Abstract
 |
| Dr Anju Devianee Keetharuth |
Aim: The aim of this project is to develop and
assess a mapping function to predict ReQoL-UI (a patient-reported mental
health-specific preference-based measure) scores from HoNOS scores
(clinician-reported measure, Health of Nation Outcomes Score).
Methods:
Participants were recruited from 14 secondary mental health services in
England, UK, and their clinician completed HoNoS. Mapping models were estimated
using Ordinary Least Squares (OLS) on individual level and mean level data and
different model specifications were explored. Model performance was assessed
using mean absolute error (MAE), root mean square error (RMSE), percentage of
observations with absolute errors greater than 0.1, and plots of the observed
and predicted ReQoL-UI utilities and errors.
Results:
Matched ReQoL-UI and HoNOS scores were collected for 649 participants. The
sample comprised 56% inpatients, with overall mean ReQoL-UI utility of 0.683
and range from 1 to -0.195. Correlations between ReQoL-UI (items and utility)
and HoNOS scores were moderate (0.2<r<0.4) or small (<0.2). The best
model was OLS estimated using mean level data, with lowest MAE (0.046) and RMSE
(0.056).
Discussion: There is little conceptual overlap between ReQoL-UI and HoNOS. They measure different concepts and, arguably, service users and clinicians, who complete the measures respectively, have different perspectives. Under these circumstances, caution is recommended when applying these estimates.
