribbean

% o

f live b

irth

s in t

he last

five y

ears


OutlineOutline


care?




ChallengesChallenges

� Limited data

– Amount

– Blood or blood components

� Estimated need versus actual transfusion requirements

� Other issues

– Epidemiology – Malaria, helminthiasis, HIV

– Recognising the need for blood transfusion

– Intervention rates

– Access to care


Anaemia in among pregnant women Proportion of pregnant women age 15-49 with anaemia. Anaemia

includes mild anaemia (haemoglobin count d/dl 10.0-10.9), moderate anaemia (haemoglobin count d/dl 7.0-9.9), and severe anaemic

(haemoglobin count d/dl below 7.0)

26.9 25.7 30.3 27.3 30.6 31.2 30.8 33.224.6 25.8 22.7 23.4

18.8 19.6 20.9 22.527.4 28.8

22.728 23.5 26.5

17.721.8

16.5 13.119.7

14.7 15.4

44.239.8

3838.2 35.4 30.6 28 26.7

32.7 30.632.8 30.3

31.4 27.4 27.7 22.918.1 15.6

19.1 12.516.3 11.6

18.8 14.719.5

16.914.2

135.8

5.9

5.1 1.5 4 2.32.6

2.7 1.2 2.7 2.2 2.7 3.40.7 3.3 1.5

1.9 1.5 0.20.7 0 0.4 0.6 0.5 0.1 0

5 0.33

0.2

0

10

20

30

40

50

60

70

80

90

Ma

li 2

00

6

Se

ne

ga

l 2

00

5

Co

ng

o (

Bra

zz

av

ille

) 2

00

5

Gu

ine

a 2

00

5

Bu

rkin

a F

as

o 2

00

3

Ug

an

da

20

06

Nig

er

20

06

Gh

an

a 2

00

3

Co

ng

o D

em

oc

ratic

Re

pu

blic

20

07

Ind

ia 2

00

5-0

6

Ta

nz

an

ia 2

00

4-0

5

Ca

mb

od

ia 2

00

5

Ca

me

roo

n 2

00

4

Ha

iti 2

00

5-0

6

Ma

da

ga

sc

ar

20

03

-04

Ma

law

i 2

00

4

Zim

ba

bw

e 2

00

5-0

6

Az

erb

aija

n 2

00

6

Ne

pa

l 2

00

6

Mo

ldo

va

20

05

Sw

az

ilan

d 2

00

6-0

7

Arm

en

ia 2

00

5

Bo

livia

20

03

Jo

rda

n 2

00

7

Le

so

tho

20

04

Rw

an

da

20

05

Eg

yp

t 2

00

5

Eth

iop

ia 2

00

5

Ho

nd

ura

s 2

00

5-0

6 %

of

pre

gn

an

t w

om

en

wh

o a

re a

na

em

ic Mild anemia (%) Moderate anemia (%) Severe anemia (%)


5 - 20%

81 -100 %

41 - 60%

No data available

21 - 40%

61 - 80%

Data source: proportion of births attended by a skilled health worker 2008 updates, WHO

The name as shown and the designations used in this map do not imply official endorsement off

acceptance by the United Nations.

Gaps in skilled care

In Ethiopia, only 6% of women deliver with skilled professionals.

In Bangladesh, only 18% of women deliver with skilled professionals. Wealthy women had 11 times higher access to skilled care than their poor counterparts.

In China, women in the least affluent areas are twice as likely to deliver without a trained health worker as women in large cities.

While Colombia has very high overall levels of trained health workers, over a quarter of the poorest will still deliver without skilled professionals


4


Less than 5 %

5-15 %

More than 15 %

No data available

Percentage of births delivered by Caesarean section

In Nepal, only 0.8% of poorest women have

access to C-section compared to 12% of the

most wealthy women.

In Indonesia, women in urban areas are

three times more likely to have access to C-section than their rural counterparts.

In Nigeria, while 70% of births occur in rural

areas, only 1% of women in rural areas have

access to C-section.

Data source: Demographic and Health Survey

The name as shown and the designations used in this map do not imply official endorsement off acceptance by the United Nations. WHO Experts' Consultation on Estimation of Blood Requirements

Geneva Feb 3-5, 201020 |

Source: Macro International Inc, 2010. MEASURE DHS STATcompiler. http://www.measuredhs.com, February 2 2010.

Blood transfusion% of births for which mothers received a blood transfusion

Nepal 2006

2.9

0.1

1.4

0.40.6

0.30.1

0.81

0.8

0.4

0.1

0.70.5 0.4

1.3

0

0.5

1

1.5

2

2.5

3

3.5

Health

facility

Els

ew

here

Urb

an

Rura

l

Poore

st

Poore

r

Mid

dle

Ric

her

Ric

hest 1

2 to 3

4 to 5 6+

<20

20-3

4

35-4

9

Place of

delivery

Residence Wealth quintile Birth order Mother's age at

birth

% o

f birth

s

1

Requirements of blood

and blood components for trauma care

Pablo Perel

To know blood requirements

• How frequent is trauma?

• How frequent is bleeding in trauma patients?

• Which patients should receive transfusions?

• Which blood components should they receive?

In addition

• CRASH-2 Trial • How frequent is trauma?





Injury related mortality*, WHO Regions, 2000Africa Americas Eastern

MediterraneanEurope South-East Asia Western Pacific

HIC† LMIC‡ HIC LMIC HIC LMIC India Other LMIC HIC China Other LMIC118.8 53.8 76.2 51.1 70.4 47.6 131.5 96.9 75.0 56.2 51.5 78.4

* Rate per 100 000 population †High income countries ‡Low/middle income countries

Global injury-related Mortality

The boundaries and names shown and the designations used on this map do not imply the expression of any

opinion whatsoever on the part of the World Health Organization concerning the legal status of any country,

territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on

maps repre sent approximate border lines for which there may not yet be full agreement.

© WHO 2002. All rights re served

No data120 - 131.1

95.0 - 119.9

70.0 - 94.9

45.0 - 69.9

Legend*

Deaths DALYs

1990 rank 2020 rank 1990 rank 2020 rank

Road Traffic Injuries 9 6 9 3

Self Inflicted Injuries 12 10 17 14

Interpersonal Violence 16 14 19 12

War 20 15 16 8

If current trends continue, road traffic and

intentional injuries will rank in the 15 leading

causes of death and burden of disease.

If current trends continue, road traffic and

intentional injuries will rank in the 15 leading

causes of death and burden of disease.

Rankings of Deaths & DALYs: 1990 - 2020

2

Reference: Patton GC, et al. Global patterns of mortality in young people: a systematic analysis of population health data. Lancet. 2009 Sep 12;374(9693):881-92.

Ten most common causes of death in young people (10-24)






Exsanguination CNS injury

Organ failureOther

45% 41%

10%4%

Reference: Sauaia A et al. Epidemiology of trauma deaths: a reassessment. J Trauma 1995;38:185-193

In-hospital trauma deaths Transfusion rates in trauma patients

Country Source Number of patientsTransfusion rateMassive transfusion

United Kingdom Registry (TARN) 28,703 3.4% 0.5%

GermanyRegistry

(DGU)2,475 54% 17.1%

US Trauma Centre 5,645 8% 3%

Israel Trauma Centre 986 33% 4.7%

- Maegele, M Changes in transfusion practice in multiple injury between 1993 and 2006: a retrospective analysis on 5389 patients from the German Trauma Registry. Transfusion Medicine. 19(3):117-124, June 2009.- Como JJ et al Blood transfusion rates in the care of acute trauma. Transfusion. 2004 Jun;44(6):809-13.- Soffer, D et al. Usage of Blood Products in Multiple-Casualty Incidents: The Experience of a Level I Trauma Center in Israel. Archives of Surgery. 143(10):983-989, October 2008.






Recommendation 19

“We recommend a target Hb of 7

to 9 g/dl (1C)”

Crit Care. 2007;11(1):R17.

3

Reference: Hill S Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2002;(2):

30 days mortality

Transfusion threshold Red cell transfusions

Mortality in patients who declined blood transfusions

14

Carson JL et al. Mortality and morbidity in patients with very low postoperative Hb levels who decline blood transfusion Transfusion. 2002

Jul;42(7):812-8.

Red cell transfusionsMassive Bleeding






Blood components

In stable patients (European Guideline)FFP if PT > 1.5

Platelets if <50 x 109

In patients with massive bleeding Plasma:RBC ratio (1:3)

Trauma exsanguination protocol (1:1)

(Cotton, BA et al. J. of Trauma-64(5):1177-1183, May 2008)

however, all of the studies are observational(Snyder C The Relationship of Blood Product Ratio to Mortality: Survival Benefit or

Survival Bias? Journal of Trauma66(2):358-364, February 2009)

How frequent is trauma?

How frequent is bleeding in trauma patients?

Which patients should receive transfusions?

Which blood components should they receive?


4

blood loss

Point at which benefits of transfusion exceeds harms

Fre

qu

en

cy

Point at which benefits of transfusion exceeds harms

blood loss

Fre

qu

en

cy

Point at which benefits of

transfusion exceeds harms

blood loss

Fre

qu

en

cy

Risk will be different according to the region

What do we know about interventions that

can shift the curve ?

Cochrane reviews of blood sparing

interventions (surgery)

1)Hill S, Carless PA, Henry DA, Carson JL, Hebert PPC, Henderson KM, McClelland B. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. CDSR 2000 Issue 1.

1)Lin Y, Stanworth S, Birchall J, Doree C, Hyde C. Recombinant factor VIIa for the prevention and treatment of bleeding in patients without haemophilia. CDSR 2007, Issue 2

1)Carless PA, Henry DA, Anthony DM. Fibrin sealant use for minimising peri-operative allogeneic blood transfusion. CDSR 2003 Issue 1.

1)Carless PA, Henry DA, Moxey AJ, O'Connell D, Brown T, Fergusson DA. Cell salvage for minimising perioperative allogeneic blood transfusion. CDSR 2006 Issue 4

1)Henry DA, Carless PA, Moxey AJ, O'Connell D, Stokes BJ, McClelland B, Laupacis A, Fergusson DA. Anti-fibrinolytic use for minimising perioperative allogeneic blood transfusion. CDSR 2007 Issue 4.

Favours treatment

Favours control

Number exposed to allogeneic bloodRR (95% CI), random effects

5

0 0.4 0.8 1.2 1.6 2.0

Blood units

1.1 (0.6-1.6)TXA

Blood units saved

Effects of TXA

RR (95% CI)

Antifibrinolytic better Antifibrinolytic worse

0 0.4 0.8 1.2 1.6 2.0

TXA 0.67 (0.41-1.09)

Re-operation

Effects of TXA

TXA

RR (95% CI)

Antifibrinolytic better Antifibrinolytic worse

0 0.4 0.8 1.2 1.6 2.0

0.60 (0.32-1.12)

Mortality

Effects of TXA

Outcome Tranexamic Acid

RR 95% CI

Myocardial Infarction 0.96 0.48-1.90

Stroke 1.25 0.47-3.31

Deep venous thrombosis 0.77 0.37-1.61

Renal failure 0.73 0.16-3.32

No evidence of adverse effects for tranexamic acid

Adverse effects of tranexamic acid

• Bleeding is a leading cause of trauma death

• Antifibrinolytics reduce blood loss after surgery

• A simple intervention like TXA could prevent thousands

of trauma deaths and transfusion associated infections

A large randomised controlled trial among trauma

patients with significant haemorrhage, of the

effects of antifibrinolytic treatment on death and

transfusion requirement

Rationale for the CRASH-2 Participating countries

6

Number of patients per country

Results I Results II

Characteristics of patients included

N %

Gender Male 15,932 83.75

Female 3,091 16.25

Age categories

<25 5,320 27.97

25-34 5,720 30.07

35-44 3,573 18.78

>44 4,410 23.18

Hours since injury

<1 1,791 9.41

1 to 3 10,963 57.63

>3 6,269 32.95

Results III

Mortality and transfusion practices

Results IV

Outcomes by subgroup – Systolic blood pressure

Mean blood units

Results VII

Outcomes by subgroup – Type of injury

Mean blood units

Results VIII

Outcomes by region

Region Mortality Transfusion Units

transfused

Total

patients

Africa 0.23 0.44 2.67 2,317

South East Asia 0.16 0.58 4.75 5,256

Western Pacific 0.15 0.72 12.30 74

Europe 0.13 0.33 10.24 2,127

Americas 0.15 0.51 7.65 5,425

Eastern Mediterranean 0.09 0.53 3.81 2,737

7

Results IX

Outcomes and units transfused by region according to subgroup

AFRICA Systolic Blood Pressure

>89 76-89 <76

Mortality 16 31 43

Mean no of units 2.5 2.7 2.9

SOUTH EAST ASIA

Mortality 13 17 35


WESTERN PACIFIC

Mortality 8 24 0


EUROPE Systolic Blood Pressure

>89 76-89 <76

Mortality 7 14 42


AMERICAS

Mortality 9 19 32


EASTERN MEDITERRANEAN

Mortality 4 9 24


Traumatic bleeding (CRASH-2 trial – completed)

Postpartum bleeding (WOMAN trial – in progress)

GI bleeding (in preparation)

If tranexamic acid also reduces blood loss in these conditions

then could have a substantial impact on global demand for

blood.

Tranexamic acid and blood loss

www.crash2.lshtm.ac.uk www.woman.lshtm.ac.uk

World Health Organization 12 April 2010

1

1 |

Nutritional anaemias: physiological

and public health considerations

Nutritional anaemias: physiological

and public health considerations

Luz Maria de Regil, PhD, MSc

Epidemiologist, Micronutrients Unit

Department of Nutrition for Health and Development

Experts' Consultation on Estimation of Blood RequirementsGeneva, 03-05 Feb, 2010

2 |

AnaemiaAnaemia

A condition in which the number of red blood cells or their

oxygen-carrying capacity is insufficient to meet physiologic

demands. Such demands varies by age, gender, altitude, smoking,

and pregnancy status.

Causes: diet reduced in nutrients/low bioavailability, chronic

inflammation, parasitic infections, and inherited disorders of

haemoglobin structure.

WHO

3 |

AnaemiaAnaemia

Microcytic Normocytic Macrocytic

Iron Reticulocytes Megaloblasts

Low High Low High Yes No

Sideroblasts

No Yes

iron deficiency

thalasse

miasidero

blastic

anaemia

aplasticanaemia

Leukaemia

haemolytic

disease

transfusion

reaction

vitamin

B12

anaemia

folic acid

anaemia

hepatic

disease

haemolytic

anaemia

Low High

Reticulocytes

Adapted: Casanueva et al, 2008

4 |

AnaemiaAnaemia




Sideroblasts

No Yes

iron deficiency

thalasse

miasidero

blastic

anaemia

aplasticanaemia

Leukaemia

haemolytic

disease

transfusion

reaction

vitamin

B12

anaemia

folic acid

anaemia

hepatic

disease

haemolytic

anaemia

Low High

Reticulocytes

5 |

Nutritional anaemiasNutritional anaemias

DNA synthesisThiamine

DNA and RNA synthesisFolic acid

DNA and RNA synthesisVitamin B12

Hb synthesisIron

Hb synthesis: alcoholismPyridoxine

Ceruloplasmin: ferric to ferrous ironCopper

Iron mobilizationVitamin C

Lysis of membranesVitamin E

Effect onEffect onNutrientNutrient

6 |

Iron deficiency anaemiaIron deficiency anaemia

0

20

40

60

80

100

120

5 10 15 20 30 40 50 60 70 80

Prevalence of anaemia (%)

Pre

vale

nce o

f ir

on

defi

cie

ncy

(%)

w/o anaemia

Anaemia

Source: WHO/ UNICEF / UNU. Iron deficiency anaemia: Assessment, prevention and control, a guide for programme managers. Geneva ,WHO, 2001.


2

7 |

!!

!

!

Category of public health significance(anaemia prevalence)

Normal (<5.0%)

Mild (5.0-19.9%)

Moderate (20.0-39.9%)

Severe (≥40.0%)

No Data

293 million children under 5 are anaemic

Source: WHO/CDC. Worldwide prevalence of anaemia 1993-2005. WHO Global Database on Anaemia. Geneva, World Health Organization, 2008.

8 |

Iron deficiency: health implicationsIron deficiency: health implications

� Total body iron: 3-5 g

� Adequate growth and development

� Immunity

� Cognition and development– attention span, concentration, memory, learning ability– muscle function and manual dexterity, behaviour, social

interaction

� Work productivity

� Reproductive performance

� Raising of other metals levels

9 |

Iron deficiency: health implicationsIron deficiency: health implications

Source: WHO Global burden of disease, 2009

10 |

Cut off pointsCut off points

<8080-109110-129<130Men (above 15 years of age)

<7070-99100-109<110Pregnant women

<8080-109110-119<120

Non-pregnant women (above 15 years of age)

<8080-109110-119<120Children 12-14 years

<8080-109110-119<115Children 5-11 years

<7070-99100-109<110Children 6 – 59 months

SevereSevereModerateModerateMildMildAnaemiaAnaemiaPopulationPopulation

Haemoglobin g/LHaemoglobin g/L

Source: WHO, VMNIS, 2010

11 |

AltitudeAltitude

� In addition to a diet with low iron/poor bioavailability

Altitude (m)

Incre

ase i

n H

b(m

g/L

)

12 |

SmokingSmoking

+ 0.72 packets/day

+ 0.51-2 packets/day

+ 0.3½-1 packet/day

+ 0.3Smoker

0Non smoker

HaemoglobinHaemoglobin

Source: WHO, VMNIS, 2010


3

13 |

15 20 25 30 35 40

RBC

Fetus

1

2

3

4

Iro

n n

ee

ds

(mg

/ d

ay

)

Fe losses

Weeks of pregnancy

PregnancyPregnancy

800mg

Source: Viteri

14 |

Increased demandsIncreased demands

2.10S. haematobium (severe)

0.16T. trichuria (mild)

Other parasitic infections

2.30A. duodenale

1.10N. americanus

Mild intestinal parasitic infections

0.23Breastfeeding

0.44Menstruation

0.72Baseline Requirements

Iron needs or lossesmg/day

Physiologic condition

Source: Stoltzfus y Dreyfuss, 1998

15 |

Intestinal lossesIntestinal losses

0

2

4

6

8

10

12

0 1 - 1999 2000-3999 4000-5999 6000-7999 >7999

eggs/g of fecal matter

Haem

og

lob

in/(

mg

/dL

)

Source: Stoltzfus y Dreyfuss, 1998

16 |

Iron status indicatorsIron status indicators

<16Transferrin saturation (%)

<110110-130>130Hb (g/L)

International Reference

Reagent

STR

<40115±50>175Plasma serum (mg/L)

<7070RBC protoporphyrin

(µg/dL)

<1212-150>150Ferritin (µg/L)

AnaemiaAnaemiaNormalNormalPositivePositive

BalanceBalanceIndicatorIndicator

Source: WHO/ UNICEF / UNU. Iron deficiency anaemia: Assessment, prevention and control, a guide for programme managers. Geneva ,WHO, 2001.

17 |

Treatment of anaemiaTreatment of anaemia

Population levelLow prevalence of anaemia in GAR

Intermediate

prevalence of anaemia in GAR

• Fortification

• Preventive supplementation• Nutrition counselling

• Nutrition counselling

High prevalence of anaemia in GAR

• Fortification

• Therapeutic supplementation• Nutrition counselling

Individual level

DiagnosisIncreased iron

losses?

• Treatment of cause of anaemia

• Therapeutic supplementation

Belong to a vulnerable group?

• Nutrition counselling

• Therapeutic supplementation• Nutrition counselling

Yes

No

No

No

No

No

Yes

Yes

Yes

Yes

Yes

Adapted: Casanueva et al, 200818 |

WHO recommendationsWHO recommendations


4

19 |

WHO-VMNISWHO-VMNIS

20 |

AnaemiaAnaemia




Sideroblasts

No Yes

iron deficiency

thalasse

miasidero

blastic

anaemia

aplasticanaemia

Leukaemia

haemolytic

disease

transfusion

reaction

vitamin

B12

anaemia

folic acid

anaemia

hepatic

disease

haemolytic

anaemia

Low High

Reticulocytes

21 |

AcknowledgementsAcknowledgements

Financial and/or technical support for the Micronutrients Unit

The Government of Luxembourg

US Centers for Disease Control and Prevention (CDC)

The Micronutrient Initiative (MI)

US Agency for International Development (USAID)

The Bill and Melinda Gates Foundation

1

Estimating National Blood

Requirements in Africa

Lawrence H. Marum, MD, FAAP, MPH

Centers for Disease Control and

Prevention - Zambia

Estimating National Blood Requirements –

what should we measure?

1. Needs/demand for blood in the existing

health system

2. Capacity and gaps of health system to

deliver services

Should a national blood service focus on estimating and meeting needs within existing health system

OR expanding the number and distribution of facilities with capacity for transfusion?

