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Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system

BACKGROUND: Mental health (MH) care often exhibits uneven quality and poor coordination of physical and MH needs, especially for patients with severe mental disorders. This study tests a Population Health Management (PHM) approach to identify patients with severe mental disorders using administrativ...

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Autores principales: Tozzi, Valeria D., Banks, Helen, Ferrara, Lucia, Barbato, Angelo, Corrao, Giovanni, D’avanzo, Barbara, Di Fiandra, Teresa, Gaddini, Andrea, Compagnoni, Matteo Monzio, Sanza, Michele, Saponaro, Alessio, Scondotto, Salvatore, Lora, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483754/
https://www.ncbi.nlm.nih.gov/pubmed/37679722
http://dx.doi.org/10.1186/s12913-023-09655-6
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author Tozzi, Valeria D.
Banks, Helen
Ferrara, Lucia
Barbato, Angelo
Corrao, Giovanni
D’avanzo, Barbara
Di Fiandra, Teresa
Gaddini, Andrea
Compagnoni, Matteo Monzio
Sanza, Michele
Saponaro, Alessio
Scondotto, Salvatore
Lora, Antonio
author_facet Tozzi, Valeria D.
Banks, Helen
Ferrara, Lucia
Barbato, Angelo
Corrao, Giovanni
D’avanzo, Barbara
Di Fiandra, Teresa
Gaddini, Andrea
Compagnoni, Matteo Monzio
Sanza, Michele
Saponaro, Alessio
Scondotto, Salvatore
Lora, Antonio
author_sort Tozzi, Valeria D.
collection PubMed
description BACKGROUND: Mental health (MH) care often exhibits uneven quality and poor coordination of physical and MH needs, especially for patients with severe mental disorders. This study tests a Population Health Management (PHM) approach to identify patients with severe mental disorders using administrative health databases in Italy and evaluate, manage and monitor care pathways and costs. A second objective explores the feasibility of changing the payment system from fee-for-service to a value-based system (e.g., increased care integration, bundled payments) to introduce performance measures and guide improvement in outcomes. METHODS: Since diagnosis alone may poorly predict condition severity and needs, we conducted a retrospective observational study on a 9,019-patient cohort assessed in 2018 (30.5% of 29,570 patients with SMDs from three Italian regions) using the Mental Health Clustering Tool (MHCT), developed in the United Kingdom, to stratify patients according to severity and needs, providing a basis for payment for episode of care. Patients were linked (blinded) with retrospective (2014–2017) physical and MH databases to map resource use, care pathways, and assess costs globally and by cluster. Two regions (3,525 patients) provided data for generalized linear model regression to explore determinants of cost variation among clusters and regions. RESULTS: Substantial heterogeneity was observed in care organization, resource use and costs across and within 3 Italian regions and 20 clusters. Annual mean costs per patient across regions was €3,925, ranging from €3,101 to €6,501 in the three regions. Some 70% of total costs were for MH services and medications, 37% incurred in dedicated mental health facilities, 33% for MH services and medications noted in physical healthcare databases, and 30% for other conditions. Regression analysis showed comorbidities, resident psychiatric services, and consumption noted in physical health databases have considerable impact on total costs. CONCLUSIONS: The current MH care system in Italy lacks evidence of coordination of physical and mental health and matching services to patient needs, with high variation between regions. Using available assessment tools and administrative data, implementation of an episodic approach to funding MH could account for differences in disease phase and physical health for patients with SMDs and introduce performance measurement to improve outcomes and provide oversight. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09655-6.
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spelling pubmed-104837542023-09-08 Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system Tozzi, Valeria D. Banks, Helen Ferrara, Lucia Barbato, Angelo Corrao, Giovanni D’avanzo, Barbara Di Fiandra, Teresa Gaddini, Andrea Compagnoni, Matteo Monzio Sanza, Michele Saponaro, Alessio Scondotto, Salvatore Lora, Antonio BMC Health Serv Res Research BACKGROUND: Mental health (MH) care often exhibits uneven quality and poor coordination of physical and MH needs, especially for patients with severe mental disorders. This study tests a Population Health Management (PHM) approach to identify patients with severe mental disorders using administrative health databases in Italy and evaluate, manage and monitor care pathways and costs. A second objective explores the feasibility of changing the payment system from fee-for-service to a value-based system (e.g., increased care integration, bundled payments) to introduce performance measures and guide improvement in outcomes. METHODS: Since diagnosis alone may poorly predict condition severity and needs, we conducted a retrospective observational study on a 9,019-patient cohort assessed in 2018 (30.5% of 29,570 patients with SMDs from three Italian regions) using the Mental Health Clustering Tool (MHCT), developed in the United Kingdom, to stratify patients according to severity and needs, providing a basis for payment for episode of care. Patients were linked (blinded) with retrospective (2014–2017) physical and MH databases to map resource use, care pathways, and assess costs globally and by cluster. Two regions (3,525 patients) provided data for generalized linear model regression to explore determinants of cost variation among clusters and regions. RESULTS: Substantial heterogeneity was observed in care organization, resource use and costs across and within 3 Italian regions and 20 clusters. Annual mean costs per patient across regions was €3,925, ranging from €3,101 to €6,501 in the three regions. Some 70% of total costs were for MH services and medications, 37% incurred in dedicated mental health facilities, 33% for MH services and medications noted in physical healthcare databases, and 30% for other conditions. Regression analysis showed comorbidities, resident psychiatric services, and consumption noted in physical health databases have considerable impact on total costs. CONCLUSIONS: The current MH care system in Italy lacks evidence of coordination of physical and mental health and matching services to patient needs, with high variation between regions. Using available assessment tools and administrative data, implementation of an episodic approach to funding MH could account for differences in disease phase and physical health for patients with SMDs and introduce performance measurement to improve outcomes and provide oversight. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09655-6. BioMed Central 2023-09-07 /pmc/articles/PMC10483754/ /pubmed/37679722 http://dx.doi.org/10.1186/s12913-023-09655-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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
Tozzi, Valeria D.
Banks, Helen
Ferrara, Lucia
Barbato, Angelo
Corrao, Giovanni
D’avanzo, Barbara
Di Fiandra, Teresa
Gaddini, Andrea
Compagnoni, Matteo Monzio
Sanza, Michele
Saponaro, Alessio
Scondotto, Salvatore
Lora, Antonio
Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title_full Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title_fullStr Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title_full_unstemmed Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title_short Using big data and Population Health Management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
title_sort using big data and population health management to assess care and costs for patients with severe mental disorders and move toward a value-based payment system
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483754/
https://www.ncbi.nlm.nih.gov/pubmed/37679722
http://dx.doi.org/10.1186/s12913-023-09655-6
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