ArticlemedRxiv : the preprint server for health sciences2024
"We have been so patient because we know where we are coming from" Exploring the acceptability and feasibility of a mobile electronic medical record system designed for community-based antiretroviral therapy in Lilongwe, Malawi.
Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
- Updated by
Authors and funding
10 authors.
Funding
Abstract
Background: Mobile health (mHealth) is reshaping healthcare delivery, especially in HIV management. The World Health Organization advocates for mHealth to provide healthcare workers (HCWs) with real-time data, enhancing patient care. However, in Malawi's Lighthouse Trust antiretroviral therapy (ART) clinic, the nurse-led community-based ART (NCAP) program faces hurdles with data management due to lack of access to electronic medical records systems (EMRS) in the community setting. EMRS is not typically available in differentiated service delivery settings where reliable power and internet are often unavailable. We used human-centered design (HCD) processes to create a mobile EMRS prototype, the Community-based ART Retention and Suppression (CARES) app. We explore progress to simplify workflow for HCWs and improve client care. Methods: To evaluate the CARES app's feasibility and acceptability among NCAP HCWs, we conducted in-depth interviews among 15 NCAP HCWs. We used a rapid qualitative analysis approach guided by the extended Technology Acceptance Model. The study complied with the Consolidated Criteria for Reporting Qualitative Research (COREQ). Results: As a likely result of HCD, HCWs demonstrated high expectations for the CARES app to improve healthcare delivery and data management. However, challenges such as app performance, data integration, and system navigation were significant barriers to acceptance or feasibility. Despite challenges, HCWs remained optimistic about the potential for CARES to enhance NCAP clinical decision-making and data flow. HCWs emphasized the need for continuous training and stakeholder engagement, improved infrastructure, data security protections, and establishing the CARES app and EMRS integration to facilitate CARES' longterm success at scale. Conclusion: The study's findings underscore the importance of HCD for mHealth buy-in. As HCWs were invested in CARES success, they remained optimistic that the app could enhance NCAP services if user experience and app performance improved. Incorporation of HCW feedback would help deliver beyond the promise of CARES.
Identifiers
What OpenQuestion holds
Registered trials
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.