gms | German Medical Science

63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

02. - 06.09.2018, Osnabrück

Apomediative e-decision support for self-produced health

Meeting Abstract

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  • Mette Kjer Kaltoft - Odense University Hospital Svendborg, Svendborg, Denmark; University of Southern Denmark, Odense, Denmark
  • Jesper Bo Nielsen - University of Southern Denmark, Odense, Denmark
  • Jack Dowie - London School of Hygiene and Tropical Medicine, London, Great Britain; University of Southern Denmark, Odense, Denmark

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Osnabrück, 02.-06.09.2018. Düsseldorf: German Medical Science GMS Publishing House; 2018. DocAbstr. 30

doi: 10.3205/18gmds023, urn:nbn:de:0183-18gmds0234

Veröffentlicht: 27. August 2018

© 2018 Kaltoft et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: In the human capital paradigm, subject to external constraints, a person’s health capital is self-produced. In this producing role they spend time, effort, and financial resources acquiring inputs that either enhance or deplete their health through consuming goods and services relevant to health. Among these are the services provided by healthcare organisations and in this model the person’s demand for health services is derived from their demand for health. Accordingly, the main function of health services is not to produce health, but to support the person in their self-production investment decision making. (A second, derived, function is to facilitate the implementation of the decision if it requires professional prescription or competence). Personalised decision support is a pre-requisite for self-production given the complexity of optimising health decisions in relation to prevention, testing, and treatment for multiple conditions across the lifespan.

Methods: In the health context the decision support tools depend on the role of the provider (e.g. clinician) and person. Non-mediative tools are designed to help the clinician decide what is best for the patient. Inter-mediative Patient Decision Aids are designed to help the clinician and patient decide together, in a ‘co-creation’ encounter, what is best for the patient. Apomediative Personalised Decision Support Tools are designed to help the person decide what is best for themselves, including whether to seek a professional consultation and/or to prepare for, and engage in, an apomediation-empowered inter-mediative consultation. We develop Apomediative support by ‘translating’ research output/guidelines/key messages into a generic MyDecisionSuite format via Multi-Criteria Decision Analysis (MCDA-) based software, which complies with data security requirements in the regional/national context.

Results: A personalised MCDA-support tool is provided for the statin decision: Should I go to my general practitioner either to ask for a statin prescription or to discuss taking statins? This tool (available online) involves the person completing an online instrument to assess their personalised risks of All-Cause Mortality and Cardiovascular Disease Mortality in the next ten years; self-assessing their blood pressure and cholesterol level (the two inputs required, along with age, sex, and smoking status, to complete the instrument); self-rating the treatment burden of statins; and relative weighting the four criteria (10 year mortalities, statin side effects, and statin burden). The opinion of the tool comes in the form of the expected value of the two options (percentage-scores).

Discussion: Preference-sensitive Apomediative support tools cater for the key requirements of self-produced health, along with informed and preference-based consent to any subsequent provider action. The desirable form of Apomediative support is a publicly accessible, provider-independent, MCDA-based decision support, familiar via consumer organization comparative magazines which support self-production decisions. Expanding the scope of those may generate preference-sensitive decisions via MCDA while also ensuring a fully informed and preference-based consent to any subsequent health provider actions.

MCDA-based personalised decision support tools are offered to provide the apomediative support which probably is necessary for the efficient, preference-sensitive self-production of health.

Competing interests: Jack Dowie has a financial interest in the Annalisa software used in the MCDA-based tools.

The authors declare that an ethics committee vote is not required.