prof. ran balicer, director, clalit research institute, health policy planning, clalit health...

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Data-Driven Integrated Care in Clalit Health Services: Innovation in Practice

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1

A data‐driven integrated system 

approach to tackling chronic diseases

Prof. Ran Balicer, MD, PhD, MPH

Director, Clalit Research Institute

Director, Health Policy Planning, Clalit

rbalicer@Clalit.org.il

‘The New Normal’

• 1 of 2 members >45 have chronic multi‐morbidity

• 3 of 4members aged >65 are multi‐morbid

2

‘The New Normal’

• 1 of 2 members >45 have chronic multi‐morbidity

• 3 of 4members aged >65 are multi‐morbid

10.0%

13.0%

16.0%

19.0%

22.0%

2006 2007 2008 2009 2010 2011

20.0%

21.0%

22.0%

23.0%

24.0%

2006 2007 2008 2009 2010 2011

Age 45-65, 2+ NCDs

Age 65+, 5+ NCDs

25% of

60% of $$

20% of

50% of $$

3

NCD multi‐morbidity – key challenge

• >50% of 45+ old have NCD multi‐morbidity

• 3 of 4members aged >65 are multi‐morbid

• Rapidly aging population

Do more?

4

Paradigm shift is a requisite

• Increasing demand, decreasing resources

• ‘Do more’ option - exhausted

Our system is (also) broken

Work in silos

‘Equal’

Therapeutic

Reactive

Paternalistic

Waste everywhere

5

Helpful attributes in Israel

• Universal health insurance

– 4 Sick funds, wide basic ‘basket’ of services for 8M citizens

• Strong emphasis on community primary care

– 90% are happy with their health fund

• Incentives well aligned for value vs. volume

– Life‐long insurer membership (1% ann. attrition)

– Salaried physicians, bundled procedure hospital payments

• Innovative spirit, strong health IT infrastructure

• Covers 50% of Israelis – 4.2 Million members

– Over‐representing minorities, low SES, elderly

– Funding by age‐gender capitation

• 1,500 primary care clinics, 

– Multi‐disciplinary teams

– Most physicians ‐ salaried

• 30% of hospital acute beds in Israel

Clalit Health Services:Israel’s integrated healthcare provider

6

Policy planning: strategy principlesParadigm shift: the Clalit strategy

= a requisite and driving force

for transforming chronic disease care

Data-driven management of chronic disease

Data in Clalit

• Centralized Data Warehouse – real‐time data: 

– Electronic information since late 1980’s

– Single EMR Coverage in all community clinics

– Inpatient and outpatient detailed data

– Smoking, BMI, BP measures…

– Detailed Socio‐demographic data

– Labs, Pharmacies, Imaging

– Full data on Costs

– >100 chronic disease registries

Decades of full life-span, ID-tagged, Geo-coded,

EMR-based data on > 4M people

7

• Multi-disciplinary group, established March 2010

• A marked change in the organization mindset

• Mandate: Turn data to insights, insights to policy

Clalit Research Institute

• Real-life Outcome Research

• Data-driven care models design

• New measures for patient-centered care

• Multidisciplinary group:• Physicians

• Epidemiologists

• Biostatisticians

• IT specialists

• Mathematicians / algorithm specialists

• International collaborations

• WHO

• Academic institutes

• Science and development

Clalit Research Institute

8

Brief Case studies: Data ‐> Insights ‐> Policy

• Coordinated: Readmission reduction

• Preventive: Predictive proactive prevention

• Equitable: Reducing disparities in quality of care

• Proactive :Care of the multi‐morbid

• Real World Evidence  :What really works?

Data driven policy: Implementation

Case study 1:Data‐driven integrated care for 

preventing readmissions

9

Readmissions: a common challengethe UK experience

10

Readmissions are just the symptom

Patient‐centered care coordination           is the real target

(%)

Variance after case‐mix adjustment

7‐day readmissions

11

Readmissions ‐ Israel

Clalit

rates

Readmission rates

Subgroupcountry

16.7%Internal med wards

2007

Hong Kong(Wong et al, BMC HSR, 2011)

19.6%Medicare (65+)

2003/4

US (Jencks et al, NEJM, 2009)

9.1%16-74 yo

UK(Department of Health, 2008)

Shadmi, Balicer et al, Clalit 2012

Readmissions ‐ Israel

Clalit

rates

Readmission rates

Subgroupcountry

14.3%(age adjusted)

16.7%Internal med wards

2007

Hong Kong(Wong et al, BMC HSR, 2011)

17.5%(Urgent & planned readmission)

19.6%Medicare (65+)

2003/4

US (Jencks et al, NEJM, 2009)

8.9%

9.1%16-74 yo

UK(Department of Health, 2008)

Shadmi, Balicer et al, Clalit 2012

12

23

Hospital

Data may be misleading7 days readmission rate

24

Hospital Blue – to same hospitalRed – to any hospital

Data may be misleading7 days readmission rate

13

• Across life course, between providers and care settings:

– Continuity of care 

– Continuity in communication

– Continuity of data

Aiming for integration

• Discharge planning from day 1

– Direct nurse‐to‐nurse hospital‐community communication

• Post‐discharge outreach to patients by GP clinic

• Home teams for the bed‐ridden patients

Continuity of care

14

• Most patients treated by a multidisciplinary team      (GP, nurses, allied health professionals)

