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Introduction of an Electronic Clinical Decision Support Tool to Inform Prescribing for Pediatric Diarrhea in Bangladesh and Mali: Do Provider Expectations Predict Experiences?

Abstract

Nonindicated antibiotics for childhood diarrhea is a major contributor to global antimicrobial resistance. Electronic clinical decision support tools (eCDSTs) may reduce unnecessary antibiotics. This study examined how providers' expectations of an eCDST to predict diarrhea etiology compared with their experiences using the tool. Providers were enrolled from public hospitals in Bangladesh (n = 15) and Mali (n = 15), and surveys were completed at baseline and after using the eCDST. Baseline surveys assessed expectations (utility, ease of use, and threat to autonomy), and post surveys assessed experiences in the same domains. Providers' experiences with ease of use exceeded their baseline expectations, and providers reported less experienced threat to autonomy after use, compared with baseline expectations. Providers' expectations of threat to autonomy significantly predicted their experienced threat to autonomy. Findings suggest that an eCDST to inform antimicrobial prescribing for diarrhea is feasible and acceptable, but training should promote local ownership for sustainability.

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References
1.
Haque F, Ball R, Khatun S, Ahmed M, Kache S, Chisti M . Evaluation of a Smartphone Decision-Support Tool for Diarrheal Disease Management in a Resource-Limited Setting. PLoS Negl Trop Dis. 2017; 11(1):e0005290. PMC: 5283765. DOI: 10.1371/journal.pntd.0005290. View

2.
Khan A, Mack J, Salimuzzaman M, Zion M, Sujon H, Ball R . Electronic decision support and diarrhoeal disease guideline adherence (mHDM): a cluster randomised controlled trial. Lancet Digit Health. 2020; 2(5):e250-e258. PMC: 8045011. DOI: 10.1016/S2589-7500(20)30062-5. View

3.
Biswas D, Hossin R, Rahman M, Bardosh K, Watt M, Zion M . An ethnographic exploration of diarrheal disease management in public hospitals in Bangladesh: From problems to solutions. Soc Sci Med. 2020; 260:113185. PMC: 7502197. DOI: 10.1016/j.socscimed.2020.113185. View

4.
Ingle D, Levine M, Kotloff K, Holt K, Robins-Browne R . Dynamics of antimicrobial resistance in intestinal Escherichia coli from children in community settings in South Asia and sub-Saharan Africa. Nat Microbiol. 2018; 3(9):1063-1073. PMC: 6787116. DOI: 10.1038/s41564-018-0217-4. View

5.
Howteerakul N, Higginbotham N, Freeman S, Dibley M . ORS is never enough: physician rationales for altering standard treatment guidelines when managing childhood diarrhoea in Thailand. Soc Sci Med. 2003; 57(6):1031-44. DOI: 10.1016/s0277-9536(02)00478-1. View