Shaping healthcare quality through data - i-hd.eu presentations/Joint_event_Madrid_2017... · Ulcus cruris Dekubitus Retinopathie Herzinsuffizienz Koronare Herzkrankheiten Nierenleiden

Shaping healthcare quality through data

The role of public health insurers in Germany Madrid, September 21st 2017

Christoph J. Rupprecht Head of the department for Health Policy and Health Economics AOK Rheinland/Hamburg- Die Gesundheitskasse

2

Evolution...

20 - 40% of the services data recording

In the health care data processing

system: communication

Duplication of the medical

knowledge every 5 years

The diagnostic and therapeutic spectrum of care

is getting more and more complex

Globalisation and european

integration

Sectoral care as barrier

Communicational

shortcomings

Actual situation in

the health care system

Information, communication and knowledge...

Establishment of innovative and insuree-friendly models • Improvement of low-threshold access for vulnerable patient groups such as socially

disadvantaged, migrants, people with disabilities, people with dementia (Billstedt/Horn)

• Structured treatment programs in DMP succession

• Further development of care in a meaningful way ("life air"), enable transitions (psychiatry)

• Shaping the transition from science to healthcare (gene sequencing)

• Interlinking new and proven interaction possibilities (apps and personal contact options)

• Developing alliances (self-help, interest groups, consumer protection)

Contracts: Identity, fields of action, data and perspective

The scope of routine claims data

Health services data

Outpatient sector

ICD-10 diagnosis data

(outpatient and inpatient)

ATC Code for medication

prescriptions

Invoicing data from auxiliary

service providers (wheelchairs,

clutches, physiotherapy…)

Emergency care transportation

services

Rehabilitation services

4 AOK Rheinland/Hamburg • Christoph J. Rupprecht

Inpatient sector

DRG Codes

Length of stay

Admission diagnosis

Discharge diagnosis

Patient demographics

Age

Gender

Address

Social security status

Disability status

Income

Provider information

Lifelong

physician/pharmacist

number

Lifelong practice number

Hospital ID

Supplemented by Patient satisfaction surveys

QoL surveys (SF 36 etc.)

Madrid, September 21st 2017

Advantages and drawbacks of routine claims data

Advantages of routine billing data:

1) Full view on patient „trajectory“ across providers and sectors

2) No additional data collection effort

3) High spatial granularity allowing for a „zoom“ on healthcare delivery at city level

4) Highly regulated area with decades of practice

Drawbacks of routine data:

1) Generally no clinical data (exception: e.g. Disease Management Program

Diabetes)

2) Availability time-lag of approximately 6 to 9 months in outpatient care

3) Difficult to operationalise for „outcome quality“, limited number of „use cases“



Source: results from 98.194 questionnaires collected in the framework of a joint survey by AOK Rheinland/Hamburg, Barmer GEK und hkk

60%

65%

70%

75%

80%

85%

90%

95%

1 5 9

13

17

21

25

29

33

37

41

45

49

53

57

61

65

69

73

77

81

85

89

93

97

10

1

10

5

10

9

11

3

11

7

12

1

12

5

12

9

13

3

13

7

14

1

14

5

14

9

Ø Federal average: 82 %

149 hospitals in Rhineland region with at least 75 responses

Results of a patient satisfaction survey: rates of recommendation

AOK Rheinland/Hamburg • Christoph J. Rupprecht 6 Madrid, September 21st 2017

I – each blue line represents one hospital

Elective hip surgery: results from the QSR analysis

1,0 = risk adjusted event rate corresponds to federal average

Below 1,0 = risk adjusted event rate is better than federal average

Over 1,0 = risk adjusted event rate is worse than federal average

AOK Rheinland/Hamburg • Christoph J. Rupprecht 7 Madrid, September 21st 2017 I – each blue line represents one hospital

Pflegeberaterinnen der AOK

Examples of innovative projects that run on routine healthcare data



AOK claims data evaluation

AOK participation in a select number of projects

INVEST Billstedt-Horn: integrated care network at city district level

ACD: holding physician networks accountable for quality

Arena: combating antibiotic resistance through data-based quality feedback in physician networks

TeLiPro: establishing a telemedical lifestyle intervention for Diabetes Typ 2 patients


Predictive modelling

Physician score-cards

Patient-tailored interventions


Project INVEST: Establishing an integrated care system at city district level

A deprived neighbourhood in Hamburg: „Billstedt-Horn“



Project „INVEST“ background

A deprived city district: Hamburg district „Billstedt-Horn“ characterised by

106.000 inhabitants with mostly low socio-economic status

Above average per capita healthcare expenditure

Citizens with mixed ethnic origins

Poor access to healthcare services

Average age at time of death: 71


Actors and processes in project INVEST

AOK Rheinland/Hamburg • Christoph J. Rupprecht

Participating providers

Health care controlling

Participation declarations, program participation,

Treatments, and surveys

Data delivery

Data protection

Consent verification

Feedback for providers

Health insurers' administrative data

Datastorage

Datacheck

Data evaluation

Declaration of participation of the service providers and insureds

Prevention

Diagnostics

Therapy

Interventional objectives: • Improve medication safety/prescription • Reduce unnecessary hospital admissions • Activate patients, improve access

