PMD127 - FIRST DO NO HARM? EXPLORING THE INTERPRETATION OF NICE DIAGNOSTIC ASSESSMENTS WITH COST SAVINGS AND QALY LOSS

Abstract

The National Institute for Health and Care Excellence (NICE) currently employs a threshold range between £20,000 to £30,000 per QALY gained to use as a decision rule and interpret the results of cost-effectiveness analysis. This decision rule is generally applied to the commonly observed scenario in which a new technology generates a gain in quality adjusted life years but at an increased cost to the healthcare system. The aim of this study was to explore the interpretation of cost-effectiveness analyses for diagnostics that were cost-saving but resulted in a decrease in QALYs of the relevant patient population. Semi-structured telephone interviews were conducted with a sample of health economists. All interviews were digitally recorded and transcribed. Thematic analysis was used to analyse the qualitative data. 17 health economists were interviewed. The majority of interviewees believed that the same decision rule should apply to investment and disinvestment decisions. There were some health economists who stated that disinvestment required a different cost-effectiveness threshold, reflecting the different value individuals place on loss when compared with a gain in health status. Some interviewees expressed that there may be economic reasons to have different thresholds, and raised the need for empirical work to determine if opportunity cost or benefit, represented by incremental cost-effectiveness ratio thresholds, is the same at different points across the cost-effectiveness plane and for different budgetary impacts. A number of political considerations were raised about: identifiability; transparency in decision-making; public agreement on value judgements; impact of NHS budget reduction; different objective functions of NICE and commissioners. The appropriate decision rule to use when a new diagnostic generates cost-saving but resulted in a decrease in QALYs of the relevant patient population was not consistent. To understand the appropriate decision rule requires an informed consultation exercise involving decision-makers and the public.