Research Article: What utility scores do mental health service users, healthcare professionals and members of the general public attribute to different health states? A co-produced mixed methods online survey

Date Published: October 23, 2018

Publisher: Public Library of Science

Author(s): Chris Flood, Sally Barlow, Alan Simpson, Amanda Burls, Amy Price, Martin Cartwright, Stefano Brini, Takeru Abe.

http://doi.org/10.1371/journal.pone.0205223

Abstract

Utility scores are integral to health economics decision-making. Typically, utility scores have not been scored or developed with mental health service users. The aims of this study were to i) collaborate with service users to develop descriptions of five mental health states (psychosis, depression, eating disorder, medication side effects and self-harm); ii) explore feasibility and acceptability of using scenario-based health states in an e-survey; iii) evaluate which utility measures (standard gamble (SG), time trade off (TTO) and rating scale (RS)) are preferred; and iv) determine how different participant groups discriminate between the health scenarios and rank them.

This was a co-produced mixed methods cross-sectional online survey. Utility scores were generated using the SG, TTO and RS methods; difficulty of the completing each method, markers of acceptability and participants’ preference were also assessed.

A total of 119 participants (58%) fully completed the survey. For any given health state, SG consistently generated higher utility scores compared to RS and for some health states higher also than TTO (i.e. SG produces inflated utility scores relative to RS and TTO). Results suggest that different utility measures produce different evaluations of described health states. The TTO was preferred by all participant groups over the SG. The three participant groups scored four (of five) health scenarios comparably. Psychosis scored as the worst health state to live with while medication side-effects were viewed more positively than other scenarios (depression, eating disorders, self-harm) by all participant groups. However, there was a difference in how the depression scenario was scored, with service users giving depression a lower utility score compared to other groups.

Mental health state scenarios used to generate utility scores can be co-produced and are well received by a broad range of participants. Utility valuations using SG, TTO and RS were feasible for use with service users, carers, healthcare professionals and members of the general public. Future studies of utility scores in psychiatry should aim to include mental health service users as both co-investigators and respondents.

Partial Text

Mental ill health is a key contributor to the burden of disease [1] costing an estimated £70-£100 billion per year in the United Kingdom (UK), equivalent to 4.5% of gross domestic product (GDP) [2]. Over half of this cost relates to reduced quality of life [3]. There is a need to prioritise interventions that are cost-effective and target health states that service users report have the greatest impact on their lives.

In this study, we sought to collaborate with service users to co-produce descriptions of mental health states from which to generate utility scores and frame utility questions so that they are comprehensible to service users. Another aim was to determine the feasibility of using different utility methods via an online questionnaire. We compared utility scores provided by service users, healthcare professionals, members of the public, and carers (descriptively). The acceptability of the co-produced health states and the different utility methods to determine health utility was also examined.

This study involved service users and reports the initial steps towards developing and embracing a process of research co-production in a complex field [42, 43]. Additional studies involving service users in utility measurement are needed in the attempt to promote sensitive measurement design, increase instrument validity, study feasibility and the acceptability of the measures. Future studies may aim to build on more extensive involvement by developing knowledge and understanding to include service users in the analysis of data and interpretation of results [44].

 

Source:

http://doi.org/10.1371/journal.pone.0205223

 

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