Analysis of data items and gaps in Australia's national mental health services activity and capacity data collections for integrated regional service planning.
{"title":"Analysis of data items and gaps in Australia's national mental health services activity and capacity data collections for integrated regional service planning.","authors":"Claudia Pagliaro, Arabella Mundie, Harvey Whiteford, Sandra Diminic","doi":"10.1177/18333583231175770","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Services data are an important source of information for policymakers and planners. In Australia, significant work has been undertaken to develop and implement collections of mental health services data. Given this level of investment, it is important that collected data are fit for purpose. <b>Objective:</b> This study aimed to: (1) identify existing national mandated and best endeavours collections of mental health services activity (e.g. occasions of service) and capacity (e.g. full-time equivalent staff) data in Australia; and (2) review the content of identified data collections to determine opportunities for data development. <b>Method:</b> A grey literature search was conducted to identify data collections. Where available, metadata and/or data were analysed. <b>Results:</b> Twenty data collections were identified. For services that received funding via multiple funding streams, data were often captured across several collections corresponding with each funder. There was significant variability in the content and format of collections. Unlike other service sectors, there is no national, mandated collection for psychosocial support services. Some collections have limited utility as they do not include key activity data; others do not include descriptive variables like service type. Workforce data are often not collected, and where data are collected, they are often not comprehensive. <b>Conclusion:</b> Findings are an important source of information for policymakers and planners who use services data to inform priorities. <b>Implications:</b> This study provides recommendations for data development, including mandating standardised reporting for psychosocial supports, filling workforce data gaps, streamlining data collections and including key missing data items in some collections.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health information management : journal of the Health Information Management Association of Australia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/18333583231175770","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/6/6 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Services data are an important source of information for policymakers and planners. In Australia, significant work has been undertaken to develop and implement collections of mental health services data. Given this level of investment, it is important that collected data are fit for purpose. Objective: This study aimed to: (1) identify existing national mandated and best endeavours collections of mental health services activity (e.g. occasions of service) and capacity (e.g. full-time equivalent staff) data in Australia; and (2) review the content of identified data collections to determine opportunities for data development. Method: A grey literature search was conducted to identify data collections. Where available, metadata and/or data were analysed. Results: Twenty data collections were identified. For services that received funding via multiple funding streams, data were often captured across several collections corresponding with each funder. There was significant variability in the content and format of collections. Unlike other service sectors, there is no national, mandated collection for psychosocial support services. Some collections have limited utility as they do not include key activity data; others do not include descriptive variables like service type. Workforce data are often not collected, and where data are collected, they are often not comprehensive. Conclusion: Findings are an important source of information for policymakers and planners who use services data to inform priorities. Implications: This study provides recommendations for data development, including mandating standardised reporting for psychosocial supports, filling workforce data gaps, streamlining data collections and including key missing data items in some collections.