Methodology and Computing in Applied Probability

, Volume 19, Issue 4, pp 1169–1190 | Cite as

Performance Monitoring and Competence Assessment in Health Services

  • Sotirios Bersimis
  • Athanasios Sachlas
  • Ross Sparks


Health and health service monitoring is among the most promising research area today and the world work towards efficient and cost effective health care. This paper deals with monitoring health service performance using more than one performance outcome variable (multi-attribute processes), which is common in most health services. Although monitoring whether a health service changes or improves over time is important this is well covered in the current literature. Therefore this paper focuses on comparing similar health services in terms of their performance. The proposed procedure is based on an appropriate control chart. The paper deals with firstly the case when no risk adjustment is required because the health services being compared treat the same patient case-mix which does not vary over time. Secondly it deals with comparing health services where risk adjustment is required because the patient case-mix they service do differ because they service either very different geographical locations or service very different demographics of the same population. The technology developed in this paper could be used for example to assess and compare health practitioners’ competence over time, i.e. to decide if two doctors are equivalent in terms of their outcome performances. The waiting time random variable associated with the run length distribution of the control charts (as well as to competence testing) is studied using a Markov Chain embedding technique. Numerical results are provided that exhibit the value of the proposed procedures.


Competence assessment Control charting Health services monitoring Markov Chain embedding technique Multi-attribute comparative processes Process monitoring Testing competence 

Mathematics Subject Classification (2010)

60J20 62P10 


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Sotirios Bersimis
    • 1
  • Athanasios Sachlas
    • 1
  • Ross Sparks
    • 2
  1. 1.Department of Statistics & Insurance ScienceUniversity of PiraeusPiraeusGreece
  2. 2.CSIROMarsfieldAustralia

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