Researcher profile

Sabrina Molinaro

Dr. Molinaro, PhD, MSc ,Psy D, is Head of the Department of Epidemiology and Health Services of the Institute of Clinical Physiology of the National Research Council of Italy (CNR), in Pisa. Dr. Molinaro’s formal training includes Psychology (Bologna University), and MS in Epidemiology (University of Torino) and a PhD in Public Health and Education (University of Pavia). Since 2001 she has been designing, activating and coordinating epidemiological studies/researches on general and specific populations, focusing on hidden populations. Since 2006 she has been designing clinical studies to evaluate the efficacy and efficiency of therapeutic patterns and treatment outcomes, developing models of statistical and epidemiological analysis of large data flows to support planning of healthcare governance policies. She collaborates with the European Monitoring Center of Drug and Drug abuse (EU Commission). Since 2008 she has been investigating synthesis and presentation of epidemiological and clinical information (databases of subjects in treatment), stored in social/healthcare “datawarehouse” (standard flows) and analyzing the aspects related to possible deterministic/probabilistic links among different types of databases to monitor and evaluate the outcomes. Since 2009 she oversees the activities of the Epidemiology and Health Service Research Department and its 38 staff members. Since 2010 she has been developing research projects and technology transfer within the Personalized Medicine field, especially new tools of data mining and development of healthcare and clinical prediction models, in partnership with national and international companies. Since 2012 she concluded partnerships with US, Chinese and African Institutions in order to develop technologies supporting personalized medicine.Since 2013 she has been involved in teaching activity at Medical Statistics courses addressed to the students of the “Scuola Superiore Sant’Anna” university of Pisa. The crucial element of her research is to bring different disciplines into dialogue with the aim of pursuing the integration of different expertise and heterogeneous data sources. One of the major strands of applied research followed over the years is geared toward drawing the greatest possible density of knowledge, both quantitative and qualitative, from the information already existing in the available databases and specialized archives, with the ultimate goal of increasing and qualifying actions referred to public health. It is also involved in designing and conducting numerous studies and disseminating the results through innovative ways. The main lines of research can be summarized in 3 main areas: POPULATION STUDIES FOR MONITORING HEALTH RISK BEHAVIORS IN HIDDEN POPULATIONS (e.g., individuals with substance use disorders, pathological gamblers) The study of hidden populations has always been its main interest. To estimate their prevalence, he has developed ad hoc surveys and ecological studies from the integration of different data sources. To understand disease trajectories and patterns, he uses interactive tools for participatory research. DEVELOPMENT OF ANALYSIS MODELS FOR THE PUBLIC HEALTH SYSTEM AND PRECISION MEDICINE Thanks to the interdisciplinary nature of her research group, it has been possible to develop her skills in the integrated use of data from heterogeneous sources (standard health streams and clinical data extracted from patient history from imaging or self-reported by citizens/patients) to analyze the disease process seen as a continuum from the pre-clinical phase of risk to disease, in addition to classical methods he uses artificial intelligence tools in order to improve the effectiveness of the care pathway. The goal is to develop replicable analysis models for health policy planning. HEALTH POLICY EVALUATION THROUGH INNOVATIVE ECONOMETRIC MODELS. The area of policy impact evaluation is the most recent challenge she has undertaken. The main goal is to combine the expertise developed on the study of hidden populations, those related to models of care pathway analysis and health policies with impact evaluation, the goal is to develop a language that allows fluent communication between the worlds of economics and epidemiology in order to give policy makers elements for evidence-based evaluation.