Principles for Flow Improvement #1: Understand, measure and achieve a balance between upstream and downstream demand

Principles for Flow Improvement #1: Understand, measure and

achieve a balance between upstream and downstream demand

Basic Dynamic

Door to doctor time

Decision to admit to admit

Ready to Tx to tx

Decision toDx to dx

Length of Stay

System demand Look at all the streams of demand (all the kinds of

work) into each step Different demand streams will have different units of

measure Demand = volume of demand X LOS (time)+parking Look at the variation (volume, arrivals and handling

time) of demand in each stream Look at the supply set aside against each demand

stream both within the step and between demand streams (allocation)

Supply is time of various converging components Measure the variation of supply Compare demand to all the supply- all lines need to

balance

Measurement for Each Step

Demand: Volume External/internal Who Where What Variation/range in

volume, in arrivals and in handling time

D= Volume X LOS (time)

Supply: Volume Competing venues Variation/range Volume X Time Converging

components

Delay: How long Variation in

delays

Metrics at each step Input Throughput Output Output for one step is input for the

next step

HOSPITAL FLOORICU/CCUAdvanced Care

Other Places

MENTALHEALTH

WORLD

SPECIALTY CARE

ED

PRIMARY CARE

HOME

SURGERY

DiagnosticTests

Prepare Clinic

PACU

PREP

S

S

S

S

SSSS

S

S

D

D D

D

D

D

D

D

D

D

D

D

D

D

MMA MEASURES


Other Places

MENTALHEALTH

WORLD

SPECIALTY CARE

ED

PRIMARY CARE

HOME

SURGERY

DiagnosticTests

Prepare Clinic

PACU

PREP

D

S

Demand at each stepSupply at each step

Variation at each stepWait time for each step

Process time at each step

FLOW DIAGNOSTIC MEASURES


Other Places

MENTALHEALTH

WORLD

SPECIALTY CARE

ED

PRIMARY CARE

HOME

SURGERY

DiagnosticTests

Prepare Clinic

PACU

PREP

LOS

S(beds)

* Admissions* Discharge patient days* Discharges* CMI* Potential Bed Turns (365/LOS)* Un + Adjusted Bed Turns* Utilization–Unadjusted bed turns/potential bed turns A/S

LOS for patients who went to NH(activity) = demand

Adjusted bed turns = CMI admissions +OBs + SDCs / functional beds

Unadjusted bed turns = admissions + OBs+ SDCs / functional beds

Delay for the step: input In some steps, demand= arrivals so

there is no delay (for ED) Between and within other steps,

there is a delay (from ED to floor)

Delay within the step (throughput)

ED cycle time Door to doctor time

Each floor or service LOS Decision to discharge to discharge wasted capacity (defect)

Throughput for a specific patient stream (CHF)

ED Hospital LOS

DoorTo

Doctor Time

Length of Stay in EDDecision to

Admit to Admission

Lead Time in ED

Cycle 1 Cycle 2 Cycle 3

ED Hospital LOS

AdmitProcess Days in Hospital

Decision to Discharge to

Discharge

Cycle 1 Cycle 2 Cycle 3

Day 1 Day 2 Day 3

ED Lead time

Emergency Department Lead Time

0

20

40

60

80

100

120

7/0

2

9/0

2

11

/02

1/0

3

3/0

3

5/0

3

7/0

3

9/0

3

11

/03

1/0

4

3/0

4

5/0

4

7/0

4

9/0

4

11

/04

1/0

5

Med

ian

min

ute

s

Door to Discharge Door to Doctor Decision to Admit

Hospital Overall Length of StayMonthly ALOS

3.1

3.3

3.5

3.7

3.9

4.1

4.3

4.5

January 2003 - January 2007

Day

s

LOS LOS Delay Days 2005-2006

0

50

100

150

200

250

300

350

Cardiol

ogy

Med

icine OB

GYNOrth

oPed

s

Surger

y

Day

s

From 7/1/05 to 6/30/06 Top 10 DRG’s/specialtyCalculated from Days > Benchmark TIMES volume

