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Chiara Seghieri has joined the Institute of Management of the Sant'Anna School and EMbeDS as an Associate professor of Social Statistics. She holds a Ph.D. in Applied Statistics and has over 15 years of research experience in national and international projects, mainly dealing with multidimensional measures of standard of living and quality of life -- including methods for assessing the performance of healthcare services and systems.


Since 2008, Chiara has been a researcher at the Management and Health Laboratory (MES) of the Institute of Management. Through close collaborations with policy makers, physicians, and health economists, MES produces public reports on health and healthcare performance measures in the public sector -- throughout Italy, as well as internationally. In this context, Chiara’s develops and applies statistical methods for analyzing health services and outcomes using large databases (e.g., healthcare administrative databases) and healthcare surveys (e.g., patient satisfaction surveys, organizational climate surveys of healthcare professionals) with a special focus on the analysis of patterns of treatment and quality of care for patients with chronic conditions such as cardiovascular diseases and diabetes.

Chiara has been the Sant'Anna scientific coordinator for the “QUALICOPC” European project (Quality and costs of primary care in Europe) funded under FP7-HEALTH, and is currently  the scientific coordinator of the “HarmonicSS” project (Harmonization and integrative analysis of regional, national and international Cohorts on primary Sjögren’s Syndrome) funded under the Horizon 2020 research and innovation programme.

She collaborates with several international academic institution and research centers including FAO (Rome), the Dartmouth Institute for Health Policy and Clinical Practice (Dartmouth University, VT, U.S.A.) and the Netherlands Institute for Health Services Research (NIVEL).

What are Chiara's plans for this new chapter of her academic career, in connection with the objectives of EMbeDS?

"I will study methods for aggregating, integrating, and analyzing different health data sources– such as patient surveys, administrative care databases, routinely collected clinical and socio-economic information, at different level of aggregation (individual, healthcare provider, healthcare catchment area). The main idea is to apply statistical methods to these large volumes of data to report on different health system performance dimensions (e.g., equity of access, or quality and efficiency) and give a richer picture of the relationship between them at meaningful levels of analysis; to make predictive models for healthcare outcomes; and to discover many other interesting insights."