Borsa di dottorato "Advanced Healthcare Analytics on administrative data" - Politecnico di Milano

Il Dipartimento di Matematica del Politecnico di Milano segnala la selezione pubblica per il conferimento di N.1 borsa triennale di Dottorato di Ricerca.

Scuola: Dottorato in Data Analytics and Decision Sciences (DADS).

Durata: 1° febbraio 2022 – 31 gennaio 2024

Obiettivi: Valorizzazione dei dati Real World nel contesto delle azioni di governance per la sanità pubblica.

La figura ci si aspetta che sia in grado durante e alla fine del percorso di effettuare:

  • Raccolta, analisi e studio dati disponibili sanitari nel sistema di Regione Lombardia
  • Individuazione con i referenti e decisori di Regione Lombardia delle priorità, esigenze e limiti attuali di dati ed analisi.
  • Sviluppo di un nuovo sistema delle conoscenze, attraverso tecniche avanzate di health analytics.
  • Sistematizzazione e messa a disposizione dei dati ai diversi interlocutori interni ed esterni in modo profilato.

Tematica vincolata: Advanced Healthcare Analytics on administrative data

Responsabile scientifico e contatto per informazioni: Prof.ssa Francesca Ieva (francesca.ieva@polimi.it)

Sede lavorativa: Regione Lombardia – DG Welfare + Politecnico di Milano.

Il percorso dottorale prevede un percorso di almeno 6 mesi presso Regione Lombardia – DG Welfare e un periodo all’estero di 6 mesi.

Scheda:

 

Scholarships and Financial support

Monthly net income of  PhD scholarship (max 36 months)

€.  1300

                                                   

                                                    Context of the research activity

Motivations and objectives of the research in this field

Healthcare analytics is the process of analyzing current and historical healthcare data to predict trends, improve outreach, and better manage the spread of diseases. The field covers a broad range of data sources and related methodologies, and offers insights that complement the clinical and healthcare government experience. In fact, it can reveal paths to improvement in patient care quality, clinical data itself, diagnosis, and healthcare management. When combined with advanced statistical and Machine Learning methods, as well as data visualization tools, healthcare analytics help managers operate better by providing real-time information that can support decisions and deliver actionable insights.

Methods and techniques that will be developed and used to carry out the research

The research will focus on the design, development and application of novel statistical and machine learning methods to the healthcare administrative datawarehouse of Regione Lombardia.

It will cover techniques spanning from traditional statistical methodologies, functional data analysis, pharmacoepidemiology, survival and multi-state modelling, to the novel and complex machine learning techniques in order to i) monitor and evaluate the effectiveness of different policies; ii) support scenario analyses; iii) develop policies evaluation strategies.

Educational objectives

The successful candidate is expected to be able to collect, analyse and manage healthcare data available in the administrative datawarehouse of Lombardia Healthcare Regional District. Moreover, the candidate is expected to support the healthcare division management in pointing out potential and limitations of the data as well as to develop knowledge and evidences from data, through the use of advanced data analytics techniques

Job opportunities

The profile of data scientist and the applications proposed in this project are of interest to of a broad range of actors, including (but not limited to): public and private institutions dealing with healthcare, hospitals, clinical and pharmaceutical companies, as well as international institutions and research centres working in healthcare research, and policy makers in charge with healthcare governance.

In particular, Regione Lombardi healthcare district will be a favoured interlocutor for the discussion about job opportunities.

Composition of the research group

Currently:

Number of Full Professors: 3

Number of Associate Professors: 3

Number of Researchers: 4

Number of Post-Docs: 2

Number of PhD students: 6

https://statistics.mox.polimi.it/

Names of the research directors

Prof. Francesca Ieva

E-mail address, phone number and web-page

francesca.ieva@polimi.it

Department of Mathematics, Politecnico di Milano

Via Bonardi 9, 20133, Milano (MI), Italy

02 2399 4578

https://sites.google.com/view/francesca-ieva/home

List of Universities, Companies, Agencies and/or National or International Institutions that are cooperating in the research

1. Regione Lombardia – DG Welfare

2. Center for Health Data Science (CHDS) – Human Technopole