Evidence map›Paper›PMID 39629395›Full record

ArticleJournal of family medicine and primary care2024

Knowledge, Attitude and Practice about Ayushman Bharat Digital Mission and Digital Health among hospital patients.

M C Arjun, S Poorvikha, Anura V Kurpad, Tinku Thomas

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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

4 authors.

M C ArjunClinical Research Fellow, St. John's Research Institute, Sarjapur Road, Koramangala, Bengaluru, Karnataka, India.
S PoorvikhaMedical Student, St. John's Medical College, Sarjapur Road, Koramangala, Bengaluru, Karnataka, India.
Anura V KurpadDepartment of Physiology, St. John's Medical College, Sarjapur Road, Koramangala, Bengaluru, Karnataka, India.
Tinku ThomasDepartment of Biostatistics, St. John's Medical College, Sarjapur Road, Koramangala, Bengaluru, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: The Government of India launched the Ayushman Bharat Digital Mission (ABDM) to digitize the national healthcare system. The aim of this study was to estimate the knowledge, attitude and practice regarding the ABDM and benefits of digital health among urban patients, who are likely to be early adopters of digital technologies. Methods: We interviewed 150 outpatients above 18 years of age, in a hospital in urban Bengaluru, India. Our questionnaire captured the knowledge, attitude and practice regarding ABDM and Digital Health, including open-ended questions to evaluate perceptions of the benefits and concerns regarding digital health. Results: Most of the participants belonged to the upper and upper middle socioeconomic classes. Only 8% of participants knew about the ABDM, although their knowledge and practice related to other Government digital services, like National Teleconsultation services (eSanjeevani), Arogya Setu and DigiLocker, were high. Many participants perceived digital health to be beneficial, but there were serious concerns regarding data safety, data privacy and misuse of health data by insurance companies. Conclusion: We established a baseline survey for assessing the knowledge, attitudes and practices of ABDM and digital health among urban patients. The results suggest that implementation agencies of ABDM should increase the Information, Education and Communication (IEC) and devise new strategies to create awareness, disseminate correct information and address the concerns of citizens.

Indexed as

Ayushman Bharat Digital MissionAyushman Bharat Health Accountdigital healthHealth IDNational Digital Health Mission

Identifiers

PMID39629395
PMCPMC11610875

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.