Drivers of demand for blood in Africa

1. Malaria associated anaemia (children

and mothers)

2. Emergency obstetrical services

• Post-partum haemorrhage

3. Surgical services

4. Trauma

5. Medical treatment

• HIV treatment associated anaemia

17.716.6

11.86.5

8.89.1

7.55.4

5.73.7

5.43.4

4.83.8

4.33.8

3.33.5

3.31.2

2.70.0

1.81.0

0.30.2

0.10.0

0 2 4 6 8 10 12 14 16 18

South Africa

Botswana

Namibia

Guyana

Zambia

Mozambique

Cote d'Ivoire

Uganda

Rwanda

Kenya

Tanzania

Haiti

Ethiopia

Nigeria

Units of Whole Blood Collected per 1000 Population

Figure 1: National Blood Transfusion Service (NBTS) collections per 1000 population in PEPFAR partner countries: 2003 and 2007

2003 Blood Collections per 1000 Population

2007 Blood Collections per 1000 Population

* Nigeria and Tanzania had no NBTS in 2003

*

*

WHO Recommended Target

Zambia National Blood Transfusion Service:

progress in meeting national needs

100,000

(8.0)

38,477

(3.7)

Units blood collected

(collections per 1000 population)

132 (9)90 (90)Transfusion outlets/ blood centres

100%72%Proportion voluntary donors

9.2%

(3.0%)

15.5%

(6.9%)

Discards

(HIV discards)

12.5 million10.5 millionPopulation of Zambia

20092004

Transfusions/bed at different hospital levels - Zambia

0

2

4

6

8

10

12

14

16

Level 1 Level 2 Level 3

#1 08

#1 09

#2 08

#2 09

2

Proportion of paediatrictransfusions - Zambia

0

5

10

15

20

25

30

35

40

Level 1 Level 2 Level 3

#1 08

#1 09

#2 08

#2 09

University Teaching Hospital: changing uses of blood

Maternity

Paediatric

Medical

Surgical

Other

• 1864 beds

• Uses 27% of national

blood supply

• Maternity 30%

• Paediatric 17%

• Medical 21%

• Surgical 14%

• Other: outpatient and

special services 14%

Zambia HIV summary

• 12.5 million population; total fertility rate = 7

• Adult HIV prevalence (15-49 years) 14.3%

• >250,000 on ARVs (19,000 children)

– Primary first-line treatment changed from AZT-

3TC to TDF-FTC backbone regimes

– 70% of those with CD4 < 250

– 40% of HIV+ pregnant women in 2010 (25,000) will initiate AZT backbone regime (CD4<350)

Progress in malaria control

• Deaths in hospitalized patients with malaria decreased 60%

• 54% decrease in parasitemia (under 5 y/o)

• 69% decrease in severe anaemia

• Distributing 400,000 nets per year

• Indoor residual spraying in 37 of 73 districts (over 1,000,000 homes annually)

• Artemesinin Combination Therapy 1st line and Sulfadoxine-pyrimethamine in pregnancy

Blood Use at Macha

(rural mission/district hospital)

Children’s

Ward Transfusions

Non –Children’s

Ward Transfusions

Total Transfusions

Proportion given

to Children ≤ 6 yrsYear

2000 588 219 807 73%

2001 512 267 779 66%

2002 336 258 594 57%

2003 393 305 698 56%

Macha Hospital - All Blood

Transfusions

0

20

40

60

80

100

120

140

160

180

200

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

2000 2001 2002 2003

nu

mb

er

pe

r m

on

th

Childrens Ward

TB Ward

Maternity Ward

Womens Ward

Mens Ward

3

Macha Hospital - Non Children's

Ward Blood Transfusions

0

50

100

150

200

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

2000 2001 2002 2003

Macha Hospital - Children's Ward

Blood Transfusions

0

50

100

150

200

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

Ja

n

Ap

r

Ju

l

Oc

t

2000 2001 2002 2003

0

50

100

150

200

250

300

350

400

450

500

JA

N

AP

R

JU

LY

OC

T*

JA

N

AP

R

JU

LY

OC

T

JA

N

AP

R

JU

LY

OC

T

JA

N

AP

R

JU

LY

OC

T

JA

N

AP

R

JU

LY

OC

T

JA

N

AP

R

JU

LY

OC

T

JA

N

AP

R

JU

L

2000 2001 2002 2003 2004 2005 2006

Macha Hospital – Children’s Ward Malaria Diagnoses

A/L out of

stock

A/L Introduced

as First Line Rx for

Malaria

Year

Children’s

WardMalaria Dx

Children's

Ward BloodTransfusions

2000 1479 588

2001 1778 512

2002 1294 336

2003 1418 393

2004 423 155

2005 123 60

2006 565 225

2007 336 118

Macha Hospital - Children's Ward Blood

Transfusions

0

20

40

60

80

100

120

140

160

180

Ju

ne

Se

pt

De

cJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

rJ

ul

Oc

tJ

an

Ap

r

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Blood Use at Macha

• Conclusions:

– Historically, over 50% of blood use is for

children under 6 years of age

– Blood is primarily given during the peak

malaria transmission season

• Hypothesis:

– Control of malaria may lead to a significant decrease in the need for blood at district

level hospitals in sub-Saharan Africa

4

Emergency Obstetric Services

• 1230 ANC facilities; 937 offer PMTCT

– 132 transfusing facilities

• Lack of trained nurse/clinical officers

– Only 60% of national health posts filled

– Rural retention schemes; retired nurses

• Expansion of C-section capacity to level 1 hospitals and larger health centres – many

that do not have transfusion capability

Conclusions

• Changing blood needs– Reduced paediatric transfusion w/ malaria control

– Expansion of emergency obstetric services

– Increased chronic disease treatment (ARVs)

• M&E needs– Comprehensive data on use of blood; vein to vein linkages

– Prescriber information for monitoring and supervising

– SmartDonor and SmartCare: national electronic records

• Address national transfusion coverage in Health System Strengthening efforts – how quickly can we safely expand?

1

Dr Francine DécaryPresident and CEO

Carolina SarappaBusiness Analyst

Héma-Québec

03-05 February 2010

WHO Experts’ Group Consultation on Estimation

of Blood requirements

DIFFERENT MODELS OF BLOOD ESTIMATION

A BLOOD CENTRE PERSPECTIVE

Background : national health care

CanadaPopulation:33,968,200

Territory:9,984,670 km²

QuebecPopulation:7,828,879

Territory:

1,542,056 km²

Hospitals:99

Model:Blood banks in hospitals

Blood Management System in Quebec Quebec statistics 2008-09

� Blood units drawn: 245,938

� RBC shipped to hospitals: 231,958

� Inventory at HQ: 8 days

� Outdating at HQ: 0.62%

� Outdating in the hospitals: 1,4%

RBC utilization in hospitals

100Total

12Others

43Hematologicaldisease & transplant

7Trauma

1Obstetrics

12Urgent

25Surgery: Elective

% Indications

Comparison of RBC utilization with other countries

USAFrance

QUEBEC

45.5

33.028.5

0

10

20

30

40

50

Un

its

/10

00

po

pula

tio

n/y

ea

r

2

Types of Forecasting Techniques

1. Informal: intuitive depending on individual experience and abilities

2. Formal:

2.1 Qualitative techniques2.1.1 Delphi2.1.2 Market surveys2.1.3 Life cycle analogy

2.2 Quantitative techniques2.2.1 Auto Projection2.2.2 Moving average2.2.3 Exponential smoothing2.2.4 Causal2.2.5 Regressive2.2.6 Box Jenkins2.2.7 Econometric2.2.8 input-output

Demand Forecasting: Key Criteria to Consider

1. Item to be forecasted : RED BLOOD CELLS

Availability of RBC depends on :

– Availability of blood donors– Quality of the donors– Management of the RBC by the blood center (discard & outdate rate)

Utilization of RBC depends on :

– Inventory management by client-hospitals• Stock rotation between hospitals• Outdate rate target 2%

– Depends distance from blood center

– Age of the population

– Availability of data from hospitals

Key Criteria to Consider

2. Major challenges

– Donors

• Quality of donors – deferral rate 18%

– Blood group distribution (ABO and Rh) in the population

– Customer service and satisfaction

• The right product at the right time

– Maintaining adequate levels of Inventory

• No shortages of stock

– Economic situation

• Must consider the health care system model because the economic situation may or may not influence your forecast.

– Disaster planning

• Capability of responding to emergencies


3. Amount of historical data available

– Total number of RBC shipped :

• By ABO Rh

• Per year, month, week…

– Records exist on a daily basis at Héma-Québec

– Hospital utilization :

• Historical data for sentinel hospitals

• Usage by diagnosis-related group (DRG)

• Outdate rate

– Events that affected the past demand

• Ex.: Letter requesting hospitals to decrease the expiry rate of RBC

– Presence of a transfusion committee


4. Time allowed to prepare the forecast

– Tied into the annual budgeting period

– Also depends on the resources allocated to the forecast

– Horizon:

• Long term (5-10 yrs)

• Short term (1-2 yrs)

• Very short term (< 1yr)

Short-term forecasting

(1 to 2 years)

3

Quantitative techniques

Naïve method

Dt = Dt-1 + c

– Where c is determined by historical data and /or expert judgement

– One of the simplest methods to use

� For Héma-Québec, this method works well since the demand is relatively stable.

Exponential smoothing

This method is a special form of the weighted average and focuses on the most recent period.

Dt = aDt-1 + (1 - a)Dt-1

– Where a (the smoothing constant) is determined by trial and error

� Fairly complex statistical methods are involved

Results obtained

+ 4.0 %228,090Holt-Winters

(Seasonality – quarter)


(Seasonality – month)


+ 23.4 %270,844Exponential smoothing

Reference219,406Simple linear trend

% errorForecast(12 months)

Forecasting method

Research on the factors that affect

hospital demand (2006)

� A sample of 8 blood banks, accounting for 56,673/221,256 (24%) of the demand for the year 2005-06, were interviewed.

� The results indicate that the following variables have the most important effect on the demand for red blood cells:

– improvement of surgical and medical practices

– medical and technological advancement

– substitute products and alternative treatments

– education of hospital personnel

– protocols of transfusion

– expiration targets for blood products

� However, the findings appear almost impossible integrate into a regression model, historical data remained the best indicator of the future demand for the purpose of this study.

Final model

� The proposed model is a particular version of the ARIMA (Autoregressive Integrated

Moving Average) models.

� It is based on a chronological series related to the quantity of red blood cells distributed to hospitals for a 349 week period

– from 11/22/1999 to 07/31/2007

� For the following 18 week period, the absolute percentage errors range from 0.31% to 10.61%

– the mean error is 4.90% per week or 0.70% per day.

ARIMA model

Week

Dis

trib

ution o

f P

acked

Red C

ells

0 100 200 300 400

3000

3500

4000

4500

50

00

55

00

ObservedForecasted

211 901

227 581

231 958

221 256 223 100221 659

223 723

220 215

-6.48%

-5.27%

6.00%

9.00%

4.70%

0.84%

-1.83% -1.94%

190 000

200 000

210 000

220 000

230 000

240 000

250 000

2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 2008-2009

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

Actual Demand Forecast % Error

Demand ForecastingRed Blood Cells Shipped to Hospitals

4

So how DO we forecast?

Demand Forecasting– 2 forecasting techniques based on historical demand are currently used at Héma-Québec

� Naïve method� Arima model

Communication with hospitals– Creation of Hospital Relations Department

• 99 hospitals

� Our conclusion:

Although very efficient, the quantitative forecast should be coupled with expert judgement and increased communication efforts with hospitals in order to maximize the accuracy of the forecast and effectively optimize the efficiency of the decision-making process.

� Results in:

Very short-term forecasting

Monitoring daily inventory

163%124%WEIGHTED INVENTORY*:

179%1843135%57714260TOTAL

352%59301%346115AB+

224%125182%546300B+

175%554134%18131350A+

163%587124%18551500O+

262%15229%10345AB-

91%4942%42100B-

163%179112%393350A-

190%275135%673500O-

%TO LABEL%LABELLEDMINIMAL

(6 days)

TOTAL INVENTORYMONTREAL & QUEBEC

RED BLOOD CELLS

Date: 01-10-2010 Time: 6:00 amAvailable 5 times a day via Intranet

* Considers minimal stock for B+ and AB+

Inventory management

BusinessAnalyst

INVENTORY COMMITTEEProcessing& Shipping

ProductQualification

HospitalRelations

BloodCollection &

Transport HospitalServices

Staffing

DonorRecruitment

Inventory management

� The committee meets on a weekly basis in order to:

– Monitor inventory levels by product and by ABO/Rh (when applicable)

– Review the week’s activities:

• Success of blood drives

• O negative in stock

• Age of RBC inventory

• Inventory of platelets collected by apheresis

• Turn-around time at laboratory testing

• Shortage/surplus of personnel

• Special cases and projects (ex.: TRALI, ISBT 128)

– Weekly inventory report from sentinel hospitals (on average = 5 days)

– Client-hospitals communicate active cases with blood product requirements

– Adjust short term collection targets based on fluctuations in hospital demand and inventory levels.

– Plan for holidays or other events

4

6

8

10

12

14

Apr-06 Sep-06 Feb-07 Jul-07 Dec-07 May-08

Days of Inventory Minimal Inventory Optimal Inventory

Days of Inventory per Weekfrom April 3rd 2006 to July 20th 2008 Further research

Long-term forecasting (5 – 10 years)

• Forecast based on the population pyramid

• Drawbacks:

– Does not consider the usage per

DRG

– Does not take into account

medical and scientific advances

5

DIFFERENT MODELS OF BLOOD ESTIMATION A BLOOD CENTRE PERSPECTIVESummary

1. Short-term forecasting (1-2 yrs): in a stable mature system, forecasting in best done by simple techniques based on historical data, professional judgment and

constant communications with hospitals.

2. Long-term forecasting (5-10 yrs): for strategic planning, demographics and DRGsare critical elements.

3. BUT: Very short term forecasting (daily, weekly and monthly): the most important one since only this forecasting prevents shortage of blood and thus gives the best service to the patients in need of blood.

1

Assessment of Needs for Blood Products – Pilot study of a model

based on clinician experience

Elizabeth Vinelli, Rashid Salmi, Brian McClelland, Marco Pinel, Rosa Kafati, Guillermo Guivobich, Juana Lozano, Ana del Pozo,

Christian Hertlein

Presented on behalf of the project group by Brian McClelland WHO

February 3, 2009

Introduction

• The blood needs for a population could be defined as the sum of the needs for all patients

with all diseases.

• Since there are countless combinations of

disease, stage, co morbidity and intervention that can put a patient at risk of needing a transfusion.

• It is difficult to define the information required and extract it from conventional registers of

clinical data.

Hypotheses 1

For a given period and given category of

disease, blood needs will be a function of:

• The number of individuals having the disease

during the period

• The proportion of them which develop a

pathophysiological condition requiring transfusion

• Quantity of blood needed for each category

Hypotheses 2

• The majority of blood needs are related to compensation of acuteor chronic anemia; therefore, if red cell needs were met, this should be sufficient to meet the needs for platelets and plasma since these can be separated from whole blood

• Experienced specialist clinicians should be able to assign the main groups of patients at risk of transfusion (GPRT) into broad clinical categories in relation to transfusion needs

• These are the categories that will have a major impact on the total need for blood, either because they include – many patients requiring a modest amount of blood, or because

they include a – smaller number of patients each requiring a large amount of

blood

• Disease groups other than the main GPRT should have a small impact on blood needs .

Model

The model is based on estimates of four parameters

• N size of the population;

• P(Bi) frequency of the GPRT i in the population;

• P(Ai) proportion of patients in the GPNB that will actually have anemia requiring transfusion of red blood cells;

• µi i average number of units needed per patient.

The estimate of overall needs is given by

∑ [N x P(Bi) x P(Ai) x µi], i=1

Pilot study - Honduras

• Country population 6.6 million (2004)

• Aimed to include the whole country

• Included clinicians from hospitals thatprovide coverage to 80% of the population

2

• Formal consensus methods have been shown to be helpful in developing initial estimates of patient populations in the absence of accurate clinical and epidemiological data.

Information sought from clinicians

• List of Groups of patients needing blood

• Number/ of individuals in each group during the defined period

• Proportion of these having a pathophysiological condition requiring blood

• Quantity of blood needed for each pathophysiological condition tha requires blod

Stage 1:Nominal group concensus

• The participants took part in a structured two hour face to face meeting.

• To define common ground and maximize areas of agreement, participating clinicians were organized by broad clinical specilaties.

• Experts were asked to discuss among themselves and to list the top 3 clinical conditions requiring red cell replacement.

• Through a series of scoring, voting and ranking methods a list of nine clinical conditions was obtained.

Stage 2:Survey

• A survey of 35 clinician (different from the nominal group) indicated that the original categories were too broad which made estimating the basic parameters very difficult, 31% of those surveyed felt that the original list was incomplete.

• No usable information of prevalence was provided since clinicians felt they did not have enough information to give a reasonable estimate.

• Information on proportion of patients needing blood andunits needed per patient was provided for all nineoriginal conditions.

Stage 3:Face to Face Interviews

• To come to a formal agreement about how specific the experts considered the selected clinical categories must be, face to face interviews with 121 clinicians from 10 hospitals were conducted.

• By medical doctors that have been trained to request the 3 basic parameters.

• Clinicians were asked to answer only on those clinical categories they were familiar with.

• The consensus generated a larger list of clinical conditions which were classified by ICD category with the help of an expert from the local Pan American Health Organization office.

Stage 4 Delphi round

• During the final phase to obtain consensus on the basic parameters an initial letter explaining the Delphi process and inviting participation was sent by electronic mail to 138 clinicians. 120 responded

• Tables containing all the criteria collated from the previous exercise were included with the invitation. If the clinician had participated in the previous round his/her results were highlighted. Results from other clinicians were also included but their names were kept confidential. Each clinician was requested to agree with their previous answers or to change in view of the group’s response.

• Averages were obtained for the proportion of patients needing blood as well as the number of products that the clinician estimated were necessary for the patient.

• Final consensus is included in the following table.

3

Comparison with observational datablood request forms

• 1376 blood request forms from the main reference hospital were available for review, in 1335 there was a reason for the request

• 68% of the reasons for transfusion matched one of the GPRT

•• The remaining 433 blood request forms fell into two categories:

unspecified anemia and “others”.

• 100 transfusion requests were matched to discharge diagnosis. Only patients who had been transfused were included in this sample. In 67% of charts the discharge diagnosis coincided with one of the GPRT. Anemia, diabetes and solid tumors accounted for most of the remaining diagnosis.

• Clinicians were able to select 67-68% of all the clinical conditions for which patients were transfused during 2004.

