Dr Umesh T KadamSenior Lecturer, Clinical Epidemiologist & GP

 Co-morbidity & Cost Implications

 Wednesday 15 October12noon – 12.45pm

Wednesday Lunch & Learn SeriesComing soon

Date Webinar Hosted by

19 November 2014 Frailty as a long term condition

Professor John YoungNational Clinical Director for Integration & Frail Elderly, NHS England

21 January 2015 Commissioning for Outcomes

Bob Ricketts CBEDirector of Commissioning Support Services & Market Development, NHS England

To register email LTC@nhsiq.nhs.uk

Wednesday Lunch & Learn SeriesHave you seen

Webinar Hosted by

How to make care and support planning a 2-way dynamic

Dr Alan Nye, AQuA Clinical LeadBrook Howells, AQuA Programme Lead

www.nhsiq.nhs.uk

Bev MatthewsA nurse by background, Beverley has worked extensively throughout the NHS in a variety of clinical, managerial and strategic roles. Beverley’s current role as Programme Delivery Lead for Long Term Conditions Improvement Programmes: LTC Year of Care Commissioning Model and LTC Framework. Prior to joining NHS Improving Quality in April 2013, Beverley was Director of NHS Kidney Care and NHS Liver Care. Passionate about service transformation through developing networks and leading complex programmes. Providing strategic leadership to partners within health communities, managing stakeholders and working across agencies.

Dr Umesh T KadamLeading a cardiovascular multi-morbidity programme at care interfaces as a Senior Lecturer in Health Services Research Unit and as an honorary Consultant in University Hospital North Staffordshire (UHNS). GP and Consultant Epidemiologist leading multi-morbidity and frailty academic-service partnerships with UHNS, local CCGs and Public Health. Until 2010, development of the musculoskeletal multi-morbidity programme in primary care within the Arthritis Research UK Primary Care Centre. These programmes have been funded by MRC and NIHR with national and international collaborations in Sweden and the Netherlands.

Meet the Speakers

Co-morbidity and Cost Implicationsof Care foundation. Understand the importance of transition for people with multi

morbidity

Know how to use local data for targeted improvement interventions for people with multiple long term conditions

• Consider how to use pairing of complex diseases to drive pathway development and potential contracting arrangements.

Learning Outcomes

Bespoke Support

The approach:• Identify sites guided by intelligence from the LTC Dashboard and local

advice• Support local health economies to understand their baseline position

through the self assessment Diagnostic Tool• Provide coaching support to start identifying interventions that will

drive change and develop the local action plan.• Agree bespoke support package with memorandum of understanding• Developing a facilitators network of local champions• Use evidenced based improvement methodologies to facilitate

change• Embed measurement and evaluation expertise throughout the

delivery• Development of implementation guide in real time

Tools and Resources

LinksLong Term Conditions Dashboardhttp://ccgtools.england.nhs.uk/ltcdashboard/flash/atlas.html

Long Term Conditions House of Care Toolkitwww.nhsiq.nhs.uk/improvement-programmes/long-term-conditions-and-integrated-care/house-of-care.aspx

SIMUL8: Simulation Modelhttp://www.simul8.com/viewer/download.htm

#LTCyearofcare #LTCframework #NHSIQ

LTC Learning Forum

Wednesday “Lunch & Learn” Webinar Series&

Bite Size Master-classes

Virtual Learning Network Wednesday “Lunch & Learn”

• 45 minute “real time” Webinar sessions

• Topics agreed and learning outcomes identified

• Faculty of Speakers identified

Open invitation

Bite Size Learning Master-Classes

• Pre-recorded 20 minute Master-classes

• Master-class either as stand alone sessions or pre-requisites for Wednesday “Lunch & Learn” Webinars

• Faculty of Speakers identified

Open invitation

Health Services Research Unit

HSRU

Umesh T. Kadamu.kadam@keele.ac.uk

Co-morbidity and cost implications

Health Services Research Unit

HSRU

Commissioning Levers and Potential Tools

• How to use co morbidity pairing within a profiling process to link cost effective potential.

• Use academic studies for practical commissioning applications to targeted interventions

Health Services Research Unit

HSRU

This session will…

• Give a brief overview of the one practical healthcare approach to looking at comorbidity

• Share the results from a published study to show how case finding can be informative of healthcare costs prediction of the future.

• Explore how specific multimorbid pairs were associated with different levels of healthcare transitions and costs in a 3-year time-period.

• Consider a way forward for LTCs care where simple identification of multimorbidity type and linkage of information across healthcare interfaces might enable opportunities for targeted intervention and delivery of cost-effective integrated care in the future.

Health Services Research Unit

HSRU

Definitions• Comorbidity– influence of other conditions on an index condition

• Multimorbidity– Multiple conditions in the same person

Health Services Research Unit

HSRU

Multiple = How many?• Specific combinations

– A chronic disease and depression– Diabetes and heart disease

• Clinical clustering

• Counts

• Classifications/Risk scores– e.g. ‘Morbidity severity’ classification– e.g. John Hopkins ambulatory case-

mix

• Statistical Clustering– Change over time

• Simple

• Complex

What is the purpose?

Health Services Research Unit

HSRU

‘Pairs’ approach• Mostly single disease pathways

• GP LTC registers provide indicator pathways that patient

might be engaged in

• Do specific pairs indicate the likely healthcare use and costs?

