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Conference Abstracts

Building the evidence base for integrated care planning: proof-of-concept analysis of a multi-sector integrated dataset in Estonia


Adriana Poppe ,

PMV research group, DE
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Gerli Aavik-Märtmaa,

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Ene Rebane,

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Ingo Meyer

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A major problem in achieving person-centered and integrated care is the fragmentation of individual support into the different service silos. This fragmentation carries through into the world of information, with siloed data systems for different sectors. Therefore, no uniform picture can be formed across different sectors about all the support a person has received. This can result in problems understanding the individuals’ needs, their current care situation and how both matches. To tackle those problems and moreover, to improve the quality and efficiency of support systems integrated care models are perceived as an important, innovative and promising way [1].

Aims Objectives Theory or Methods

Data integrated from different sectors is needed for better policy-making, administration of services and people and providing integrated care services at the service delivery level. Therefore, a proof-of-concept version of an integrated dataset to support care integration has been developed in Estonia. It contains data of the social insurance board, the municipalities (responsable for different services), unemployment insurance fund and the health insurance fund and etc.. By using personalized IDs, data sheets from different sectors were linked. The data sets were tested for plausibility in their association, for example, whether people receive pension and unemployment benefit at the same time.

Highlights or Results or Key Findings

Since the dataset is based on registration, social and health data, no population biases are present, which is an advantage in the attempt to display the population of a country/region. Generally, the plausibility checks and proof-of-concept analyses show that the dataset is plausible. Research questions such as the share of persons where trajectory includes hospital services and duplication of service periods can be answered. Nevertheless, it must be said that the data from one sector was of poor quality, which limits the quality of the entire data set. In addition, different coding methods of, for example, dates, lead to error-proneness when linking the data. Some dates contain only a month and/or year, making them difficult to use while, for example, building periods of service provision. Adjustment of the coding strategies among the sectors would be helpful to improve the quality of the dataset.


It is generally suitable for delivering aggregated data for planning and decision-making processes in the context of integrated care. It provides coverage of the different sectors and their services that can be brought together. What assessments, services, benefits etc. was received at a given time can be shown.

Implications for applicability/transferability sustainability and limitations

Several limitations such as coding precision have to be considered while carrying out data integration of more regions and/or further analyses.



[1]       Council of the European Union. Council conclusion on the Reflection process on modern, responsive and sustainable systems; 2013 [cited 2021 May 31] Available from:

How to Cite: Poppe A, Aavik-Märtmaa G, Rebane E, Meyer I. Building the evidence base for integrated care planning: proof-of-concept analysis of a multi-sector integrated dataset in Estonia. International Journal of Integrated Care. 2022;22(S2):67. DOI:
Published on 16 May 2022.


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