( „Gesundheitskiosk“)

Vulnerable insurants

Diabetes

Multi-morbility

Migration background

Services

Program participation

14 Madrid, September 21st 2017

INVEST Billstedt/Horn – project consortium insurers – providers – research organisations


Gesundheit für Billstedt/Horn UG

Ärztenetz Billstedt-Horn e.V.

OptiMedis AG

Stadtteilklinik Hamburg

NAV-Virchow-Bund e.V.

Cooperating partners


The concept of „ambulatory care sensitive conditions“


2015 report by WHO Regional Office for Europe

In 2012: 5,04 mio. inpatient cases classified as sensitive to ambulatory care

Of which 3,52 mio. considered avoidable

7,2 bn EURO avoidable expenditure

Most likely causes: Insufficient outpatient

coordination Insufficient cross-sectoral

coordination


ACD – Methods 1


1. Step: Quantitative analysis of claims data by AOK RH, AOK NW and TK as well as routine data by regional physician associations

Quelle: Projektposter ACD, 2017

a) Identify provider networks

c) Observe care pathways

b) Analyse quality of care


ACD – Methods 2


2. Step: Identified networks are randomly assigned to an intervention and a control group; intervention group receives quality feedback based on data analysis; health-economic effects are analysed

Quelle: Projektposter ACD, 2017

Cluster randomisation of physican networks

Control group

Endpoint: hospital admissions

Endpoint: hospital admissions

Intervention group: Quality feedback


TeliPro: a life-style intervention for diabetic patients



Kreis Kleve

Kreis Viersen

Kreis Heinsberg

Aachen Kreis

Aachen

Krefeld

Kreis Wesel

Ober-

hausen

EssenDuisburg

Mülheim

a.d.R.

Düsseldorf

Kreis Mettmann

Leverkusen

Mönchen-

gladbach

Rhein-Kreis Neuss

Kreis Düren

Rhein-Erft-Kreis

Köln

Rhein-Sieg-Kreis

Rheinisch-

Bergischer

Kreis

Solingen

Wuppertal

Remscheid

Oberbergischer Kreis

Kreis Euskirchen

Bonn

Klassengrenzen≥ 10,1% - < 10,9% (6)

≥ 10,9% - < 11,2% (5)

≥ 11,2% - < 11,7% (6)

≥ 11,7% - < 12,0% (5)

≥ 12,0% - < 12,8% (6)

Hamburg

Diabetes mellitus share of patients, 2015

22 AOK Rheinland/Hamburg • Christoph J. Rupprecht Source: AOK Rheinland/Hamburg, standardised according to federal census

ICD10-Code: E10-E14

ø Rheinland/Hamburg 11,4%

12,8%

12,2%

12,2%

12,1%

12,1%

12,0%

11,9%

11,9%

11,9%

11,8%

11,8%

11,7%

11,6%

11,5%

11,5%

11,3%

11,2%

11,2%

11,1%

11,1%

11,0%

11,0%

10,8%

10,7%

10,4%

10,2%

10,1%

10,1%

0% 5% 10% 15%

Essen

Duisburg

Krefeld

Mönchengladbach

Oberhausen

Remscheid

Kreis Aachen

Wuppertal

Kreis Düren

Leverkusen

Köln

Rhein-Erft-Kreis

Bonn

Hamburg

Mülheim a. d. Ruhr

Kreis Viersen

Kreis Heinsberg

Rhein-Kreis Neuss

Kreis Mettmann

Solingen

Düsseldorf

Rhein-Sieg-Kreis

Kreis Wesel

Rheinisch-Berg. Kreis

Oberbergischer Kreis

Aachen

Kreis Euskirchen

Kreis Kleve

| = 2010 ø 9,9%


Prevalence of select chronic conditions comparison of insureers with and without diabetes, 2015


0%

5%

10%

15%

20%

25%

30%

35%

Diabetisches

Fußsyndrom

Ulcus cruris Dekubitus Retinopathie Herzinsuffizienz Koronare

Herzkrankheiten

Nierenleiden

kein Diabetes Diabetes

Source: AOK Rheinland/Hamburg, comparison based on matching process

0,0%

0,1%

0,2%

0,3%

0,4%

0,5%

0,6%

0,7%

0,8%

0,9%

Herzinfarkt


Inpatient admissions as a consequence of


0

10

20

30

40

50

60

70

80

90

Beschäftigte ALG-II-Bezieher

Cases p

er

100.0

00 Insure

e y

ears

Quelle: AOK Rheinland/Hamburg, indirekt standardisiert

Diabetes mellitus Heart attack cases (diabetics) Soc. Security recipients vs. regular employed, 2015 social security recipients vs. regular

