Evidence map›Paper›PMID 32423447›Full record

ArticleBMC health services research2020

Preferences heterogeneity of health care utilization of community residents in China: a stated preference discrete choice experiment.

Ming-Zhu Jiang, Qiang Fu, Ju-Yang Xiong, Xiang-Lin Li, Er-Ping Jia, Ying-Ying Peng, Xiao Shen

Abstract read
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 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

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors.

Ming-Zhu JiangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Qiang FuDepartment of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO, USA.
Ju-Yang XiongSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China. xiongjuyang@hust.edu.cn.
Xiang-Lin LiSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Er-Ping JiaSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Ying-Ying PengSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Xiao ShenSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.

Funding

National Natural Science Foundation of China 71673095
6 · The paper itself

Abstract

backgroundTo tackle the issue with the low usage of primary healthcare service in China, it is essential to align resource distribution with the preferences of the community residents. There are few academic researches for describing residents' perceived characteristics of healthcare services in China. This study aims to investigate the preferences of healthcare services utilization in community residents and explore the heterogeneity. The findings will be useful for the policy makers to take targeted measures to tailor the provision of healthcare services.

methodsThe face-to-face interviews and surveys were conducted to elicit four key attributes (care provider; mode of services; cost; travel time) of the preference from community residents for healthcare utilization. A rational test was presented first to confirm the consistency, and then 16 pairs of choice tasks with 12 sociodemographic items were given to the respondents. Two hypothetical options for each set, without an opt-out option, were presented in each choice task. The latent class analysis (LCA) was used to analyse the data.

resultsTwo thousand one hundred sixty respondents from 36 communities in 6 cities were recruited for our study. 2019 (93.47%) respondents completed valid discrete choice experiment (DCE) questionnaires. The LCA results suggested that four groups of similar preferences were identified. The first group (27.29%) labelled as "Comprehensive consideration" had an even preference of all four attributes. The second group (37.79%) labelled as "Price-driven" preferred low-price healthcare services. The third group labelled as "Near distance" showed a clear preference for seeking healthcare services nearby. The fourth group (34.18%) labelled as "Quality seeker" preferred the healthcare service provided by experts. Willingness to pay (WTP) results showed that people were willing to accept CNY202.12($29.37) for Traditional Chinese Medicine (TCM) services and willing to pay CNY604.31($87.81) for the service provided by experts.

conclusionsOur study qualitatively measures the distinct preferences for healthcare utilization in community residents in China. The results suggest that the care provider, mode of services, travel time and cost should be considered in priority setting decisions. The study, however, reveals substantial disagreement in opinion of TCM between different population subgroups.

Indexed as

AdolescentAdultChinaChoice BehaviorFemaleHealth Care SurveysHumansMaleMiddle AgedPatient Acceptance of Health CarePatient PreferenceQualitative ResearchYoung AdultDiscrete choice experimentHealthcare utilizationPreference heterogeneity

Identifiers

PMID32423447
PMCPMC7236293

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.