– Coordinated teamwork at clinic level

• Hospital‐community direct communication

– Discharge planning e‐letters

– Transition care nurses

Continuity of communication

• GPs, specialists share the same EMR system

– Direct delivery of consult e‐summary in GP inbox 

• Interoperable online system links hospitals and GPs

– Clalit hospitals but also most key out‐of‐chain facilities

– Soon – all hospitals in Israel are joining

• Single organization‐wide database + BI

Continuity of data

15

•Work in the hospital (i.e. discharge planning)

•Work in the community (i.e. home care)

• Bridge the gap:

• Continuity of data

• Transition care

• Coordinated Teamwork

Improving: Where should we aim

CoC nurses: Hospital‐based community nurses, in every hospital

Structured outreach protocols for GP clinics, CTM

Home teams enhanced, activated by GP clinic nurse

Dedicated targets, indicators & IT support systems

Set of care coordination indicators

New work processes in the hospitals and in the clinics 

Further care coordination: Action taken 2012

16

Risk Stratification

30‐Day readmission rates among 65+ years old in 2012

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6

30‐day Read

mission Rate

Clalit Pre‐admission Risk Score ‐ Stratum

17

Implementation% of elderly patients not approached by GP within 7 days of

discharge(lower = better)

Project onset Q3, 2012

20.0%

20.5%

21.0%

21.5%

22.0%

22.5%

23.0%

1 2 3 4Annual Quater

Readmissions among the elderly: 2012 vs 2010 by quarter

2012

2010

2012 vs 2010By quarter

Interven

tion

Readmission reduction30‐Day readmission rates, 65+ years old

18

Case study 2:

Personalizing preventive caredriven by integrated data

Preventive Nephrology

11.50%

4.60%

1.80%

0.60%0.20% 0.10%

0%

2%

4%

6%

8%

10%

12%

14%

<96% 92-96% 80-92% 60-80% 30-60% 0-30%

5‐year deterioration rates to RRTamong CKD stage 3 patients, Clalit

Clalit Research Institute Risk Scores

100-foldRRT increased risk !

19

Proactive prevention: NephrologyPreventive Nephrology

Case study 3:

Using integrated data for reducing disparities while improving quality

20

Despite decades of work…

Clalit, in 2008 made a strategic decision to reduce

inequality driven health gaps

21

Strategy assumptions

• Equal treatment will not reduce disparities

• Must use existing successful platforms

• Primary care is most important

• (almost) All solutions are local

• Measure, measure, measure

• EMR-data based quality measures (e-QM)

Utilize existing platforms

22

Data-driven policy

EMR-based care indicators used for:

1. Target setting

2. Real-time achievements monitoring

1. Diabetes control

2. Blood pressure control

3. Hyperlipidemia control 

4. Influenza immunization  

5. Mammography tests

6. Fecal occult blood tests

7. Anemia in infants 

Composite Score

Disparity Reduction in chronic disease prevention & management

7 Selected Indicatorslowest

performing clinics(400,000 members)

23

Use of Data in ClalitClalit: Disparity Reductionin preventive medicine measures

Intervention plan components: bottom‐up planning

Disparity Reduction 

24

25

Low SES High SES

2008 498 350

2011 474 340

% reduction 2008-2011

4.8% 2.8%

• Compared to 2008, a decrease in AMI incidence was observedin all SES groups.

• A relatively higher decrease was observed in the low‐SES groupcompared to high‐SES group.

AMI morbidity – promising trend

26

Case study 4:

Care for the most complex multi‐morbid patients

System‐wide change:GP time allocation by morbidity

52

Annual visits per patient by comorbidity level

Clalit ACG primary care comorbidity score category

27

Proactive care: Risk‐based outreach interventions

Proactive Care for the chronically ill:The Clalit adapted model

X 18

X 7

$$ Impact: Cost per patient

X 8

X 4

28

Care for the ‘pyramid tip’

• Key Challenge – patient selection:– Multi‐morbid, High Risk patients 

– Balance impactability and predicted risk• Complex integration of multifaceted data

• Selection process chosen: – Available EMR‐data risk‐based prediction system

– Excluding low‐impactability patients using criteria determined through physician input 

– 40% positive predictive value for future highest costs• C‐statistic >0.75

Care for the ‘pyramid tip’

• Inspired by Chad Boult’s Guided Care model– Select multi‐morbid High Risk patients (not high cost!)

– Dedicated qualified nurse (1:100)

• Training process

• Proactively assess overall patient needs

• With GP, create care plans for patients

• Provide self management and caregiver support

• Coordinate transitions 

• Facilitate access to community resources

– 3 Year controlled clinical trial in process

PI: Dr. Efrat Shadmi

29

In Summary

Using data to drive care transformation 

Identifying priorities and achieving mgmt support

Risk stratification 

Individually targeted intervention programs

Clinical staff decision support

Patient participation

Real‐time continuous feedback

Comparative effectiveness… Signal assessment… Research… Precision medicine… genetics…

30

Requisites

Harmonization of EMR systems Central database

ID issues

Coding/software

Data sharing 

Analytic capacity

Intervention platform willing to innovate

Aligned incentives

To meet the challenges ahead (plus more)…

• Data driven policy – Maximize data streamlining and use

• Build on infrastructure strengths – Improve in areas of fragmentation

• Develop innovative approaches – Patient‐centered care

– Proactive self‐care support

– Integrated care

– Right incentives

31

Thank you!

“It is not enough to do your best; 

you must know what to do, and then do your best.

W. Edwards Deming

32

Contact

Prof. Ran Balicer

Director, Clalit Research Institute

& Director, Health Policy Planning, Clalit

Tel:+972‐3‐6923104

101 Arlozorov St. Tel‐Aviv 62098

rbalicer@clalit.org.il

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