Values and Decision-making within an Acute Medicine Service

Abstract

Theoretical frameworks of values in healthcare tend to come in one of two kinds: monism and pluralism. However, both value-monism and value-pluralism prove inconsistent and unrealistic when applied to controversial cases. The lack of clarity about values in healthcare contributes to the contentious nature of key concepts in decision-making, such as sickness and futility. The prominent decision-making models considered in this thesis are substituted decision-making, supported decision-making, shared decision-making, dual process theory, values-based practice and values-based medicine. Whilst each has its strengths, each model fails to provide a compelling account of the role of values in decision-making, on the grounds of arbitrariness, incompleteness or ambiguity. A lack of clarity about the role of values in decision-making is particularly problematic in busy and pressured clinical environments. An Acute Medicine Service (AMS) is a part of a hospital which is dedicated to the early management of medical emergencies. The workload of an AMS entails a heavy decision burden concerning a broad range of clinical problems under time pressure. In this ethnographic study, I was participant-observer within an AMS over a period of 16 months. This involved numerous informal interviews and 27 formal interviews with staff, patients and relatives. A thematic analysis of empirical data, borrowing insights from the tradition of philosophical hermeneutics, provides a plausible interpretation of the role of values in decision-making within an AMS. The data I present are organised around three main themes: restoring order, working together and what’s best. Within an AMS, a course of action is appraised according to three values: welfare, choice and effectiveness. These values are interdependent in a manner distinct from monism and pluralism. The implications of these findings for the philosophy of medicine and clinical decision-making are discussed, with some suggestions for future prescriptive models and further research.