0

200

400

600

800

1000

1200

Beschäftigte ALG-II-Bezieher

Cases p

er

100.0

00 Insure

e y

ears


TeLiPro Intervention

Individual coaching based on bloodsugardata, body weight and physical acitivty as input factors



Telemedical life-style intervention for Diabetes patients (TeLiPro)

Background: insulin dependence can be reduced, if diet is changed

Objective: improve health and quality of life of Typ 2 diabetics through a long-term and sustainable change of life-style using telephone coaching in addition to routine care

Avoid permanent dependence on insulin-medication

Provide 1:1 data-driven telephone coaching

26

AOK Rheinland/Hamburg • Christoph J. Rupprecht


Relevance of TeliPro

Achieving an insulin-free, high quality of life for diabetic patients

Address individual needs of patients, especially for people with low health literacy

Identify and address patient groups with specific needs

Scaleability of telemedical solution



Improving care for patients with diabetic foot syndrome

Background: Diabetic Foot Syndrome (DFS) is a severe complication of Diabetes; in coordinated care networks, it is largely preventable

Objective: reduce major amputation rates

AOK‘s DFS care contract:

Establishment of a formal network of physicians responsible for DFS patients with clear structural requirements on the kind of expertise that needs to be available

Definition of „wound assistant“ qualifications

Appointment within 24 hrs

Hospital referral only to specialised units

Quality management system

Clear financial incentives for surgeons to treat DFS conservatively



Improvement of major amputation rate, DMP vs. non-DMP participation


0%

1%

2%

3%

4%

5%

DMP-Teilnahme keine DMP-

Teilnahme

Ante

il an V

ers

ichert

en m

it D

iabetischem

Fußsyn

dro

m


Conclusion

Routine claims data is one vital tool to drive innovation in health service delivery

Insurers can use their data to:

Control quality of care

Analyse weaknesses in the care delivery system (over- and undersupply)

Identify patient groups with particular needs (low health literacy, access problems)

Build new care contracts based on insights gained from data analysis

AOK Rheinland/Hamburg is actively engaged in a high number of projects that make use of routine data to improve healthcare



Innovative Treatment

Molecular diagnostics and personalized therapy for lung cancer (University of Cologne): An integrated care contract as a motor for innovation

Patient from Cologne with ROS1 translocation under therapy with ROS inhibitor


32

Multitude of potential starting points

target orientated therapy in oncology

Tumor

growth

Cyclin dependent

Kinaseininhibitors

Immune-activating

Anti-CTLA4 mAb

Telomerase-

inhibitors

Inhibitors of the

VEGF-Signalling

PARP-Inhibitors

proapoptotic

BH3-Mimetika

Inhibitors of the

aerobic glycolysis

EGFR-

Inhibitors

Selective anti-

inflammatory agents

Inhibitors

HGF/c-Met

Deregulation of

cellular energy

balance

Preservation of

proliferative signal

cascade

Circumvention of

growth inhibition

Prevention of

destruction by the

immune system

Unlimited

Replication

Tumor stimulating

inflammation

Apoptosis-

resistance

Instability of

the genome

and mutation

Stimulation of the

angiogenesis Activation of invasive

growth and metastasis

Source: Adapted from Steward J, Naeymi-Rad N, et al.

Lung-Ca e.g.…EGFR, ALK, MET, ROS-1,

KRAS , RET…

Network Genomic Medicine (NGM) lung cancer of the University of Cologne

Many years of experience with mutation analysis and high method competence

(high number of NGS-based diagnostics per year)

High level of consulting competence

Continuous accompanying evaluation

Participation in relevant clinical studies

Knowledge and guarantees of the latest therapeutic approaches

Second opinion for patients

Patient-oriented study participation

Contract on the basis of integrated health care (§§ 140a-d SGB V [old]).

Start with the AOK Rheinland/Hamburg in April 2014

Accession of other German health insurance companies:

KKH, BKK Novitas, BKK VBU, BIG direkt gesund, BKK Viactiv,

Barmer, SBK, and TK.

Genome profiling

Implementation of molecular diagnostics and

personalized therapy in lung cancer

Source: aacc.org 33

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Shaping healthcare quality through data - i-hd.eu presentations/Joint_event_Madrid_2017... · Ulcus cruris Dekubitus Retinopathie Herzinsuffizienz Koronare Herzkrankheiten Nierenleiden