JMIR Publications

ABSTRACT

Background:

Diagnostics in many low- and middle-income countries are conducted through centralized laboratory networks. Samples are collected from patients at remote point-of-care health facilities and diagnostic tests are performed at centralized laboratories. Sample transportation (ST) systems that deliver diagnostic samples and test results are crucial for timely diagnosis and treatment in such diagnostic networks. However, they often lack the timely and accurate data (e.g., the quantity and location of samples prepared for collection) required for efficient operations.

Objective:

This study aimed to demonstrate the feasibility, acceptability, and effectiveness of a distributed data-collection system, leveraging basic mobile phone technology, to gather reports on the quantity and location of patient samples and test results prepared for delivery in the diagnostic network of Malawi.

Methods:

We designed a system which leverages Unstructured Supplementary Service Data (USSD) technology to (i) enable health workers to submit daily reports describing the quantity of transportation-ready diagnostic samples and test results at specific healthcare facilities, free of charge with any mobile phone, and (ii) aggregate this data for ST administrators. We then conducted a year-long field trial of this system in 51 health facilities serving 3 districts in Malawi. Between July 2019 and July 2020, participants submitted daily reports containing the number of patient samples or test results designated for viral load (VL), early infant diagnosis (EID), and tuberculosis (TB) testing at each facility. We used program data to monitor daily participation and data accuracy over the course of the field trial and administered a post-trial survey to assess system feasibility, acceptability, and effectiveness.

Results:

Participating facilities submitted 37,771 reports over the duration of the field trial. Daily facility participation increased from an average of 50% in the first two weeks of the trial to around 80% by the mid-point of the trial and remained at or above 80% until the conclusion of the trial. On average, more than 80% of the reports submitted by a facility for a specific type of sample matched the actual number of patient samples collected from that facility by a courier.

Conclusions:

Our findings suggest that a USSD-based system is a feasible, acceptable, and effective solution to the challenge of untimely, inaccurate, or incomplete data in diagnostic networks. Certain design characteristics of our system, such as the use of USSD, and implementation characteristics, such as the supportive role of the field team, were necessary to ensure high participation and accuracy rates without any explicit financial incentives.