Designing a Novel Clinician Decision Support Tool for the Management of Acute Diarrhea in Bangladesh: Formative Qualitative Study

Abstract

Background The availability of mobile clinical decision support (CDS) tools has grown substantially with the increased prevalence of smartphone devices and apps. Although health care providers express interest in integrating mobile health (mHealth) technologies into their clinical settings, concerns have been raised, including perceived disagreements between information provided by mobile CDS tools and standard guidelines. Despite their potential to transform health care delivery, there remains limited literature on the provider’s perspective on the clinical utility of mobile CDS tools for improving patient outcomes, especially in low- and middle-income countries. Objective This study aims to describe providers’ perceptions about the utility of a mobile CDS tool accessed via a smartphone app for diarrhea management in Bangladesh. In addition, feedback was collected on the preliminary components of the mobile CDS tool to address clinicians’ concerns and incorporate their preferences. Methods From November to December 2020, qualitative data were gathered through 8 web-based focus group discussions with physicians and nurses from 3 Bangladeshi hospitals. Each discussion was conducted in the local language—Bangla—and audio recorded for transcription and translation by the local research team. Transcripts and codes were entered into NVivo (version 12; QSR International), and applied thematic analysis was used to identify themes that explore the clinical utility of an mHealth app for assessing dehydration severity in patients with acute diarrhea. Summaries of concepts and themes were generated from reviews of the aggregated coded data; thematic memos were written and used for the final analysis. Results Of the 27 focus group participants, 14 (52%) were nurses and 13 (48%) were physicians; 15 (56%) worked at a diarrhea specialty hospital and 12 (44%) worked in government district or subdistrict hospitals. Participants’ experience in their current position ranged from 2 to 14 years, with an average of 10.3 (SD 9.0) years. Key themes from the qualitative data analysis included current experience with CDS, overall perception of the app’s utility and its potential role in clinical care, barriers to and facilitators of app use, considerations of overtreatment and undertreatment, and guidelines for the app’s clinical recommendations. Participants felt that the tool would initially take time to use, but once learned, it could be useful during epidemic cholera. Some felt that clinical experience remains an important part of treatment that can be supplemented, but not replaced, by a CDS tool. In addition, diagnostic information, including mid-upper arm circumference and blood pressure, might not be available to directly inform programming decisions. Conclusions Participants were positive about the mHealth app and its potential to inform diarrhea management. They provided detailed feedback, which developers used to revise the mobile CDS tool. These formative qualitative data provided timely and relevant feedback to improve the utility of a CDS tool for diarrhea treatment in Bangladesh.

Use of Framework Matrix and Thematic Coding Methods in Qualitative Analysis for mHealth: The FluidCalc app

“…Details of the thematic analysis have been previously published (Rosen et al, 2022). That paper uses direct participant quotes for illustration and as evidence for participants’ thought processes and the decision-making behind their opinions and choices (Rosen et al, 2022). It provides context about clinicians’ willingness to use FluidCalc, suggestions for needed training, options about which types of clinicians could and should use the app, and details about the role of clinician experience versus treatment models for guiding patient care.…”

“…After participant feedback on key app features were summarized using FA, we also developed thematic codes and wrote summaries to look in detail at a few specific features, including age, danger signs, and dehydration assessment. Details of the thematic analysis have been previously published (Rosen et al, 2022). That paper uses direct participant quotes for illustration and as evidence for participants' thought processes and the decision-making behind their opinions and choices (Rosen et al, 2022).…”

A comparison of the NIRUDAK models and WHO algorithm for dehydration assessment in older children and adults with acute diarrhoea: a prospective, observational study

“… 24 Test characteristics for the overall models (using probability cut-points along the ROC curves for the NIRUDAK models determined a priori by clinician focus groups in Bangladesh) and for individual clinical signs were also summarised. 18 All statistical analyses were performed using R version 4.2.2.…”

“… 17 Along with our previously validated DHAKA score for young children, 13 these NIRUDAK models were incorporated into a mobile health (mHealth) clinical decision support tool (CDST) named FluidCalc to help frontline clinicians provide more appropriate, evidence-based management of this common yet deadly disease ( appendix 2 p 2 ). 18 The FluidCalc CDST also incorporates models to predict the specific fluid deficit of each patient and provides individualised guidance on fluid resuscitation. Finally, a numerical score was developed based on the simplified NIRUDAK model that could be implemented without the need for a smartphone ( table 1 ).…”

Understanding variations in diarrhea management across healthcare facilities in Bangladesh: a formative qualitative study

“…A pre-written focus group agenda was used to obtain feedback from participants on the development of the NIRUDAK App, a new diarrhea management mHealth tool. Full details of the app’s development process are described elsewhere as the focus of the present study is not on the development of this particular app, but rather on variations in diarrhea management [ 27 , 34 ].…”