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Methods Inf Med 2013; 52(05): 374-381
DOI: 10.3414/ME12-01-0074
Original Articles
Schattauer GmbH

A Probabilistic Method for Computing Quantitative Risk Indexes from Medical Injuries Compensation Claims

S. Dalle Carbonare
1   Dipartimento di Ingegneria Industriale e dell’Informazione, Università di Pavia, Pavia, Italy
,
F. Folli
2   Risk Manager, Azienda Ospedaliera di Lodi, Lodi, Italy
,
E. Patrini
3   MARSH S.p.A., Milano, Italy
,
P. Giudici
4   Dipartimento di Scienze Economiche ed Aziendali, Università di Pavia, Pavia, Italy
,
R. Bellazzi
1   Dipartimento di Ingegneria Industriale e dell’Informazione, Università di Pavia, Pavia, Italy
› Author Affiliations
Further Information

Publication History

received: 10 August 2012

accepted: 05 February 2013

Publication Date:
20 January 2018 (online)

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Summary

Background: The increasing demand of health care services and the complexity of health care delivery require Health Care Organizations (HCOs) to approach clinical risk management through proper methods and tools. An important aspect of risk management is to exploit the analysis of medical injuries compensation claims in order to reduce adverse events and, at the same time, to optimize the costs of health insurance policies.

Objectives: This work provides a probabilistic method to estimate the risk level of a HCO by computing quantitative risk indexes from medical injury compensation claims.

Methods: Our method is based on the estimate of a loss probability distribution from compensation claims data through para -metric and non-parametric modeling and Monte Carlo simulations. The loss distribution can be estimated both on the whole dataset and, thanks to the application of a Bayesian hierarchical model, on stratified data. The approach allows to quantitatively assessing the risk structure of the HCO by analyzing the loss distribution and deriving its expected value and percentiles.

Results: We applied the proposed method to 206 cases of injuries with compensation requests collected from 1999 to the first se -mester of 2007 by the HCO of Lodi, in the Northern part of Italy. We computed the risk indexes taking into account the different clinical departments and the different hospitals involved.

Conclusions: The approach proved to be useful to understand the HCO risk structure in terms of frequency, severity, expected and unexpected loss related to adverse events.

Keywords

Probabilistic models - Monte Carlo methods - Loss Distribution Approach - risk management
 

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