• Link GP registers to A&E and hospital data

http://bmjopen.bmj.com/content/3/7/e003109.abstract

Health Services Research Unit

HSRU

Pairs approach: an empirical test• Hypothesis: Specific ordered pair

examples i.e. risk stratification by LTC status will indicate healthcare use and costs

• Only six common LTCs and specified pairs– Hypertension and Diabetes

Mellitus– DM and Coronary Heart Disease– DM and Chronic Kidney Disease– CHD and COPD– Chronic Heart Failure and COPD– CHF and CKD

• 53 General Practices – local data• 60 660 patients aged 40 years• 3-year time-period

• Linkage data

– LTC registers

– A&E episodes and costs

– Hospital admissions and costs

Health Services Research Unit

HSRU

Outcomes• 3-year time frame– A&E attendance – at least once in each of the 3 years

• 0 = none in 3 years• 1 = at least once in one of the three years• 2 = at least once in two of the three years• 3 = at least once in all three years

– Hospital admission – at least once in each of the 3 years

– Estimated healthcare costs – total for the 3 years

Health Services Research Unit

HSRU

Example pairs and transitionsStudyGroups†

A & E episodes

  0 1 2 3

  No. (%) No. (%) No. (%) No. (%)

HT+ DM- 26019 (68.6)

8903 (23.5)

2466 (6.5)

548 (1.4)

DM+ HT- 2733 (63.2)

1154 (26.4)

372 (8.4)

96 (2.1)

HT & DM 6168 (63.4)

2581 (26.5)

776 (8.0)

210 (2.2)

StudyGroups†

A & E episodes

  0 1 2 3

  No. (%) No. (%) No. (%) No. (%)

CHF+ CKD-

1173 (53.0)

665 (30.0)

295 (13.3)

80 (3.6)

CKD+ CHF-

6122 (58.7)

3113 (29.9)

981 (9.4)

211 (2.0)

CKD & CHF

481 (33.4)

595 (41.3)

284 (19.7)

80 (5.6)

• Diabetes status is important in the associated A&E episodes,

irrespective of hypertension

• CHF status is associated with higher likelihood of A&E attendance than

other LTCs• CHF and CKD has much higher ‘risk’

Health Services Research Unit

HSRU

Example pairs and transitionsStudyGroups†

Hospital admissions

  0 1 2 3

  No. (%) No. (%) No. (%) No. (%)

HT+ DM- 21957 (54.0)

10443 (27.5)

4223 (11.1)

1313 (3.5)

DM+ HT- 2343 (54.0)

1192 (27.5)

601 (13.8)

204 (4.7)

HT & DM 4800 (49.3)

2888 (29.7)

1456 (15.0)

591 (6.1)

StudyGroups†

Hospital admissions

  0 1 2 3

  No. (%) No. (%) No. (%) No. (%)

CHF+ CKD-

884 (39.9) 737 (33.3) 414 (18.7) 178 (8.0)

CKD+ CHF-

4678 (44.9) 3456 (33.1) 1723 (16.5) 570 (5.5)

CKD & CHF

305 (21.4) 538 (37.8) 398 (27.9) 184 (12.9)

• Hypertension and Diabetes status was associated with higher

likelihood of a hospital admission

• CHF status is associated with higher likelihood of A&E attendance than

other LTCs• CHF and CKD has much higher ‘risk’

Health Services Research Unit

HSRU

Pairs and costs• Adjusted

– Age

– Gender

– Index of Multiple Deprivation

StudyGroups

3-year IP £ costsMean (SD)

Adjusted Regression* Estimates £ (SE)

p-value

HT+ DM- 1647 (4085) 0 DM+ HT- 2061 (4490) 595 (68) <.001HT & DM 2289 (4585) 607 (48) <.001 DM+ CHD- 1825 (3977) 0 CHD+ DM- 2512 (5825) 431 (73) <.001DM & CHD 3372 (5789) 1270 (101) <.001 DM+ CKD- 1850 (3996) 0 CKD+ DM- 2559 (4380) 403 (73) <.001DM & CKD 3642 (6063) 1480 (97) <.001 COPD+ CHD- 2642 (4814) 0 CHD+ COPD- 2537 (5812) -152 (92) .097COPD & CHD 3992 (5775) 1158 (151) <.001 COPD+ CHF- 2769 (4925) 0 CHF+ COPD- 3877 (5732) 904 (125) <.001CHF & COPD 4901 (6199) 1954 (206) <.001 CHF+ CKD- 3282 (4880) 0 CKD+ CHF- 2477 (4404) -629 (114) <.001CKD & CHF 5344 (6907) 2116 (163) <.001

Results suggest that multimorbidity pairs provide a way of risk

stratifying populations

Health Services Research Unit

HSRU

This session has…

• Given a brief overview of the one practical healthcare approach to looking at comorbidity

• Shared the results from a published study to show how case finding can be informative of healthcare costs prediction of the future.

• Explored how specific multimorbid pairs were associated with different levels of healthcare transitions and costs in a 3-year time-period.

• Considered a way forward for LTCs care where simple identification of multimorbidity type and linkage of information across healthcare interfaces might enable opportunities for targeted intervention and delivery of cost-effective integrated care in the future.

Useful ResourcesBMJ OpenChronic disease multi-morbidity transitions across healthcare interfaces and associated costs: a clinical-linkage database study Umesh T Kadam1, John Uttley2, Peter W Jones1, Zafar Iqbal3

Consumer Mosaic segmentation, COPD and CHF multi-morbidity and hospital admission costs: a clinical linkage study. Doos L, Uttley J, Onyia I, Iqbal Z, Jones PW, Kadam UT.

J Public Health (Oxf) 2014;36(2):317-24. doi: 10.1093/pubmed/fdt070.

http://bmjopen.bmj.com/content/3/7/e003109.abstract