Sum = 850 days/year

Within the step (throughput) Measures

Length of Stay

•Diagnostic admission•Time from presentation to w/u complete•Time from order for diagnostic test to information

•Treatment admission•Time from admission to treatment complete•Time from arrival for pneumonia to first antibiotic start

Delay after the step: Output Measures

Output for one step is input for the next ED: Decision to discharge to admit Flow: Decision to discharge to

discharge

Delay after the step (output) ED

decision to admit to admit Transfers or direct admits

decision to admit to admit Each floor or service

decision to discharge to discharge discharge appointment measures

Demand Measures

Average Visits by Day of Week

0

10

20

30

40

50

60

70

80

90

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

Num

ber o

f pat

ient

s

Jan-Dec 2004 Jan-Dec 2005

Emergency Department

Demand

60 To 80


Average Visits by Day of Week

0

10

20

30

40

50

60

70

80

90


Nu

mb

er o

f p

atie

nts


Average Visits by Time of Day

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour

Nu

mb

er o

f p

atie

nts


60 To 80

Variation from 1 to 5 per hour

Peak is at 6 PM

Emergency Department Hospital

Demand FOR ED

Demand FOR HospitalAverage Visits by Day of Week

0

10

20

30

40

50

60

70

80

90


Nu

mb

er o

f p

atie

nts



0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour

Nu

mb

er o

f p

atie

nts


Overall ED Admits (as a percent of all ED Visits)

0%

5%

10%

15%

20%

25%

Jan-01

Apr-01

Jul-01

Oct-01

Jan-02

Apr-02

Jul-02

Oct-02

Jan-03

Apr-03

Jul-03

Oct-03

Jan-04

Apr-04

Jul-04

Oct-04

Jan-05

Apr-05

Jul-05

Oct-05

Jan-06

Eight to Ten Percent are Admitted

Admissions from Bellin's ED

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour

Av

g #

of

pts

per

ho

ur

2004 2005

0.4 to 0.6Per hour

From Noon ToMidnight

Overall ED Admits (as a percent of all ED Visits)

0%

5%

10%

15%

20%

25%

Jan-01

Apr-01

Jul-01

Oct-01

Jan-02

Apr-02

Jul-02

Oct-02

Jan-03

Apr-03

Jul-03

Oct-03

Jan-04

Apr-04

Jul-04

Oct-04

Jan-05

Apr-05

Jul-05

Oct-05

Jan-06

Emergency Department Hospital

Demand FOR Hospital


0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Hour

Nu

mb

er o

f p

atie

nts


Admit PatternWithin the Day

Scorecard of Key System Measures: OutcomesHow well we match demand to supply (velocity)

Bed turns Adjusted bed turns Potential bed turns Utilization LOS (throughput) LWBS and diversions (defects)

Adjusted bed turns

0

20

40

60

80

100

120

FQ104

FQ204

FQ304

FQ404

FQ105

FQ205

FQ305

FQ405

FQ106

FQ206

FQ306

FQ406

FQ107

Adjusted bed turns Adjusted goal (>90)

Unadjusted bed turns

0123456789

10

10/1/2004

12/1/2004

2/1/2005

4/1/2005

6/1/2005

8/1/2005

10/1/2005

12/1/2005

2/1/2006

4/1/2006

6/1/2006

8/1/2006

10/1/2006

12/1/2006

#2: Eliminate any backlogs of work

Initial step into ED has no BL but all other steps have a BL (delayed workload)

Stabilize the wait, then eliminate BL To stabilize the wait, reduce the variation Eliminating BL may move the workload and the

wait time deeper into the system Use standard BL reduction strategies

#3: Reduce the queues from one entity to another

Workload channeled into more and narrower queues increases the risk of adversity due to variation

“Priority” is often a euphemism for more queues Priority variation Segment/route for “different” queues Segment in front of the constraint, not beyond

Reduce the Queues Concept: Bank and Grocery Store Are these appropriate queues?

1 line for each phlebotomist? “In-patients first” in Imaging? Preadmission unit? Discharge lounge? Separate OR for emergencies? “Fast Track” in ED?

