Published in:
Open Access 01-12-2019 | Research article
Investigating healthcare contacts of Dialysis patients by age and gender
Published in: BMC Health Services Research | Issue 1/2019
Login to get accessAbstract
Background
The objective of this paper is to utilise a clinical costing system to investigate differences in the patient journey, defined as the sequence and timing of contacts with the Gold Coast Hospital and Health Services (GCHHS), for four dialysis patient groups defined based on age and gender. It is hypothesised that frequency of contact and form of contact will differ based on both gender and age.
Methods
Data were provided for 393 patients discharged from the GCHHS facility with dialysis treatment between the 1st of January 2015 and the 31st of December 2016. Features extracted from the data included the number and type of contacts (inpatient admissions, outpatient appointments, and emergency department presentations), the likelihood of subsequent contact types, and time spent in and between contact types. Likelihoods of subsequent contact types were estimated by treating the sequence of contacts observed for each patient as a Markov chain and estimating transition probabilities.
Results
Differences in patient journey were most prominent when considering age differences, with older patients being characterised by a greater volume of average contacts over the two-year period. The larger volume of average contacts was attributable to shorter times between all types of contacts with the GCHHS as well as an increased volume of inpatient admissions for older patients. Patient journeys did not consistently differ by gender, though some isolated differences were noted for older female patients relative to older male patients.
Conclusions
Different patient groups are characterised by different patient journeys, and better understanding these differences will facilitate improved management of the resources required to service these patients. Clinical costing systems represent a valuable and easily accessible source of data for formulating institution-specific expectations of healthcare utilisation for different groups.