Data collected from patient charts

• Demographic data: age, gender

• Hospital Stay: events, length of stay

• Anemia: Hb and Hct at admission and before transfusion

• Presence of acute bleeding

• Number of patients for whom blood requested

• Number of red cell units requested by the physician

• Number of patients transfused

• Number of red cell units transfused

Limitations of chart review

• Many charts were unavailable

• Deceased patients could not be included as their charts were not sccessible

• Transfusions were poorly documented in

the charts

Stage 1 result:

GPNB defined by Nominal Group

BurnsNeonates with pathologyGynaecologic and obstetric complicationsTrauma Orthopedic surgeryCardiovascular surgeryUpper GI haemorrhageHematological and Hemato-oncological diseasesNon-hematological cancers

GPRT defined by the complete

concensus process

0.190.190.190.190.510.510.510.510.420.420.420.42Y.28Y.28Y.28Y.28StabbingsStabbingsStabbingsStabbings18181818 0.220.220.220.220.800.800.800.800.650.650.650.65Y.24Y.24Y.24Y.24GunGunGunGun----shot woundshot woundshot woundshot wound17171717 0.340.340.340.341.001.001.001.000.170.170.170.17D25D25D25D25MyomasMyomasMyomasMyomas16161616 0.180.180.180.180.600.600.600.600.440.440.440.44S72S72S72S72Fracture of the femurFracture of the femurFracture of the femurFracture of the femur15151515 0.380.380.380.380.600.600.600.600.540.540.540.54S 32.1S 32.1S 32.1S 32.1----32.832.832.832.8Fracture of the pelvisFracture of the pelvisFracture of the pelvisFracture of the pelvis14141414 0.230.230.230.230.280.280.280.280.150.150.150.15P36P36P36P36Prematurity and SepsisPrematurity and SepsisPrematurity and SepsisPrematurity and Sepsis13131313 0.260.260.260.260.280.280.280.280.110.110.110.11P07P07P07P07Premature babiesPremature babiesPremature babiesPremature babies12121212 0.240.240.240.240.860.860.860.860.510.510.510.51O 72O 72O 72O 72Postpartum HemorrhagePostpartum HemorrhagePostpartum HemorrhagePostpartum Hemorrhage11111111 0.160.160.160.160.940.940.940.940.280.280.280.28O 03O 03O 03O 03----06060606Incomplete AbortionIncomplete AbortionIncomplete AbortionIncomplete Abortion10101010 0.340.340.340.340.840.840.840.840.190.190.190.19N93.8N93.8N93.8N93.8----93.993.993.993.9Abnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine Bleeding9999 0.440.440.440.440.650.650.650.650.900.900.900.90N18N18N18N18Chronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal Insufficiency8888 0.620.620.620.620.720.720.720.720.450.450.450.45K25K25K25K25----K29K29K29K29Peptic/ Peptic/ Peptic/ Peptic/ DoudenalDoudenalDoudenalDoudenal UlcerUlcerUlcerUlcer7777 0.760.760.760.760.860.860.860.860.960.960.960.96I85I85I85I85Esophageal Esophageal Esophageal Esophageal VaricesVaricesVaricesVarices6666 0.420.420.420.420.900.900.900.900.730.730.730.73Cardiovascular SurgeryCardiovascular SurgeryCardiovascular SurgeryCardiovascular Surgery5555 0.740.740.740.740.760.760.760.760.770.770.770.77D61D61D61D61AplasticAplasticAplasticAplastic AnemiaAnemiaAnemiaAnemia4444 0.730.730.730.730.730.730.730.730.890.890.890.89C91C91C91C91----C95C95C95C95LeukemiasLeukemiasLeukemiasLeukemias3333 0.640.640.640.640.860.860.860.860.720.720.720.72C53C53C53C53Cervical CarcinomaCervical CarcinomaCervical CarcinomaCervical Carcinoma2222 0.370.370.370.370.570.570.570.570.800.800.800.80C16C16C16C16Gastric CarcinomaGastric CarcinomaGastric CarcinomaGastric Carcinoma1111 Units transfusedUnits transfusedUnits transfusedUnits transfusedUnits requestedUnits requestedUnits requestedUnits requestedPortion requiring Portion requiring Portion requiring Portion requiring transfusion: transfusion: transfusion: transfusion: ConcensusConcensusConcensusConcensusICD CodeICD CodeICD CodeICD CodeGroupGroupGroupGroup

4

22220.420.420.420.422.26E2.26E2.26E2.26E----0404040412121212StabbingsStabbingsStabbingsStabbings18181818 33330.650.650.650.651.80E1.80E1.80E1.80E----0404040413131313GunGunGunGun----shot woundshot woundshot woundshot wound17171717 22220.170.170.170.171.92E1.92E1.92E1.92E----040404046666MyomasMyomasMyomasMyomas16161616 22220.440.440.440.442.01E2.01E2.01E2.01E----0404040422222222Fracture of the femurFracture of the femurFracture of the femurFracture of the femur15151515 22220.540.540.540.542.96E2.96E2.96E2.96E----0505050519191919Fracture of the pelvisFracture of the pelvisFracture of the pelvisFracture of the pelvis14141414 .3.3.3.30.150.150.150.152.55E2.55E2.55E2.55E----0404040413131313Prematurity and SepsisPrematurity and SepsisPrematurity and SepsisPrematurity and Sepsis13131313 .3.3.3.30.110.110.110.112.65E2.65E2.65E2.65E----0404040414141414Premature babiesPremature babiesPremature babiesPremature babies12121212 33330.510.510.510.512.03E2.03E2.03E2.03E----0404040411111111Postpartum HemorrhagePostpartum HemorrhagePostpartum HemorrhagePostpartum Hemorrhage11111111 22220.280.280.280.281.11E1.11E1.11E1.11E----030303036666Incomplete AbortionIncomplete AbortionIncomplete AbortionIncomplete Abortion10101010 22220.190.190.190.192.22E2.22E2.22E2.22E----0404040410101010Abnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine Bleeding9999 22220.900.900.900.901.95E1.95E1.95E1.95E----040404043333Chronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal Insufficiency8888 33330.450.450.450.451.89E1.89E1.89E1.89E----0404040410101010Peptic/ Peptic/ Peptic/ Peptic/ DoudenalDoudenalDoudenalDoudenal UlcerUlcerUlcerUlcer7777 44440.960.960.960.963.34E3.34E3.34E3.34E----050505058888Esophageal Esophageal Esophageal Esophageal VaricesVaricesVaricesVarices6666 44440.730.730.730.734.50E4.50E4.50E4.50E----050505053333Cardiovascular SurgeryCardiovascular SurgeryCardiovascular SurgeryCardiovascular Surgery5555 77770.770.770.770.773.40E3.40E3.40E3.40E----050505059999AplasticAplasticAplasticAplastic AnemiaAnemiaAnemiaAnemia4444 44440.890.890.890.898.07E8.07E8.07E8.07E----0505050512121212LeukemiasLeukemiasLeukemiasLeukemias3333 33330.720.720.720.721.20E1.20E1.20E1.20E----0404040412121212Cervical CarcinomaCervical CarcinomaCervical CarcinomaCervical Carcinoma2222 33330.800.800.800.807.16E7.16E7.16E7.16E----0505050510101010Gastric CarcinomaGastric CarcinomaGastric CarcinomaGastric Carcinoma1111 Units/Units/Units/Units/PxPxPxPx/Yr/Yr/Yr/YrNeed BloodNeed BloodNeed BloodNeed Blood2004200420042004CliniciansCliniciansCliniciansCliniciansCONDICIONCONDICIONCONDICIONCONDICIONNo.No.No.No. EstimatEstimatEstimatEstimat NeedNeedNeedNeedProp Prop Prop Prop PxPxPxPxPrevalencePrevalencePrevalencePrevalenceParticipatParticipatParticipatParticipat222233332222Y.28Y.28Y.28Y.28StabbingsStabbingsStabbingsStabbings18181818 222233333333Y.24Y.24Y.24Y.24GunGunGunGun----shot woundshot woundshot woundshot wound17171717 222233332222D25D25D25D25MyomasMyomasMyomasMyomas16161616 222233332222S72S72S72S72Fracture of the femurFracture of the femurFracture of the femurFracture of the femur15151515 333344442222S 32.1S 32.1S 32.1S 32.1----32.832.832.832.8Fracture of the pelvisFracture of the pelvisFracture of the pelvisFracture of the pelvis14141414 0.130.130.130.13.13.13.13.130.300.300.300.30P36P36P36P36Prematurity and SepsisPrematurity and SepsisPrematurity and SepsisPrematurity and Sepsis13131313 0.0970.0970.0970.097,10,10,10,100.300.300.300.30P07P07P07P07Premature babiesPremature babiesPremature babiesPremature babies12121212 222222223333O 72O 72O 72O 72Postpartum HemorrhagePostpartum HemorrhagePostpartum HemorrhagePostpartum Hemorrhage11111111 222222222222O 03O 03O 03O 03----06060606Incomplete AbortionIncomplete AbortionIncomplete AbortionIncomplete Abortion10101010 222233332222N93.8N93.8N93.8N93.8----93.993.993.993.9Abnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine BleedingAbnormal Uterine Bleeding9999 333355552222N18N18N18N18Chronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal InsufficiencyChronic Renal Insufficiency8888 333344443333K25K25K25K25----K29K29K29K29Peptic/ Peptic/ Peptic/ Peptic/ DoudenalDoudenalDoudenalDoudenal UlcerUlcerUlcerUlcer7777 555566664444I85I85I85I85Esophageal Esophageal Esophageal Esophageal VaricesVaricesVaricesVarices6666 333333334444Cardiovascular SurgeryCardiovascular SurgeryCardiovascular SurgeryCardiovascular Surgery5555 444488887777D61D61D61D61AplasticAplasticAplasticAplastic AnemiaAnemiaAnemiaAnemia4444 333366664444C91C91C91C91----C95C95C95C95LeukemiasLeukemiasLeukemiasLeukemias3333 444455553333C53C53C53C53Cervical CarcinomaCervical CarcinomaCervical CarcinomaCervical Carcinoma2222 333344443333C16C16C16C16Gastric CarcinomaGastric CarcinomaGastric CarcinomaGastric Carcinoma1111 TRANSFUSIONSTRANSFUSIONSTRANSFUSIONSTRANSFUSIONSUNITS UNITS UNITS UNITS UNITS REQUIREDUNITS REQUIREDUNITS REQUIREDUNITS REQUIREDCODECODECODECODECONDITIONCONDITIONCONDITIONCONDITIONNo.No.No.No. OBSERVEDOBSERVEDOBSERVEDOBSERVEDREQUESTEDREQUESTEDREQUESTEDREQUESTEDCONSENSUSCONSENSUSCONSENSUSCONSENSUSICDICDICDICDCLINICALCLINICALCLINICALCLINICAL

Results: Prevalence

• Through all the stages, clinicians were

unable to provide any information on prevalence of the selected clinical

conditions.

Verifying Clinical data by chart review

• Based on the national database and

largest reference hospital database a sample was selected for chart review for

all 19 clinical conditions ( 5% of all cases with a minimum sample of 50 charts

• For patients with chronic conditions all hospital admissions for the year 2004

were included

Results - verification

Hospital dataBlood request forms: 1376 forms from the main reference hospital were available for review.

In 41 the cause for transfusion was not documented.

Of the remaining 1335, •68% of the requests indicated conditions that matched one of the final clinical groups••32% requests fell into two categories: unspecified anemia and “others” of which most were anemia, diabetes and solid tumors

Data from Scottish Transfusion Epidemiology database

Other

38%

Solid

Tumours

Surgical

20%

Haematology

18%

5

AnalysisIntraclass correlation coefficient was used to calculate the level of agreement

between the clinician based need estimate versus the calculated need based on units requested or units transfused.

• ICC calculated against units requested was 0.750

• ICC calculated against units transfused was 0.834

• Overall ICC between clinician based estimates and hospital records data was 0.951

• The intraclass correlation coefficient ranges from 0 and 1, a value of 1 indicates complete agreement

• Residual variability (1 - intraclass correlation coefficient) is due to true variation between clinicians and measurement error.

Results: comparison of observed data with cliniciansconcensus

168465050924612TOTAL NEEDSTOTAL NEEDSTOTAL NEEDSTOTAL NEEDS 580264012922.24E-04Y.28Stabbings 540326923931.79E-04Y.24Gun-shot wound 88634144431.90E-04D25Myomas 491204812011.99E-04S72Fracture of the femur 2324702172.93E-05S 32.1-32.8Fracture of the pelvis 5163782.53E-04P36Prematurity and Sepsis 4551602.63E-04P07Premature babies 661237021082.01E-04O 72Postpartum Hemorrhage 24171420042301.10E-03O 03-06Incomplete Abortion 102740495742.20E-04N93.8-93.9Abnormal Uterine Bleeding 1756410023811.93E-04N18Chronic Renal Insufficiency 2386388917321.87E-04K25-K29Peptic/ Doudenal Ulcer 86811798723.31E-05I85Esophageal Varices 3818268944.46E-05Cardiovascular Surgery 679132512453.37E-05D61Aplastic Anemia 1204220719548.00E-05C91-C95Leukemias 2097331017691.19E-04C53Cervical Carcinoma 544109911697.10E-05C16Gastric Carcinoma TRANSFUSIONS*TRANSFUSIONS*TRANSFUSIONS*TRANSFUSIONS*UNITS *UNITS *UNITS *UNITS *ESTIMATEESTIMATEESTIMATEESTIMATE2004200420042004CODECODECODECODECONDITIONCONDITIONCONDITIONCONDITION OBSERVEDOBSERVEDOBSERVEDOBSERVEDREQUESTEDREQUESTEDREQUESTEDREQUESTEDMODEL MODEL MODEL MODEL PREVALENCEPREVALENCEPREVALENCEPREVALENCEICDICDICDICDCLINICALCLINICALCLINICALCLINICALUnits available for transfusion in 2004: 37,000

Strengths

• Clinicians were able to define a group of clinical conditions to which 67-68% of all transfused patients could be assigned

• Their estimates of the red cell transfusion requirements showed reasonable comparability to those obtained from hospital records.

• Requires the investigators and blood services to consult clinicians about the transfusion requirement for their patients

• Should engage clinicians to think about blood requirements about the quality of data that could help to assess need, and the adequacy of the data currently available.

• Anecdotal evidence from the project team that these approaches have been welcomed.

• This would seem to be supported by the high levels of clinician participation in the present project

Weaknesses

• Labour intensive, time consuming,costly• Depends on the willingness of clinicians to participate,

and on the adequacy of their knowledge of blood utilisation in their own specialties

• Clinicians could not estimate prevalence of the conditions identified, so there is dependence on an additional data source

• Validation against other data sources depends on the existence, availability and quality of hospital records and on availability of human resources to extract data from them

• Method does not take account of access to health care• Additional data on this would be essential to calculate

blood requirements in any country where an important proportion of the population lacks access to facilities in which the availability of safe blood transfusion could benefit the outcomes of GPRT

Conclusions

• Clinicians were able to define a group of clinical conditions to which 67-68% of all transfused patients could be assigned

• Their estimates of the red cell transfusion requirements showed reasonable comparability to those obtained from hospital records.

• Neither source of data can adequately identify the adequacy or otherwise of the current supply levels.

• To estimate the blood requirements for a given population at a given time, data such as those obtained in this study should be combined with information on access to hospital care

1

WHO Expert Consultation on estimation of blood

requirements

Day 1

Objectives

• Review parameters in health system and clinical care which influence requirement of blood and blood components

• Review of existing mechanisms/ methodologies and models of blood estimation based on regional/country experience

• Assess the feasibility and accordingly define the steps in developing a simple model to estimate blood needs

Neelam Dhingra

• Overview of current situation• Little progress in the area of predicting blood

requirements

• Essential for planning

• Historical perspective• Various non-evidence based estimations

– Advanced healthcare systems

» Donations- 5% of population

» 3% of population regular blood donors

• Previous approaches

– Blood usage with different denominators

» Per 1000 population

» Per acute hospital bed

Gretchen Stevens

• Global burden of disease database– New estimates due 2011

• Important principles in preparing cross-national statistics– Selecting health indicator and metrics

• Framework for monitoring health systems

– Facility assessments

– Population-based surveys

– Clinical reporting systems

– Correcting for bias in available data

– Estimating and communicating uncertainty• Input uncertainty

– Poor quality data

• Model uncertainty

• Parameter uncertainty

Peter Olumese

• Declining falciparum malaria due to nets, spraying and ACT

• Parallel decline in paediatric blood transfusions

• Seasonal demand

• Potential impact of paediatric blood packs on blood supply and safety– Evaluation and bulk procurement? (WHO)

– (Also protective needle cover)

Matthews Mathai

• Haemorrhage implicated in a high proportion of pregnancy-related deaths

• Existing surveys and data on incidence of haemorrhage and blood transfusion requirements

• Access and equity issues

• Costs and planning tool already exists (to be shared)

• 9 signal functions of comprehensive obstetric care

2

Pablo Perel

• Frequency of trauma– Low resolution data on mortality and DALYs (but no/little data on

incidence and morbidity)

– Increasing in importance

• Frequency of bleeding in trauma– Bleeding probably important cause of death

– Reported transfusion rates differ widely

• Evidence base for transfusion of blood/products in trauma– Weak/contradictory

• Interventions to reduce transfusions– Well conducted clinical trials (e.g. CRASH-2) required

• Clinical trials such as CRASH-2 may provide better and higher resolution data on frequency of trauma and frequency of bleeding in trauma (WOMAN- PPH)

Luz Maria De Regil

• Global burden of disease database has data on anaemia but

• Variable Hb cut offs and definitions

• Adjustments required for altitude (1g/dL per 1000m), smoking and gestation

• Targeting of public health interventions depends on prevalence of anaemia in Groups at Risk

• VMNIS (Vitamin and Mineral Nutritional Information System

• Estimates of micronutrient deficiencies at national and regional levels

• Helminth infections?

• Haemoglobinopathies?

Larry Marum

• Zambia continues to make significant progress in improving its national blood supply

• Patterns of transfusion by hospital type

• Tertiary facility

– High (27%) and changing blood usage

• Unknown and increasing burden of HIV-related transfusions

• Malaria control and decreasing paediatric transfusions

• Obstetrics- mismatches between pregnancy care and blood supply

• Potential of SmartCare (patient/donor held electronic

record)

Francine/Carolina

• Hema-Quebec: stable, mature and efficient service

• Demand defined as units shipped

• High resolution historical data

• Complex models do not seem to outperform naïve method

• Where supply meets demand prediction is enhanced by inventory committee and good communication with hospitals

Brian McClelland

• If RBC needs are met, the needs for other components should also be met

• Categorisation of GPRT by clinicians using consensus methods (multi-stage)

• Comparison with observational data (limitations)

• Prevalence/incidence difficult to define

• Good statistical correlation between predicted and observed data but large numerical discrepancies

• Engagement with clinicians

• No measure of unmet demand (access)

Additional thoughts

• Clear idea of what we are trying to estimate– Agreed definitions

– Access, appropriate prescribing (evidence/consensus)

• Minimum data set

• Existing data sets

• ‘Toolkit’ cf simple mathematical model

• Assessment and communication of uncertainty of predictions

1

Ideal: need

Donor selection / motivation (management)

Donor deferral

Donor screening (testing)

Processing of blood products

Patients

Inventory

Y Potential Donors

X units for transfusion, such that no patient experiences (at no time) morbidity/mortality

due to shortages in RBCsIn fact: X is driving Y

Ideal: need

Patient need

-Define spatial and temporal specific drivers for transfusion, McClelland- Malaria (ATLAS, Marum, Olumese, WHO)- Trauma (Perel)- Nutrition (De Regil)- Maternal Health (Mathai)- etc

- Define methodology (McClelland, Rao, GBD)

- Perfect transfusion practices

- Optimal use of alternatives (drugs, colloids, salvage, EACA etc)

- No uncertainty and bias

X units for transfusion, such that no patient experiences (at

no time) morbidity/mortality due to shortages in RBCs, X is driving number of potential donors (Y)

Access 100% No Morbidity/Mortality

Real: demand

Donor selection / motivation (management)

Donor deferral

Donor screening (testing)

Processing of blood products

Patients

Inventory

Y Potential Donors

X units for transfusion, such that current demand is covered

Y and/or capacity is driving X

Anaemia (Fe def. etc), De Regil

+ TTI Marker, GDBS; WHO, Marum

Losses in processing, Marum

Outdating, Décay/Sarappa

Access (€,£,$) Morbidity/Mortality, ?

Real: use and demand

Patients

- Define spatial and temporal specific drivers for transfusion, McClelland and others

-Define methodology (McClelland, Rao, GBD)

- Expect difficult hurdles (Sarappa)

- Uncertainty (parameter (need for distributions,@Risk, R, Stevens), model)

- Bias (Rural vs Urban, etc)

- Incorporate transfusion practices (McClelland, Marum, )

- Availability and use of alternatives (drugs Oxytocin, EACA, etc)

X units for transfusion, such that current demand is

covered, Y (number of potential donors) and capacity is driving X

Access ?% Morbidity/Mortality

How many DALYs* lost

do we

accept?

DALYs = Disability Adjusted Life Years = The sum of years of potential life lost due to premature mortality and the years of productive life lost due to disability.

Use Demand

Proposed definitionsDemand: The amount of blood that would be transfused if all requests for blood were met (includes inappropriate transfusions and unmet demand)

Use: The amount of blood actually transfused (excludes unmet demand)

Need: The amount of blood that would be used if all those who needed a bood transfusion were recognised and had blood appropriately prescribed i.e. includes unmet demandand excludes inappropriate transfusions

Proposed definitionsDemand: The amount of blood that would be transfused if all requests for blood were met (includes inappropriate transfusions and unmet demand)

Use: The amount of blood actually transfused (excludes unmet demand)

Need: The amount of blood that would be used if all those who needed a bood transfusion were recognised and had blood appropriately prescribed i.e. includes unmet demandand excludes inappropriate transfusions

1

1

Demand Forecasting atCanadian Blood Services

Tony SteedDirector, Market Knowledge & Donor Insight

2

Co

pyrig

ht ©

20

03

Fa

rWorks

Inc.

“Yes, yes, I know that, Sidley — everybody knows that!... But look: Four wrongs squared, minus two wrongs to the fourth power, divided by this formula, do make a right.”

“If you have to forecast, forecast often.”

– Edgar R. Fiedler,

The Three Rs of Economic Forecasting: Irrational, Irrelevant and Irreverent

“It is often said there are

two types of forecasts... lucky or wrong.”

– Control magazine, Institute of Operations Management

“Good forecasters are not

smarter than everyone else, they merely have

their ignorance better organized.” – Anonymous

3

Key Canadian demographics

• Area: 10 million sq. km. (3.3 people per sq. km.)

• 2 doctors and 4 hospital beds per 1,000 population

• High physician utilization rate (About 80% of Canadian use family physician services once a year; 58% more than twice a year

• Health services utilization patterns, for both individuals and for regions, are influenced by age, gender, self-rated health status, education income, etc.

