Author(s)

Antonella Massari¹, Biagio Solarino², Paola Perchinunno¹, Angela Maria D’Uggento³, Marcello Benevento², Viviana D’Addosio¹, Vittoria Claudia De Nicolò¹, Samuela L’Abbate¹

¹Department of Economics, Management and Business Law, University of Bari Aldo Moro, Bari, Italy.
²Institute of Legal Medicine, Department of Interdisciplinary Medicine, University of Bari Aldo Moro, Bari, Italy.
³Department of Economics and Finance, University of Bari Aldo Moro, Bari, Italy.

The recent pandemic crisis has highlighted the importance of the availability and management of health data to respond quickly and effectively to health emergencies, while respecting the fundamental rights of every individual. In this context, it is essential to find a balance between the protection of privacy and the safeguarding of public health, using tools that guarantee transparency and consent to the processing of data by the population. This work, starting from a pilot investigation conducted in the Polyclinic of Bari as part of the Horizon Europe Seeds project entitled “Multidisciplinary analysis of technological tracing models of contagion: the protection of rights in the management of health data”, has the objective of promoting greater patient awareness regarding the processing of their health data and the protection of privacy. The methodology used the PHICAT (Personal Health Information Competence Assessment Tool) as a tool and, through the administration of a questionnaire, the aim was to evaluate the patients’ ability to express their consent to the release and processing of health data. The results that emerged were analyzed in relation to the 4 domains in which the process is divided which allows evaluating the patients’ ability to express a conscious choice and, also, in relation to the socio-demographic and clinical characteristics of the patients themselves. This study can contribute to understanding patients’ ability to give their consent and improve information regarding the management of health data by increasing confidence in granting the use of their data for research and clinical management.

Privacy, Health Data, Consent, Cluster Analysis, Logit

Massari, A. , Solarino, B. , Perchinunno, P. , D’Uggento, A. , Benevento, M. , D’Addosio, V. , Nicolò, V. and L’Abbate, S. (2024) Statistical Analysis of Abilities to Give Consent to Health Data Processing. Applied Mathematics, 15, 508-542. doi: 10.4236/am.2024.158032.