Lab

0

5

10

15

20

25

1/13

/200

3

1/27

/200

3

2/10

/200

3

2/24

/200

3

3/10

/200

3

3/24

/200

3

4/7/

2003

4/21

/200

3

5/5/

2003

5/19

/200

3

6/2/

2003

6/16

/200

3

6/30

/200

3

7/14

/200

3

7/28

/200

3

8/11

/200

3

8/25

/200

3

9/8/

2003

9/22

/200

3

10/6

/200

3

10/2

0/20

03

11/3

/200

3

11/1

7/20

03

12/1

/200

3

12/1

5/20

03

12/2

9/20

03

1/12

/200

4

1/26

/200

4

2/9/

2004

2/23

/200

4

3/8/

2004

3/22

/200

4

4/5/

2004

(Wa

it T

ime

min

)

Banker’sQueueImplemented

#4: Develop contingency plans to manage variation

Measure the variation Determine common from special

cause Have a plan Use a tool or two

Variation

Within Day

Between Day

Measure Approach: Variation

Natural/Unplanned Run Chart Statistical Process Control Queuing Formulas

Artificial/Planned Run Chart Statistical Process Control Modeling

Tools and Theories to manage variation

UK formula: low demand +80% of the variation

Erlang’s formula

Standard queuing models

Demand-Capacity Tool

80% 100%

S u pp ly

Wai

t T

ime

Wait Time VariabilityCompared to D/S ratio

Demand /

Supply variation in surgery: the 5 Why's Bolus of elective admissions with a delay Surgeon(s) worked in clinic a lot Surgeon catching up after being away

Had to catch up/make up “on call” first Generated immediate surgery Had to do operations now and did before leaving

Call and surgery can’t wait Clinic waits Surgeon(s) does not fill block time Loses block time Back to office Generates workload and bolus

#5: Reduce demand Some volume of demand can be reduced by

correct routing ( error proofing) Impact of volume of demand can be reduced by

Service Agreements Demand can be reduced by reduction of LOS

Admit the Right Patients% Admissions Not Meeting Criteria 2006

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

A C E G I K M O Q S U W YAA

Other way to Decrease Demand Increase reliability: Take on Clinical

Care VA ICU Collaborative Increase safety and reliability

Decrease those patients off service: One study shows mortality increases 25% for patients “off service”. Hospital within a hospital

Hospitalist

Hospitalist ChangeAnd

Joint N-P Rounds

Yearly savings estimated at 300 bed-days of care!

Decreasing Demand by Shortening LOS Have a senior clinician review each

admission critically to have a clear workup or treatment plan and timeline

Multidisciplinary Rounds Daily Round twice a day Rounds checklist Plan discharge at time of admit Eliminate waits for any ancillary services

#6: Increase supply If there is a D- S mismatch, then add

supply- permanently or temporarily with flex

Can “add” supply by subtraction TOC: identify supply constraint in

entire flow and at each step in the flow and take away the “unnecessary” workload

Supply Components Supply Components

Patient Provider of care Staff Beds Information Equipment Supplies

Increase Supply Link admissions to discharges Do a “wasted inpatient bed” study

Snapshot measure Physically confront each bed Note if bed empty of full Note reason for empty bed Tabulate % of time bed wasted Track over time

Reasons for Inpatient Bed Not in Productive Use

Reasons for Unused Bed #1. Pt. receiving care (elsewhere) (OK)

2. Pt. in discharge process (OK)

3. Pt. disch complete, waiting to go

4. Bed needs to be cleaned

5. Bed held for surgical

6. Bed held for admission/transfer

7. Bed contains a body

8. Bed out of service (why?)

9. Bed empty. No demand today

One Hospital Results

Hospital had high turns and high utilization

Looked closer at capacity Found 25% of capacity was “wasted” (bottom

7 of 9 reasons on study) Most common reason pt. waiting to go home Second: Bed waiting to be cleaned Third: Held for surgical