4

CBS in the Canadian context

• Health care in Canada is a provincial / territorial responsibility, with federal government contributions

• Canadian Blood Service (CBS) is Canada’s national supplier of blood and blood products

• Arm’s length, not-for-profit agency “independent” of government

• Exclusively serve 9 of 10 provinces and all 3 northern territories, who collectively fund CBS. (Quebec province operates its own blood service—Hema Quebec)

• Regulator: Health Canada, a federal agency

• Global budget; no charge to hospitals

• Funding is based on annual estimates of blood requirements

5

438,400Donor

Customers

732Hospital

Customers

ProductionTesting

InventoryR&D

Education

• 916,000 WB units• 41,000

plateletpheresis units • 55,000 plasmapheresis

units • All units are freely

donated• 2.16 WB donations per

donor

• 600,000 patient transfusions a year

• Cost to recipient is fully covered under provincial / territorial government health plans

• 4,525 employees• 17,000 volunteers• 41 permanent

collection sites• 12 manufacturing

centres• 3 blood-testing

centres

Operations overview

6

Why forecast demand in the first place?

The collection, manufacturing and delivery of blood products is a complex business,

supported by a host of enablers. Demand forecasts can provide the lead time necessary to ensure that adequate supply is available to meet expected customer demand. It allows

CBS to maximize service delivery and stakeholder value.

Supply Chain Management Enablers

Donor Base

Clinic Events

Component Production & Testing

Inventory & Issuing

Hospital Shipments

Supply Chain Management

Supply Demand

Demand Forecasts

• Donor Recruitment

• Donor Retention

• Donor Contact

• Donor Segmentation

• Corporate Partners

• Event Planning

• Locations and Hours

• Appointment Booking

• Donor Influx & Flow

• Staff & Volunteer Mgmt

• Customer Mgmt

• Product Disposition

• Product Utilization

• Demand Estimates

• Integrated Systems

• Inventory Mgmt

• Inventory Protocol

• Product Delivery

• Order Fill

• Production Planning

• Discard Mgmt

• Recall Mgmt

Supply Chain Management Enablers

Donor Base

Clinic Events

Component Production & Testing

Inventory & Issuing

Hospital Shipments

Supply Chain Management

Supply Demand

Demand Forecasts

• Donor Recruitment

• Donor Retention

• Donor Contact

• Donor Segmentation

• Corporate Partners

• Event Planning

• Locations and Hours

• Appointment Booking

• Donor Influx & Flow

• Staff & Volunteer Mgmt

• Customer Mgmt

• Product Disposition

• Product Utilization

• Demand Estimates

• Integrated Systems

• Inventory Mgmt

• Inventory Protocol

• Product Delivery

• Order Fill

• Production Planning

• Discard Mgmt

• Recall Mgmt

2

7

What's behind the demand for blood?

Average units of blood/blood products required per recipient = 4.6 units

8

How is demand trending?

Total RBC Demand - 52 Week Moving Average

750,000

760,000

770,000

780,000

790,000

800,000

810,000

820,000

830,000

840,000

2005

-03-

27

2005

-05-

27

2005

-07-

27

2005

-09-

27

2005

-11-

27

2006

-01-

27

2006

-03-

27

2006

-05-

27

2006

-07-

27

2006

-09-

27

2006

-11-

27

2007

-01-

27

2007

-03-

27

2007

-05-

27

2007

-07-

27

2007

-09-

27

2007

-11-

27

2008

-01-

27

2008

-03-

27

2008

-05-

27

2008

-07-

27

2008

-09-

27

2008

-11-

27

2009

-01-

27

2009

-03-

27

2009

-05-

27

2009

-07-

27

2009

-09-

27

2009

-11-

27

2010

-01-

27

O Neg RBC Demand - 52 Week Moving Average

75,000

80,000

85,000

90,000

95,000

100,000

2005

-03-

27

2005

-06-

27

2005

-09-

27

2005

-12-

27

2006

-03-

27

2006

-06-

27

2006

-09-

27

2006

-12-

27

2007

-03-

27

2007

-06-

27

2007

-09-

27

2007

-12-

27

2008

-03-

27

2008

-06-

27

2008

-09-

27

2008

-12-

27

2009

-03-

27

2009

-06-

27

2009

-09-

27

2009

-12-

27

•The longer-term underlying growth in total RBC demand has been in the order of 2% per

year, but this growth has not always been consistent. Note the slow down in the latter half of FY0708, the rapid growth throughout FY0809 and the current decline in FY09/10.

•Even O Neg growth has eased off in FY09/10 - slowing, but not declining. The

proportion of total RBC issues which are O Neg has grown from 10% at the start of FY2004/05 to 11.3% this fiscal YTD

9

Almost 57% of the blood transfused in Canada is used by recipients aged 65 years or older

Who uses blood?

0

300

600

900

1,200

1,500

1,800

2,100

2,400

2,700

3,000

0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Po

pu

lati

on

(000)

0

20

40

60

80

100

120

140

160

180

200

Un

its T

ran

sfu

sed

per 1

,000 P

op

ula

tion

2005 Units Transfused per 1,000 FY0506 Blended

Source: BC Provincial Blood Coordinating Office (PBCO) 10

The proportion of the population aged 65 years or older is expected to grow from

14% in 2009 to 22% by 2030. In addition, the line representing the number of units transfused per 1,000 population has been shifting upwards over time.

Aging: A key influence on blood demand

0

300

600

900

1,200

1,500

1,800

2,100

2,400

2,700

3,000

0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

Po

pu

lati

on

(000

)

0

20

40

60

80

100

120

140

160

180

200

Un

its T

ran

sfu

sed

per 1

,00

0 P

op

ula

tion

2005 2013 2020 2030 Units Transfused per 1,000 FY0506 Blended

11

Collision course:

Demand meets supply

Supply

• Aging population• Health-cost

containment• Creating new donors• New pathogens

• Increasing deferrals• Regulatory issues

• System capacity, flexibility, scalability

• Technology deficit• Skills deficit• Supply management

• Blood’s competitive brand and profile

Demand

• Aging population• Increasing morbidity

• Increasing medical procedures

• Changing product mix

• Population growth• Ethnicity

• Expanding role of the blood business

• Global competition for fractionated products

12

Concentration of hospital demand

Concentration of hospital customer demand...

The Pareto Principle (80/20 rule) is alive and well at Canadian

Blood Services

0% 10% 20% 30% 40% 50% 60% 70% 80%

Top 25 Medical

Centres

Top 50 Medical

Centres

Top 100 Medical

Centres

Concentration of Demand

% of RBC Shipments 40% 60% 80%

% of Medical Centres 5% 10% 20%

Top 25 Medical Centres Top 50 Medical Centres Top 100 Medical Centres

3

13

Hospital shipments by day

The number of units shipped varies from one day to the next and

typically ranges from between 500 and 3,500 units.

# of RBC Units Issued to Hospitals per Day

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

2007

/04/

01

2007

/04/

27

2007

/05/23

2007

/06/

18

2007

/07/

14

2007

/08/

09

2007

/09/

04

2007

/09/

30

2007

/10/

26

2007

/11/21

2007

/12/

17

2008

/01/

12

2008

/02/

07

2008

/03/

04

2008

/03/

30

2008

/04/

25

2008

/05/21

2008

/06/

16

2008

/07/

12

2008

/08/07

2008

/09/

02

2008

/09/

28

2008

/10/

24

2008

/11/

19

2008

/12/

15

2009

/01/

10

2009

/02/

05

2009

/03/

03

2009

/03/29

2009

/04/24

2009

/05/

20

2009

/06/

15

2009

/07/

11

2009

/08/

06

2009

/09/

01

2009

/09/

27

2009

/10/

23

2009

/11/

18

2009

/12/14

14

Smoothed hospital shipments by day

Smoothing daily shipments make it easier to identify that customer shipments have been growing over time and that there are troughs

and peaks in demand surrounding the statutory holidays.

# of RBC Units Issued to Hospitals per Day (7 Day Moving Average)

10,000

11,000

12,000

13,000

14,000

15,000

16,000

17,000

18,000

19,000

2007

/04/

01

2007

/04/

27

2007

/05/23

2007

/06/

18

2007

/07/

14

2007

/08/09

2007

/09/

04

2007

/09/

30

2007

/10/26

2007

/11/21

2007

/12/

17

2008

/01/12

2008

/02/07

2008

/03/

04

2008

/03/

30

2008

/04/25

2008

/05/

21

2008

/06/

16

2008

/07/12

2008

/08/07

2008

/09/

02

2008

/09/28

2008

/10/24

2008

/11/

19

2008

/12/

15

2009

/01/10

2009

/02/

05

2009

/03/

03

2009

/03/29

2009

/04/24

2009

/05/

20

2009

/06/15

2009

/07/11

2009

/08/

06

2009

/09/

01

2009

/09/27

2009

/10/

23

2009

/11/

18

2009

/12/14

15

Distribution of demand by ABO Rh

Not all blood groups are in equal demand.

Almost 70% of all demand is concentrated in O Pos and A Pos.

Percentage of RBC Units Issued to Hospitals by ABO Rh

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007

/Apr

2007

/May

2007

/Jun

2007

/Jul

2007

/Aug

2007

/Sep

2007

/Oct

2007

/Nov

2007

/Dec

2008

/Jan

2008

/Feb

2008

/Mar

2008

/Apr

2008

/May

2008

/Jun

2008

/Jul

2008

/Aug

2008

/Sep

2008

/Oct

2008

/Nov

2008

/Dec

2009

/Jan

2009

/Feb

2009

/Mar

2009

/Apr

2009

/May

2009

/Jun

2009

/Jul

2009

/Aug

2009

/Sep

2009

/Oct

2009

/Nov

2009

/Dec

Total AB-

Total B-

Total A-

Total O-

Total AB+

Total B+

Total A+

Total O+

16

Demand growth rates by ABO Rh

Not all blood types grow at the same rate.

Demand for B+ and AB+ is declining; growth rates for Neg Rh are

higher than for Pos.

Yr/Yr Growth in Demand 2009 vs 2008

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

O+ A+ B+ AB+ O- A- B- AB- Blood

Group Rh

17

Customer demand forecasting process

Blend of Top-down (statistics based) and Bottom-up (customer canvass based) forecasting techniques.

May

June & Nov Nov/Dec

• Feeds high level Budget sizing,

Collection & Production target setting

• Utilizes two months of current year data

Preliminary Top Down

Forecast

Preliminary Bottom Up Forecast

Top Down/ Bottom Up

Rationalization

“Official ”Demand Forecast

Prepare &

Distribute Hospital Canvass

Worksheets

HCSR ’s

Review Worksheets

with Hospital Contacts

Strategic/ Executive Direction

(Overlays)

Time Series Analysis

(Historical Data Trends)

Strategic/ Executive

Rationalization

Bottom Up Forecast:

• RBC, Platelets & Plasma

• Feeds detailed Budget distribution,

Collection & Production tactics

Utilizes six months current year data

Top Down Forecast:

• Product level of detail as required



• Utilizes one month of current year data


Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization


Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:

•



Preliminary Top Down Forecast:


Updated Top

Down Forecast:

• Quarterly updates

May

Ju Nov/Dec





Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:





Top Down Forecast:






Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization


Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:

•





Updated Top

Down Forecast:


May

June Nov/Dec





Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:





Top Down Forecast:






Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization


Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets


May

Nov/Dec





Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:





Top Down Forecast:






Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization


Forecast


Top Down/ Bottom Up

Rationalization


Prepare &


Worksheets

HCSR ’s

Review Worksheets



(Overlays)




Rationalization

Bottom Up Forecast:

•





Updated Top

Down Forecast:


18

Why this process?

• Provides Top-Down and Bottom-Up perspectives

• Provides Base-Line and Overlay functionality

• The past is generally a good predictor of the future

• Lots of detailed hospital shipment data is readily available (hospital level of detail; by product; daily, weekly, monthly, quarterly, annually)

• Comprehensive clinical driver data is not currently available (how many transfusions; what types of procedures; etc.)

• Clinical driver data available has not been particularly effective at forecasting variations in customer demand (still need to forecast the clinical drivers)

4

19

Model selection process

• Damped trend with multiplicative seasonality models because they remain finite and flatten out over time

• Weekly data model (R-squared = .45) outperformed monthly data model (R-squared = .26)

• Model with event adjustment variables (R-squared = .83) outperformed weekly model

• Higher level model produced best fit so ABO Rh distributions were made using a Top Down Multiple Level model

• ABO Rh forecasts were further distributed by Region

20

Volatility of demand ...

Annualized year over year growth rates ranged from 3.8% in March 2009 to 0.2% in December 2009.

Underlying trend is in the neighbourhood of 2% per year, but exponential smoothing models will weight

recent data more heavily than past data.

12 Month Moving RBC Issue Yr/Yr Growth Rates

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

2005

/Jan

2005

/Apr

2005

/Jul

2005

/Oct

2006

/Jan

2006

/Apr

2006

/Jul

2006

/Oct

2007

/Jan

2007

/Apr

2007

/Jul

2007

/Oct

2008

/Jan

2008

/Apr

2008

/Jul

2008

/Oct

2009

/Jan

2009

/Apr

2009

/Jul

2009

/Oct

Monthly RBC Issue Yr/Yr Growth Rates

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

2005

/Jan

2005

/Apr

2005

/Jul

2005

/Oct

2006

/Jan

2006

/Apr

2006

/Jul

2006

/Oct

2007

/Jan

2007

/Apr

2007

/Jul

2007

/Oct

2008

/Jan

2008

/Apr

2008

/Jul

2008

/Oct

2009

/Jan

2009

/Apr

2009

/Jul

2009

/Oct

21

Forecast model performance ...

The exponential smoothing model does a reasonable job of predicting future

demand - at least at an aggregate level of detail. The budget view remains fixed for each fiscal period, but quarterly forecast updates are reviewed.

10,000

11,000

12,000

13,000

14,000

15,000

16,000

17,000

18,000

19,000

20,000

2007

-04-

01

2007

-06-

01

2007

-08-

01

2007

-10-

01

2007

-12-

01

2008

-02-

01

2008

-04-

01

2008

-06-

01

2008

-08-

01

2008-

10-01

2008

-12-

01

2009

-02-

01

2009

-04-

01

2009

-06-

01

2009

-08-

01

2009

-10-

01

2009

-12-

01

2010

-02-

01

Actual Budget View

22

Inventory - the buffer between supply & demand

Volatility in demand & supply can lead to unavoidable imbalances between the two. Inventory acts as a buffer to offset these imbalances, shrinking when demand outpaces

supply and growing when the opposite occurs. A minimum of 5 days of inventory on hand for each ABO Rh type is recommended.

Daily Red Blood Cell Inventory Levels

5,000

7,500

10,000

12,500

15,000

17,500

20,000

22,500

25,000

27,500

30,000

32,500

35,000

04-0

4-01

04-0

7-01

04-1

0-01

05-0

1-01

05-0

4-01

05-0

7-01

05-1

0-01

06-0

1-01

06-0

4-01

06-0

7-01

06-1

0-01

07-0

1-01

07-0

4-01

07-0

7-01

07-1

0-01

08-0

1-01

08-0

4-01

08-0

7-01

08-1

0-01

09-0

1-01

09-0

4-01

09-0

7-01

09-1

0-01

10-0

1-01

23

Demand forecasting - just the beginning ...

Demand forecasting is just the beginning. Performance during the year must

be closely monitored, analyzed and reviewed and lead to the development of appropriate corrective actions or adjusted goals and strategies.

Aging Population Hospital Expansion/

Contraction

Extraneous:

• Weather

• Trauma

• Labour Action

Analysis of

Key Drivers

Cause & Effect

Demand Forecast

Formal Results

Review

Recommended

Actions

Regulation

Technology

CBS Strategies/

Goals/Tactics

Comparison of

Actual Results to

Target

Aging Population Hospital Expansion/

Contraction

Extraneous:

• Weather

• Trauma

• Labour Action

Analysis of

Key Drivers

Cause & Effect

Demand Forecast

Formal Results

Review

Recommended

Actions

Regulation

Technology

CBS Strategies/

Goals/Tactics

Comparison of

Actual Results to

Target

24

When detailed demand data isn't available ...

Population statistics and forecasts are usually readily available. Relating hospital

demand to population growth will explain some, but not all of the growth in demand. Refining population estimates to weighted cohorts (e.g. by age band)

would likely yield improved demand forecasts. Provisioning for non-population

related overlays (e.g. increased health care funding) could also be considered.

2004/05 2005/06 2006/07 2007/08 2008/09Q2 2009/10

Annualized

Issued

CAGR

CAGR per

1,000 pop

Canada (Excl Quebec) 31.2 31.4 31.7 31.7 32.7 32.3 1.8% 0.7%

Newfoundland and Labrador 37.7 37.7 36.9 37.3 35.9 33.5 -2.7% -2.4%

Prince Edward Island 25.5 28.2 26.5 28.2 30.9 26.8 1.4% 1.0%

Nova Scotia 35.3 34.8 35.9 33.3 33.7 32.8 -1.4% -1.5%

New Brunswick 30.7 31.3 32.8 32.4 33.4 32.4 1.0% 1.1%Quebec 29.2 29.1 29.2 29.6 29.9 29.8 1.1% 0.4%

Ontario 31.4 31.3 31.2 30.9 32.3 32.3 1.5% 0.6%

Manitoba 36.9 36.7 38.0 38.5 37.4 36.9 0.8% 0.0%

Saskatchewan 36.0 36.6 37.3 37.8 38.5 38.6 2.1% 1.4%

Alberta 30.4 31.7 32.1 31.6 32.2 31.0 3.0% 0.4%

British Columbia 27.2 28.1 28.8 30.5 31.0 31.0 3.8% 2.6%

Yukon Territory 26.4 25.8 30.1 26.1 27.9 26.3 1.5% -0.1%

Northwest Territories 21.6 19.2 17.4 17.2 17.3 19.1 -2.4% -2.4%

Nunavut 10.1 9.7 9.2 8.4 9.6 9.4 -0.1% -1.6%

RBC Units Issued per 1,000 population by fiscal period

(Number)

5

25

[email protected]

Thank you! Questions?

