Establishment of a Public Mental Health Database for Research Purposes in the Ferrara Province: Development and Preliminary Evaluation Study

Maria Ferrara; Elisabetta Gentili; Martino Belvederi Murri; Riccardo Zese; Marco Alberti; Giorgia Franchini; Ilaria Domenicano; Federica Folesani; Cristina Sorio; Lorenzo Benini; Paola Carozza; Julian Little; Luigi Grassi

doi:10.2196/45523

Establishment of a Public Mental Health Database for Research Purposes in the Ferrara Province: Development and Preliminary Evaluation Study

JMIR Med Inform. 2023 Aug 9:11:e45523. doi: 10.2196/45523.

Authors

Maria Ferrara^{1

2

3}, Elisabetta Gentili⁴, Martino Belvederi Murri^{1

2}, Riccardo Zese⁵, Marco Alberti⁶, Giorgia Franchini⁷, Ilaria Domenicano¹, Federica Folesani^{1

2}, Cristina Sorio², Lorenzo Benini², Paola Carozza², Julian Little⁸, Luigi Grassi^{1

2}

Affiliations

¹ Institute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy.
² Integrated Department of Mental Health and Pathological Addictions, Ferrara Local Health Trust, Ferrara, Italy.
³ Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States.
⁴ Department of Engineering, University of Ferrara, Ferrara, Italy.
⁵ Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Ferrara, Italy.
⁶ Department of Mathematics and Computer Science, University of Ferrara, Ferrara, Italy.
⁷ Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, Modena, Italy.
⁸ School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.

PMID: 37584563
PMCID: PMC10461404
DOI: 10.2196/45523

Abstract

Background: The immediate use of data exported from electronic health records (EHRs) for research is often limited by the necessity to transform data elements into an actual data set.

Objective: This paper describes the methodology for establishing a data set that originated from an EHR registry that included clinical, health service, and sociodemographic information.

Methods: The Extract, Transform, Load process was applied to raw data collected at the Integrated Department of Mental Health and Pathological Addictions in Ferrara, Italy, from 1925 to February 18, 2021, to build the new, anonymized Ferrara-Psychiatry (FEPSY) database. Information collected before the first EHR was implemented (ie, in 1991) was excluded. An unsupervised cluster analysis was performed to identify patient subgroups to support the proof of concept.

Results: The FEPSY database included 3,861,432 records on 46,222 patients. Since 1991, each year, a median of 1404 (IQR 1117.5-1757.7) patients had newly accessed care, and a median of 7300 (IQR 6109.5-9397.5) patients were actively receiving care. Among 38,022 patients with a mental disorder, 2 clusters were identified; the first predominantly included male patients who were aged 25 to 34 years at first presentation and were living with their parents, and the second predominantly included female patients who were aged 35 to 44 years and were living with their own families.

Conclusions: The process for building the FEPSY database proved to be robust and replicable with similar health care data, even when they were not originally conceived for research purposes. The FEPSY database will enable future in-depth analyses regarding the epidemiology and social determinants of mental disorders, access to mental health care, and resource utilization.

Keywords: clinical database; electronic health records; electronic health registry; epidemiology; health care; machine learning; medical health records; mental disorder; mental health; mental health care; psychosis; resource utilization; social determinants; support.

© Maria Ferrara, Elisabetta Gentili, Martino Belvederi Murri, Riccardo Zese, Marco Alberti, Giorgia Franchini, Ilaria Domenicano, Federica Folesani, Cristina Sorio, Lorenzo Benini, Paola Carozza, Julian Little, Luigi Grassi. Originally published in JMIR Medical Informatics (https://medinform.jmir.org).