title: A probabilistic method for computing quantitative risk indexes from medical injuries compensation claims.
abstract: 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.
  
  
  OBJECTIVE
  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 parametric 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 semester 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.
authors.affiliation: Riccardo Bellazzi, Dipartimento di Ingegneria Industriale e dell'Informazione, Via Ferrata 1, 27100 Pavia (PV), Italy, E-mail: riccardo.bellazzi@unipv.it.
authors.forename: S
authors.initials: S
authors.lastname: Dalle Carbonare
authors.forename: F
authors.initials: F
authors.lastname: Folli
authors.forename: E
authors.initials: E
authors.lastname: Patrini
authors.forename: P
authors.initials: P
authors.lastname: Giudici
authors.forename: R
authors.initials: R
authors.lastname: Bellazzi
mesh_terms: D035881:Compensation and Redress; D016208:Databases, Factual; D006268:Health Facilities / Q000191:economics; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D008318:Malpractice / Q000191:economics; D019300:Medical Errors / Q000191:economics*; D015233:Models, Statistical; D011336:Probability; D012308:Risk Management / Q000706:statistics & numerical data
keywords: Loss Distribution Approach; Monte Carlo methods; Probabilistic models; risk management