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. 2024 Oct 7:26:e45122.
doi: 10.2196/45122.

Implementation of a Clinical Decision Support System for Antimicrobial Prescribing in Sub-Saharan Africa: Multisectoral Qualitative Study

Nathan Peiffer-Smadja  1   2   3 , Sophie Descousse  1 , Elsa Courrèges  1 , Audrey Nganbou  1 , Pauline Jeanmougin  2 , Gabriel Birgand  4 , Séverin Lénaud  5 , Anne-Lise Beaumont  3 , Claire Durand  1 , Tristan Delory  2   6 , Josselin Le Bel  1   2   7 , Elisabeth Bouvet  2   3 , Sylvie Lariven  2   3 , Eric D'Ortenzio  3   8 , Issa Konaté  9 , Marielle Karine Bouyou-Akotet  10 , Abdoul-Salam Ouedraogo  11 , Gisèle Affoue Kouakou  12 , Armel Poda  11 , Corinne Akpovo  12 , François-Xavier Lescure  1   2   3 , Aristophane Tanon  12
Affiliations

Implementation of a Clinical Decision Support System for Antimicrobial Prescribing in Sub-Saharan Africa: Multisectoral Qualitative Study

Nathan Peiffer-Smadja et al. J Med Internet Res. .

Abstract

Background: Suboptimal use of antimicrobials is a driver of antimicrobial resistance in West Africa. Clinical decision support systems (CDSSs) can facilitate access to updated and reliable recommendations.

Objective: This study aimed to assess contextual factors that could facilitate the implementation of a CDSS for antimicrobial prescribing in West Africa and Central Africa and to identify tailored implementation strategies.

Methods: This qualitative study was conducted through 21 semistructured individual interviews via videoconference with health care professionals between September and December 2020. Participants were recruited using purposive sampling in a transnational capacity-building network for hospital preparedness in West Africa. The interview guide included multiple constructs derived from the Consolidated Framework for Implementation Research. Interviews were transcribed, and data were analyzed using thematic analysis.

Results: The panel of participants included health practitioners (12/21, 57%), health actors trained in engineering (2/21, 10%), project managers (3/21, 14%), antimicrobial resistance research experts (2/21, 10%), a clinical microbiologist (1/21, 5%), and an anthropologist (1/21, 5%). Contextual factors influencing the implementation of eHealth tools existed at the individual, health care system, and national levels. At the individual level, the main challenge was to design a user-centered CDSS adapted to the prescriber's clinical routine and structural constraints. Most of the participants stated that the CDSS should not only target physicians in academic hospitals who can use their network to disseminate the tool but also general practitioners, primary care nurses, midwives, and other health care workers who are the main prescribers of antimicrobials in rural areas of West Africa. The heterogeneity in antimicrobial prescribing training among prescribers was a significant challenge to the use of a common CDSS. At the country level, weak pharmaceutical regulations, the lack of official guidelines for antimicrobial prescribing, limited access to clinical microbiology laboratories, self-medication, and disparity in health care coverage lead to inappropriate antimicrobial use and could limit the implementation and diffusion of CDSS for antimicrobial prescribing. Participants emphasized the importance of building a solid eHealth ecosystem in their countries by establishing academic partnerships, developing physician networks, and involving diverse stakeholders to address challenges. Additional implementation strategies included conducting a local needs assessment, identifying early adopters, promoting network weaving, using implementation advisers, and creating a learning collaborative. Participants noted that a CDSS for antimicrobial prescribing could be a powerful tool for the development and dissemination of official guidelines for infectious diseases in West Africa.

Conclusions: These results suggest that a CDSS for antimicrobial prescribing adapted for nonspecialized prescribers could have a role in improving clinical decisions. They also confirm the relevance of adopting a cross-disciplinary approach with participants from different backgrounds to assess contextual factors, including social, political, and economic determinants.

Keywords: CDSS; Consolidated Framework for Implementation Research; antimicrobial resistance; eHealth; implementation research; mHealth; mobile health; mobile phone.

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Conflict of interest statement

Conflicts of Interest: Some co-authors of this study, namely NP-S, AT, FXL, and GK, participated in the development of the free academic Antibioclic Afrique app, which is the subject of the qualitative evaluation conducted in this work. These authors are employees of the public health sector in their countries, and none of them have a financial conflict of interest with Antibioclic Afrique, which is a non–profit-oriented decision support system. All other authors declare no other conflicts of interest.

Figures

Figure 1
Figure 1
Global challenges in the design and implementation of Antibioclic Afrique. CDSS: clinical decision support system.
Figure 2
Figure 2
Barriers and facilitators at the different levels of the health pyramid. CDSS: clinical decision support system.
See this image and copyright information in PMC

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