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Using de-identified electronic health records to research mental health supported housing services: A feasibility study

BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical studies of their effectiveness due to the logistic c...

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Autores principales: Dalton-Locke, Christian, Thygesen, Johan H., Werbeloff, Nomi, Osborn, David, Killaspy, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444482/
https://www.ncbi.nlm.nih.gov/pubmed/32817624
http://dx.doi.org/10.1371/journal.pone.0237664
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author Dalton-Locke, Christian
Thygesen, Johan H.
Werbeloff, Nomi
Osborn, David
Killaspy, Helen
author_facet Dalton-Locke, Christian
Thygesen, Johan H.
Werbeloff, Nomi
Osborn, David
Killaspy, Helen
author_sort Dalton-Locke, Christian
collection PubMed
description BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical studies of their effectiveness due to the logistic challenges and costs of standard research methods. The Clinical Record Interactive Search (CRIS) tool, developed to de-identify and interrogate routinely recorded electronic health records, may provide an alternative to evaluate supported housing services. METHODS: The feasibility of using the Camden and Islington NHS Foundation Trust CRIS database to identify a sample of users of mental health supported accommodation services. Two approaches to data interrogation and case identification were compared; using structured fields indicating individual’s accommodation status, and iterative development of free text searches of clinical notes referencing supported housing. The data used were recorded over a 10-year-period (01-January-2008 to 31-December-2017). RESULTS: Both approaches were carried out by one full-time researcher over four weeks (150 hours). Two structured fields indicating accommodation status were found, 2,140 individuals had a value in at least one of the fields representative of supported accommodation. The free text search of clinical notes returned 21,103 records pertaining to 1,105 individuals. A manual review of 10% of the notes indicated an estimated 733 of these individuals had used a supported housing service, a positive predictive value of 66.4%. Over two-thirds of the individuals returned in the free text search (768/1,105, 69.5%) were identified via the structured fields approach. Although the estimated positive predictive value was relatively high, a substantial proportion of the individuals appearing only in the free text search (337/1,105, 30.5%) are likely to be false positives. CONCLUSIONS: It is feasible and requires minimal resources to use de-identified electronic health record search tools to identify large samples of users of mental health supported housing using structured and free text fields. Further work is needed to establish the availability and completion of variables relevant to specific clinical research questions in order to fully assess the utility of electronic health records in evaluating the effectiveness of these services.
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spelling pubmed-74444822020-08-27 Using de-identified electronic health records to research mental health supported housing services: A feasibility study Dalton-Locke, Christian Thygesen, Johan H. Werbeloff, Nomi Osborn, David Killaspy, Helen PLoS One Research Article BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical studies of their effectiveness due to the logistic challenges and costs of standard research methods. The Clinical Record Interactive Search (CRIS) tool, developed to de-identify and interrogate routinely recorded electronic health records, may provide an alternative to evaluate supported housing services. METHODS: The feasibility of using the Camden and Islington NHS Foundation Trust CRIS database to identify a sample of users of mental health supported accommodation services. Two approaches to data interrogation and case identification were compared; using structured fields indicating individual’s accommodation status, and iterative development of free text searches of clinical notes referencing supported housing. The data used were recorded over a 10-year-period (01-January-2008 to 31-December-2017). RESULTS: Both approaches were carried out by one full-time researcher over four weeks (150 hours). Two structured fields indicating accommodation status were found, 2,140 individuals had a value in at least one of the fields representative of supported accommodation. The free text search of clinical notes returned 21,103 records pertaining to 1,105 individuals. A manual review of 10% of the notes indicated an estimated 733 of these individuals had used a supported housing service, a positive predictive value of 66.4%. Over two-thirds of the individuals returned in the free text search (768/1,105, 69.5%) were identified via the structured fields approach. Although the estimated positive predictive value was relatively high, a substantial proportion of the individuals appearing only in the free text search (337/1,105, 30.5%) are likely to be false positives. CONCLUSIONS: It is feasible and requires minimal resources to use de-identified electronic health record search tools to identify large samples of users of mental health supported housing using structured and free text fields. Further work is needed to establish the availability and completion of variables relevant to specific clinical research questions in order to fully assess the utility of electronic health records in evaluating the effectiveness of these services. Public Library of Science 2020-08-20 /pmc/articles/PMC7444482/ /pubmed/32817624 http://dx.doi.org/10.1371/journal.pone.0237664 Text en © 2020 Dalton-Locke et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dalton-Locke, Christian
Thygesen, Johan H.
Werbeloff, Nomi
Osborn, David
Killaspy, Helen
Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title_full Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title_fullStr Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title_full_unstemmed Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title_short Using de-identified electronic health records to research mental health supported housing services: A feasibility study
title_sort using de-identified electronic health records to research mental health supported housing services: a feasibility study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444482/
https://www.ncbi.nlm.nih.gov/pubmed/32817624
http://dx.doi.org/10.1371/journal.pone.0237664
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