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Needs forecast and fund allocation of medical specialty positions in Emilia-Romagna (Italy) by system dynamics and integer programming

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Health Systems

Abstract

Each year Emilia-Romagna health managers have to negotiate the number of medical specialization grants to be financed by the National government and define the number of additional grants to be funded by the regional budget. The final goal of this study is to provide a Decision Support System for grant allocation to medical specializations within Emilia-Romagna over a 20-year planning horizon. We have developed a System Dynamics (SD) model that represents regional medical specialist human resources and forecasts population needs over the planning horizon. The SD model provides a requirement indicator for each medical specialization. On the basis of these indicators, an Integer Programming model computes optimal assignments of medical specialization grants. We then define three demand scenarios and show how regional and national funded grants can be managed in order to reduce future gaps by comparing our results with current policies.

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Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Energia Elettrica e dell’Informazione \Guglielmo Marconi’ – DEI – Università di Bologna, Bologna, Italy

    Andrea Lodi & Paolo Tubertini

  2. Agenzia Sanitaria e Sociale Regionale dell’Emilia-Romagna, Bologna, Italy

    Roberto Grilli, Corrado Ruozi & Francesca Senese

  3. Servizio statistica e informazione geografica della Regione Emilia-Romagna, Bologna, Italy

    Angelina Mazzocchetti

Authors
  1. Andrea Lodi
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  2. Paolo Tubertini
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  3. Roberto Grilli
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  4. Angelina Mazzocchetti
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  5. Corrado Ruozi
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  6. Francesca Senese
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Corresponding author

Correspondence to Paolo Tubertini.

Appendices

Appendix A

Simulation detailed outputs

Surgical area

Table A1

Table A1 Surgical class supply: 2011 status quo and 2030 forecasts
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Table A2

Table A2 Surgical class demand: 2011 status quo and 2030 forecasts
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Medical area

Table A3

Table A3 Medical class supply: 2011 status quo and 2030 forecasts
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Table A4

Table A4 Medical class demand: 2011 status quo and 2030 forecasts
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Diagnostic and clinical services area

Table A5

Table A5 Diagnostic and Clinical Services Class Supply: 2011 status quo and 2030 forecasts
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Table A6

Table A6 Diagnostic and clinical services class demand: 2011 status quo and 2030 forecasts
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Appendix B

Detailed allocation results

Table B1

Table B1 Cumulative allocation of regional and national grants per year (2012–2024) classified for general area according to the three demand scenarios
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Appendix C

Graphs forecast legend

illustration

figure a

Appendix D

Surgical area forecasts

Figure D1

Figure D1
figure 8

General surgeries class.

(a) General Surgery; (b) Pediatric Surgery; (c) Plastic Surgery.

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Appendix E

Medical area forecasts

Figure E1

Figure E1
figure 9

General medicine class.

(a) Internal Medicine; (b) Geriatrics; (c) Sports Medicine; (d) Oncology.

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Appendix F

Diagnostic and clinical services area forecasts

Figure F1

Figure F1
figure 10

Therapeutic and diagnostic services class.

(a) Anatomic pathology; (b) Microbiology and virology; (c) Clinical pathology.

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Lodi, A., Tubertini, P., Grilli, R. et al. Needs forecast and fund allocation of medical specialty positions in Emilia-Romagna (Italy) by system dynamics and integer programming. Health Syst 5, 213–236 (2016). https://doi.org/10.1057/hs.2015.11

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