Nakibuuka Joan, Semwanga Agnes R, Were Martin C
Institute of Biomedical Informatics, Moi University, Eldoret, Kenya.
College of Computing and Information Sciences,Makerere University, Uganda.
Stud Health Technol Inform. 2019 Jul 4;262:162-165. doi: 10.3233/SHTI190042.
Health decision-making is heavily premised on routinely reported data from lower levels of healthcare delivery to the national level. The reported data are of best use if their quality is high. Unfortunately, in many resource-limited settings in sub-Saharan Africa, the quality of reported data is often poor. Among the reasons attributed for poor data quality is use of sub-optimal modalities for collecting and transmitting data, such as paper-based and Short Message Service (SMS). Through a user-centered approach, we developed and implemented an Unstructured Supplementary Service Data (USSD)-based health data reporting intervention in a district in Uganda. The impact of the developed system on report accuracy, timeliness and completeness was evaluated against the expected 100% rates by the Ministry of Health (MoH). A total of 224 reports were submitted over the two-month study period. Of the submitted reports, 171 (76.3%) were complete (p<0.0001) compared to MoH's required 100%). 161 (71.9%) were accurate (P<0.0001), and 158 (70.5%) of the reports were submitted on time (p<0.0001). The deficiencies were largely attributed to a few facilities, as only 17.9% of facilities had data discrepancies with a mean of - 2.11 (P=0.38), 96.4% (0.130) of the facilities had complete reports and 87.4% (0.100) of the facilities reported on time. Poor network coverage was an outstanding challenge to reporting.
健康决策在很大程度上基于从基层医疗服务到国家层面的常规报告数据。如果报告数据质量高，其用途将得到最佳发挥。不幸的是，在撒哈拉以南非洲的许多资源有限地区，报告数据的质量往往很差。数据质量差的原因之一是使用了次优的数据收集和传输方式，如纸质和短信服务（SMS）。通过以用户为中心的方法，我们在乌干达的一个地区开发并实施了一项基于非结构化补充服务数据（USSD）的健康数据报告干预措施。根据卫生部预期的100%的比率，评估了所开发系统对报告准确性、及时性和完整性的影响。在为期两个月的研究期间，共提交了224份报告。在所提交的报告中，171份（76.3%）是完整的（p<0.0001），而卫生部要求的是100%。161份（71.9%）是准确的（P<0.0001），158份（70.5%）的报告按时提交（p<0.0001）。这些不足主要归因于少数设施，因为只有17.9%的设施存在数据差异，平均差异为-2.11（P=0.38），96.4%（0.130）的设施有完整报告，87.4%（0.100）的设施按时报告。网络覆盖差是报告面临的一个突出挑战。
