SBIR-STTR Award

Acute gastroenteritis (AGE)--infectious diarrhea—is a common condition that is costly in the US and high- mortality in developing nations. The cornerstone of AGE management is oral rehydration therapy (ORT), an evidence-based technique that has saved over 54 million lives in the 50 years since its introduction. The problem we aim to address is ORT’s underuse in developed countries—specifically in the home setting. If widely adopted, ORT could reduce 80% of AGE-related healthcare visits and costs among children, eliminating 1.3 million emergency department visits and $1.5 billion in hospital costs annually. The product of this Phase I proposal is a minimum viable product of a mobile health application (app)--ORCAH (Orally Rehydrate Children at Home)—that guides caregivers of dehydrated children through administering ORT in the home. ORCAH's innovation is in the use of the mobile device's native functions for analytics, database parameters, timers, notifications, and process state—for a novel aim: making ORT accessible in the home setting in developed countries. We hypothesize we will achieve an effectiveness (percentage of ORT tasks completed) of 80%. We will achieve our objective through 3 Aims: Aim 1. Use key informant interviews with card sort testing to explicitly understand subjects’ prioritization of ORT workflow tasks and how to deliver these in a user- centered design interface, and thereby develop the optimal information architecture of ORCAH. Aim 2. Perform cycles of iterative, user-centered design using a synchronous remote platform to optimize the app’s usability. Aim 3. Pilot test ORCAH in a simulation context to demonstrate the feasibility of conducting a trial of the app using synchronous online methods. Based on the impact of ORT in developing settings, the gap presented by the absence of an intervention for improving home ORT use in developing countries, and the match between the key advantages of mobile health apps and the ORT underuse problem, we expect that the ORCAH app will provide a usability-optimized, effective and efficient technology for supporting home ORT delivery that will ultimately allow users to avoid costly and inconvenient ED visits. Objectives for Phase II include trialing ORCAH’s efficacy compared to usual care and further developing ORCAH to include a cloud-based machine learning algorithm that will continuously optimize the parameters of ORT dosing for each user based on patient- generated data and will provide generalizable evidence about ORT dosing. The long-term goals are to further develop the machine-learning functionalities to update best practices for ORT, and to develop ORCAH for developing settings. The market for ORCAH—caregivers of children with AGE—represents a promising commercial potential, as about 57.9 million children in the US experience an AGE episode annually of at least 24 hours duration. Data2Care’s commercialization strategy includes direct business-to-consumer marketing, as well as co-marketing with business partners including after-hours advice centers, rehydration fluid companies and urgent care centers.

Public Health Relevance Statement:
Project Narrative Acute gastroenteritis—infectious diarrhea—is a high-mortality condition in developing nations, where a public health intervention called oral rehydration therapy (ORT) has saved over 54 million lives and is considered the cornerstone of management; however, ORT is underused in developed nations including the United States, resulting in an estimated excess of 1.3 million emergency department visits by children and $1.5 billion in hospital costs for children annually. Through developing a mobile health application—ORCAH (Orally Rehydrate Children at Home)—that guides caregivers of dehydrated children through giving ORT in the household setting, we expect that this application will enhance health and reduce illness in the short term by enabling users to avoid costly and inconvenient emergency department visits, and the associated costs. In the long term, through adding a cloud-based machine learning algorithm to ORCAH that will continuously optimize the parameters of ORT dosing for each user based on patient-generated data, we expect to generate generalizable evidence about ORT dosing parameters that will improve the science, delivery and efficacy of ORT.

Project Terms:
Accident and Emergency department; Acute; Address; Adopted; Architecture; Area; base; Businesses; Caregivers; Child; Childhood; Clinical; Clinical Research; cloud based; Collaborations; Colorado; commercial application; commercialization; comparative efficacy; cost; Critical Illness; Data; Databases; Developed Countries; Developing Countries; Diarrhea; Dose; Effectiveness; Emergency Department Physician; Emergency department visit; Emergency Situation; Enrollment; evidence base; experience; Fostering; Gastroenteritis; Goals; handheld mobile device; Health; Health Care Costs; Health Care Visit; Home environment; Hospital Costs; Hospitals; Hour; Household; improved; informant; innovation; Intervention; Interview; iterative design; IV Fluid; Knowledge; Liquid substance; Machine Learning; machine learning algorithm; Marketing; Medical; Methods; mHealth; mobile application; Mobile Health Application; model development; mortality; National Institute of Child Health and Human Development; Notification; novel; Oral; Oral Rehydration Therapy; Outcome; Patients; pediatric emergency; pediatric trauma; Phase; Process; programs; prototype; public health intervention; recruit; Rehydrations; Research; Research Personnel; Science; Scientist; simulation; Small Business Technology Transfer Research; software development; Software Engineering; Target Populations; Techniques; Technology; Testing; treatment as usual; United States; Universities; Update; urgent care; usability; user centered de