Should Severity Assessments in Healthcare Priority Setting be Risk- and Time-Sensitive?

Health Care Analysis 31 (3):169-185 (2023)
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Abstract

Background: Severity plays an essential role in healthcare priority setting. Still, severity is an under-theorised concept. One controversy concerns whether severity should be risk- and/or time-sensitive. The aim of this article is to provide a normative analysis of this question. Methods: A reflective equilibrium approach is used, where judgements and arguments concerning severity in preventive situations are related to overall normative judgements and background theories in priority-setting, aiming for consistency. Analysis, discussion, and conclusions: There is an argument for taking the risk of developing a condition into account, and we do this when we consider the risk of dying in the severity assessment. If severity is discounted according to risk, this will ‘dilute’ severity, depending on how well we are able to delineate the population, which is dependent on the current level of knowledge. This will potentially have a more far-reaching effect when considering primary prevention, potentially the de-prioritisation of effective preventive treatments in relation to acute, less-effective treatments. The risk arguments are dependent on which population is being assessed. If we focus on the whole population at risk, with T 0 as the relevant population, this supports the risk argument. If we instead focus on the population of as-yet (at T 0 ) unidentified individuals who will develop the condition at T 1, risk will become irrelevant, and severity will not be risk sensitive. The strongest argument for time-sensitive severity (or for discounting future severity) is the future development of technology. On a short timescale, this will differ between different diagnoses, supporting individualised discounting. On a large timescale, a more general discounting might be acceptable. However, we need to also consider the systemic effects of allowing severity to be risk- and time-sensitive.

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