Evidence map›Paper›PMID 30813915›Full record

ArticleBMC health services research2019

Investigating healthcare contacts of Dialysis patients by age and gender.

James Todd, Adrian Gepp, Bruce Vanstone, Brent Richards

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Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

James ToddBond Business School, Bond University, Robina, Queensland, 4229, Australia.
Adrian GeppBond Business School, Bond University, Robina, Queensland, 4229, Australia. adgepp@bond.edu.au.ORCID http://orcid.org/0000-0003-1666-5501
Bruce VanstoneBond Business School, Bond University, Robina, Queensland, 4229, Australia.
Brent RichardsDirector Critical Care Research, Gold Coast University Hospital, Southport, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsData 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.

resultsDifferences 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.

conclusionsDifferent 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.

Indexed as

Renal DialysisAgedContinuity of Patient CareFemaleHospitalizationHumansMaleMiddle AgedPatient Acceptance of Health CarePatient DischargeRetrospective StudiesDialysisMarkov modelPatient demographicsPatient journeyRenal failure

Identifiers

PMID30813915
PMCPMC6391767

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