1

Estimating blood demand Estimating blood demand ––

methodology practiced in HKmethodology practiced in HK

WHO ExpertsWHO Experts’’ Consultation on Consultation on ‘‘Estimation of Blood RequirementsEstimation of Blood Requirements’’

0303--05 February 2010, WHO, HQ, 05 February 2010, WHO, HQ, GenevaGeneva

CheChe--Kit LinKit Lin

Hong Kong Red Cross Blood Transfusion Service, Hospital Authority

Background Background –– Hong KongHong Kong

�� Area: 1,103 square kmArea: 1,103 square km

�� Population: Population: 77 millionmillion

�� Chinese 95%Chinese 95%

�� Overall density: 6,300 peopleOverall density: 6,300 people// kmkm22

�� Total health expenditure: 5.1% of GDPTotal health expenditure: 5.1% of GDP

�� Public Public health expenditurehealth expenditure::

2.6% 2.6% (2005(2005//06) (US$4.13 billion)06) (US$4.13 billion)

�� Birth rate: 11.3 live births per 1000 populationBirth rate: 11.3 live births per 1000 population

�� Infant mortality rate: 1.8 per 1000 live birthsInfant mortality rate: 1.8 per 1000 live births

�� Life expectancy: male 79.3 yr, female 85.5 yrLife expectancy: male 79.3 yr, female 85.5 yr


Background Background -- BTSBTS

�� Hong Kong Red Cross initiated the voluntary Hong Kong Red Cross initiated the voluntary nonnon--remunerated blood donation remunerated blood donation programmeprogramme in in 19521952

�� BTS established in 1984BTS established in 1984

�� SServing 20 public & 12 private hospitalserving 20 public & 12 private hospitals

�� Since 1991, Since 1991, BTS BTS has become has become part of the public part of the public hospital system (Hospital Authority)hospital system (Hospital Authority)

�� Public hospitals account for 90% of blood Public hospitals account for 90% of blood consumptionconsumption

�� Supply of blood components Supply of blood components is is free of chargefree of charge


Yr 2008 Blood Collection StatisticsYr 2008 Blood Collection Statistics

�� WB collection = 206636 unitsWB collection = 206636 units

�� PlasmapheresisPlasmapheresis = 2114 units= 2114 units

�� PlateletpheresisPlateletpheresis = 868 units= 868 units

�� AutologousAutologous WB = 130 unitsWB = 130 units

�� % of age eligible trade population donating = % of age eligible trade population donating = 3.3%3.3%

�� Donor deferral rate = 13%Donor deferral rate = 13%

�� Average age of donor Average age of donor �� Male = 39 , Female = 36 Male = 39 , Female = 36


Annual Blood Collection


2

Hong Kong Red Cross Blood Transfusion Service, Hospital Authority Hong Kong Red Cross Blood Transfusion Service, Hospital Authority


Yr 2008 Blood Supply StatisticsYr 2008 Blood Supply Statistics

�� WB derived Red Cell issued = 192,467 units; WB derived Red Cell issued = 192,467 units;

�� Standard Red Cell (derived from 470ml of WB) issued Standard Red Cell (derived from 470ml of WB) issued per 1000 population = 25.0 unitsper 1000 population = 25.0 units

�� WB derived WB derived PltPlt issued = 127,152 unitsissued = 127,152 units

�� One adult equivalent One adult equivalent pltplt dose issued /1,000 population dose issued /1,000 population = 4.54 units= 4.54 units

�� WB derived FFP issued = 57,330 unitsWB derived FFP issued = 57,330 units

�� 250250--300 300 mLmL equivalent FFP issued /1,000 population = equivalent FFP issued /1,000 population = 6.25 units6.25 units

�� Average age of WB+RBC on issue Average age of WB+RBC on issue == 14.7 days14.7 days



Frozen Plasma For Fractionation


Blood Blood Inventory and Inventory and DDistribution istribution

MManagementanagement

�� MMaintain optimal inventory levelsaintain optimal inventory levels in BTS and HBB in BTS and HBB

at all times with minimal expirationat all times with minimal expiration

�� FirstFirst--inin--firstfirst--out out -- based on the work of Cohen based on the work of Cohen

and and PierskellaPierskella 1975: application of management 1975: application of management

science and mathematical inventory theory to science and mathematical inventory theory to

control blood inventory management in a regional control blood inventory management in a regional

blood bankblood bank((Cohen MA, Cohen MA, PierskellaPierskella WP: Management policies for a regional WP: Management policies for a regional blood bank. Transfusion 1975;15:58blood bank. Transfusion 1975;15:58--67)67)

3


Inventory Inventory in BTS and in BTS and HBBsHBBs

�� BTS aims to maintain inventory of WB/RBC BTS aims to maintain inventory of WB/RBC ≥≥5 5

days of supply days of supply

�� Stock holding of WB+RBC (all blood groups) at BTSStock holding of WB+RBC (all blood groups) at BTS

-- 8.89 days (8.89 days (yr 2008 annual yr 2008 annual average)average)

�� Each Each HBB holdHBB holdss about 3about 3--5 days of 5 days of hospital hospital

consumptionconsumption

�� Inventory level in HBB is set out in the Inventory level in HBB is set out in the ““Blood Blood

Supply AgreementSupply Agreement”” which is reviewed annuallywhich is reviewed annually


BTS WB/RBC inventory levels

< 200< 200< 350DangerousV

200 - 399200 - 399350 - 599AlarmIV

400 - 599400 - 599600 -

1099

ActionIII

600 - 799600 - 7991100 -

1399

SafeII

Not applicable

as patient can

receive RBC of

any ABO group

≥≥≥≥ 800≥≥≥≥ 800≥≥≥≥ 1400DesirableI

Group AB+Group B+Group A+Group O+DescriptionLevel


HBB HBB Inventory Inventory AAllocation llocation PPolicyolicy

�� If BTS inventory dropped below safe levelIf BTS inventory dropped below safe level, , all HBB all HBB

inventories inventories will be reduced will be reduced on a proon a pro--rata basis rata basis with with

extra requests extra requests to be considered on to be considered on casecase--byby--casecase basisbasis

Further reduce stock supply and handle difference by case requests.< II< II< III

Top up Client’s RBC stock to ≥70% of agreed level.III

Top up Client’s RBC, platelet & FFP stocks to at least 90%, 70% &

70% of agreed levels respectively.

IIIIII

Top up Client’s stock as requested, provided that Client’s RBC,

Platelet & FFP stocks do not exceed 110%, 100% and 100% of

agreed levels respectively.

III

BTS CommitmentFFPPltRBC


Electronic Blood Transfusion Network SystemElectronic Blood Transfusion Network System

�� Connect with Connect with blood banks in blood banks in all public hospitalsall public hospitals––

enable viewing of realenable viewing of real--time inventories time inventories inin both both

BTS and BTS and HBBsHBBs

�� The system also enables:The system also enables:

�� Blood ordering & shipment Blood ordering & shipment

�� Product trackingProduct tracking

�� CChecking of patientshecking of patients’’ previous cross match resultsprevious cross match results


Client Client SSatisfactionatisfaction

0

50000

100000

150000

200000

250000

Re

d c

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

Re

d C

ell

Pla

tele

tP

las

ma

2001 2002 2003 2004 2005 2006 2007 2008 2009

An

nu

al

Ta

rge

r (U

nit

)

0

20

40

60

80

100

120

Pe

rce

nta

ge

Annual Target

Achievement (%)

Client Satisfaction (%)


Blood Utilization StatisticsBlood Utilization Statistics

4


Red Cells Utilization by Red Cells Utilization by SSpecialtiespecialties in Public Hospitalsin Public Hospitals

8927892761756175489548957852785250645064OtherOther

17510175101801118011178601786018040180401759717597PaediatricsPaediatrics

171316171316

856856

21472147

28652865

51915191

86108610

1139511395

1274612746

3164831648

7167271672

20072007

161126161126

701701

17031703

28922892

51305130

75967596

1109111091

1155011550

3012430124

6646066460

20062006

162925162925

12081208

17841784

16031603

51675167

73507350

1120511205

1137411374

3190631906

6543665436

20052005

160715160715

27352735

16241624

24382438

51615161

73977397

1094910949

1159811598

3187331873

6427964279

20042004

173608173608TotalTotal

947947ICUICU

18651865NeurosurgeryNeurosurgery

29402940ChestChest

54255425OncologyOncology

89088908O & GO & G

1049010490A & EA & E

1370913709OrthopaedicsOrthopaedics

3153331533SurgerySurgery

7157771577M & GM & G

20082008YearYear



Platelet Utilization by Platelet Utilization by SSpecialtiespecialties in Public Hospitalsin Public Hospitals

1019710197789378939489486066606669226922OtherOther

109108109108

338338

929929

13841384

18181818

21392139

28522852

79147914

1139311393

1510215102

5734657346

20072007

100191100191

404404

605605

12781278

15821582

14941494

27762776

68066806

1094010940

1457714577

5332253322

20062006

9612196121

373373

19601960

13171317

14661466

16801680

30723072

69136913

1084810848

1492214922

4750447504

20052005

9467494674

245245

43384338

14791479

15191519

12881288

21092109

82048204

93749374

1266512665

4653146531

20042004


310310A & EA & E

11621162ICUICU

13851385O & GO & G



26392639ChestChest




5737857378M & GM & G

20082008YearYear


FFP Utilization by specialtiesFFP Utilization by specialties in Public Hospitalsin Public Hospitals

441441405405479479373373333333A & EA & E

1609160916716762862813891389742742OtherOther

5125651256

990990

10601060

12511251

18881888

21832183

17711771

18291829

1710217102

2208222082

20072007

5276452764

13381338

936936

961961

19991999

22772277

16511651

19701970

1706917069

2331623316

20062006

5156451564

14131413

932932

19601960

22092209

27112711

16361636

15041504

1575115751

2168621686

20052005

5284352843

10911091

10031003

54975497

24262426

21642164

17311731

14431443

1502015020

2139321393

20042004



11781178O & GO & G

16181618ICUICU


21572157ChestChest




1990619906M & GM & G

20082008YearYear


WB+RCWB+RC Expiration Expiration in Publicin Public HospitalsHospitals

0.51%0.51%0.40%0.40%0.60%0.60%0.78%0.78%0.72%0.72%Overall % of Overall % of WB+RC WB+RC

ExpirationExpiration

691691

170625170625

20072007

894 894

160152160152

20062006

11511151

159564159564

20042004

12651265

161660161660

20052005

172722172722WB+RC issuedWB+RC issued

886886Total ExpirationTotal Expiration

20082008


PltPlt & FFP& FFP Expiration Expiration in Publicin Public HospitalsHospitals

0.21%0.21%

5125651256

5.42%5.42%

103197103197

20072007

0.23%0.23%

5276452764

5.33%5.33%

9485294852

20062006

0.52%0.52%

5156451564

5.70%5.70%

9064190641

20052005

0.37%0.37%

5284352843

6.54%6.54%

8848388483

20042004

100891100891Platelet issuedPlatelet issued

0.33%0.33%% of FFP % of FFP

ExpirationExpiration

5141151411FFP FFP issuedissued

6.18%6.18%% of Platelet % of Platelet ExpirationExpiration

20082008

5


Benchmarking Benchmarking BBlood lood UUtilizationtilization in Public in Public

HospitalsHospitals

�� A territoryA territory--wide peerwide peer--toto--peer review of blood peer review of blood utilization and expiration by hospitals and various utilization and expiration by hospitals and various clinical specialties.clinical specialties.

�� BTS provides report every six months.BTS provides report every six months.

�� Hospital Transfusion Committee has the responsibility Hospital Transfusion Committee has the responsibility to review its hospitalto review its hospital’’s performance and implements s performance and implements improvement measures accordingly.improvement measures accordingly.


Production planningProduction planning

�� Estimate annual blood requirementEstimate annual blood requirement

�� Review qReview quarterly demand of blood components uarterly demand of blood components

of different blood groupsof different blood groups, , blood collection, blood blood collection, blood

inventory and wastage and inventory and wastage and planplan short term short term

adjustments.adjustments.

�� Monthly communication with HBBMonthly communication with HBB on matters on matters

that potentially affect shortthat potentially affect short--term demandterm demand

�� WWeekly stochastic forecasting based on historical eekly stochastic forecasting based on historical

demand and communication with HBBdemand and communication with HBB to plan to plan

daily daily productionproduction of componentsof components


Estimation of Annual Blood RequirementEstimation of Annual Blood Requirement

�� Annual production planningAnnual production planning by cby causal ausal

forecastingforecasting

�� Review previous 12 month utilizationReview previous 12 month utilization

�� DeterminDeterminee driving factordriving factor

�� DeterminDeterminee the the utilizationutilization trend factortrend factorss


Driving FactorDriving Factor


HospitalsHospitals’’ Forecast of WB/RC DemandForecast of WB/RC Demand

�� Commence the process in November each yearCommence the process in November each year

�� Request each hospital to participate by Request each hospital to participate by

completing a questionnaire to forecast demand completing a questionnaire to forecast demand

for next year based on:for next year based on:

�� Previous 12 month utilizationPrevious 12 month utilization

�� ±± projected projected changes in demand due to factors such changes in demand due to factors such

as organic growth, changes in level of services, as organic growth, changes in level of services,

changes in patient population served and patient changes in patient population served and patient

demographics, etc. demographics, etc.


BTS Calculation of hospital WB/RC Demand

�� WB/RBC issued to WB/RBC issued to hospitalshospitals for the for the previous 12 month previous 12 month period period from from November to OctoberNovember to October, ,

�� adjustadjustinging for for shortage shortage of WB/RBC of WB/RBC stock replenishment stock replenishment during the period,during the period,hospitalshospitals’’ forecast increase or decrease forecast increase or decrease in blood demand in blood demand for next year for next year due to due to expansion or contraction of servicesexpansion or contraction of servicesand and population growthpopulation growth..

6


BTS Calculation of WB/RBC Demand BTS Calculation of WB/RBC Demand

for 2010for 2010--2011 2011

�� WB/RBC issued to clients in the period of WB/RBC issued to clients in the period of November 2008 to October 2009: 200,027 units November 2008 to October 2009: 200,027 units

�� Average satisfaction rate of WB/RBC stock Average satisfaction rate of WB/RBC stock replenishment during the period of November replenishment during the period of November 2008 to October 2009: 99.66%2008 to October 2009: 99.66%

�� ClientsClients’’ estimated potential increase/decrease in estimated potential increase/decrease in annual WB/RBC demand = 20 units annual WB/RBC demand = 20 units

�� HK population growth: 0.4% HK population growth: 0.4%


BTS Calculation of WB/RBC Demand BTS Calculation of WB/RBC Demand

for for 20102010--2011 2011

= [WB/RBC issued in 2009 x population growth / = [WB/RBC issued in 2009 x population growth /

Blood stock replenishment satisfaction in 2009] Blood stock replenishment satisfaction in 2009]

+ Clients+ Clients’’ estimated potential increase/decrease estimated potential increase/decrease

in WB/RBC demand for 10in WB/RBC demand for 10--11 11

= (200,027 x 1.004 / 0.9966) + 20 = (200,027 x 1.004 / 0.9966) + 20

= 201,532 units = 201,532 units


Baseline of WB/RBC DBaseline of WB/RBC Demandemand for for

2010/20112010/2011

�� HospitalsHospitals’’ demand forecast : 205,682 demand forecast : 205,682 unitsunits

�� BTS calculation : BTS calculation : 201,532 units 201,532 units

�� Since hospitalsSince hospitals’’ forecast isforecast is greatergreater than the BTS than the BTS calculationcalculation, , it will be it will be taken as the taken as the baseline baseline demanddemand for for further calculation to determine the further calculation to determine the annual annual WB/RBC demandWB/RBC demand for 2010/2011for 2010/2011. .


Additional Factors that Need to be Additional Factors that Need to be

Incorporated in the Final CalculationIncorporated in the Final Calculation

�� Average production discard rate in Average production discard rate in the the

previous three years i.e. previous three years i.e. 20062006--2008 = 6.63% 2008 = 6.63%

�� Average WB/RBC expiry rate Average WB/RBC expiry rate in the previous in the previous

three years, i.e. three years, i.e. 20062006--2008 = 0.013% 2008 = 0.013%


Final Estimation of Blood Demand Final Estimation of Blood Demand for for

20102010--20112011

= Baseline= Baseline demand / (1demand / (1 -- average average production discard rate production discard rate

-- average WB/RBC expiry rate) average WB/RBC expiry rate)

= 205,682 / (1= 205,682 / (1 -- 0.06630.0663 -- 0.00013) 0.00013)

= 220,318 = 220,318

AAnnual nnual blood blood collection target for 2010collection target for 2010--2011 2011

= 220,000 = 220,000 ±± 2% 2%

= = 215,600 to 224,400 units 215,600 to 224,400 units


Actual Annual Collection against Target Actual Annual Collection against Target

7


Long Term FLong Term Forecastorecast

Increase 25% in next 25 years

Population


Effect of the Effect of the ‘‘Silver TsunamiSilver Tsunami’’

�� In yr 2009, median age In yr 2009, median age

of population is 40.9 of population is 40.9

with 12.8% aged with 12.8% aged ≥≥ 6565�� In yr 2033, 26.8% of In yr 2033, 26.8% of

population will be population will be ≥≥ 6565


% Utilization of different a% Utilization of different age groupsge groups in in

variousvarious specialtiesspecialties

3.6%3.6%1.0%1.0%1.7%1.7%7.2%7.2%11.8%11.8%23.2%23.2%51.6%51.6%> 70> 70

4.0%4.0%2.4%2.4%4.7%4.7%12.5%12.5%5.2%5.2%23.2%23.2%48.0%48.0%61 61 –– 7070

11.8%11.8%1.7%1.7%9.2%9.2%10.1%10.1%7.2%7.2%20.6%20.6%39.4%39.4%51 51 –– 6060

20.0%20.0%1.2%1.2%6.4%6.4%11.6%11.6%4.8%4.8%15.6%15.6%40.4%40.4%41 41 -- 5050

30.4%30.4%1.2%1.2%7.7%7.7%2.8%2.8%12.1%12.1%5.1%5.1%9.6%9.6%31.2%31.2%31 31 –– 4040

26.8%26.8%1.1%1.1%39.4%39.4%1.1%1.1%4.3%4.3%2.3%2.3%4.3%4.3%20.8%20.8%21 21 –– 3030

12.6%12.6%0.9%0.9%72.1%72.1%1.4%1.4%2.0%2.0%1.8%1.8%4.2%4.2%5.0%5.0%11 11 –– 2020

7.4%7.4%90.2%90.2%0.5%0.5%1.8%1.8%1 1 –– 1010

98.9%98.9%1.1%1.1%< 1 yr< 1 yr

100%100%< 1 m< 1 m

Other*Other*CTSCTSPAEDPAEDONCONCICUICUORTORTSURSURMEDMED


Unique patients 10542 11129 10980 11575 11464 12413

Admission 14515 15079 14999 15790 15801 16879

44.4% used by patients aged > 7044.4% used by patients aged > 70

57.3% used by patients aged > 6057.3% used by patients aged > 60


ConclusionConclusion

�� Involving hospitals in forecasting short term demand Involving hospitals in forecasting short term demand seemed to be an effective approachseemed to be an effective approach

�� To achieve maximum use of the precious gifts of life To achieve maximum use of the precious gifts of life from blood donorsfrom blood donors and to ensure all demands are met and to ensure all demands are met timelytimely, it is important to understand the complex , it is important to understand the complex interrelations of supply and demand, factors that interrelations of supply and demand, factors that impact upon them and have all parts impact upon them and have all parts and parties and parties of of supply chain working togethersupply chain working together

�� BBlood utilization lood utilization is increasingis increasing

�� Aging of population will have significant impact on the Aging of population will have significant impact on the demand for blood supplydemand for blood supply


1

WHO Needs assessment Feb 2010

1

Epidemiology of Transfusion in

ScotlandWho gets transfused and why?

WHO Workshop on Estimation of needs for transfusion

Geneva February 3 – 5

2010


2

Needs Assessment:

How can we use this data

• in UK or similar setting

• in resource restricted setting


3

It should be part of our job to know who gets the blood, why and how much…

Develop a sustainable system providing

information about the clinical use of blood

Estimate current requirements

Predict future requirements

Identify variations in practice

Encourage clinical review of blood use

Understand demographic, socioeconomic and epidemiological influences

on blood use


4

Presentation

• Evolution and why

• AIMS

• Methods

• Results

• What next


5

Evolution

2000: STEP

Scottish Transfusion Epidemiology Project


6

Introduction of tailored information system software to enable the easy collection and analysis of transfusion data for prompt feedback to clinicians and Hospital Transfusion Committees. This would involve the construction of a merged record that is a by-product of routine clinical practice (held on the existing hospital patient administration system) and data extracts from the local hospital laboratory system (and in some cases operating theatre).

2005: STED

Scottish Transfusion

Epidemiology database

2


7

2008 NHSS-AFB

NHS Scotland

Account for Blood


8

Why…

• Progressively uncovered problems in

– data quality

– terminology and definitions for data items

– opacity of Progesa data

– heterogeneity of hospital blood bank IT systems

– heterogeneity of setting up – [same system used in different ways]

– human resource for regular data extraction and QA

– Etc etc


9

It should be part of our job to know who gets the blood, why and how much…

Develop a sustainable system providinginformation about the clinical use of blood

Predict requirements

Identify variations in practice

Encourage clinical review of blood use

Understand demographic, socioeconomic and epidemiological influences on blood use


10

Biggin K et al Transfusion 2009


11

STEDMethods in outline


12

Extract patient - specific transfusion data from 2002/03 –2005/06 from majority of Health boards

Link using Patient Identifiers with hospital inpatient and day case records (Scottish Morbidity Record)

Prepare reports for clinical users, other stakeholders

Disseminate

3


13

Structure of linked data

Patient Id 4 Procedure and 6 diagnosis fields

Procedure and diagnosis fields

Procedure and diagnosis fields

RBC, Plt,

Cyro,FFP

RBC,Plt,

Cyro,FFP

RBC,Plt,

Cyro,FFP

Inpatient episode recordsBlood bank transfusion records

Record linkage

RBC,Plt,

Cyro,FFP


14

Associating transfusion record with clinical episodes

Patient IdRBC

RBC

January

December

RBC

Date

RBC

Date rule Clinical rule…

Patient had 6 admissions,28 procedure codes

15 diagnosis codes and 4 transfusion episodes


15

PatientInpatient and Day

case Records (SMR1)

Date of admission

Date of discharge

Procedures

Diagnosis

Consultant responsible for care

Hospital of Treatment

Transfusion Records

Date of Transfusion

RBC Used

Platelets used

FFP used

Cryo used

Maternity

Neonatal

Outpatients

Ward Watcher (ICU)

Other Health Service data

sets

Incidence Date

Morphology/Stage/

Tumour size

Diagnosis

Cancer Registry

General Register Office Death Records

Census Data

Non Health Service Data sets

PIS Hospital Prescribing

A&E

SCI referrals


16

On line report on red cell use for surgical

procedures


17

ResultsTransfusion for surgical procedures

• Red cell use for defined surgical episodes (OPCS)

• Utilises ~20% of total red cell use per year (~38,000 units)*

• Substantial reduction over period 2003-2006

• Reduced variation among clinical units

– Cardiac: Coronary Artery Bypass Grafting

– Vascular: Elective repair of aortic aneurysm

– Orthopaedic: Primary total hip replacement


18

Red cell use in coronary artery bypass graft

0

0.5

1

1.5

2

2.5

3

3.5

4

Grampian Greater

Glasgow

Lothian Grampian Greater

Glasgow

Lothian

RB

C u

nit

s p

er

pro

ce

du

re

2003 2006

Coronary artery bypass grafts

Substantial reductions in one of the 3 cardiac

surgery units, associated with

intensified blood saving initiatives

including cell salvage

Variation between units reduced

4


19

Red cell use in aortic aneurysm repair

0

1

2

3

4

5

6

7

Ayrs

hir

e &

Arr

an

Fife

Gra

mp

ian

Gre

ate

r G

lasg

ow

Hig

hla

nd

La

na

rksh

ire

Lo

thia

n

Ta

ysid

e

Ayrs

hir

e &

Arr

an

Fife

Gra

mp

ian

Gre

ate

r G

lasg

ow

Hig

hla

nd

La

na

rksh

ire

Lo

thia

n

Ta

ysid

e

RB

C u

nit

s p

er

pro

ce

du

re

2003 2006

Elective repair of aortic aneurysm

Substantial reductions

across all health boards

variation variation in practice between health

boards continues but reduced


20

Red cell use in primary total hip replacement

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Ay

rsh

ire

& A

rra

n

Bo

rde

rs

Fif

e

Gra

mp

ian

Gre

ate

r G

las

go

w

Hig

hla

nd

La

na

rks

hir

e

Lo

thia

n

Ta

ys

ide

We

ste

rn I

sle

s

Ay

rsh

ire

& A

rra

n

Bo

rde

rs

Fif

e

Gra

mp

ian

Gre

ate

r G

las

go

w

Hig

hla

nd

La

na

rks

hir

e

Lo

thia

n

Ta

ys

ide

We

ste

rn I

sle

s

RB

C u

nit

s p

er

pro

ce

du

re

2003 2006

Primary total hip replacement

• Reductions in all health

boards, some greater than others.

