Under careful construction: combining findings, arguments, and values into robust health care coverage decisions

BMC Health Serv Res. 2022 Jun 7;22(1):756. doi: 10.1186/s12913-022-07781-1.

Abstract

Background: Health care coverage decisions deal with health care technology provision or reimbursement at a national level. The coverage decision report, i.e., the publicly available document giving reasons for the decision, may contain various elements: quantitative calculations like cost and clinical effectiveness analyses and formalised and non-formalised qualitative considerations. We know little about the process of combining these heterogeneous elements into robust decisions.

Methods: This study describes a model for combining different elements in coverage decisions. We build on two qualitative cases of coverage appraisals at the Dutch National Health Care Institute, for which we analysed observations at committee meetings (n = 2, with field notes taken) and the corresponding audio files (n = 3), interviews with appraisal committee members (n = 10 in seven interviews) and with Institute employees (n = 5 in three interviews), and relevant documents (n = 4).

Results: We conceptualise decisions as combinations of elements, specifically (quantitative) findings and (qualitative) arguments and values. Our model contains three steps: 1) identifying elements; 2) designing the combinations of elements, which entails articulating links, broadening the scope of designed combinations, and black-boxing links; and 3) testing these combinations and choosing one as the final decision.

Conclusions: Based on the proposed model, we suggest actively identifying a wider variety of elements and stepping up in terms of engaging patients and the public, including facilitating appeals. Future research could explore how different actors perceive the robustness of decisions and how this relates to their perceived legitimacy.

Keywords: Expertise; Health Care Coverage; Health Care Decision-making; Patient and Public Involvement and Engagement; Robustness.

MeSH terms

  • Academies and Institutes
  • Biomedical Technology*
  • Delivery of Health Care*
  • Health Facilities
  • Humans