Global Health Informatics Research Overview

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In collaboration with our partners in Sub-Saharan Africa and the Dominican Republic, the Global Health Informatics Program has worked on Research, Innovation, Education, and Clinical Quality Improvement projects that support the implementation of digital health systems in LMICs. These projects were designed with a focus on patient health to directly improve healthcare amongst the local community. Below are examples of how the Program used technology to improve healthcare.

An interdisciplinary team comprised of CHOP Global Health and Clinical Informatics faculty designed, deployed, and evaluated a mobile tablet-based electronic data capture tool in the Dominican Republic at the CHOP-affiliated outpatient clinic, Niños Primeros en Salud. The team used digital data on the individual level for passive decision support and on the aggregate level for clinical outcome evaluations of bi-annual deworming campaigns in surrounding neighborhoods. They evaluated implementation success (feasibility, sustainability, usability) and data quality (accuracy, timeliness, completeness).

The team created a registry of the clinic’s 406 patients in the software database. Of the 246 patients eligible to receive deworming medications during the pilot campaign, 120 (48 percent) patients were documented as receiving the medication using the software. Compared to manual data entry, electronic data entry was more complete and accurate, with low rates of missed or wrong patient documentation; however, the team discovered software limitations that could jeopardize long-term success, including integration into the daily clinical workflow, the cost of the tool, and the scalability to meet more complex data needs. As a pilot, the electronic data capture tool was superior to paper data entry with regard to data completeness and accuracy. They identified barriers and facilitators to building capacity and deploying electronic data capture software in resource-limited settings.

Tuberculosis (TB) contact tracing is typically conducted in resource-limited settings with paper forms, but this approach may be limited by inefficiencies in data collection, storage, and retrieval and poor data quality. In Botswana, a CHOP study team developed, piloted, and evaluated a mobile health (mHealth) approach to TB contact tracing that replaced the paper form-based approach for a period of six months. For both approaches, the researchers compared the time required to complete TB contact tracing and the quality of data collected. For the mHealth approach, they also administered the Computer System Usability Questionnaire to two healthcare workers who used the new approach, and they identified and addressed operational considerations for implementation. Compared to the paper form-based approach, the mHealth approach reduced the median time required to complete TB contact tracing and improved data quality. The mHealth approach also had favorable overall rating, system usefulness, information quality, and interface quality scores on the Computer System Usability Questionnaire. Overall, the mHealth approach to TB contact tracing improved on the paper form-based approach used in Botswana. This new approach may similarly benefit TB contact tracing efforts in other resource-limited settings.

CHOP faculty and clinical informatics fellows, in collaboration with CHOP partner University of Botswana (UB), implemented a REDCap Instance on a Botswanan web server to make online survey and database management software accessible and secure for faculty trying to do health research and quality improvement.

The team held workshops heavily focused on sustainability and education in the eResearch unit of the university to teach REDCap to 21 trainees. They gave lectures at UB Teaching Hospital and UB Health Sciences building to a total of 50 participants, mostly faculty from computer science, health sciences, medical school students, and Information Science students. As of July 11, 2017, the UB REDCap instance had 64 unique users, 15 of whom were active on the platform since June 2017. Of 33 unique registered projects not for demonstration or learning purposes, 15 had at least 50 items, 14 had been edited or accessed in the past four weeks, and four were in production status. The REDCap server had only one downtime independent of the UB internet.

This project aims to use RAP and TAM-RLS models to assess the landscape of healthcare data processing and understand front-line workers’ perceptions of data sharing. Over 30 institutions are involved.