Evidence map›Paper›PMID 40009284›Full record

ArticleThe patient2025

Using Best-Worst Scaling Survey to Investigate the Relative Importance of Attributes Associated with Public Hospital Outpatient Appointments.

Tilley Pain, Amy Brown, Gail Kingston, Stephen Perks, Corey Patterson, Nerida Firth, Jessica Lester, Luke Sherwood, Sonja Brennan, Deborah Street

Abstract read
In one paragraph

Article in The patient, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Tilley PainAllied Health Governance Office, Townsville Hospital and Health Service, Townsville, QLD, Australia. tilley.pain@health.qld.gov.au.ORCID 0000-0002-1032-1831
Amy BrownTownsville Cancer Centre, Townsville Hospital and Health Service, Townsville, QLD, Australia.ORCID 0000-0003-4520-2485
Gail KingstonAllied Health Governance Office, Townsville Hospital and Health Service, Townsville, QLD, Australia.ORCID 0000-0002-2275-8256
Stephen PerksCollege of Medicine and Dentistry, James Cook University, Townsville, QLD, Australia.ORCID 0000-0001-8971-4373
Corey PattersonAllied Health Services Division, Townsville Hospital and Health Service, Townsville, QLD, Australia.ORCID 0009-0004-1613-203X
Nerida FirthCollege of Medicine and Dentistry, James Cook University, Townsville, QLD, Australia.ORCID 0000-0002-4390-8006
Jessica LesterClinical Governance Directorate, Townsville Hospital and Health Service, Townsville, QLD, Australia.
Luke SherwoodAllied Health Services Division, Townsville Hospital and Health Service, Townsville, QLD, Australia.
Sonja BrennanNorth Queensland Maternal Fetal Medicine Unit, Townsville Hospital and Health Service, Townsville, QLD, Australia.ORCID 0000-0002-7634-9546
Deborah StreetCentre for Health Economics Research and Evaluation, University of Technology, Sydney, Australia.ORCID 0000-0002-4476-0656

Funding

Townsville Hospital and Health Service THHSSERTA_RPG16
6 · The paper itself

Abstract

introductionObtaining patient input before healthcare redesign improves patient experience. The Townsville Hospital and Health Service, a regional Australian public health service, seeks to reduce the long wait list for medical specialist appointments by introducing allied health substitution models of care for low-acuity patients. This paper describes a best worst scaling survey conducted to refine attributes associated with outpatient appointments which will be used in a future discrete choice experiment (DCE).

methodsA literature review was conducted to identify attributes associated with medical specialist outpatient appointments and allied health substitution models. An object (or case 1) best worst scaling (BWS) survey was designed using blocks of a balanced incomplete block design and analysed using multinomial logit and mixed logit models. Patients waiting at local specialist outpatient clinics were invited to complete the survey via an iPad. The interviewer collected field notes, which were analysed using content analysis.

resultsA total of 12 attributes were identified in the literature review and one from local discussion. The 167 completed responses demonstrated the ranking of attributes were diagnostic accuracy, symptom relief, continuity of care, satisfaction with care, healthcare professional, manner and communication, time on waitlist and onward referral. The least important attributes were reassurance offered, appointment wait time, cost and appointment duration.

conclusionsThis BWS survey allows us to reduce the attributes for inclusion in the DCE from 13 to 8. Diagnostic accuracy and symptom relief were of most importance, and appointment wait time and duration were of least importance. This suggests that patients would be willing to be attend different models of care such as allied health primary contact model if clinical outcomes were equivalent to the current medical-led models.

Indexed as

Appointments and SchedulesHospitals, PublicPatient SatisfactionAdultAgedAustraliaFemaleHumansMaleMiddle AgedOutpatientsSurveys and QuestionnairesWaiting Lists

Identifiers

PMID40009284
PMCPMC11985688

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.