Performance Monitoring and Competence Assessment in Health Services

Sotirios Bersimis (), Athanasios Sachlas () and Ross Sparks ()
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Sotirios Bersimis: University of Piraeus
Athanasios Sachlas: University of Piraeus
Ross Sparks: CSIRO

Methodology and Computing in Applied Probability, 2017, vol. 19, issue 4, 1169-1190

Abstract: Abstract 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.

Keywords: Competence assessment; Control charting; Health services monitoring; Markov Chain embedding technique; Multi-attribute comparative processes; Process monitoring; Testing competence; 60J20; 62P10 (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11009-017-9563-6

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