Overview of outcomes measurement in diabetes and refmections on - - PowerPoint PPT Presentation

Overview of outcomes measurement in diabetes and refmections on diabetes registry research

Fabrizio Carinci

T e c h n i c a l C

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d i n a t

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t h e E U B I R O D N e t wo r k Adjunct Professor of Biostatistics, University of Bologna, Italy Visiting Professor, University of Surrey, UK

fabrizio.carinci@unibo.it

www.eubirod.eu www.hirs-research.eu/eubirod.html

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• provide broader and faster access to an ever increasing amount of

data of critical importance to improve health systems in the public interest

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• support research and make policy makers accountable for the

results obtained through their National legislation, policies and plans

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• evaluate adherence to evidence-based guidelines

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To set achievable targets for quality of care and outcomes, taking into account the costs and benefjts of difgerent alternatives

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• share best practices and avoid common mistakes

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• benchmark the efgect of local policies and health services
• rganization against difgerent alternatives, using same criteria and

methods for fair comparisons

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• avoid drawing conclusions from random fmuctuations, which can

be critical when data is incomplete or not suffjciently reliable

Why do we need standardised health information?

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O E C D H e a l t h a t a G l a n c e 2 1 7

Publications are useful, but late and not detailed enough to support policy decisions and personal choices

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OECD Health System Performance Framework 2015

Global standards are essential to share common principles for performance evaluation

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At a population-level, all segments of the population should be taken into account: missing those “hard to reach” will lead to “biased” results (e.g. blind not going to visits, etc)

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At a personal level, measurements should cover all relevant levels

• f care (from prevention to primary, specialist and acute care)

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Databases maintained by regions/countries may not include all people with diabetes in the denominator (e.g. undiagnosed or not recognised as person with diabetes)

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Databases maintained by single providers may report results only for specifjc patients (selection bias) and for catchment areas (geographical location) that cannot be compared to the population

How well are we doing?

Outcomes should refer to comparable, well defjned populations!

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How well are we doing?

Measures should cover all relevant aspects and be regularly monitored

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Epidemiological studies provide essential references, but do not represent a permanent source of information to understand how well are we doing on a permanent basis

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We need more detail that currently have to compare quality and

• utcomes at a global level. Even countries that are more evolved in

diabetes reporting, cannot compare systematically without robust global standards.

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Which indicators are available today?

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General data on diabetes prevalence (IDF ATLAS, total number of people in diabetes at a specifjc point in time), poor data on incidence (how many new cases per year)

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Few indicators calculated from administrative data sources (e.g. hospital data), prone to bias due to fjnancing mechanisms (e.g. DRGs)

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No indicators on intermediate and terminal outcomes (those that really matter for people with diabetes)

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D e a t h s d u e t

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i a b e t e s m e l l i t u s

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D i a b e t e s P r e v a l e n c e

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D i a b e t e s P r e v a l e n c e b y l e v e l

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D i a b e t e s H

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p i t a l A d m i s s i

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Recent attempts to strengthen the information base: useful, but diffjcult to compile and interpret

Examples: Prescription of hypertensive and Lower extremity amputations in diabetes, 2015

Source: OECD Health at a Glance 2017

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A global standard set in diabetes will help monitoring actions and plans in a comparable way, Using more granular data of clinical relevance: same approach from single provider to countries and international organizations

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A complete set of measurement will allow exploring aspects that cannot be covered today: integrated care, patient experiences and personal choices, etc.

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A multidimensional approach can represent a valid model for all non communicable diseases

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The standard set will help connecting information stored in difgerent silos (networks) and/or dispersed at the national/sub-national level

From local to global: Relevance of a new standard set in diabetes

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HIGH QUALITY INFORMATION … but...

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Heterogeneous

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Fragmented/Diffjcult to connect

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Regulated by difgerent policy mechanisms

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Not based on standardised measures

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Lacking solid international comparisons

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Difgerent principles for data sharing

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Regularly available only in national language

Example: diabetes registers in Europe

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METHODOLOGY IS CRUCIAL IN THE CONSTRUCTION AND USE OF DISEASE REGISTERS

Different types of models for data collection may bias the results...

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Different data sources may lead to very different results...

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Structure of a population- based disease register

Allows collecting a range of measures in a rigorous manner!

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Survey of diabetes data sources in Europe

Source: EUBIROD Network 2017

Instrument: Questionnaire including structured items on: Description; Scope of information; Governance; Technical Infrastructure; Outputs. Data collection system: REDCap open source research server, hosted in Slovenia Timeframe: August-September 2017 Taxonomy

• A. Population-based Registers. Croatia, Sweden,

UK-Scotland

• B. National Audits and surveillance systems.

Belgium, Germany, UK-England

• C. National databases for quality indicators.

Israel, Latvia

• D. Different types and levels of data sources.

Cyprus, Hungary, Israel, Italy, Malta, Poland, Romania, Slovenia

How to merge approaches?

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EU BIRO and EUBIROD projects

EU DG-SANCO co-funded public health projects BIRO project (2005-2009) EUBIROD project (2008-2012) BRIDGE-HEALTH (2015-2017)

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Successful Road Test EUBIROD Report (2012)

8/2/2012: New BIRO Release 2.1.12 15/2/2012: Collection of statistical objects 21/2/2012: EU Draft Report from 18 countries (N=79 indicators) 13 Days from Software Release to Online Publication of the results ! 1/3/2012 Project Ends SUSTAINABILITY: DIABETES INFORMATION NOT INCLUDED AS A TOPIC IN EU PROGRAMS SINCE THEN!

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General Software for Federated Analysis

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• Joanneum Research, Austria
• International Diabetes Federation (IDF),

Belgium

• Scientifjc Institute of Public Health, Belgium
• National Institute of Public Health, Croatia
• University of Zagreb, Croatia
• Ministry of Health, Cyprus
• Adult National Diabetes Register,Denmark
• University of Debrecen, Hungary
• Ministry of Health, Israel
• Serectrix, Italy
• Ministry of Health, Latvia
• University of Malta, Malta
• NOKLUS, Norway
• Silesian University of T

echnology, Poland

• T

elemedica Consulting, Romania

• University of Ljubljana, Slovenia
• IDIBAPS, Spain
• Foundation for Care Information, The

Netherlands

• University of Dundee, UK
• University of Surrey, UK

 Sharing:  Information  Best practices  T

• ols

 Methods  Creating Opportunities for:  T

argeted Research Partnerships

 Direct Involvement with

EU/International Organizations

 Building together:  Global platform for diabetes monitoring

Coordinating Centre

www.eubirod.eu http://www.hirs-research.eu/eubirod.html

Linking registers through common information standards: “federated” model

Partnerships are essential to implement common standards in the public interest

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At the OECD Health Ministerial 2017, Health Ministers from around the globe:

 committed to realise person-centred health systems  expressed their interest to measure person reported

• utcomes and costs for each individual with a

specifjed target condition (fundamental prerequisite for Value-based Health Care)

...a wind of change?

Person-centred health systems

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Numerator

• Denominator

DATA

(LINKAGE)

INDICATOR

ACTIONABLE

time

admission event contacts

QUALITY OF CARE COST HEALTH

Triple aim

A data model for person-centred health care

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T i m e t

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e t h e r ?