Health Care System Change Via Data Analytics To Enable Collaboration

The case of decentralised assisted living in the Netherlands

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Abstract

The gap between planning and budgeting is a problem for improving health systems. In decentralisation health care services, authority, resources, and responsibilities are moved from central actors (i.e. national government) to peripheral actors (i.e. municipalities). Adding the risk of creating silos within sub-national governments, creating the need for collaboration in some form. Data analytical forecasting, like prognosis tools, may facilitate planning for health care service implementation. When operating on the interface between actors, as a boundary object, they may mitigate the risk of fragmentation and isolation associated to decentralisation, by enabling collaboration.

In the case of decentralised Assisted Living in the Netherlands ("Beschermd Wonen") citizens dealing with psycho-social problems, receive guidance to participate in society. Newly responsible sub-regions have limited facilities and funds for their own citizens.

Newly responsible sub-regions having limited facilities and funds, may face incurring costs and inaccessible care when citizens seek to other areas due to uncoordinated implementation and elimination of facilities. To plan these, a prognosis tool was designed and developed for the three sub-regions.

A literature review was conducted on decentralisation of health care services globally. The prognosis tool’s technical design and development, and observations during, were studied. Analysed Interviews with actors involved in the prognosis tool, assessed if and how collaborating was enabled.

Lack of research on the implementation of decentralisation for health services, the use of prognosis tools for this purpose, the risk fragmentation resulting from independent processes and lack of system focus and the need for collaboration were highlighted in the literature, justifying building and testing a tool.

The design of the tool was therefore intentional: colour codes stimulated usability, the three sub-regions sub-files were stored in one place promoting transparency, and standardisation was stimulated by representing all sub-regions’ demands and resources into a general fitting categorisation and identical calculations from input to results for all sub-regions.

The tool and outcome is usable for agreements with care suppliers (procurement) or housing and enables organisation through agreements between sub-regions.

The meta-analysis of the interviews revealed that from the prognosis tool’s design and development, shared understanding emerged through shared language and extensive problem demarcation.
An independent expert mediated the needs of sub-regions, staying close to the task. This combined with the factual outcome led to insight and clarity in the content of subregions’ own and other’s task.

Inducing trust and confidence in the relation and in achieving own and shared goals. Leading to tranquility and comfort, setting the atmosphere for collaboration. By clarifying the uncertainties and interdependencies, where or why collaboration is needed (the identified risk) has stimulated collaborative action.

This prognosis tool has enabled collaboration for decentralised health services by addressing both socio-technical aspects. The latter integrate the effected sub-systems, ensuring the outcome can be used for organising future steps (such as procurement). The former, extensive problem demarcation and shared language emerged a shared understanding of the system. In combination with the factual outcome (prognosis), insight and clarity was created into the actual need and to enable trust and comfort, enabling collaboration.