• Tayside increase is an artefact of an identified anomaly with the source data for 2006 and should

be ignored.


21

Red cell use for patients with haematological malignancies

Conditions included (ICDM 10)

• Lymphoma• Myeloma• Myeloid Leukaemia • Lymphoid Leukaemia• Other Leukaemias• Malignant immunoproliferative disease • Other & unspecified malignant neoplasms of lymphoid,

haematopoietic & related tissues


* STED Data for 2006 WHO Needs assessment Feb 2010

22

Incidence Prevalence

Annual mortality

Total cases with first diagnosis of C91 during

1996 -2002

Total mortality 1996 -2002

Example of STED report: red cell use in a medical condition – lymphoid leukaemia

Red cell use data


23

Red cell use for patients with diagnoses of malignant tumours

Conditions described• Bronchus & lung• Prostate• Breast• Stomacho Small intestine• Ovary• Oesophagus• Kidney• Pancreas


Colon, rectosigmoid junction & rectum Cervix uteriCorpus uteriLiver & intrahepatic bile ductsThyroid & endocrine glandsEye, brain & other parts of CNSTestisTrachea

* STED Data for 2006 WHO Needs assessment Feb 2010

24

Summary

Other

38%

Solid

Tumours

Surgical

20%

Haematology

18%

5


25

Which clinical conditions do we still have to label as “other”?

– patients who have multiple admissions with several diagnoses

– many have markers for gastrointestinal & liver disease.


26

Demographics

AGE


27

The Scottish Population

Population in Scotland

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

2002

2004

2006

2008

2010

2012

2014

2016

2018

Year

Po

pu

lati

on

Total Scotland

Male

Female


28

Projected change in age structure

Figure 4 The projected percentage change in age structure of Scotland's population,

2004-20311

-40

-20

0

20

40

60

80

100

0-15 16-29 30-44 45-59 60-74 75+

Age1 2004-based pr ojections

-15% -12%-18%

-11%

+39%

+75%


29

RBC Units Transfused per 1,000Population by age/sex

Ageband 2003 2005 2003 2005

0-4 19.1 19.5 18.6 14.7

5-9 3.2 2.8 2.7 2.8

10-14 3.9 4.4 3.0 3.7

15-19 9.7 7.3 7.8 7.3

20-24 6.5 10.5 10.5 9.0

25-29 10.2 10.6 13.4 13.3

30-34 12.0 10.4 20.0 20.3

35-39 14.9 14.3 16.9 16.9

40-44 20.0 15.1 18.6 14.9

45-49 28.2 22.8 20.7 21.5

50-54 42.5 32.4 28.3 27.1

55-59 54.1 54.8 39.4 40.4

60-64 83.4 76.4 55.7 47.7

65-69 117.9 117.2 86.0 78.9

70-74 179.9 151.0 112.1 112.1

75-79 212.0 213.7 131.7 135.2

80-84 241.2 237.0 172.2 162.6

>=85 277.5 273.3 188.1 179.2

Total 44.3 42.2 40.3 39.1

Male Female

Scotland (Excl FV) RBC units tx per

1,000 population by age/sex


30

RBC Units Transfused

by age band, 2005/06

RBC units transfused per 1,000 population by agegroup

and sex (all Scotland , exluding FV)

0

50

100

150

200

250

300

0-4

5-9

10-1

4

15-1

9

20-2

4

25-2

9

30-3

4

35-3

9

40-4

4

45-4

9

50-5

4

55-5

9

60-6

4

65-6

9

70-7

4

75-7

9

80-8

4

>=

85

Age group

RB

C u

nits p

er

1,0

00

po

pu

latio

n

Male

Female

6


31

RBC Projections for Scotland (excluding Forth Valley), 2006-2018

170,000

180,000

190,000

200,000

210,000

220,000

230,000

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

RBC projection

(2005 HB rates

applied to

population

estimates)

RBC projection

(age/sex rates

applied to

age/sex

population

estimates)


32

Population Change in Europe

Figure 9 Projected Percentage Population Change in Selected European Countries, 2004-2031

-30

-20

-10

0

10

20

30

Bu

lga

ria

La

tvia

Ro

ma

nia

Es

ton

ia

Lit

hu

an

ia

Hu

ng

ary

Cz

ec

h R

ep

ub

lic

EU

ne

w m

em

be

rs

Po

lan

d

Slo

va

kia

Ge

rma

ny

Ita

ly

Sc

otl

an

d

Slo

ve

nia

Po

rtu

ga

l

Gre

ec

e

EU

25

De

nm

ark

EU

15

Fin

lan

d

Au

str

ia

Be

lgiu

m

Sp

ain

Ne

the

rla

nd

s

No

rth

ern

Ire

lan

d

Fra

nc

e

Wa

les

Sw

ed

en

UK

En

gla

nd

Ma

lta

Ire

lan

d

Lu

xe

mb

ou

rg

Cy

pru

s

Pe

rce

nta

ge

ch

an

ge

Source: GAD (UK and constituent countries) and Eurostat. Note: Eurostat also produce an alternative UK projection not shown here.


33

Socio-economic factors

DEPRIVATION


34

Ayrshire & Arran

33.8

Borders

35.7

Dumfries & Galloway

31.7*

Fife

39.2

Forth Valley

ND

Grampian

36.0

Greater Glasgow

57.3

Lanarkshire

32.6

Lothian

43.6

Orkney Islands

17.9

Shetland Islands

21.6

Tayside

45.4*

Western Isles

32.2

Highland

31.2

2006(* 2005)

Red cell use/1000 population by health board

Context: the population

demographics & clinical

practice of each area.

Why?


35

In patient/day case records per 1000 population

Health Board 2003 2005

Argyll & Clyde 205.3 214.5

Ayrshire & Arran 236.5 247.5

Borders 196.2 217.4

Dumfries & Galloway 206.8 214.5

Fife 196.5 204.4

Grampian 213.8 212.9

Greater Glasgow 340.4 349.5

Highland 261.5 269.4

Lanarkshire 238.0 238.3

Lothian 226.5 236.8

Orkney 162.4 175.4

Shetland 163.6 192.7

Tayside 240.8 242.5

Western Isles 249.6 229.5

Scotland Excl FV 244.8 251.5

Inpatient/daycase records

per 1000 popn


36

RBC units transfused per 1,000 Inpatient/Daycase records

Health Board 2003 2005

Argyll & Clyde 194.0 149.4

Ayrshire & Arran 141.1 138.2

Borders 169.9 161.6

Dumfries & Galloway 143.8 146.6

Fife 185.5 187.7

Grampian 179.3 172.6

Greater Glasgow 171.9 155.3

Highland 127.4 114.9

Lanarkshire 147.9 135.5

Lothian 213.8 189.5

Orkney 130.1 125.4

Shetland 113.2 18.6

Tayside 200.2 183.3

Western Isles 199.1 146.0

Scotland Excl FV 177.4 161.5

RBC units tx per 1,000

Inpatient/Daycase records

7


37

Scottish Index of Multiple Deprivation 2006

� " Deprivation takes many different forms in every known society. People can be said to be deprived if they lack the types of diet, clothing, housing,

household facilities and fuel and environmental, educational, working and

social conditions, activities and facilities which are customary, or at least widely encouraged and approved, in the societies to which they belong.“Townsend, P (1987) Deprivation, Journal of Social Policy 16 (1) pp 125-146

� 37 indicators

Income, Employment, Crime, Education, Health (including standardised mortality ratios), Housing, Geographic access to services

� SIMD 2006 divides Scotland into 6,505 ‘data zones’ with median

population size of 769. These are ranked from 1 ‘most deprived’ to 6,505

‘least deprived’


38


39

Greater Glasgow: Scottish Index of Multiple Deprivation2002/03 – 2005/06

A categorisation which divides the population of Greater Glasgow Health Board

into five equal categories based on the range of SIMD scores so that 20% of the population falls into each quintile (population weighted). Quintile 1 is the

least deprived, quintile 5 the most deprived.

Greater Glasgow Health Board Area

SIMD 2006

Quintile *

Inpatient/

Daycase

episodes

RBC units

Transfused

Platelet

units

Transfused

FFP units

Transfused

Cryo units

Transfused

Transfused

Patients

1 (Least Deprived) 15.3% 14.0% 14.5% 11.8% 10.7% 13.5%

2 14.2% 8.1% 8.1% 7.7% 6.3% 7.8%

3 19.0% 8.7% 9.5% 9.1% 10.6% 8.6%

4 21.8% 16.6% 18.5% 14.4% 18.9% 16.2%

5 (Most Deprived) 29.8% 52.6% 49.4% 57.1% 53.5% 53.8%


40

Alcoholic Liver Disease (ICD10 K70)

Red Blood Cell Units Transfused for patients with ALD*, 2002-2005

No Tx

Patients with

ALD

No Tx

patients with

ALD per

1,000

RBC Units

Transfused

RBC/

Tx

Patient

Ayrshire & Arran 314 0.2 2,591 8.3

Borders 31 0.1 369 11.9

Argyll & Clyde 396 0.2 3,762 9.5

Fife 227 0.2 2,302 10.1

Greater Glasgow 1,135 0.3 9,443 8.3

Highland 136 0.2 1,079 7.9

Lanarkshire 506 0.2 5,222 10.3

Grampian 287 0.1 2,553 8.9

Orkney 12 0.2 116 9.7

Lothian 640 0.2 6,341 9.9

Tayside 214 0.1 2,014 9.4

Western Isles 24 0.2 178 7.4

Dumfries & Galloway 53 0.1 583 11.0

Shetland 5 0.1 20 4.0

Scotland (excl FV) 3,980 0.2 36,573 9.2

* with any diagnosis of ICD10 K70 in their clinical history


41

Greater Glasgow ALD by SIMD quintile

No Patients Transfused who have a history of Alcoholic Liver Disease and were transfused in 2005

Alcoholic Liver Disease in Greater Glasgow, 2005

SIMD Quintile

No Patients

Tx with ALD

in 2005

RBC Units

Transfused in

2005

RBC per

patient Tx

(2005)

1 (Least depived) 12 57 4.8

2 10 113 11.3

3 18 118 6.6

4 39 242 6.2

5 (Most deprived) 173 1,264 7.3

Greater Glasgow 252 1,794 7.1


42

From now on…

• NHS Scotland Account for blood: data

warehouse development with automated harvest of standardised data from hospital

blood bank systems.

• Finally – it is adequately funded

8


43

Needs Assessment:

• How can we use this data - in UK or

similar setting


44

Needs Assessment:

How can we use this data - in resource

restricted setting

1

National Blood Collection and UtilizationNational Blood Collection and Utilization

andand

Blood Availability and Safety Information System Blood Availability and Safety Information System

(BASIS)(BASIS)

Jerry A. Holmberg, Jerry A. Holmberg, Ph.DPh.D, MT(ASCP)SBB, MT(ASCP)SBB

Senior Advisor for Blood PolicySenior Advisor for Blood Policy

Office of the SecretaryOffice of the Secretary

Office of Public Health and ScienceOffice of Public Health and Science

Aggregated Blood Report from Aggregated Blood Report from

AABB (ARC and ABC facilities)AABB (ARC and ABC facilities)

US Blood Centers Estimated Days of Supply

January 29, 2010

6.8

4.0

6.7

3.1 4.6

6.9

14.2

7.2

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

Blood Groups/Types

Esti

mate

d D

ays

O +

O -

A +

A -

B +

B -

AB +

AB -

Aggregated Blood Report from Aggregated Blood Report from

AABB (ARC and ABC facilities)AABB (ARC and ABC facilities)

Estimated Quantity In Blood Centers and Hospital

January 29, 2010

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

O + O - A + A - B + B - AB + AB -

Blood Type

Qu

an

tity

of

Blo

od

Estimated In Blood Center

307,450

Fixed estimate In hospital

based on assumption of

constant 6 day supply, i.e.,

281,731

Estimated US Blood SupplyEstimated US Blood Supply

Jan 29, 2010Jan 29, 2010

589,181589,181281,731281,731307,450307,450TotalTotal

6,1816,1812,8172,8173,3643,3647.27.2ABAB--

28,40128,4018,4528,45219,94919,94914.214.2AB+AB+

9,3599,3595,6355,6353,7243,7244.04.0BB--

54,68754,68725,35625,35629,33129,3316.96.9B+B+

29,96029,96016,90416,90413,05613,0564.64.6AA--

204,124204,12495,78895,788108,336108,3366.86.8A+A+

30,05330,05319,72119,72110,33210,3323.13.1OO--

226,416226,416107,058107,058119,359119,3596.76.7O+O+

Estimated Estimated

US Blood US Blood

Supply Supply

(RBC)(RBC)

Estimated Estimated

Hospital Hospital

Inventory: Inventory:

constant 6 constant 6

day supplyday supply

BloodBlood

Distribution Distribution

InventoryInventory

Estimated Estimated

Days of Days of

SupplySupply

Blood Blood

Groups/ Groups/

TypeType

ImpressionImpression

The blood supply is adequate to meet needs with The blood supply is adequate to meet needs with just over 6 just over 6 ½½ days supply of O Positive blood days supply of O Positive blood and just over 3 days supply of O Negative blood and just over 3 days supply of O Negative blood available at blood centers across the nation.available at blood centers across the nation.

Hospital inventory shortage reporting in the Blood Hospital inventory shortage reporting in the Blood Availability and Safety Information System Availability and Safety Information System (BASIS) continue to reflect instances of RBC (BASIS) continue to reflect instances of RBC and platelet shortages; however, alternate and platelet shortages; however, alternate source purchases remain relatively low.source purchases remain relatively low.

Platelet inventories continue to appear tight as a Platelet inventories continue to appear tight as a national aggregate.national aggregate.

BASIS ReportBASIS Report

Represents approximately 95 Sentinel Hospitals reporting consistently

2

BASIS ReportBASIS Report


BASIS Hospital Red Cell SupplyBASIS Hospital Red Cell Supply

(All Group/Types)(All Group/Types)


BASIS Hospital Platelet SupplyBASIS Hospital Platelet Supply


BASIS ShortagesBASIS Shortages






3

National Blood Collection and National Blood Collection and

Utilization Survey OverviewUtilization Survey Overview�� IntroductionIntroduction

�� MethodsMethods

�� Key FindingsKey Findings

�� BiovigilanceBiovigilance

�� Hospital Costs of BloodHospital Costs of Blood

�� Collection and Processing Collection and Processing ExperienceExperience

�� Transfusion Experience Transfusion Experience

�� Cellular Therapy ProductsCellular Therapy Products

�� Historical PerspectivesHistorical Perspectives

�� Current Issues in Transfusion and Current Issues in Transfusion and TransplantationTransplantation

www.hhs.gov/bloodsafety

Whole Blood and Whole Blood and

Red Blood Cell ApheresisRed Blood Cell Apheresis

-- 27.6%*27.6%*463,000463,000335,000335,00093,00093,000242,000242,000WB WB

AutologousAutologous

93.7% *93.7% *836,000836,0001,619,0001,619,00016,00016,0001,603,0001,603,000RBC RBC

ApheresisApheresis

0.5% 0.5% 14,087,00014,087,00014,151,00014,151,000665,000665,00013,486,00013,486,000WB WB

AllogeneicAllogeneic

4.3%4.3%15,503,00015,503,00016,174,00016,174,000796,000796,00015,378,00015,378,000TotalTotal

-- 40.3%*40.3%*117,000117,00070,00070,00022,00022,00047,00047,000WB DirectedWB Directed

Per Cent Per Cent

Difference Difference

((∆∆) ) TotalTotalTotalTotalHospitalHospitalBlood Blood

CenterCenter

2004200420062006Type of Type of

RBC RBC

CollectionCollection

Estimated Collections by Blood Centers and HospitalsEstimated Collections by Blood Centers and Hospitals

• May not be a appreciable increase due to blood centers were not weighted in 2004

• Significant Difference (*) from 2004 to 2006• 95% Confidence Intervals calculated

2006 Key Findings: Donors2006 Key Findings: Donors

�� 12,142,000 donors presented12,142,000 donors presented

�� 9,554,000 allogeneic donors9,554,000 allogeneic donors

��2,726,000 first2,726,000 first--time donors (28.5%)time donors (28.5%)

��6,828,000 repeat donors (71.5%)6,828,000 repeat donors (71.5%)

�� Repeat donors provided 11,697,000 Repeat donors provided 11,697,000

donations donations –– 1.7 donations/donor1.7 donations/donor

2006 Key Findings2006 Key Findings

�� 30,044,000 components transfused30,044,000 components transfused

�� 14,650,000 red cells14,650,000 red cells

�� 10,388,000 platelet concentrate eq.10,388,000 platelet concentrate eq.

�� 4,010,000 plasma4,010,000 plasma

�� 993,000 cryoprecipitate993,000 cryoprecipitate

Whole Blood and Whole Blood and

Red Blood Cell ApheresisRed Blood Cell Apheresis

-- 44.9%*44.9%*274,000274,000151,000151,00014,00014,000137,000137,000Rejected on Rejected on

TestingTesting

4.3%4.3%15,503,00015,503,00016,174,00016,174,000796,000796,00015,378,00015,378,000TotalTotal

5.2%5.2%15,299,00015,299,00016,023,00016,023,000782,000782,00015,241,00015,241,000Available Available

SupplySupply

Per Cent Per Cent



CenterCenter

2004200420062006Type of Type of

RBC RBC

CollectionCollection

Estimated Collections by Blood Centers and HospitalsEstimated Collections by Blood Centers and Hospitals

• Significant Difference (*) from 2004 to 2006

• 95% Confidence Intervals calculated

4

Red Blood Cell TransfusionsRed Blood Cell Transfusions

-- 30.3%*30.3%*271,000271,000189,000*189,000*182,000182,0007,0007,000AutologousAutologous

504.8%*504.8%*59,00059,000357,000*357,000*352,000352,0005,0005,000PediatricPediatric

1.8%1.8%13,728,00013,728,00013,978.00013,978.00013,262,00013,262,000716,000716,000Allogeneic Allogeneic

(not (not

directed)directed)

3.2%3.2%14,191,00014,191,00014,650,00014,650,00013,921,00013,921,000729,000729,000TotalTotal

-- 4.6%4.6%132,000132,000126,000126,000126,000126,00000DirectedDirected

Per Cent Per Cent



CenterCenter

2004200420062006Type of Type of

RBC RBC

TransfusionTransfusion

Estimated Transfusions by Blood Centers and HospitalsEstimated Transfusions by Blood Centers and Hospitals

• Significant Difference (*) from 2004 to 2006

• 95% Confidence Intervals calculated

WB and RBC RecipientsWB and RBC Recipients

�� 3.0 units per recipient (3.0 units per recipient (unweightedunweighted))

�� 8,275,000 allogeneic units (8,275,000 allogeneic units (inclincl directed)directed)

�� 2,740,000 recipients 2,740,000 recipients

�� 2004: 2004: 2.7 units per recipient2.7 units per recipient

�� Extrapolation of ratio of Extrapolation of ratio of transfused/recipient transfused/recipient

�� Estimated 5 M recipientEstimated 5 M recipient

�� 6.6% decrease in transfusion recipients 6.6% decrease in transfusion recipients (compared to 2004)(compared to 2004)

Platelets TransfusedPlatelets Transfused

9.0%9.0%8,343,0008,343,0009,092,000 9,092,000

(1,515,000)(1,515,000)8,681,0008,681,000411,000411,000Apheresis Apheresis

PlateletsPlatelets

--15.7%15.7%1,537,0001,537,0001,296,0001,296,0001,073,0001,073,000223,000223,000WB Derived WB Derived

PlateletsPlatelets

5.1%5.1%9,881,0009,881,00010,388,000*10,388,000*9,754,0009,754,000634,000634,000TotalTotal

Per Cent Per Cent



CenterCenter

2004200420062006Type of Type of

Product Product

TransfusedTransfused

Estimated Transfusions by Blood Centers and HospitalsEstimated Transfusions by Blood Centers and Hospitals

• Parenthesis notation is apheresis units including splits

• Significant Difference (*) from 2004 to 2006• 95% Confidence Intervals calculated

Apheresis

83%

WBDP

17%

WBDP

Apheresis

Platelet Dose for TransfusionsPlatelet Dose for Transfusions

0

10

20

30

40

50

60

Per Cent

of

Hospitals

5 or

less

7 9 >10

Dose of Platelet

Concentrate

2001

2004

2006

FFP

77%

Jumbo

Plasma

2%

Pediatric

1%

Plasma w/i 24

hours

15%

Cryo-

Reduced

Plasma

5%FFP

Plasma w/i 24 hours

Jumbo Plasma

Pediatric

Cryo- ReducedPlasma

Plasma Type TransfusedPlasma Type Transfused

3%3%13,00013,000Whole BloodWhole Blood

1%1%5,0005,000DirectedDirected

401,000401,00016,745,00016,745,000WB/RBCWB/RBC

63%63%252,000252,000AllogeneicAllogeneic

Outdate of Red CellsOutdate of Red Cells

Processed/ Processed/

producedproduced

33%33%131.000131.000AutologousAutologous

Per Cent Per Cent

OutdateOutdateTotal Total

OutdateOutdateComponentComponent

Allogeneic

63%

Directed

1%

Whole Blood

3%

Autologous

33%

Allogeneic

Autologous

Directed

Whole Blood

5

Current Issues in TransfusionCurrent Issues in Transfusion

�� Blood inventory shortages for nonBlood inventory shortages for non--surgical proceduressurgical procedures

2006

� 13.5% (231/1707) reported at

least one day shortage

� Mean number of days was 22

� Six (6) hospitals reported 365 days the blood needs were not

met.