Identify the System Constraint

• The constraint is the rate limiting step

• Can only go as fast as slowest step or the slowest step within the step

• Any step or service that is 100% full to capacity will be the constraint

• This is the last place where there is a system delay

• This is where there is a demand–supply mismatch and a delay

• Take work away from the constraint

• Balance at the constraint (may have to reduce demand, increase supply or improve the process delay)

• The constraint shifts

Potential Constraints Dependent on the specific patient flow

map Rate limiting step in that specific flow Last place where there is a significant

delay Examples: surgery, test/procedure, ICU,

hospital bed, office appointment, ED The constraint moves

Example: Surgery OR

Supply at Surgery

A. Surgeon

B. Room

C. Equipment

D. Technician

E. Anesthesiologist

F. Hospital BedA

BC

DE

F

D

S

Harmonic convergence of components

Surgeon as Constraint

Value stream for customer Competing venues for

surgeon/dilution Decision about venues Limit the demand/enhance the

supply at each competing venue

OR Itself Hours of operation OR utilization during those hours Percent utilization Block time Industrial models (85%) Downstream constraint (bed) may

make OR appear to be the constraint or increase wait to OR

Big System Flow/Cancer

Test

SC Surgery

Discharge

External Demand

PC Bed

MDTOncology

Radiation

Chemo

Follow up

Test

Test

Follow up

Internal Demand

Inte

rnal

Dem

and

Test

MDT

MDT

C

• 1-7 day variable wait

Findings

The constraint was not surgery The octanes at SC office were very

poor creating an office anti-dilutional effect

Surgeon not in the OR Long wait for surgery OR’s open MDT caused 2 delays

Changes

Used principles Changed MDT ( false demand + timing) Looked at value: Surgery Moved surgeons to the OR Identified constraint (front door)

Changed octanes Initial/total Surgery/initial Created linkage

Other Potential Constraints ED (wait time to get out, wait time to get

in) ICU ( wait time to get in, wait time to get

out) Beds ( wait time to get in, wait time to get

out) Dependencies Discharge venues ( wait time to get in)

#7: Synchronization of all supply components to the demand

Synchronize the Work What is synchronization? “Gap” between possible and actual

time of occurrence of: Admission - Tests Discharge - Procedure Rounds - Operation Medicine Passes

Increase Supply Story of Freddie Problem:

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

1 3 5 7 9 11 13 15 17 19 21 23

hour Total Admissions Total Discharges

“Discharge by 11 is absurd.It assumes everyone is out there

with their nose pressed to the glass wanting to come in at 11, which is absurd.”

- IHI Faculty

VA FY ’05 # Admits/Discharges by Time of Day

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

1 3 5 7 9 11 13 15 17 19 21 23

hour Total Admissions Total Discharges

Actual and Modeled Discharges vs. AdmissionsVA Nationwide 2005

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour of Day

Admit % by Hour Discharge % by Hour Model Discharge % by Hour

NOON

Multidisciplinary Rounds: Where?

Multidisciplinary Rounds Outcomes

Reduced mortality Improve clinical care

Vent days, infections, readmits, decubiti ulcers, prevent DVT,

Improved Efficiency Reduced length of stay/increase

throughput Increase patient/staff satisfaction

Daily Goals Sheet M T W TH F Sa

Pain?

Test/Proc?

Activity?

Med Chg?

Lines/tubes?

Spiritual?

Nutrition?

Disch Plans?

#8: Predict and anticipate needs Communication strategies Command Center Philosophy Tools/Information System

Allows view of workload flow retrospectively and in real time

Allows for a required interventions Czar or Czarina

Flow system scorecard Retrospective data Monitors ongoing performance Can be converted to run charts and

SPC graphs Explicit focus on delay: input,

throughput and output Additional focus on matching and

velocity measures

Measure Goal Actual Measure Goal Actual

Number of Parked

Patients > 30 minutes

Number of Parked Patients > 30 minutes

3.7 days

2.3

3.7

Number of Parked Patients > 30 minutes

Time Patient Meets Aldrete Score To

Time Patient Transferred

N/A

15 min

0

ALOS

0

0

30.0

0.2

2.2

19.8

88.0

0

#DIV/0!

