The HIN (Health Issue Network) Project

On June 29, researcher Fabrizio Pecoraro from the IRPPS Health and Society group participated in the 𝐂𝐨𝐧𝐯𝐞𝐠𝐧𝐨 𝐝𝐢 𝐓𝐞𝐥𝐞𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐚 𝐚 𝐏𝐞𝐬𝐜𝐚𝐫𝐚 (Telemedicine Conference in Pescara). The conference provided an opportunity to discuss the opportunities opened by the decree of September 28, 2023 for the innovation of the National Health Service, driven by the transition toward new technological infrastructures dedicated to both Telemedicine—the set of healthcare services that can be performed remotely through innovative technologies—and the Electronic Health Record, which enables the digital collection of a patient’s clinical history.

Pecoraro’s contribution focused specifically on the Electronic Health Record, emphasizing the need to develop a tool containing structured information that is interoperable with other health information systems. Furthermore, the Record must serve not only as a care support tool—facilitating patient management and diagnostic and treatment operations across different professionals and healthcare facilities—but also as a source of data for decision-makers and the research community for epidemiological and governance studies.

You can listen to the researcher’s intervention here.

The latest IRPPS Working Paper, to which the Health and Society group contributed, is instead dedicated to the user experience of a Telemedicine service piloted at the San Giovanni Addolorata Hospital in Rome. You can read it here.

To facilitate collaborations in the university environment and clinical practice, HIN (Health Issue Network) — a project born within the Health and Society group of IRPPS — has recently been registered as a trademark.

HIN is a method that facilitates clinical reasoning and improves the training of students and professionals in the healthcare sector (in both human and veterinary medicine).

Fabrizio Pecoraro (CNR-IRPPS) retraces the highlights of the project in an audio-abstract.

Find out more on the website https://www.healthissuenetwork.org/ita/home

And on the working papers:

• Antonio D’Uffizi, Fabrizio L. Ricci, Fabrizio Pecoraro, Oscar Tamburis (2023). The flexibility of a clinical case (an HIN diagram) Rome: National Research Council Institute for Research on Population and Social Policies, (IRPPS Working papers n. 142/2024, p. 2 0

• Antonio D’Uffizi, Fabrizio L. Ricci, Fabrizio Pecoraro, Daniela Luzi, Giuseppe Stecca, Fabrizio Consorti, Fabrizio Murgia (2023). A Complexity Measure for Clinical History Models. Rome: National Research Council – Institute for Research on Population and Social Policies, (IRPPS Working papers n. 138/2023, p. 20).
  
• Ricci, F. L., Pecoraro, F., Luzi, D., Consorti, F., & Tamburis, O. (2020). HIN (Health Issue Network). Health problem network. Use of Petri nets for education in medical sciences. IRPPS Working Papers, 1–140.

The new call for papers from the journal Welfare & Ergonomia, edited by Alberto Pesce and Veronica Valenti, is dedicated to “Investing in the care of social reintegration for incarcerated individuals: trends and new perspectives of Italian welfare.”

Proposals may be submitted by March 29, 2024, by sending an abstract of approximately 3,000 characters (including spaces).

All information is available in the call.

Welfare & Ergonomia is a Class A journal (Anvur), published by Franco Angeli, based on an editorial project and direction by IRPPS (thanks to researcher Antonella Ciocia).

By way of example, contributions for this edition may cover:

• social and health aspects resulting from overcrowding at both collective and individual levels;
• the importance of maintaining emotional and family ties in prison to gather suggestions for reform perspectives;
• the mutual relationship between forms of restorative justice and social reintegration;
• the importance of educational paths and professional training in prison;
• the analysis of Italian or European best practices aimed at promoting training, placement, and employment;
• the analysis of traditional welfare models and their implementation regarding persons deprived of liberty, with attention also to new models or policies concerning inmates or former inmates;
• the analysis of legislation and jurisprudence regarding the social and professional reintegration of inmates;
• a critical analysis of the role of local authorities, social private organizations, and the private sector in ensuring training, placement, and employment;
• the analysis of local best practices or those piloted in individual penal institutions;
• the analysis of factors leading to recidivism:
• the analysis of state and regional spending aimed at promoting social and professional integration paths;
• the treatment of inmates nearing release at the end of their sentence;
• the impact of new technologies, such as Artificial Intelligence or neuroscience, on the social and professional reintegration of incarcerated individuals.

October 9, 2023 – h. 10.00

Sala Europa, IRPPS via Palestro 32 – Rome

Abstract

Artificial Intelligence (AI) is transforming people’s life in unprecedented ways. AI models have human or superhuman abilities in multiple tasks, e.g., gaming, driving, conversation, and content organization. In biomedical research, however, AI demonstrated as much promise, e.g., in molecular drug design, as much disappointment, e.g., in clinical drug repurposing or public health intervention. One of the reasons is that the datasets AI feeds on –sourced from real world databases such electronic health records (EHR)– are often littered with bias. Such bias might be irrelevant to predict the happening of health conditions, but it influences any strategy to prevent such conditions from happening. In this talk, we will take a dive into the promises and perils of AI in healthcare, and its troubled relationship with data, bias, and causality. We will explore novel causal AI methodologies able to both provide accurate individual health predictions as well as interventions. Finally, we will present use cases of causal AI on large, integrated EHR data, and an eagle’s view of EHR consortia in the USA.

Short biographies

Mattia Prosperi, PhD, FAMIA, is Professor in the Department of Epidemiology, and Associate Dean of AI and Innovation in the College of Public Health and Health Profession at University of Florida. His background is in computer science engineering, with expertise in machine learning, bio-health informatics, and epidemiology. His research leverages technology and data intelligence to develop prediction and intervention models for improving future health and lives. In his administrative role, his mission is to expand AI infrastructure, training, research and expertise capacity in public health and health professions.

Yi Guo, PhD, is Associate Professor in the Department of Health Outcomes, Policy and Biomedical Informatics, College of Medicine, University of Florida. He has a multi-disciplinary background in the analysis of real-world data, including electronic health records and administrative claims, experimental and observational study design, predictive modeling (e.g., statistical and machine learning), causal modeling, and analysis of patient-reported outcomes in clinical and public health applications, and among various populations, especially vulnerable populations.