Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.

<h4>Background</h4>Healthcare systems monitor and improve mental health treatment quality, access, continuity and satisfaction through use of population-based and efficiency-based staffing models, the former focused on staffing ratios and the latter, staff productivity. Preliminary evide...

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Autores principales:	Matt Boden, Clifford A Smith, Jodie A Trafton
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e116e54bbdb04df0926f4b9ff49ab8dd
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spelling	oai:doaj.org-article:e116e54bbdb04df0926f4b9ff49ab8dd2021-12-02T20:18:04ZInvestigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.1932-620310.1371/journal.pone.0256268https://doaj.org/article/e116e54bbdb04df0926f4b9ff49ab8dd2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0256268https://doaj.org/toc/1932-6203<h4>Background</h4>Healthcare systems monitor and improve mental health treatment quality, access, continuity and satisfaction through use of population-based and efficiency-based staffing models, the former focused on staffing ratios and the latter, staff productivity. Preliminary evidence suggests that both high staffing ratios and moderate-to-high staff productivity are important for ensuring a full continuum of mental health services to indicated populations.<h4>Methods & findings</h4>With an information-theoretic approach, we conducted a longitudinal investigation of mental health staffing, productivity and treatment at the largest integrated healthcare system in American, the Veterans Health Administration (VHA). VHA facilities (N = 140) served as the unit of measure, with mental health treatment quality, access, continuity and satisfaction predicted by facility staffing and productivity in longitudinal mixed models. An information-theoretic approach: (a) entails the development of a comprehensive set of plausible models that are fit, ranked and weighted to quantitatively assess the relative support for each, and (b) accounts for model uncertainty while identifying best-fit model(s) that include important and exclude unimportant explanatory variables. In best-fit models, higher staffing was the strongest and most consistent predictor of better treatment quality, access, continuity and satisfaction. Higher staff productivity was often, but not always associated with better treatment quality, access, continuity and satisfaction. Results were further nuanced by differential prediction of treatment by between- and within-facility predictor effects and variable interactions.<h4>Conclusions</h4>A population-based mental health staffing ratio and an efficiency-based productivity value are important longitudinal predictors of mental health treatment quality, access, continuity and satisfaction. Our longitudinal design and use of mixed regression models and an information-theoretic approach addresses multiple limitations of prior studies and strengthen our results. Results are discussed in terms of the provision of mental health treatment by healthcare systems, and analytical modeling of treatment quality, access, continuity and satisfaction.Matt BodenClifford A SmithJodie A TraftonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0256268 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Matt Boden Clifford A Smith Jodie A Trafton Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
description	<h4>Background</h4>Healthcare systems monitor and improve mental health treatment quality, access, continuity and satisfaction through use of population-based and efficiency-based staffing models, the former focused on staffing ratios and the latter, staff productivity. Preliminary evidence suggests that both high staffing ratios and moderate-to-high staff productivity are important for ensuring a full continuum of mental health services to indicated populations.<h4>Methods & findings</h4>With an information-theoretic approach, we conducted a longitudinal investigation of mental health staffing, productivity and treatment at the largest integrated healthcare system in American, the Veterans Health Administration (VHA). VHA facilities (N = 140) served as the unit of measure, with mental health treatment quality, access, continuity and satisfaction predicted by facility staffing and productivity in longitudinal mixed models. An information-theoretic approach: (a) entails the development of a comprehensive set of plausible models that are fit, ranked and weighted to quantitatively assess the relative support for each, and (b) accounts for model uncertainty while identifying best-fit model(s) that include important and exclude unimportant explanatory variables. In best-fit models, higher staffing was the strongest and most consistent predictor of better treatment quality, access, continuity and satisfaction. Higher staff productivity was often, but not always associated with better treatment quality, access, continuity and satisfaction. Results were further nuanced by differential prediction of treatment by between- and within-facility predictor effects and variable interactions.<h4>Conclusions</h4>A population-based mental health staffing ratio and an efficiency-based productivity value are important longitudinal predictors of mental health treatment quality, access, continuity and satisfaction. Our longitudinal design and use of mixed regression models and an information-theoretic approach addresses multiple limitations of prior studies and strengthen our results. Results are discussed in terms of the provision of mental health treatment by healthcare systems, and analytical modeling of treatment quality, access, continuity and satisfaction.
format	article
author	Matt Boden Clifford A Smith Jodie A Trafton
author_facet	Matt Boden Clifford A Smith Jodie A Trafton
author_sort	Matt Boden
title	Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
title_short	Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
title_full	Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
title_fullStr	Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
title_full_unstemmed	Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
title_sort	investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/e116e54bbdb04df0926f4b9ff49ab8dd
work_keys_str_mv	AT mattboden investigationofpopulationbasedmentalhealthstaffingandefficiencybasedmentalhealthproductivityusinganinformationtheoreticapproach AT cliffordasmith investigationofpopulationbasedmentalhealthstaffingandefficiencybasedmentalhealthproductivityusinganinformationtheoreticapproach AT jodieatrafton investigationofpopulationbasedmentalhealthstaffingandefficiencybasedmentalhealthproductivityusinganinformationtheoreticapproach
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Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach.

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