� Number of days regular or

standing order was incomplete

� 44,910 total days (estimated?)

� On any given day, 123

hospital did not have their standing order met.

2004

� 16% (257/1604) reported at

least one day shortage

� Mean number of days was 19.27

� Eight (8) hospitals reported 365 days the blood needs were not

met.

Trends in WB and RBC Collections Trends in WB and RBC Collections

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

1989 1992 1994 1997 199 2001 2004 2006

Survey Year

Millio

ns o

f U

nit

s

Total

Allogeneic

Autologous

Trends in WB and RBC Collections Trends in WB and RBC Collections

and Transfusionsand Transfusions

10

11

12

13

14

15

16

17

1989 1992 1994 1997 1999 2001 2004 2006Survey Year

Mil

lio

ns o

f U

nit

s

Collections

Transfusions

Available Collections1.3 M

150K

Trends in Estimated Rates of Blood Trends in Estimated Rates of Blood

Collection and Transfusion in the Collection and Transfusion in the

US, 1980US, 1980--20062006

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

1980 1982 1984 1986 1987 1989 1992 1994 1997 1999 2001 2004 2006

Survey Year

Un

its

/10

00

US

Po

pu

lati

on

Transfusions ± 95% Cl/1000 pop. (all ages)

Collections ±95%CI/1000 pop. (ages 18-64)

2006: 48.9

2006: 84.1

Comparison in Developed Comparison in Developed

Countries Countries

M 53.2%M 53.2%

F 46.8%F 46.8%

<39 9.4%<39 9.4%

4040--59 18.2%59 18.2%

> 60 72.4%> 60 72.4%

54.0854.08

58.6 (200058.6 (2000--

2002)2002)

DenmarkDenmark

M 52.9%M 52.9%

F 47.1%F 47.1%

M 52.5%M 52.5%

F 47.5%F 47.5%

M 50.4%M 50.4%

F 49.6F 49.6

M 48.5%M 48.5%

F 51.5%F 51.5%

GenderGender

<39 9.8%<39 9.8%

4040--59 15.1%59 15.1%

> 60 75.2%> 60 75.2%

<40 15.4%<40 15.4%

4040--70 36.7%70 36.7%

> 70 47.9%> 70 47.9%

<40 14.4%<40 14.4%

4040--70 38.4%70 38.4%

> 70 47.2%> 70 47.2%

<41 18.8%<41 18.8%

4141--65 27.8%65 27.8%

>65 53.3%>65 53.3%

Recipient Recipient

AgeAge

45.3 (199645.3 (1996--

2002020020282844.944.948.75 (2001)48.75 (2001)

48.9 (2006)48.9 (2006)

Units of Units of

RBC per RBC per

1000 1000

PopulationPopulation

SwedenSwedenAustraliaAustraliaEnglandEnglandUSUS

Kamper-Jorgensen Transfusion 2009; 49:888-894

Cobain Transfusion Medicine 2007, 17, 10-15

In Developed CountriesIn Developed Countries

Estimation based on PopulationEstimation based on Population

��Age and sex distribution similar except Age and sex distribution similar except

more men transfused with platelets and more men transfused with platelets and

plasmaplasma

��More blood used in older populationMore blood used in older population

��Cardiovascular surgery predominated Cardiovascular surgery predominated

highest usehighest use

6

Blood SystemsBlood Systems

United Blood ServicesUnited Blood Services�� 2007 2007

�� 870,000 collects that serve 500 hospitals in 18 states 870,000 collects that serve 500 hospitals in 18 states

�� 1/3 of continental US1/3 of continental US

�� Estimation of blood needsEstimation of blood needs�� Roll up of individual hospital distribution for most recent 60 Roll up of individual hospital distribution for most recent 60

months (5 yrs) months (5 yrs) –– distribution is assumed ~ to transfusions distribution is assumed ~ to transfusions (return policy)(return policy)

�� Application of statistical software package (Decision Pro)Application of statistical software package (Decision Pro)

�� Unfilled orders are tracked solely for customer satisfactionUnfilled orders are tracked solely for customer satisfaction

�� Forward looking estimates do not currently take into Forward looking estimates do not currently take into consideration planned changes in hospital services (e.g. consideration planned changes in hospital services (e.g. cardiac surgery)cardiac surgery)

�� C:T ratio is not used as BSI collects no transfusion dataC:T ratio is not used as BSI collects no transfusion data

Information obtained via phone interview by Karen Lipton

American Red CrossAmerican Red Cross

�� 20072007�� 6,332,000 collections that served over 2500 hospitals 6,332,000 collections that served over 2500 hospitals

throughout USthroughout US

�� Roll up of individual hospital utilization data on the most receRoll up of individual hospital utilization data on the most recent nt 12 months12 months

�� Application of Sales and Operation Planning (SNOP) to create Application of Sales and Operation Planning (SNOP) to create a 12 month projectiona 12 month projection

�� Based on distribution, assumption that distribution ~ transfusioBased on distribution, assumption that distribution ~ transfusion n

�� Annual survey of hospitals to determine new changes in Annual survey of hospitals to determine new changes in services that might change utilization services that might change utilization

�� Since 2009, review of unemployment statistics which seem to Since 2009, review of unemployment statistics which seem to track blood utilization figures due to loss of health insurance track blood utilization figures due to loss of health insurance coverage coverage


American Red CrossAmerican Red Cross

�� The ARC business planning process consist of The ARC business planning process consist of

the following elements:the following elements:

�� Monthly Sales and Operations Planning ProcessMonthly Sales and Operations Planning Process

�� Monthly Manufacturing ReviewMonthly Manufacturing Review

�� Weekly Master Production SchedulingWeekly Master Production Scheduling

�� Daily Inventory Management ProcessDaily Inventory Management Process

�� All these different processes work off the same All these different processes work off the same

set of base numbers through a series of set of base numbers through a series of

connected information systems.connected information systems.


1

Estimating Blood RequirementsEstimating Blood RequirementsEstimating Blood RequirementsEstimating Blood Requirements

Blood SafetyBlood SafetyBlood SafetyBlood SafetyGeneva, SwitzerlandGeneva, SwitzerlandGeneva, SwitzerlandGeneva, SwitzerlandFebruary 4, 2010February 4, 2010February 4, 2010February 4, 20102006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population National Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services only

0000 2222 4444 6666 8888 10101010 12121212 14141414 16161616 18181818South Africa

Botswana

Namibia

Guyana

Zambia

Cote d'Ivoire

Rwanda

Uganda

Kenya

Mozambique

Tanzania

Haiti

Nigeria

Ethiopia

Units collected / 1000 population

Zambia Blood Donations 2003Zambia Blood Donations 2003--08080

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

110000

2003 2004 2005 2006 2007 2008

Un

its

co

lle

cte

d

Family/Replacementdonors

Voluntary non-remunerated donors

Regular donors

Moving TargetMoving TargetMoving TargetMoving Target--------PopulationPopulationPopulationPopulation

Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 Infrastructure and Collections in 11 countries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coveragecountries without 100% NBTS coverage68,05640,616990Zambia 130,000103,00055Uganda 109,471070Tanzania 16,987090Nigeria 115,07167,105140111Mozambique 123,78741,86965Kenya 17,0948,711175Haiti 5,4754,00851Guyana 32,44217,208124Ethiopia 92,00967,78022Cote d’Ivoire 22,23011,58322Botswana NBTS Units NBTS Units NBTS Units NBTS Units 2007200720072007NBTS Units NBTS Units NBTS Units NBTS Units 2003200320032003Centers Centers Centers Centers 2007200720072007Centers Centers Centers Centers 2003200320032003CountryCountryCountryCountry

MMWR November 28, 2008/57(47):1273-1277

2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population National Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services onlyNational Blood Services only0000 2222 4444 6666 8888 10101010 12121212 14141414 16161616 18181818South Africa

Botswana

Namibia

Guyana

Zambia

Cote d'Ivoire

Rwanda

Uganda

Kenya

Mozambique

Tanzania

Haiti

Nigeria

Ethiopia


2

CoverageCoverageCoverageCoverage 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population 2006 Blood collections per 1000 population All collections All collections All collections All collections All collections All collections All collections All collections (Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)(Red = Hospital collected/tested)0000 2222 4444 6666 8888 10101010 12121212 14141414 16161616 18181818South Africa

Botswana

Namibia

Guyana

Zambia

Cote d'Ivoire

Rwanda

Uganda

Kenya

Mozambique

Tanzania

Haiti

Nigeria

Ethiopia


Table 11: Table 11: Table 11: Table 11: Table 11: Table 11: Table 11: Table 11: Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006Number of units of blood collected in 2006174,004 (100)174,004 (100)174,004 (100)174,004 (100)TotalTotalTotalTotal 84,505 (48.6)84,505 (48.6)84,505 (48.6)84,505 (48.6)TertiaryTertiaryTertiaryTertiary 87,7575 (50.4)87,7575 (50.4)87,7575 (50.4)87,7575 (50.4)SecondarySecondarySecondarySecondary 1,742 (1)1,742 (1)1,742 (1)1,742 (1)PrimaryPrimaryPrimaryPrimary Number of units of blood Number of units of blood Number of units of blood Number of units of blood donations (%)donations (%)donations (%)donations (%)Type of facilityType of facilityType of facilityType of facility Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood Table 12: Estimated number of blood donations in 2006donations in 2006donations in 2006donations in 2006donations in 2006donations in 2006donations in 2006donations in 2006

1,784,4651,784,4651,784,4651,784,465112112112112174,004174,004174,004174,004TotalTotalTotalTotal 84,50584,50584,50584,5054848484817601760176017604848484884,50584,50584,50584,505TertiaryTertiaryTertiaryTertiary 1,534,1221,534,1221,534,1221,534,12294494494494416221622162216225454545487,75787,75787,75787,757SecondarySecondarySecondarySecondary 165,838165,838165,838165,838952952952952174.2174.2174.2174.2101010101,7421,7421,7421,742PrimaryPrimaryPrimaryPrimary Total Total Total Total donationsdonationsdonationsdonationsTotal # Total # Total # Total # of of of of facilitiesfacilitiesfacilitiesfacilitiesAverage Average Average Average per siteper siteper siteper site# of # of # of # of sites sites sites sites visitedvisitedvisitedvisited# of # of # of # of unitsunitsunitsunitsGroupsGroupsGroupsGroups

Data SourcesData SourcesData SourcesData SourcesData SourcesData SourcesData SourcesData Sources• Rapid assessmentRapid assessmentRapid assessmentRapid assessment• SurveysSurveysSurveysSurveys• Ministry DataMinistry DataMinistry DataMinistry Data

3

Stepwise Stepwise Stepwise Stepwise approachapproachapproachapproach----infrastructureinfrastructureinfrastructureinfrastructure• OrganizationOrganizationOrganizationOrganization– Hospital based?Hospital based?Hospital based?Hospital based?– Regional?Regional?Regional?Regional?– National?National?National?National?• Incorporate Ministry, Private, NGO, Faith based?Incorporate Ministry, Private, NGO, Faith based?Incorporate Ministry, Private, NGO, Faith based?Incorporate Ministry, Private, NGO, Faith based?• Usage Usage Usage Usage vsvsvsvs demanddemanddemanddemand– Family replacement Family replacement Family replacement Family replacement vsvsvsvs VolunteerVolunteerVolunteerVolunteer– TransitionTransitionTransitionTransition————utilization increase due to previous utilization increase due to previous utilization increase due to previous utilization increase due to previous unmet demandunmet demandunmet demandunmet demand• Data management capabilityData management capabilityData management capabilityData management capability--------inventoryinventoryinventoryinventory– Manual/paperManual/paperManual/paperManual/paper– ElectronicElectronicElectronicElectronicStepwise approachStepwise approachStepwise approachStepwise approach————clinical issuesclinical issuesclinical issuesclinical issues• CompositionCompositionCompositionComposition– Whole bloodWhole bloodWhole bloodWhole blood– Pediatric unitsPediatric unitsPediatric unitsPediatric units– ComponentsComponentsComponentsComponents• RBCsRBCsRBCsRBCs, FFP, platelets, FFP, platelets, FFP, platelets, FFP, platelets• Clinical guidelinesClinical guidelinesClinical guidelinesClinical guidelines– Physician familiarityPhysician familiarityPhysician familiarityPhysician familiarity————practicepracticepracticepractice– Training on new component optionsTraining on new component optionsTraining on new component optionsTraining on new component options• LaboratoryLaboratoryLaboratoryLaboratory– Baseline valuesBaseline valuesBaseline valuesBaseline values– MonitoringMonitoringMonitoringMonitoring

SummarySummarySummarySummarySummarySummarySummarySummaryCollection Utilization

Processing

Comprehensive Blood Safety

•Communication

partnerships (MDG 8)•TTI Prevention (MDG6)

•Work Force Development

•Health Care Worker Safety

•IT systems•Quality Systems

•Health Education•Waste Management

•TTI Prevention

(MDG6)•Quality Systems


•Health Care Worker Safety

•IT System•Waste Management

•TTI Prevention (MDG 6)

•Maternal Health (MDG 5)•Child Health (MDG 4)

•Trauma (MVA)•HIV/AIDS Care and Rx

•Quality Systems• Patient Safety


•Worker Safety•IT System

•Waste Management

Blood Supply and Demand:

Georgetown, Guyana

November, 2007

Sridhar Basavaraju, MDMedical Officer

Centers for Disease Control and PreventionAtlanta, USA

Objectives

• Country and National Blood Transfusion Service background

• Investigation background

• Case definitions

• Methods

• Results

• Shortage calculations

• Lessons learned

Guyana

• National borders:

Venezuela, Brazil,

Suriname, Caribbean Sea

• Population: 750,000 (30%

live in Georgetown)

• Gross National Product per

capita: <$1,000

Guyana National Blood Transfusion

Service (NBTS)

• Total Collections, 2007: 5,475 units (7.3 units

per 1,000 population)

• 90% units distributed: whole blood or packed

red cells

• 80% of collections: distributed to Georgetown

Public Hospital Corporation (GPHC)

• 60% of collections: voluntary, non-

remunerated donors

Study Background

• December, 2007: NBTS review suggests 60% of all blood orders unmet

• GPHC-NBTS opinion differences

– Reports of delayed surgeries

– Inappropriate requests

– Blood returned unused

• Field investigation to determine:

– Was enough blood collected?

– Was there a true shortage of blood?

Case Definitions

Case Definition

• Unit: An individual blood product – WB, PRC,

FFP, PLT, Cryo

• Issued: Unit given by NBTS to ward for the

purpose of transfusion

• Filled: Unit is prepared by NBTS and ready to

be issued. A unit must be filled before it is

issued. Not all filled units are issued

Case Definition

• Order: A unit is requested by GPHC by

submitting a written blood request form.

• Rejected: The order by GPHC ward is refused

by the NBTS due to a problem with

information provided to NBTS

• Unused: Issued unit is not transfused into a

patient by ward.

Case Definition

• Returned: An issued unit is returned to NBTS

unused by ward

• Reissued: A returned unit is given by NBTS to

ward for the purpose of transfusion

• Expired: A unit is no longer fit to be transfused

as > 35 days have lapsed since being filled

Case Definition

• Unit not required: An order which is stated by

ward to be no longer necessary. NBTS will not

fill this order

• Shortage: An order not filled by NBTS as the

specific blood product is not available.

Blood Request Form

Methods

Methods

• Audit of NBTS data for November 2007

• 3 Logbooks in NBTS

– Book 1: Book of Cross matched issued blood

– Book 2: Book of daily requests

– Book 3: Book of returned units

Methods

• Blood Request Form Files

– Issued

– Filled and not picked up by ward

– Rejected orders

– Orders no longer required

• Comparison between logbooks and Blood

Request Form files

Results

Units Ordered by GPHC – November, 2007

Packed Red Packed Red

CellCell11301130

Whole BloodWhole Blood 4141

PlateletPlatelet 22

Fresh Frozen Fresh Frozen

PlasmaPlasma133133

CryoprecipitateCryoprecipitate 2222

TotalTotal 13281328

Units Issued to GPHC November, 2007

Packed Red CellPacked Red Cell 431431

Whole BloodWhole Blood 2222

PlateletsPlatelets 00

Fresh Frozen PlasmaFresh Frozen Plasma 5959

CryoprecipitateCryoprecipitate 5959

TotalTotal 571571

Packed Packed

Red CellRed Cell11301130

Whole Whole

BloodBlood4141


Fresh Fresh

Frozen Frozen

PlasmaPlasma

133133

CryoCryo.. 2222

TotalTotal 13281328

Packed Packed

Red CellRed Cell431431

Whole Whole

BloodBlood2222


Fresh Fresh

Frozen Frozen

PlasmaPlasma

5959

CryoCryo.. 5959

TotalTotal 571571

GPHC NBTS

Overview of Issued and Non-issued units

Total units

ordered:

1328

Issued units:

571

Not Issued Units:

757

Issued & not

returned : 427

Request

cancelled: 482

Filled & not

issued: 86

Request rejected:

21

Returned

unused:

144

Expired: 6

Returned unused &

reissued in December,

2007: 3

Returned unused &

reissued in November,

2007: 116*

Shortage before

accounting for returned

& reissued units: 168

Actual

shortage:

52 (168-

116)

Reason not issued

Unaccounted: 19

Shortage Calculation

Georgetown Public Hospital Corporation

Blood Unit Requests: November 2007

Total Units Ordered: 1328

Units undelivered: 757

Cancelled 482

Filled, uncollected

86

Rejected 21

Shortage 168

Units Delivered: 571

Returned Unused 144

Reissued 116

Expired/Unaccounted 25

Transfused 543

Actual Shortage

168

116-

52 units

Shortage Calculation

52

543 + 52* 100 = 8.7%

Guyana total collections, 2007: 7.3 units per 1,000 population

WHO recommendation: 10-20 units per 1,000 population per year

(Calculated Shortage)

(Calculated Demand)

Shortage

Limitations

• Limited data: 1 month only (November, 2007)

– Seasonal disease/injury trends

– Variations in blood collection patterns

• Data represents GPHC

– Other local hospitals not included

– Not nationally representative

• NBTS collections only included

Lessons Learned

• 7.3 units collected per 1,000 population

resulted in an 8.7% shortage

• Blood collection requirements

recommendations should include capacity to

conduct transfusions

• Recommendations should account for stock

management (to reduce wastage)

Acknowledgements

• Guyana NBTS

– Clem McEwan

– Olwyn John

– Bonita Richards

• CDC

– Claudette Harry

– LaMar Hasbrouck

– Nicolette Henry

– Lawrence Marum

– John P. PitmanThe findings and conclusions in this presentation are those of

the author(s) and do not necessarily represent the views of the Centers for Disease Control and Prevention

Questions/Discussion

1

Level of Resources to Ensure Safe Blood in Africa

Pamela Rao

Associate Director, Global Health and Development Strategies

Social & Scientific Systems, Inc.

