Determining readmission time window using mixture of generalised Erlang distribution

Abstract

The absence of a unified definition of readmissions has motivated the development of a modelling approach, to systematically tackle the issue surrounding the appropriate choice of a time window which defines readmission. The population of discharged patients can be broadly divided in two groups - a group at high risk of readmission and a group at low risk. This approach extends previous work by the authors, without restricting the number of stages, that patients may experience in the community. Using the national data (UK), we demonstrate its usefulness in the case of chronic obstructive pulmonary disease (COPD) which is known to be one of the leading causes of readmission. We further investigate variability in the definition of readmission among 10 strategic health authorities (SHAs) in England and observe that there are differences in the estimated time window across SHAs. The novelty of this modelling approach is the ability of capturing time to readmission that exhibit a non-zero mode and to estimate an appropriate time window based on evidence objectively derived from operational data.