1.0 hr

2.1 days

0

6

#DIV/0!

0

131.0

132.0

41.5

10.9

74.1

3.0

1.9

2.9

3.6

3.4

30 min

3 days

3 days

60 min

105 min

120 min

60 min

15 min

2.7 days

3.3 days

2.1 days

Routine Access/Input Throughput/Cycle Time

MEASURE

Door to Doctor Visit Cycle Time

Exam Start To Complete

DEPARTMENT


1 South

Surgery 6

Surgery West

Chest X-ray

Overall 2007

4.0

ACD

Vascular Studies

3rd Next Available

Appointment

Order To Exam start

Pediatriacs

Direct Admit

Time Patient Meets Aldrete Score To

Time Patient Transferred

4 Medical

8 Ortho

Maternity

3.0 hrs

0

15 min

2 South

Admit To Unit Cut

2.7 days

Admit To In Room

3.9 days

Measure Goal Actual Measure Goal Actual

Admit To Start Of procedure #DIV/0!GI Lab

3rd Next Available Appointment 3 days #DIV/0!

17.0Time

Housekeeping Notified To Time

Room Clean

N/A

15 min

7.5 min

Time Patient Arrives Until Discharge Criteria Met

Time Patient Arrives Until Time Patient

Goes For Procedure

32.5 min 39.1

90 min

90 min 137.0Direct AdmitCSSU

DEPARTMENT

Overall 2007

4.0

MEASURE

Routine Access/Input Throughput/Cycle Time

8 Short Stay

Housekeeping

Discharge Order To Floor

Time P atient Leaves Room To

Time Housekeeping

Notified

Predicted Orthopedics DemandCommon and Special Cause Variation

BY DAY (Tuesday)

Green Yellow Orange Red

Census 0-8 9-11 11-12 >12

Unplanned 0-7 8 9 >9

Planned

Transfers 0 1 2 >2

Electives 0-5 5-7 8 >8

Parked 0 0 1 >1

C o m m o n S p e c ia l


DEMAND Observed Data

Census #REF! 70 or less 71 - 77 78 - 84 85 or more

AdmissionsUnplanned # REF! 0 1 - 2 3 - 4 5 or more

PlannedTransfers into Dept # REF! 0 - 2 3 - 5 6 - 9 10 or more

Electives # REF! 0 - 1 2 3 4 or more

Parked # REF! 0 1 2 3 or more

AcuityTotal Cares # REF! 10 20 30 40

Frequently Monitored Patients

# REF! 0 - 1 2 3 4 or more

Complex Teaching # REF! 0 - 1 2 3 4 or moreIsolation Patients # REF! 0 -1 2 3 4 or more

Uncovered 1:1 # REF! 0 1 2 3

DischargesLow Complexity # REF! 10 20 30 40

Moderate Complexity # REF! 0 - 3 4 - 6 7 8 or moreHigh Complexity # REF! 0 - 2 3 4 5 or more

Demand/Supply Tool


SUPPLY Observed Data

StaffingPrimary RN Staffing

Day & PM Shifts#REF! 3.5 or fewer 3.6 - 4.0 4.1 - 4.5 4.6 or more

Primary RN Staffing Night Shift

#REF! 4.5 or fewer 4.6 - 5.0 5.1 - 5.5 5.6 or more

CNA Staffing Day & PM Shifts

#REF! 5.5 or fewer 5.6 - 6.0 6.1 - 6.5 6.6 - 7.0

CNA Staffing Night Shift

#REF! 6.5 or fewer 6.6 - 7.0 7.1 - 7.5 7.6 - 8.0

Beds

Total Beds Used # REF! 70 or less 70-75 75-80 80 or More

Isolation Rooms # REF! 3 2 1 0

Female Rooms # REF! 2 1 0 0

InformationHospital-Wide

Computer Network# REF! None

System Down < 1 hour

System Down 1-2.5 hours

System Down 2.6 hours or more

EquipmentIV's Used # REF! 0-5 6 7 >8

SuppliesIsolation Rooms # REF! 3 2 1 0

Female Rooms # REF! 2 1 0 0

Demand/Supply Tool

Key to D/S Tool: Interventions (Contingencies)

