Evaluation of Standard and Mobile Health–Supported Clinical Diagnostic Tools for Assessing Dehydration in Patients with Diarrhea in Rural Bangladesh

Abstract

Diarrhea remains a leading cause of morbidity and mortality in patients worldwide. The objective of this study was to determine the relative inter-rater reliability and usability of standard and Mobile health (mHealth)-supported World Health Organization (WHO) algorithms for dehydration assessment in patients with acute diarrhea in a rural, low-income country hospital. Two nurses blinded to each other's examinations assessed dehydration status on patients soon after hospital arrival using either the standard WHO algorithm printed on a laminated card or an mHealth-supported WHO algorithm downloaded onto a smartphone. The assignment of assessment tool was based on odd or even enrollment date. The inter-rater reliability for dehydration assessment between the two nurses was calculated using Cohen's K statistic for each study group. A total of 496 patients (< 5 years = 349,> 5 years = 147) were enrolled in the study; 132 (27%) had some or severe dehydration, and 364 (73%) had no dehydration on arrival. Cohen's K statistic demonstrated greater reliability for the mHealth-supported dehydration assessment (0.59) compared with the standard assessment (0.50) in the overall population ( < 0.0001), as well as in the pediatric (0.43 versus 0.37, < 0.0001) and adult (0.79 versus 0.57, < 0.0001) populations individually. This is the first study to show that mHealth can improve the reliability of nursing dehydration assessment in patients with acute diarrhea and the first to report on the reliability of the WHO algorithm in adult patients specifically. Future studies should focus on the impact of mHealth-supported dehydration assessment on patient-centered outcomes and examine its reliability in different settings worldwide.

The effects of mobile health on emergency care in low- and middle-income countries: A systematic review and narrative synthesis

“…Methodologically, 7 studies were randomized controlled trials (RCTs), 21 were observational cohorts with control groups, and 18 were observational pre/post studies. Of the four prespecified categories of mHealth interventions delineated in this systematic review, 8 studied data collection interventions [ 15 - 22 ], 9 studied decision support interventions [ 14 , 23 - 30 ], 15 studied direct patient care interventions [ 31 - 45 ], and 14 studied health training interventions [ 46 - 59 ]. Table 2 provides detailed study characteristics.…”

“…Mobile health applications for patient triage outperformed standard paper assessments in acutely ill children and adults. These studies found improved accuracy in the triage of general ED patients in Thailand, acutely dehydrated patients with diarrhea in Bangladesh, and in a multinational cohort of children <5 years of age as compared to the gold standard paper triage assessments [ 14 , 29 , 30 ]. Finally, a single study found somewhat limited utility of remote visual diagnostics in pediatric burn patients.…”

External Validation of a Mobile Clinical Decision Support System for Diarrhea Etiology Prediction in Children: A Multicenter Study in Bangladesh and Mali

“…Mobile CDSSs have been successfully used to improve hypertension control in India, and have been developed for neonatal care in Ghana, Kenya, and Uganda. [32][33][34][35][36][37] In Bangladesh, electronic CDSSs have also been shown to improve WHO diarrhea guideline adherence including reducing non-indicated antibiotic use by 28.5% in children under five. 14 While prior studies of CDSS targeting antibiotic use have focused on improving adherence to guidelines, our prediction tool provides the clinician with an estimation of etiology.…”

Usability of Rapid Cholera Detection Device (OmniVis) for Water Quality Workers in Bangladesh: Iterative Convergent Mixed Methods Study

“…While many rapid pathogen detection technologies have undergone validity analyses, there is a literature gap of usability analyses for such technologies [14][15][16][17][18]. Many usability studies instead evaluate technologies that aid interventions such as behavioral change, treatment adherence, or clinical decision making [23][24][25][26]. Thus, this study can serve as a model of iterative convergent mixed methods research design for device development to further promote usability analysis of rapid pathogen detection technologies and produce rapid detection devices that better fit into user workflows for increased uptake.…”

“…While the field of mHealth and rapid diagnostic testing for infectious disease is fast-growing, few rapid pathogen detection technologies have been developed for environmental surveillance [12,22]. Moreover, many mHealth usability studies have evaluated interventions such as behavioral change, medication adherence, or clinical decision-making technologies, but there is a literature gap for usability studies evaluating rapid pathogen detection technology [23][24][25][26]. By providing input in the device development process, end users can become cocreators and feel ownership in the device design, enabling greater uptake and integration into workflows.…”