Evidence map›Paper›PMID 24888984›Full record

ArticleJournal of medical systems2014

Development of a decision support engine to assist patients with hospital selection.

Lichin Chen, Chih-Min Chan, Hung-Chang Lee, Yufang Chung, Feipei Lai

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

5 authors.

Lichin ChenGraduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei, 10617, Taiwan, d98945012@ntu.edu.tw.
Chih-Min Chan
Hung-Chang Lee
Yufang Chung
Feipei Lai

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hospital selection is a complicated decision-making process. Although patients have expressed greater desire to participate in decision-makings of their healthcare, it can be problematic for them to accumulate large amount of information and using it for making an optimal choice in hospital selection. The aim of this research is to develop a decision engine for hospital selection (DEHS) to support patients while accessing healthcare resources. DEHS applied the analytic hierarchy process and the geographic information system to aggregate different decision factors and spatial information. The results were evaluated through investigating the consistency of the preferences that users inputted, the degree that the results match patient choices, the satisfactions of users, and the helpfulness of the results. Data were collected for 3 months. One hundred and four users visited DEHS and 85.5 % of them used DEHS more than once. Recommendations of the institutes (36 %) was ranked as the primary decision factor that most users concerned. Sixty-seven percent of the sessions searched for hospitals and 33 % for clinics. Eighty-eight percent of the results matched the choices of patients. Eighty-three percent of the users agreed that the suggested results were satisfactory, and 70 % agreed that the information were helpful. The DEHS provides the patients with simple measurements and individualized list of suggested medical institutes, and allows them to make decisions based on credible information and consults the experiences of others at the same time. The suggested results were considered satisfactory and helpful.

Indexed as

Choice BehaviorDecision Support TechniquesHospitalsGeographic Information SystemsHospitals, SpecialHumansPatient ParticipationPatient Satisfaction

Identifiers

What OpenQuestion holds

Textmetadata
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.