DOI: 10.5061/dryad.j0zpc86dz
title: Quality of care and performance indicators of mental health supported accommodation services in England

description: This dataset includes data from Mental Health supporting accommodation
 services in England. It includes information on resources (inputs) and
 outcomes (outputs) of care, which are described in the manuscript
 published in Plos One: “Almeda, N., García-Alonso, C. R., Killaspy, H.,
 Gutiérrez-Colosía, M. R., & Salvador-Carulla, L. (2022). The
 critical factor: The role of quality in the performance of supported
 accommodation services for complex mental illness in England. Plos One,
 17(3), e0265319. https://doi.org/10.1371/journal.pone.0265319" The
 research associated with the present data focused on developing an
 analytical process for assessing the performance of the Mental health (MH)
 supporting accommodation services from 14 different regions of England
 considering the effect of the quality-of-care indicators in the
 performance. For doing so every service was classified in Residential Care
 (move on and non-move on oriented), Supported Housing or Floating
 Outreach. Then, information about the quality-of-care was collected from
 each domain of the instrument QuIRC-SA. Finally, a decision support system
 that integrated data envelopment analysis, Monte Carlo simulation and
 artificial intelligence was used. The main results of the analyses pointed
 out that the incorporation of quality domains as variables (outputs) in
 DEA had a neutral-positive or positive global impact on the performance of
 MH-supported accommodation services.
description: Data for supported accommodation services from 14 nationally
 representative local authorities in England were collected for the QuEST
 study, which was funded by the National Institute of Health Research
 (2012-2017) (http://www.ucl.ac.uk/quest). Face-to-face interviews were
 conducted with service managers, key staff, and service users to assess
 the quality and characteristics of the services and those using them. The
 Quality Indicator for Rehabilitative Care–Supported Accommodation
 (QuIRC-SA) was completed with service managers. This standardized tool
 assesses service quality in seven domains:<em> living environment,
 therapeutic environment, treatments and interventions, self-management and
 autonomy, social interface, human rights, and recovery-based
 practice</em>. Data on the service’s annual budget, weekly cost per
 user, and service resources were also provided by the service managers to
 complement standard service costs for estimation of the cost-effectiveness
 of services. A psychiatrist with national-level
 expertise in policy pertaining to people with severe MH problems, two
 national leaders in MH-supported accommodation service provision and
 policy, and three researchers who collected data from 87 supported
 accommodation services across England during the QuEST study designed the
 scenarios by choosing the variables and their interpretation in each
 scenario. The variables considered as relevant inputs were service budget
 (£ per place), places (number), and full-time equivalent staff
 (professionals per service user), and the relevant outputs were the
 average length of stay (years), occupied beds (%), the number of service
 users who moved to more independent accommodations (users per place), and
 the seven QuIRC-SA quality of care variables considering the service size
 (<em>value of the domain×available places/100</em>). By using
 the last mathematical transformation, original quality indicators
 considered the size of the service. All the considered transformations of
 original data render the selected services comparable by eliminating the
 potential “size” effect on performance assessments. Eight different
 scenarios, or input/output variable combinations, were designed to assess
 the RTE of residential care and supported housing services. For floating
 outreach services, only seven scenarios were identified because this type
 of care does not include the “living environment” QuIRC-SA service quality
 domain. Scenario 1 can be considered the “reference” scenario because it
 does not include any quality domains.
description: The README file contains an explanation of each variable in the
 dataset, including its variable name, units, and explanation. This dataset
 has been used for assessing relative technical efficiency, stability, and
 entropy indicators.