Created by the front line team Exist for every single box/criteria Impact of intervention determined by escalating

color criteria Thresholds for criteria set by SPC, common and

special cause variation Have the same level of impact across all

“departments” Continually updated and developed Allow a standard response to change in workloads Often result in “buddy” departments

#9: Optimize environment

Optimize the Environment Lean

Big system flow: special issues

Linkages and formulas

Intersections

Formula

Demand for OR time = Supply of the OR time

The delay is thus stabilized Patients per month x octane (surgical

cases per 100 patients) = OR time per month/OR time per case

Adjust by 85% (myth of 100% utilization)

Linkage or Ratio of Schedule

C

A

4 : 4 : 1 : 1

Linkage of Ratios Why?

Work Backwards to Office

Stabilize the wait time in the OR ( the constraint)

Work backwards to the office Three variables:

Days in office Appointment lengths/ types Octane

Octanes

Initial(new):initial+return Returns : surgery Surgical cases:new(initial

•Surgical Yield

Goals

High

Low

High

Linkage Formula

OR sessions/week X cases per OR session =

Office sessions per week X appointments per session X octane (surgical yield)

(adjusted to 85%)

Links surgery (ultimate value and constraint) to office that feeds the constraint

Allows measurement and monitoring Allows earlier identification of

problems

Linkage Surgery to office Procedure to office Test to office Bed to ED ICU to surgery Bed to ICU Other dependent services

Big System Flow/Intersections

Test

SC Surgery

Discharge

External Demand

PC Bed

MDTOncology

Radiation

Chemo

Follow up

Test

Test

Follow up

Internal Demand

Inte

rnal

Dem

and

Test

MDT

IntersectionsRadiation Oncology Demand

• External.internal• Stratification into who, what, where in each stream• Variation within each stream

Supply What is the constraint

• Machine• Technician• Physician• Process

Delay• For all competing components

Decisions• Who goes first

Intersections Intersections of demand streams are

common Demand is competing The competitors are blind Demand and supply are matched

but what is the model? How are decisions made What is the true constraint

Lesson 1 Value stream Delay is key We must measure demand and

variation at each step Do not confuse activity with demand Variation creates queues Do not use averages Constraints governs the speed

Lesson 2 Aiming for 100% utilization and

setting the supply at average demand will result in waits and a waiting list

Set supply at minimum demand + 80% of the variation

Lesson 3 Demand/supply Use principles at each step The system is linked Carve-outs worsen system performance Extra capacity comes from process redesign May have to increase actual resource but

only after measurement We may solve a problem but if it is not the

right problem we just move the wait

High Leverage Changes at Each Step

Balance upstream and downstream demand and supply for all services

Eliminate any backlogs of work Reduce the queues from one entity to another Develop contingency plans to address all variation Reduce demand Identify and manage each supply constraint Synchronize the work Predict and anticipate needs Optimize the environment: equipment, staff and space

Ten Flow Rules1) Follow the customer (patient).2) The goal is to eliminate all wait and delay.3) The patient’s journey through the system is often complex but at its core is a series of

value steps interspersed with long waits.4) Each step is a demand-supply matching step.5) The perspective of the customer (demand) is different than the perspective of the

supply (resource) : the patient experiences a series of waits while the resource sees single isolated waits.

6) Queues (wait times) result from:a) demand-supply mismatch which has to be solved by reducing demand or enhancing supplyb) queues are formed by system design which requires redesign, orc) queues are formed by variation which needs to be measured and addressed

7) Measurement of demand, supply, activity, wait time and variation in demand and supply at each step is crucial

8) Involve all staff in measurement at each step. 9) Look at steps beyond the constraint to improve flow. 10) There are a set of principles that, if applied appropriately at each step, will reduce the

waits.

Documents

Principles for Flow Improvement #1: Understand, measure and achieve a balance between upstream and downstream demand