Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA, United States.
Riders 4 Health, Lilongwe, Malawi.
J Med Internet Res. 2021 Jul 6;23(7):e26582. doi: 10.2196/26582.
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 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 (eg, the quantity and location of samples prepared for collection) required for efficient operation.
This study aims to demonstrate the feasibility, adoption, and accuracy of a distributed data collection system that leverages 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.
We designed a system that leverages unstructured supplementary service data (USSD) technology to enable health workers to submit daily reports describing the quantity of transportation-ready diagnostic samples and test results at specific health care facilities, free of charge with any mobile phone, and aggregate these data for sample transportation 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, the participants submitted daily reports containing the number of patient samples or test results designated for viral load, early infant diagnosis, and tuberculosis testing at each facility. We monitored daily participation and compared the submitted USSD reports with program data to assess system feasibility, adoption, and accuracy.
The participating facilities submitted 37,771 reports over the duration of the field trial. Daily facility participation increased from an average of 50% (26/51) in the first 2 weeks of the trial to approximately 80% (41/51) by the midpoint of the trial and remained at or above 80% (41/51) 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.
Our findings suggest that a USSD-based system is a feasible, adoptable, and accurate solution to the challenges 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.
在许多中低收入国家，诊断工作是通过集中式实验室网络进行的。样本由远程护理点的患者采集，然后在集中式实验室进行检测。样本运输系统对于此类诊断网络中及时进行诊断和治疗至关重要。然而，这些系统通常缺乏及时和准确的数据（例如，准备采集的样本数量和位置），这对于高效运行是必要的。
本研究旨在展示一种利用基本手机技术收集马拉维诊断网络中患者样本数量和位置报告的分布式数据收集系统的可行性、采用情况和准确性。
我们设计了一种利用非结构化补充服务数据（USSD）技术的系统，使卫生工作者能够免费使用任何手机提交描述特定医疗保健设施准备好运输的诊断样本和检测结果数量的每日报告，并为样本运输管理员汇总这些数据。然后，我们在马拉维的 51 个卫生设施中进行了为期一年的现场试验，这些设施服务于 3 个地区。在 2019 年 7 月至 2020 年 7 月期间，参与者提交了每日报告，其中包含每个设施指定进行病毒载量、早期婴儿诊断和结核病检测的患者样本或检测结果的数量。我们监测了每日参与情况，并将提交的 USSD 报告与项目数据进行比较，以评估系统的可行性、采用情况和准确性。
在现场试验期间，参与设施共提交了 37771 份报告。设施每日参与率从试验开始的前两周的平均 50%（26/51）增加到试验中期的约 80%（41/51），并在试验结束时保持在 80%（41/51）或以上。平均而言，设施针对特定类型样本提交的报告中，超过 80%与从该设施收集的患者样本数量相匹配。
我们的研究结果表明，基于 USSD 的系统是解决诊断网络中数据不及时、不准确或不完整的可行、可采用且准确的解决方案。我们系统的某些设计特征，例如 USSD 的使用，以及实施特征，例如现场团队的支持作用，是确保高参与率和准确性而无需任何明确财务激励的必要条件。
