85278 - METHODS AND TOOLS FOR HEALTH STATISTICS

Scheda insegnamento

Anno Accademico 2018/2019

Conoscenze e abilità da conseguire

By the end of the course the student knows the most commonly used medical sources at European and world level and the methods of study of health and social phenomena, with particular reference to multivariate statistical analysis. In particular, the student is able to: - use statistical methods to estimate the life expectancy of the population in health - analyze health and social phenomena in terms of the effects on the population, and analyze the effect of health policy change on the population using appropriate statistical methods and software.

Programma/Contenuti

This course is intended to support the student towards a fundamental understanding of the societal value of the health information infrastructure and the methods and tools used to report, evaluate and continuously improve policies.

In particular, the course will present solutions to current challenges involving the use of large scale routine databases available at national and international level, including practices and novel solutions to deal with confidentiality rules. Practical cases of data analysis will be presented using relevant statistical software. Issues in the correct communication of health statistics will be also discussed.

At the end of the course, the student should be able:

  • to calculate and interpret health indicators used in regional, national and international reports (in particular, the EU European Core Health Indicators, European Sustainable Development Indicators and State of Health in the EU): from life expectancy to quality of care, access and efficiency measures.

  • to apply advanced techniques for health systems performance evaluation: from risk adjustment and standardization through the use of multivariate models (generalized linear models, generalized estimating equations, multilevel and Cox-derived models), to modern approaches using privacy-enhanced information systems (distributed data processing) and person-centered statistical models (risk prediction and stratification for population health management).

  • to apply principles of study design (experimental vs observational) and analytical techniques (e.g. propensity scores, meta-analysis) to plan and evaluate health interventions and policies, considering social determinants of health and prevention.

Lectures will cover the following subjects:

  • STREAM 1. Regional, national and international health statistics

    • International data sources, projects, classification and coding systems (Health status and quality of life, Surveys, Reports and Health Databases - WHO, European Commission/EUROSTAT, OECD Health at a Glance).

    • Standardized health care data sources in the Italian National Health System.

    • Theory and applications of health systems performance assessment. The “Triple Aim” and the future of health statistics: Patient Reported Outcome Measures (PROMs) for value-based health care.

    • R Labs: analysis of health indicators

  • STREAM 2. Risk stratification and standardization

    • Standardization methods in AHRQ and OECD indicators. Multivariate models for complex data: GEE logistic regression, time dependent covariates using the Cox Proportional hazard model.

    • Healthcare performance intelligence: modern approaches for international comparisons (including the privacy problem and distributed data analysis: the BIRO approach and the OECD hospital performance benchmarking method). Advanced techniques for predictive modeling (classification and regression trees, cross validation and bootstrapping methods).

    • R Labs: risk adjustment and standardization techniques

  • STREAM 3. Statistical methods and tools to plan and evaluate health policies

    • Study design (experimental vs observational, cluster clinical trials, etc) and statistical techniques (propensity scores, etc).

    • Meta-analysis of health interventions: principles, methodology and the quantitative analysis of binary and continuous data.

    • R Labs: propensity scores and meta-analysis.

Testi/Bibliografia

Main References (extracts)

  • Kleinbaum DG, M Klein, Survival analysis. A self learning Text. 3rd Edition. Springer 2012.

  • Kleinbaum DG, Logistic Regression. A self learning text. 3rd Edition, Springer, 2010.

  • OECD, Health at a glance 2017, Paris 2017 Available at: http://www.oecd.org/health/health-systems/health-at-a-glance-19991312.htm

Papers (provisional list)

  • Carinci F et al., Towards actionable international comparisons of health system performance: expert revision of the OECD framework and quality indicators, International Journal for Quality in Health Care, Apr; 27(2):137-46, 2015. Available at: http://intqhc.oxfordjournals.org/content/27/2/137.long.

  • Carinci F et al. Lower extremity amputation rates in people with diabetes as an indicator of health systems performance. A critical appraisal of the data collection 2000-2011 by the Organization for Economic Cooperation and Development (OECD), Acta Diabetologica, 2016 Oct;53(5):825-32. Available at: http://link.springer.com/article/10.1007%2Fs00592-016-0879-4.

  • Nicolucci A, Carinci F, Ciampi A, Stratifying Patients at Risk of Diabetes Complications: An integrated look at clinical, socio-economic and care-related factors, Diabetes Care, 21 (9):1439-1444, 1998.

Metodi didattici

Lectures with open discussion + Computer labs + Selected readings

Modalità di verifica dell'apprendimento

The exam will evaluate the achievements of the student through a direct assessment of the following learning outcomes:

  • ability to identify the most suitable methods required to carry out the analysis and interpretation of health-related data

  • ability to conduct a critical appraisal of the methodology adopted in a research project or scientific publications

The exam will consist in the presentation of a small project of data analysis chosen by the student, using datasets available in the public domain, followed by an oral assessment concerning the statistical techniques and the underlying theory related to the specific study program. An understanding of the fundamental societal goals relevant to population health and health policies will be also requested for the examination.

Strumenti a supporto della didattica

Slide power point

R - scripts

Orario di ricevimento

Consulta il sito web di Fabrizio Carinci