Evidence map›Paper›PMID 41108507›Full record

ArticleThe patient2026

Eliciting Patient Preferences for the Hospital at Home Programme in Singapore; A Discrete Choice Experiment.

Sanjeewa Kularatna, Low Lian Leng, Michelle Tan Woei Jen, Tang Woon Hoe, Tan Wee Boon, Lai Yi Feng, Nicholas Graves, Sameera Senanayake

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Article in The patient, 2026. 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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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Sanjeewa KularatnaHealth Services and Systems Research, Duke-NUS Medical School, 08 College Road, Singapore, Singapore. Sanjeewa.kularatna@duke-nus.edu.sg.ORCID 0000-0001-5650-154X
Low Lian LengDivision of Population Health and Integrated Care (PHIC), Singapore General Hospital, Singapore, Singapore.
Michelle Tan Woei JenDepartment of Family Medicine and Continuing Care, Singapore General Hospital, Singapore, Singapore.
Tang Woon HoeDivision of Population Health and Integrated Care (PHIC), Singapore General Hospital, Singapore, Singapore.
Tan Wee BoonDivision of Population Health and Integrated Care (PHIC), Singapore General Hospital, Singapore, Singapore.
Lai Yi FengMOH Office for Healthcare Transformation, Singapore, Singapore.
Nicholas GravesHealth Services and Systems Research, Duke-NUS Medical School, 08 College Road, Singapore, Singapore.
Sameera SenanayakeHealth Services and Systems Research, Duke-NUS Medical School, 08 College Road, Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospital overcrowding in Singapore has reached a critical level, primarily owing to an ageing population and an increased demand for medical services. Alternative care models such as hospital-at-home (H@H) programmes have been introduced to address this issue, utilising telehealth and home-based care. We conducted a choice experiment to determine the most preferred characteristics of a hospital-at-home programme in Singapore.

methodsA desktop review, interviews with clinicians and an expert panel helped to decide on the attributes and levels of the choice sets. The attributes were the type of care team, communication method, care providers, out-of-pocket costs, additional services, and place of return to the hospital if needed. We obtained information from adult Singaporeans (age > 21 years) admitted to a hospital within the past 2 years using an online panel. The design was a fractional factorial study. A pilot study and a redesign helped to refine the choice experiment. The survey used two unlabelled alternatives.

resultsThe total study sample consisted of 602 respondents. The respondents did not have a particular preference for the type of care team, communication method or additional services provider. However, there was a strong preference for having a doctor as part of the care team and being readmitted to a specific ward rather than the emergency department. The analysis of relative importance revealed that out-of-pocket costs (71%) and the composition of care providers (12%) were the most significant attributes in decision-making. We found an anticipated adoption rate of H@H was over 83% compared with inpatient care.

conclusionsClinically eligible patients in Singapore are highly likely to accept the H@H care model. An approved private provider could provide the service without reducing patient satisfaction and trust.

Indexed as

Choice BehaviorHome Care Services, Hospital-BasedPatient PreferenceAdultAgedFemaleHumansMaleMiddle AgedSingaporeTelemedicineYoung Adult

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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.