Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review

As mental health care transitions from facility-based care to community-based services, methods to classify patients in terms of their expected health care resource use are an essential tool to balance the health care needs and equitable allocation of health care resources. This study performed a sc...

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Main Authors: Nam Tran, Jeffrey W Poss, Christopher Perlman, John P Hirdes
Format: Article
Language:English
Published: SAGE Publishing 2019-07-01
Series:Health Services Insights
Online Access:https://doi.org/10.1177/1178632919862248
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spelling doaj-b9b2f5cc15a14228bb3b59442a2f16b32020-11-25T03:52:33ZengSAGE PublishingHealth Services Insights1178-63292019-07-011210.1177/1178632919862248Case-Mix Classification for Mental Health Care in Community Settings: A Scoping ReviewNam TranJeffrey W PossChristopher PerlmanJohn P HirdesAs mental health care transitions from facility-based care to community-based services, methods to classify patients in terms of their expected health care resource use are an essential tool to balance the health care needs and equitable allocation of health care resources. This study performed a scoping review to summarize the nature, extent, and range of research on case-mix classifications used to predict mental health care resource use in community settings. This study identified 17 eligible studies with 32 case-mix classification systems published since the 1980s. Most of these studies came from the USA Veterans Affairs and Medicare systems, and the most recent studies came from Australia. There were a wide variety of choices of input variables and measures of resource use. However, much of the variance in observed resource use was not accounted for by these case-mix systems. The research activity specific to case-mix classification for community mental health care was modest. More consideration should be given to the appropriateness of the input variables, resource use measure, and evaluation of predictive performance. Future research should take advantage of testing case-mix systems developed in other settings for community mental health care settings, if possible.https://doi.org/10.1177/1178632919862248
collection DOAJ
language English
format Article
sources DOAJ
author Nam Tran
Jeffrey W Poss
Christopher Perlman
John P Hirdes
spellingShingle Nam Tran
Jeffrey W Poss
Christopher Perlman
John P Hirdes
Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
Health Services Insights
author_facet Nam Tran
Jeffrey W Poss
Christopher Perlman
John P Hirdes
author_sort Nam Tran
title Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
title_short Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
title_full Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
title_fullStr Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
title_full_unstemmed Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review
title_sort case-mix classification for mental health care in community settings: a scoping review
publisher SAGE Publishing
series Health Services Insights
issn 1178-6329
publishDate 2019-07-01
description As mental health care transitions from facility-based care to community-based services, methods to classify patients in terms of their expected health care resource use are an essential tool to balance the health care needs and equitable allocation of health care resources. This study performed a scoping review to summarize the nature, extent, and range of research on case-mix classifications used to predict mental health care resource use in community settings. This study identified 17 eligible studies with 32 case-mix classification systems published since the 1980s. Most of these studies came from the USA Veterans Affairs and Medicare systems, and the most recent studies came from Australia. There were a wide variety of choices of input variables and measures of resource use. However, much of the variance in observed resource use was not accounted for by these case-mix systems. The research activity specific to case-mix classification for community mental health care was modest. More consideration should be given to the appropriateness of the input variables, resource use measure, and evaluation of predictive performance. Future research should take advantage of testing case-mix systems developed in other settings for community mental health care settings, if possible.
url https://doi.org/10.1177/1178632919862248
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AT johnphirdes casemixclassificationformentalhealthcareincommunitysettingsascopingreview
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