Working Group 2—SSS and AABB

Challenges

Paucity of relevant empirical data in Africa

• Data on current capacity of BTS to collect, test, process and distribute blood. What proportion of the current need is met?

� Population in need of Safe Blood – epidemiology of disease conditions that require Safe Blood transfusion

� Current access of this group to health services and potentially to Safe Blood when needed

� Obtaining available cost for Safe Blood strategy, particularly in the presence of multiple funding sources..

- Forecasting scale-up costs for national programs in the

absence of data – almost impossible..

Hence, a model-based approach….

…..and it became “ 2-7-10 24/7” job !!

Comparative Analysis of Methods

� WHO Method 3, Module 1 (Requirement of blood

units = ~2% of population)

� WHO Manual—Costing Blood Transfusion Services,

1998/2001

� GOALS Model—Costing guidelines for HIV/AIDS strategies

� RDM/UNGASS Model

Strengths of RDM Approach

� Relatively simple modeling approach

� Resource estimation for individual HIV/AIDS intervention rather

than resource optimization across several interventions

� Population-based estimates therefore, addresses the

magnitude of safe blood problem in the country

� Health system performance— access to health services and

potentially access to safe blood

� Allows for cost of scaling-up therefore, addresses unmet need

� Internationally accredited—3 pieces of work (WB-MAP,

UNGASS, & Tx & Care)

Principal Steps Involved in the Model

� Establishing the size of populations that are at greatest need

and will benefit from Safe Blood strategy – Target Group

� Proportion of Target group that has access to health

services – Potential Target Group (PTG). Using PTG to

determine current and future levels of coverage.

� Estimating costs using project level cost data to scale up

programs to desired coverage levels and or feasible

coverage levels.

RDM Adapted for BTS

2

Factors Considered in Choosing Sample Countries

� Strength of blood program, country-specific health

system performance indicator, Human Development

Index (HDI)

� Size of population, HIV prevalence, Malaria status

� Geographic representation (East, South, West Africa)

� Representation of 4 organizational models for BTS

BTS Composite Indicator

� HDI (life expectancy, literacy, GDP)

� Health System Performance Indicator (WHR 2000)

� BTS indicator

• Policy variables (25%)

• Operations variables (50%)

• Quality systems variables (25%)

Size of Population, HIV Prevalence, and Malaria Status

Geographic Representation

Nigeria

Cote d’Ivoire

Kenya

Mozambique

Representation of 4 Organizational Models for BTS

� Centralized/national: One national center controls the

services for the whole country with or without regional centers

� Regionalized: Regional centers operate with some autonomy,

with degree of national control

� Hospital-based: Each hospital runs its own services with or

without coordination at national level

� Mixed: Combination of hospital-based and some regional and

national coordination (incomplete coverage)

Sample Countries for Varied Analysis

Hospital-basedW. AfricaWeakNigeria

MixedS. AfricaWeakMozambique

RegionalizedE. AfricaMediumKenya

Centralized/National

W. AfricaRel. strongCote d’ Ivoire

Organizational

Model

Geographic

LocationCapacityCountry

3

Providing a Model to Estimate the Level of Resources for Safe Blood

1. Identifying target group requiring Safe Blood

Sources to Identify the Target Groups

� Country-specific literature review of published

and grey literature

� Preliminary analysis of ongoing large study on

use of blood in Cote d’ Ivoire

� MOH applications and TA providers baseline

assessment report, if available

� Pediatric anemia (severe 8g/dL.), maternal iron

deficiency, iron-deficient diets, malaria, intestinal

helminthes, low-birth weight babies (<2,500g)

� Maternal severe anemia (WHO Criteria: Hemoglobin concentration <7.0 g/dl)

� Postpartum hemorrhage

� Shock/trauma/burns (accidents etc.)

� Elective surgery

� Adult anemia –(elderly – 64 years – GI bleeds etc.)

� Others

Conditions Requiring Blood Transfusion in Rank Order

� Children under 5

� Pregnant women

� Population with severe adult anemia (women and men)

� % of population undergoing elective surgery

� % of population undergoing trauma, shock and burns

� Others

Target Groups Requiring Safe Blood in Africa

Providing a Model to Estimate Level of Resources for Safe Blood in Africa

1. Identifying priority target group requiring Safe Blood

2. Estimating the size of priority target groups

Country-Specific Anemia Rates

30.0%

40.0%

51.7%

69.2%

Nigeria

30.0%30.0%30.0%Men3

40.0%40.0%40.0%Women2

52.3%46.7%45.9%Pregnant women

79.6%60.0%65.5%Children <51

MozambiqueKenyaCôte d’Ivoire

Source: 1

UNICEF. State of the Children 20062

IFPRI- Harvest plus3

WHO/NHD/01.3. Iron deficiency anemia: Assessment, prevention, and control

4

Estimating the Target Group Size Likely to Be Transfused—

Severe Anemia Rates as proportion of those anemic

3%Anemia in women (15-64 years) less live births, year 2004

15%Shock/trauma/burns/elective surgery

2%Anemia in men (15-64 years)

20%Low birth weight (based on annual number of live births)

20%Anemia in pregnant women (underestimated–calculated from annual number of live births)

10%Anemia in children < 5 years

Size of the Target Group—Population-Based Estimates

125.7419.1132.9816.94Total population of country (in millions)

2,862,678500,300746,300295,373Shock/trauma/ burns/surgery

745,220115,350132,200112,370Low birth weight

10,473,000

11,362,800

2,751,991

14,414,360

Nigeria

1,491,0002,739,0001,446,000Men

1,816,4002,963,2001,615,600Women

402,187617,37430,339Pregnant women

2,362,5283,340,2001,708,240Children <5

MozambiqueKenyaCôte

d’Ivoire

Size of Target Group-Conservative Estimates—Why?

� Age group: 5–15 not covered

� There seems to be significant proportion of men receiving blood in CI–more research is required

� Population attributable fraction of adult malaria due to HIV with HIV prevalence of 8% among adults is about 5% for clinical malaria

� Population attributable fraction of adult malaria due to HIV with HIV prevalence of 30% among adults is about 35% for clinical malaria

� Shock, trauma, surgery is likely to be more

� Overall number could be 10–25% more

Triangulating Population-Based Target Size

Data with Demand for Blood by Target Group

� Literature review

� CI blood use study

� MOH applications, if available

Proportion of Total Demand for Safe Blood Among Target Groups

� 50–60% children under 5

� 15–20% maternal

� Small % low-birth weight babies

� 2–5 % adult anemia

� 12–16% elective surgery, shock/trauma/burns

� Remaining for other causes

Justifications des Demandes de Produits Sanguins par Types

de Services: Périodes Février-Juillet 2004 et 2005

5

Triangulating Target Group Data With Available Country-Specific Data on ‘dd’

Proportions of PTGs requiring transfusions


13.76%15.04%15.14%11.79%Shock/trauma/burns/surgery

4.78%4.62%3.58%5.98%Low birth weight

6.71%

10.92%

17.64%

46.19%

Nigeria

5.97%7.41%7.70%Men

10.92%12.02%12.90%Women

16.12%16.70%16.15%Pregnant women

47.33%45.16%45.47%Children <5


Providing a Model to Estimate Level of Resources for Safe Blood

1. Identifying target groups

2. Estimating size of target groups in Africa

3. Estimating total PTG that may require blood

transfusion (i.e., proportion of the target group with access to health care services)

Proxy Indicators to Estimate Target Groups Access to

Health Services—Composite Indicators

For children

� Proportion of children who had completed the final

immunization dose for diphtheria, pertussis, tetanus (DPT3)

� % of children <5 with fever receiving anti-malarial drugs

� % of children < 5 with acute respiratory infections (ARIs) seen by a health worker

For pregnant women

� % of pregnant women who receive antenatal care—4 visits

� % of women giving birth who were attended by skilled health

personnel at birth

Access to Health Services

For Shock/Trauma/Burns, Surgery, and Adult Anemia

� Access to hospitals from published literature

Composite Indicators Used

20.00%19.20%15.80%21.00%Shock/trauma burns/surgery**

30.60%47.30%49.60%67.45%Low birth weight*

20.00%

20.00%

52.80%

30.60%

Nigeria

19.20%15.80%21.00%Men**

19.20%15.80%21.00%Women**

57.60%58.50%67.45%Pregnant women*

47.30%49.60%44.00%Children <5*


* Composite Indicator** Hospital Utilization Indicator

Country-Specific Estimates of PTGs

973,245199,588291,409156,806Total PTG

41,8925,7258,6556,073Men

85,88014,40917,6879,304Shock/trauma/burns/surgery

45,60710,91213,11415,159Low birth weight

125.74

68,177

290,610

441,079

Nigeria

19.1132.9816.94Total population of country (in millions)

10,46214,04610,178Women

46,33272,23340,929Pregnant women

111,748165,67475,163Children <5


6

Results—Magnitude of the ProblemProviding a Model to Estimate Level of Resources for Safe Blood

1. Identifying the TGs in Africa

2. Estimating the size of TG that may require blood transfusion

3. Developing country-specific estimates of PTG with health access needing transfusion

4. Determining average requirement of blood for each PTG to estimate requirement of blood for PTG

Average Number of Blood Units Per Case

Number of

blood unitsTarget group

2Men

2.5Women

3Shock/trauma/

burns/surgery

0.5Low birth weight

2.5Pregnant women

0.5Children <5

Total Number of Blood Units Required for PTG in a year


1,481,737275,993375,462212,986Total blood units

83,78411,45117,31012,146Men

257,64143,22653,06227,913Shock/trauma/burns/surgery

22,8045,4566,5577,579Low birth weight

170,442

726,526

220,540

Nigeria

26,15635,11425,446Women

115,830180,582102,321Pregnant women

55,87482,83737,581Children <5


Magnitude of the Problem –Base Year 2004 Providing a Model to Estimate Level of Resources for Safe Blood


2. Estimating the total TG that may require blood transfusion

3. Estimating the size of PTG with health access needing

transfusion

4. Determining average requirement of blood for each PTG

to estimate requirement of blood for PTG

5. Projecting growth over the next years

7

Growth Rates

� Preliminary Base Growth Factor was calculated by assuming that the growth factor for all countries for Sub-Saharan Africa (SSA) would range from a minimum of 0.1 to a maximum of 0.2.

� The minimum growth factor of 0.1 was assigned to the average per capita income of SSA countries with lower per

capita (per <$750) the maximum to per capita income > $4,000.

� Growth factors for all countries between the lowest income

and highest income groups were calculated by linear interpolation between 0.1 and 0.2 based on their per capita income relative to the average per capita income of the lowest

group to the average of the highest group.

Adjusted Growth Factor

� It has been observed that factors other than per capita

income influence performance of health systems and

potential expansion of BTS.

� To adjust the base growth factors for other factors, we

estimated regression equations expressing the coverage for

DPT as a function of GNI per capita and calculated the ratio

of observed coverage to predicted coverage. This ratio as a

proportion was used to adjust the base growth factor.

BTS Growth Factor

� We assumed the number of safe blood units provided would

increase in 2005 by 30% in Kenya and by a growth rate in

the other three countries in the same ratio to 30% as each

country’s adjusted growth factor is to Kenya’s adjusted

growth factor.

� The BTS growth factor (G) is defined as the proportion of

unmet need newly covered in 1 year. If At is the proportion

of unmet safe blood need that has been met in year t: At =

At-1 + (1 - At-1) * G.

Projecting Expansion of Blood Transfusion Services Capacity

Assumptions:

� Changes to BTS occur slowly over time—Max. 30%

increase in capacity

� Total need for safe units of blood (base year) will not

change during projection period i.e. increase in

access to health care will potentially increase “dd” for Safe Blood

Providing a Model to Estimate Level of Resources for Safe Blood


2. Estimating the total TG that may require blood transfusion

3. Estimating the size of PTG with health access needing

transfusion

4. Determining average requirement of blood for each PTG to

estimate requirement of blood for PTG

5. Projecting growth over the next years

6. Applying unit cost of safe blood to estimate level of

resources

Determining Unit Cost of Safe Blood

1. WHO cost projections by Working Group 1

2. Current cost of Safe Blood from the current

operating budget in Cote d’Ivoire

3. Consultation and personal communication with

Emergency Plan TA providers

4. Literature review – published and unpublished

documents

8

Blood Transfusion Costs

BLOOD TRANSFUSION SERVICECosts Allocated by Activity

Total Costs

Blood DonorRecruitment

Blood CollectionBlood testing &

ProcessingBlood Storage &

Distribution

Capital costs+

Recurrent costs

Capital costs+

Recurrent costs

Capital costs+

Recurrent costs

Capital costs+

Recurrent costs

Cost of 1 unit of whole blood (recurrent) - CI

Total recurrent cost per unit of safe blood (21500

CFA = $ 40

fixed cost - QA, informatics, administration, logistics, incineration, maintenance buildings and equipmentPersonnel – salaries.

Storage & Cold chain, Distribution

Processing ( production)

Lab testing (HIV, Hep B, Hep C, Syphilis, - labels, cost of additional test kits

Collection (materials, poches , cold chain..)

Recruitment donor (communication, vehicles etc. food for

the donors)

Country-Specific Unit Cost (recurrent) Applied in the Model

$20WHO

$25Nigeria

$45-50

$50

WHO economic

CNTS, CI

$30Mozambique

$30Kenya

$40Cote d’Ivoire

CostCountry

Assumptions – Scenario 1

� The requirement of safe blood for potential target group (with access to HS) as projected with base year (2004) BTS

capacity will remain constant

� The number of safe blood units provided would increase in

2005 by 30% in Kenya, and by a growth rate in the other three countries in the same ratio to 30% as each country’s

adjusted growth factor is to Kenya’s adjusted growth factor

� The increase in safe blood units in absolute number from year 2004 to 2005 will remain constant for the projected

years

� Recurrent cost of safe unit of blood in CI=$40, Kenya &

Mozambique=$30 and Nigeria=$25

Results Table – Scenario 1Assumptions – Scenario 2

� The requirement of safe blood for potential target group (with access to HS) as projected with base year (2004) BTS

capacity will remain constant

� The number of safe blood units provided would increase in

2005 by 30% in Kenya, and by a growth rate in the other three countries in the same ratio to 30% as each country’s

adjusted growth factor is to Kenya’s adjusted growth factor

� The same proportion of the unmet need for BTS in each country that was met in 2005 would be met in each year of

the remainder of the projection period. This constant

proportion is called the BTS growth factor

� Recurrent cost of safe unit of blood in CI=$40, Kenya & Mozambique=$30 and Nigeria=$25

9

Results Table – Scenario 2Level Resources needed for 4 countries (2006-2010)

Cost of Blood (at $40/unit) per year

$0$1$2$3$4$5$6$7$8$9

$10$11$12

2006 2007 2008 2009 2010

Year

US

Do

llar

(in

millio

ns

)

Cote d'Ivoire

Kenya

Nigeria

Mozambique

Capital Cost Budgeting

Projected 2010 capacity e.g. 189,000 units of safe blood –

Existing capacity 89,000 = 100,000 additional.

Assuming the existing BTS has reached its optimum capacity

and any additional capacity will require capital investment, we

estimated $1m of capital investment for a regional bank with a

capacity of 20,000 units.

$ 1m includes building, 2 vehicles, cold chain equipments, lab

equipments, beds, centrifuges, informatics and training cost.

Total Costs—Recurrent + Capital Costs

Total Costs—Recurrent + Capital Costs

$-

$1

$2

$3

$4

$5

$6

$7

$8

Millions

2006 2007 2008 2009 2010

Projected Expenditures for Cote d'Ivoire NBTS

Operating Budget Capital Investments

115,704 134,057 152,409 189,113170,761

Factors to consider in other scenarios

• Increase in population over 2006 -2010 will increase ‘dd’

• Unprecedented international efforts for HIV/TB/Malaria will result in health system strengthening that will increase

access to health care services, and potentially ‘dd’ for

blood.

• Increase in anemia rates in a high prevalence HIV population where ART strategy has been implemented in large

scale.

• Increase on clinical Malaria cases in high prevalence HIV

populations

• Success of Malaria efforts may decrease demand for safe

blood.

10

Points for Discussion and Recommendations

� There is a desperate need for complete and accurate data for better

planning, budgeting, and forecasting resources required to ensure

Safe Blood in African countries.

� Strengthening Safe Blood supply in isolation without an

understanding of levels of development in health system in the

country should be avoided. Strengthening should be coherent to the

level of sophistication in the overall health system.

� Major international efforts such as Roll Back Malaria, Safe

Motherhood Initiative, and Family Planning can help avoid risks in

transfusion by decreasing demand for Safe Blood in Africa.

Points for discussion

• Increase in HIV among adult population will decrease the potential supply

of safe blood and increase the ‘dd’ for blood due to increase in clinical malaria among HIV positive (Mozambique) and anemia resulting from ART (Botswana)

1

Tools for Estimation of Blood

Needs

Inappropriate

Appropriate

Un

me

t D

em

an

d

Demand

Need

Need: An estimation of the amount of blood to meet the transfusions requirements of the population according to current guidelines, best

practices and policies.

Demand: The amount of blood that would be transfused if all prescriptions for blood were met. Demand may be appropriate or inappropriate practices

Po

pu

lati

on

Ne

ed

Use

Use: The actual amount of blood currently transfused (use may be appropriate or inappropriate.

Cu

rre

nt

He

alth

Syste

m N

ee

ds

Un

pre

se

cri

pe

dn

ee

ds D

eve

lop

me

nt In

de

x

PH Leadership

BTS

Clinicians

Population NeedsH

ealth System

Strengthen

BTS

/Hospital

Capacity

Clinical Use/

Evidence Base

Cur

rent

Sys

tem

Nee

dsSup

ply

Dem

and/

USE

Tools

Data Sets Needed Resources Needed

2

Process Forward

1

Objective:

To provide resources that will assist

authorities to estimate the current and future blood transfusion needs for patients

treated in their health systems.

Need

The amount of blood that would be used if all those patients who could benefit* from transfusion were recognised and if blood was prescribed according to appropriate guidelines.

*All those patients who could benefit” implies 100% access to health services but where access to the health system is restricted to a part of the population, need is in effect limited to those who have

access.

Demand

• This term may reflect numerous additional

factors such as the reliability of the blood supply and delivery system, relationships

between clinic and blood bank etc,etc

Need, use and demand

Quantity to met need Optimum prescribing and use

[Conditioned by access to care]

Use Observed quantity actually transfused OR

Surrogate for transfused – eg delivered

DemandObserved quantity that is requested from blood

providers

Target population composed of Groups of patients at risk of transfusion GPART

[Groups of patients needing blood,GPNB]

Patients at risk of transfusion

Defined as:

Patients with conditions that may require blood transfusion, but for whom transfusion may be avoided by preventive or alternative interventions

Identifying target population 1Case definitions could be built around…

Age /gender Over 80

Under 5 in high incidence malaria zone

Combinations of diagnosis and intervention HIV on HARTT

Diagnosis ICD 10

Intervention

OPCS

Specialty – basedSurgery, paediatrics

DRG Geography or Institution

2

Identification

of target populations 2

• From existing sources in country or countries with similar demography etc

• Primary data collection

• Professional concensus

• Published or grey literature

• Burden of disease databases

• New systematic reviews may be needed

Size of the target populationsIncidence, Prevalence

• Sources of epidemiological data

• Burden of disease data

• Review the RAO model in detail

Data on blood use for target

populations

• From existing sources in country or countries with similar demography etc

• Primary data collection

• Professional concensus

• Published literature

Data sets and definitions for describing

hospital blood use

Is supply sufficient?

– Georgetown model,

Which conditions receive how much blood?

– Zambia model

How many patients per time period?

Examples of practical guidance,

training materials

• Sources of existing data – where to look

• Practical issues in accessing data

• Recording

• Analysing

• Uncertainty…importance of factoring in

• Estimates how to develop and use

• Worked examples

Worked example

Maternity

• Haemorrhage

• Other deliver complications

• Puerperal sepsis

• Maternal anaemia

3

Maternity

Data Items

• Deliveries/year

• Number with APH, PPH– Proportion with MH that bleed in hospital or reach

hospital alive and potentially resuscitatable OR

– Number of MH patients who each hospital

– Proportion who need transfusion

– Units of blood used per patient with MH who is transfused

• Number of patients having C section– Proportion needing blood

– Quantities of blood needed

Documents

Pattern of Blood Usage Estimate Blood1 Dr Neelam Dhingra Coordinator Blood Transfusion Safety WHO, Geneva Estimate Blood Requirements - Search for a Global Standard Pattern of Blood