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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

Authors :
Tozzi, V
Banks, H
Ferrara, L
Barbato, A
Corrao, G
D'Avanzo, B
Di Fiandra, T
Gaddini, A
Compagnoni, M
Sanza, M
Saponaro, A
Scondotto, S
Lora, A
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
Tozzi, V
Banks, H
Ferrara, L
Barbato, A
Corrao, G
D'Avanzo, B
Di Fiandra, T
Gaddini, A
Compagnoni, M
Sanza, M
Saponaro, A
Scondotto, S
Lora, A
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
Publication Year :
2023

Abstract

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 tota

Details

Database :
OAIster
Notes :
ELETTRONICO, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1415743116
Document Type :
Electronic Resource