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Empirically identified networks of healthcare providers for adults with mental illness
BACKGROUND: Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349008/ https://www.ncbi.nlm.nih.gov/pubmed/34362369 http://dx.doi.org/10.1186/s12913-021-06798-2 |
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author | Breslau, Joshua Dana, Beth Pincus, Harold Horvitz-Lennon, Marcela Matthews, Luke |
author_facet | Breslau, Joshua Dana, Beth Pincus, Harold Horvitz-Lennon, Marcela Matthews, Luke |
author_sort | Breslau, Joshua |
collection | PubMed |
description | BACKGROUND: Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a multi-payer database based medical claims data in a U.S. state. METHODS: Provider networks were identified and characterized using paid inpatient, outpatient and pharmacy claims related to care for people with a mental health diagnosis from an all-payer claims dataset that covers both public and private payers. RESULTS: Three nested levels of network structures were identified: an overall network, which included 21% of providers (N = 8256) and 97% of patients (N = 476,802), five communities and 24 sub-communities. Sub-communities were characterized by size, provider composition, continuity-of-care (CoC), and network structure measures including mean number of connections per provider (degree) and average number of connections who were connected to each other (transitivity). Sub-community size was positively associated with number of connections (r = .37) and the proportion of psychiatrists (r = .41) and uncorrelated with network transitivity (r = −.02) and continuity of care (r = .00). Network transitivity was not associated with CoC after adjustment for provider type, number of patients, and average connection CoC (p = .85). CONCLUSIONS: These exploratory analyses suggest that network analysis can provide information about the networks of providers that treat people with mental illness that is not captured in traditional measures and may be useful in designing, implementing, and studying interventions to improve systems of care. Though initial results are promising, additional empirical work is needed to develop network-based measures and tools for policymakers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06798-2. |
format | Online Article Text |
id | pubmed-8349008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83490082021-08-09 Empirically identified networks of healthcare providers for adults with mental illness Breslau, Joshua Dana, Beth Pincus, Harold Horvitz-Lennon, Marcela Matthews, Luke BMC Health Serv Res Research Article BACKGROUND: Policies target networks of providers who treat people with mental illnesses, but little is known about the empirical structures of these networks and related variation in patient care. The goal of this paper is to describe networks of providers who treat adults with mental illness in a multi-payer database based medical claims data in a U.S. state. METHODS: Provider networks were identified and characterized using paid inpatient, outpatient and pharmacy claims related to care for people with a mental health diagnosis from an all-payer claims dataset that covers both public and private payers. RESULTS: Three nested levels of network structures were identified: an overall network, which included 21% of providers (N = 8256) and 97% of patients (N = 476,802), five communities and 24 sub-communities. Sub-communities were characterized by size, provider composition, continuity-of-care (CoC), and network structure measures including mean number of connections per provider (degree) and average number of connections who were connected to each other (transitivity). Sub-community size was positively associated with number of connections (r = .37) and the proportion of psychiatrists (r = .41) and uncorrelated with network transitivity (r = −.02) and continuity of care (r = .00). Network transitivity was not associated with CoC after adjustment for provider type, number of patients, and average connection CoC (p = .85). CONCLUSIONS: These exploratory analyses suggest that network analysis can provide information about the networks of providers that treat people with mental illness that is not captured in traditional measures and may be useful in designing, implementing, and studying interventions to improve systems of care. Though initial results are promising, additional empirical work is needed to develop network-based measures and tools for policymakers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-021-06798-2. BioMed Central 2021-08-06 /pmc/articles/PMC8349008/ /pubmed/34362369 http://dx.doi.org/10.1186/s12913-021-06798-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Breslau, Joshua Dana, Beth Pincus, Harold Horvitz-Lennon, Marcela Matthews, Luke Empirically identified networks of healthcare providers for adults with mental illness |
title | Empirically identified networks of healthcare providers for adults with mental illness |
title_full | Empirically identified networks of healthcare providers for adults with mental illness |
title_fullStr | Empirically identified networks of healthcare providers for adults with mental illness |
title_full_unstemmed | Empirically identified networks of healthcare providers for adults with mental illness |
title_short | Empirically identified networks of healthcare providers for adults with mental illness |
title_sort | empirically identified networks of healthcare providers for adults with mental illness |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349008/ https://www.ncbi.nlm.nih.gov/pubmed/34362369 http://dx.doi.org/10.1186/s12913-021-06798-2 |
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