Evidence map›Paper›PMID 36211797›Full record

ArticleDigital health

Evaluation of a village-based digital health kiosks program: A protocol for a cluster randomized clinical trial.

Weibin Cheng, Zhang Zhang, Samantha Hoelzer, Weiming Tang, Yizhi Liang, Yumeng Du, Hao Xue, Qiru Zhou, Winnie Yip, Xiaochen Ma and 2 more

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

12 authors at 6 institutions in 3 countries.

Weibin ChengInstitute for the Application of Artificial Intelligence in Healthcare, Guangdong Second Provincial General Hospital, Guangzhou, China.ORCID https://orcid.org/0000-0002-9845-6676
Zhang ZhangGillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, USA.ORCID https://orcid.org/0000-0001-9344-6578
Samantha HoelzerGillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, USA.ORCID https://orcid.org/0000-0002-5945-4109
Weiming TangInstitute for the Application of Artificial Intelligence in Healthcare, Guangdong Second Provincial General Hospital, Guangzhou, China.
Yizhi LiangUniversity of North Carolina at Chapel Hill Project-China, Guangzhou, China.
Yumeng DuInstitute for the Application of Artificial Intelligence in Healthcare, Guangdong Second Provincial General Hospital, Guangzhou, China.ORCID https://orcid.org/0000-0002-6430-9440
Hao XueStanford Center for China's Economy and Institutions, Stanford University, Stanford, USA.
Qiru ZhouInternet Hospital, Guangdong Second Provincial General Hospital, Guangzhou, China.
Winnie YipDepartment of Global Health and Population, Harvard University, Boston, USA.
Xiaochen MaChina Center for Health Development Studies, Peking University, Beijing, China.
Junzhang TianInstitute for the Application of Artificial Intelligence in Healthcare, Guangdong Second Provincial General Hospital, Guangzhou, China.
Sean SylviaGillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, USA.
University of North Carolina at Chapel Hill · USCity University of Hong Kong · HKGuangdong Provincial People's Hospital · CNHarvard University · USPeking University · CNStanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To address disparities in healthcare quality and access between rural and urban areas in China, reforms emphasize strengthening primary care and digital health utilization. Yet, evidence on digital health approaches in rural areas is lacking. Objective: This study will evaluate the effectiveness of Guangdong Second Provincial General Hospital's Digital Health Kiosk program, which uses the Dingbei telemedicine platform to connect rural clinicians to physicians in upper-level health facilities and provide access to artificial intelligence-enabled diagnostic support. We hypothesize that our interventions will increase healthcare utilization and patient satisfaction, decrease out-of-pocket costs, and improve health outcomes. Methods: This cluster randomized control trial will enroll clinics according to a partial factorial design. Clinics will be randomized to either a control arm with clinician medical training, a second arm additionally receiving Dingbei telemedicine training, or a third arm with monetary incentives for patient visits conducted through Dingbei plus all prior interventions. Clinics in the second and third arm will then be orthogonally randomized to a social marketing arm that targets villager awareness of the kiosk program. We will use surveys and Dingbei administrative data to evaluate clinic utilization, revenue, and clinician competency, as well as patient satisfaction and expenses. Results: We have received ethical approval from Guangdong Second Provincial General Hospital (IRB approval number: GD2H-KY IRB-AF-SC.07-01.1), Peking University (IRB00001052-21007), and the University of North Carolina at Chapel Hill (323385). Study enrollment began April 2022. Conclusions: This study has the potential to inform future telemedicine approaches and assess telemedicine as a method to address disparities in healthcare access.

Indexed as

digital healthprimary careprotocoltelemedicinevillage-basedvillage doctors

Identifiers

PMID36211797
PMCPMC9537487
OpenAlexW4304117197

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.