Investigating healthcare contacts of Dialysis patients by age and gender

Abstract 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 an...

Full description

Bibliographic Details
Main Authors: James Todd, Adrian Gepp, Bruce Vanstone, Brent Richards
Format: Article
Language:English
Published: BMC 2019-02-01
Series:BMC Health Services Research
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12913-019-3962-z
id doaj-3d936e91274f4c24beec5266ec95e4c0
record_format Article
spelling doaj-3d936e91274f4c24beec5266ec95e4c02020-11-25T01:11:52ZengBMCBMC Health Services Research1472-69632019-02-011911810.1186/s12913-019-3962-zInvestigating healthcare contacts of Dialysis patients by age and genderJames Todd0Adrian Gepp1Bruce Vanstone2Brent Richards3Bond Business School, Bond UniversityBond Business School, Bond UniversityBond Business School, Bond UniversityDirector Critical Care Research, Gold Coast University HospitalAbstract 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.http://link.springer.com/article/10.1186/s12913-019-3962-zRenal failureDialysisPatient journeyMarkov modelPatient demographics
collection DOAJ
language English
format Article
sources DOAJ
author James Todd
Adrian Gepp
Bruce Vanstone
Brent Richards
spellingShingle James Todd
Adrian Gepp
Bruce Vanstone
Brent Richards
Investigating healthcare contacts of Dialysis patients by age and gender
BMC Health Services Research
Renal failure
Dialysis
Patient journey
Markov model
Patient demographics
author_facet James Todd
Adrian Gepp
Bruce Vanstone
Brent Richards
author_sort James Todd
title Investigating healthcare contacts of Dialysis patients by age and gender
title_short Investigating healthcare contacts of Dialysis patients by age and gender
title_full Investigating healthcare contacts of Dialysis patients by age and gender
title_fullStr Investigating healthcare contacts of Dialysis patients by age and gender
title_full_unstemmed Investigating healthcare contacts of Dialysis patients by age and gender
title_sort investigating healthcare contacts of dialysis patients by age and gender
publisher BMC
series BMC Health Services Research
issn 1472-6963
publishDate 2019-02-01
description Abstract 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.
topic Renal failure
Dialysis
Patient journey
Markov model
Patient demographics
url http://link.springer.com/article/10.1186/s12913-019-3962-z
work_keys_str_mv AT jamestodd investigatinghealthcarecontactsofdialysispatientsbyageandgender
AT adriangepp investigatinghealthcarecontactsofdialysispatientsbyageandgender
AT brucevanstone investigatinghealthcarecontactsofdialysispatientsbyageandgender
AT brentrichards investigatinghealthcarecontactsofdialysispatientsbyageandgender
_version_ 1725169155396599808