Evidence map›Paper›PMID 37815861›Full record

ArticleJMIR formative research2023

Evaluating the Feasibility and Acceptance of a Mobile Clinical Decision Support System in a Resource-Limited Country: Exploratory Study.

Kagiso Ndlovu, Nate Stein, Ruth Gaopelo, Michael Annechino, Mmoloki C Molwantwa, Mosadikhumo Monkge, Amy Forrestel, Victoria L Williams

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

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

8 authors.

Kagiso Ndlovu *Department of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-4175-8366
Nate Stein *Department of Product Management, VisualDx, Rochester, NY, United States.ORCID https://orcid.org/0000-0002-3001-7984
Ruth GaopeloDepartment of Computer Science, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0003-0514-0734
Michael AnnechinoDepartment of Business Development, Unleash, Rochester, NY, United States.ORCID https://orcid.org/0000-0002-9884-7319
Mmoloki C Molwantwa *Department of Medical Education, Faculty of Medicine, University of Botswana, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-2272-6000
Mosadikhumo MonkgeDepartment of Pediatrics and Adolescent Health, Princess Marina Hospital, Gaborone, Botswana.ORCID https://orcid.org/0000-0002-4229-3185
Amy ForrestelDepartment of Dermatology, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0001-9839-8675
Victoria L Williams *Department of Dermatology, University of Pennsylvania, Philadelphia, PA, United States.ORCID https://orcid.org/0000-0002-3842-2693

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn resource-limited countries, access to specialized health care services such as dermatology is limited. Clinical decision support systems (CDSSs) offer innovative solutions to address this challenge. However, the implementation of CDSSs is commonly associated with unique challenges. VisualDx-an exemplar CDSS-was recently implemented in Botswana to provide reference materials in support of the diagnosis and management of dermatological conditions. To inform the sustainable implementation of VisualDx in Botswana, it is important to evaluate the intended users' perceptions about the technology.

objectiveThis study aims to determine health care workers' acceptance of VisualDx to gauge the feasibility of future adoption in Botswana and other similar health care systems.

methodsThe study's design was informed by constructs of the Technology Acceptance Model. An explanatory, sequential, mixed methods study involving surveys and semistructured interviews was conducted. The REDCap (Research Electronic Data Capture; Vanderbilt University) platform supported web-based data capture from March 2021 through August 2021. In total, 28 health care workers participated in the study. Descriptive statistics were generated and analyzed using Excel (Microsoft Corp), and thematic analysis of interview transcripts was performed using Delve software.

resultsAll survey respondents (N=28) expressed interest in using mobile health technology to support their work. Before VisualDx, participants referenced textbooks, journal articles, and Google search engines. Overall, participants' survey responses showed their confidence in VisualDx (18/19, 95%); however, some barriers were noted. Frequently used VisualDx features included generating a differential diagnosis through manual entry of patient symptoms (330/681, 48.5% of total uses) or using the artificial intelligence feature to analyze skin conditions (150/681, 22% of total uses). Overall, 61% (17/28) of the survey respondents were also interviewed, and 4 thematic areas were derived.

conclusionsParticipants' responses indicated their willingness to accept VisualDx. The ability to access information quickly without internet connection is crucial in resource-constrained environments. Selected enhancements to VisualDx may further increase its feasibility in Botswana. Study findings can serve as the basis for improving future CDSS studies and innovations in Botswana and similar resource-limited countries.

Indexed as

Botswanaclinical decision supportdermatologyeHealthmobile phonetechnology acceptance modelVisualDx

Identifiers

PMID37815861
PMCPMC10599284

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.