RETIN

Responses To Inequalities in Non-communicable diseases: measurement and management challenges through an inter-regional perspectives

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The project

Welcome to RETIN

The RETIN project aims at conducting applied research on chronic diseases, treatment patterns, costs, and outcomes. The RETIN project will analyze chronic diseases variations in terms of geography and socio-demographic conditions by comparing three among the biggest Italian regions, namely Tuscany, Lombardy, and Sicily. The RETIN project will focus on four key areas:

  1. 1) Identification of common methods for a detailed examination of the current burden of chronicity through the use of administrative care databases and other publicly available information.
  2. 2) Comparison of differences within and between the three regions.
  3. 3) Analysis of socio-economic and contextual determinants on prevalence, costs, and outcome.
  4. 4) Lesson learnt and policy summary with the aim of building a common template for the adoption of a uniform definition of NCDs at the national level.
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Indicators


What's new on RETIN?

Latest News


Short course on
Spatial Health Econometrics

The Sant’Anna School of Advanced Studies and the Department of Statistics and Quantitative Methods of the University of Milano-Bicocca are organizing a short course on “Spatial Health Econometrics”.

The course will be held in Pisa at Sant’Anna School of Advanced Studies on July 8th, 2024.

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2024 Empirical Health Economics Workshop

The EHEW2024 workshop will take place at the Sant’Anna School of Advanced Studies of Pisa, on the 09th, 10th, 11th of July 2024.

The workshop welcomes empirical research (applied econometrics) papers that (i) evaluate current or past health policies; (ii) undertake analyses which shed light on important health policy questions.

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Kick-off meeting

The kick-off mmeeting has been held in Pisa on 14-15 of Novembre 2023.Bla Bla Bla

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Publications

Publications

The outputs of the project will be published in statistical, demographic and epidemiological journals to motivate an increasing collaboration among such fields.

[Bibliography]
[Data]

[Publisher's site] SPINELLI, Daniele. Fitting spatial autoregressive logit and probit models using Stata: The spatbinary command. The Stata Journal, 2022, 22.2: 293-318.

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Team

Principal Investigators

Paolo Berta
University of Milano-Bicocca
Chiara Seghieri
Sant'Anna School of Advanced Studies
Mauro Ferrante
University of Palermo

Principal Collaborators

Daniele Spinelli
University of Milano-Bicocca
Claudio Mazzi
Sant'Anna School of Advanced Studies
Sofia Longhi
Sant'Anna School of Advanced Studies
Contact

Contact


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