CGR-CUSUM: a continuous time generalized rapid response cumulative sum chart

Biostatistics, vol. 25, pp. 253–269

Abstract

Rapidly detecting problems in the quality of care is of utmost importance for the well-being of patients. Without proper inspection schemes, such problems can go undetected for years. Cumulative sum (CUSUM) charts have proven to be useful for quality control, yet available methodology for survival outcomes is limited. The few available continuous time inspection charts usually require the researcher to specify an expected increase in the failure rate in advance, thereby requiring prior knowledge about the problem at hand. Misspecifying parameters can lead to false positive alerts and large detection delays. To solve this problem, we take a more general approach to derive the new Continuous time Generalized Rapid response CUSUM (CGR-CUSUM) chart. We find an expression for the approximate average run length (average time to detection) and illustrate the possible gain in detection speed by using the CGR-CUSUM over other commonly used monitoring schemes on a real-life data set from the Dutch Arthroplasty Register as well as in simulation studies. Besides the inspection of medical procedures, the CGR-CUSUM can also be used for other real-time inspection schemes such as industrial production lines and quality control of services.

Authors 4

1. Daniel Gomon corresponding Aachen Department of Statistics, Mathematical Institute

   Leiden University

   Affiliation as printed

   Department of Statistics, Mathematical Institute, Leiden University , Niels Bohrweg 1, 2333CA Leiden, The Netherlands

2. Hein Putter Aachen Department of Biomedical Data Sciences

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Centre , Einthovenweg 20, 2333ZC Leiden, The Netherlands

3. Rob G. H. H. Nelissen Aachen Department of Orthopaedic Surgery

   Leiden University · Leiden University Medical Center

   Affiliation as printed

   Department of Orthopaedic Surgery, Leiden University Medical Centre , Leiden, Albinusdreef 2, 2333 ZA Leiden, The Netherlands

4. Stéphanie van der Pas

   Amsterdam University Medical Centers · Vrije Universiteit Amsterdam

   Affiliation as printed

   Department of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam , De Boelelaan 1089A, 1081HV Amsterdam, The Netherlands