In partnership with the Modena Local Health Authority (AUSL Modena), this project aims to design and evaluate a community-based social prescribing model that connects healthcare, social services, and local community resources to improve population health and wellbeing. The research develops an evidence-based framework for assessing the implementation, impact, and economic value of social prescribing interventions in the Modena area.

The project combines quantitative and qualitative methods, including the analysis of administrative and health data, surveys, interviews, and advanced impact evaluation techniques. Particular attention is devoted to understanding how community and cultural activities can support wellbeing, social inclusion, quality of life, and more appropriate use of health and social care services. Findings will inform local policy-making and contribute to the growing international evidence base on integrated, community-centred approaches to health and care.

Role: Scientific Lead (Principal Investigator) with Dr. Erica Poma & AUSL-Modena.

LENS-Bio is an interdisciplinary research project that develops new methods to generate reliable population-health evidence from routine healthcare data. The project combines laboratory blood-test records and administrative health data covering the entire population of the Province of Modena to address a fundamental challenge in health analytics: routine clinical data only capture people who interact with healthcare services, potentially overlooking vulnerable and underserved groups.
Bringing together health economics, statistics, epidemiology, and data science, the project will develop innovative approaches to identify and correct selection bias in observational health data, producing more accurate estimates of population health needs, inequalities, and unmet demand for care. Particular attention is devoted to understanding territorial disparities in access to diagnostic services across urban, rural, and mountain communities.
A key outcome of the project is the creation of the Diagnostic Equity Hub, a decision-support platform designed in collaboration with AUSL Modena to help policymakers monitor diagnostic coverage, identify underserved populations, and support more equitable health planning. By transforming routinely collected health data into actionable intelligence, LENS-Bio aims to advance both methodological research and evidence-based healthcare policymaking.

Role: Principal Investigator. (with Dr. Silvia Scarpa & AUSL-Modena)

This project investigates the adoption of assistive and digital technologies in residential care facilities for older people across the Emilia-Romagna region. Based on an original survey of accredited nursing homes, it examines the diffusion of technologies ranging from electronic health records and telemedicine to sensors, smart-home systems, and care robots, and explores the organisational and territorial factors associated with their uptake.
The study provides the first region-wide assessment of technology adoption in the long-term care sector, revealing substantial differences between types of technologies and across local areas. Findings suggest that territorial context plays a more important role than facility ownership or size in shaping adoption patterns, highlighting the need for place-based policies to promote equitable digital innovation in care services. The project contributes to understanding how technology can support quality of care, workforce sustainability, and innovation in long-term care systems.

Role: Principal investigator with my brilliant PhD student Edoardo Renato Piombini (and Solinas Giovanni & Colucci Elisabetta).

This project examines how corporate ownership and market concentration shape the quality of care in England’s specialist care home sector. Using novel administrative data on care home capacity and occupancy, it investigates how competition varies across local markets and whether more concentrated markets offer fewer high-quality care options for people with complex care needs. The findings provide new evidence on the relationship between market structure, provider behaviour, and care quality in long-term care.

Role: Principal investigator with Vasudha Wattal

This project explores innovative ways to finance long-term care in ageing societies by integrating care protection within Italy’s notional defined contribution (NDC) pension system. Using advanced actuarial modelling and administrative data, it evaluates alternative designs that combine retirement income and long-term care coverage, assessing their financial sustainability, distributional consequences, and capacity to respond to growing care needs.
The research examines how longevity and long-term care risks can be jointly managed, providing evidence on the trade-offs between contributions, pension benefits, and care entitlements. The findings contribute to policy debates on the future financing of long-term care and the design of more sustainable and equitable welfare systems.

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Role: Co-investigator with Luca Vincenzo Ballestra & Carlo Mazzaferro

We examine how a change in the administrative governance shapes equity in access to Italy’s main universal non-means-tested cash long-term care benefit, the \textit{Indennità di Accompagnamento} (IdA). We exploit a 2010 reform that strengthened central oversight of local disability-assessment commissions without altering formal eligibility rules. Using two decades of INPS data on a sample of Italian pensioners (around 159 millions of individual-years data), we combine a macro analysis of territorial dynamics with a micro analysis of post-reform socioeconomic selectivity. At the macro level, piecewise linear mixed-effects models show that the reform contributed to reducing coverage territorial heterogeneity. At the micro level, high-dimensional linear probability models indicate that tighter administrative oversight reshaped the socioeconomic composition of beneficiaries and the programme's compensatory role across different metrics of disadvantage

Role: Co-investigator with with my brilliant PhD student Martina Griseri

AMARTYA is an innovative microsimulation platform developed with the Emilia-Romagna Region to support evidence-based policymaking. By creating a digital twin of the region’s population and businesses, the project simulates the economic, social, employment, and distributional effects of public policies, providing decision-makers with detailed, geographically disaggregated evidence on their likely impacts.
Combining administrative data, statistical modelling, and policy simulation techniques, the project enables the ex-ante and ex-post evaluation of regional policies, helping to design interventions that are more effective, equitable, and responsive to local needs. AMARTYA contributes to advancing data-driven governance and territorial planning through the integration of big data, digital innovation, and public policy analysis.

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Role: Research Team Member / Scientific Collaborator with Regione Emilia Romagna, CAPP and UNIBO.

This project investigates whether assistive technologies can help reduce avoidable emergency department visits and hospital admissions among care home residents. Focusing on technologies such as remote monitoring systems, fall detectors, wearable sensors, and AI-enabled decision-support tools, the study examines how digital innovations are being adopted and used within care homes, and what evidence exists regarding their effectiveness and value for money.
The research combines evidence synthesis, data mapping, stakeholder engagement, and survey development to create a comprehensive picture of technology use in the care home sector. A key objective is to identify gaps in current knowledge, develop a practical framework for evaluating technology investments, and provide policymakers and care providers with evidence-based recommendations on how digital technologies can improve resident outcomes and support more sustainable care delivery.

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Role: Principal investigator with Edoardo Renato Piombini and Care Policy and Evaluation Centre (CPEC-LSE) colleagues (R. Wittenberg J-L. Fernandez J. Cartagena Farias)

Eligibility to publicly funded long-term care (LTC) is frequently governed by means-testing, with housing wealth playing a crucial role for many individuals in need. This multi-methods study examines England's Deferred Payment Agreements (DPA) scheme, designed to support homeowners who require care home services but are ineligible for LTC public support due to their housing equity. DPA is essentially a public loan, secured against housing equity, which effectively defers care home costs until a later date. Despite being legally mandated across England, the scheme's implementation reveals low and geographically uneven take-up rates. The quantitative analysis indicated that observed variation could be partially explained by area-level socioeconomic factors, such as poverty and the distribution of housing wealth. Interviews with professionals highlighted individual preferences, socio-cultural factors, and administrative processes as potential factors driving the variation that remained unexplained by the quantitative analysis.

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Role: Principal investigator with Care Policy and Evaluation Centre (CPEC-LSE) colleagues (C. De Poli, L. Compton & J-L. Fernandez)