Factors Affecting Data Quality and Reporting Rates for Real-Time ARV Stock Status (RASS) in the West Acholi Sub-Region, Uganda: A Mixed Methods Cross-Sectional Study.

Ignatius Ankwatsa, Herbert Bush Aguma, Fredrick Atwiine, Rajab Kalidi
Author Information
  1. Ignatius Ankwatsa: Department of Pharmacy, Makerere University, College of Health Sciences, Kampala, Uganda. ORCID
  2. Herbert Bush Aguma: Department of Pharmacy, Makerere University, College of Health Sciences, Kampala, Uganda.
  3. Fredrick Atwiine: Department of Pharmacy, Mbarara University of Science and Technology, Mbarara, Uganda. ORCID
  4. Rajab Kalidi: Department of Pharmacy, Makerere University, College of Health Sciences, Kampala, Uganda.

Abstract

Background: "The World Health Organization aims for universal HIV control by 2030, requiring robust healthcare infrastructure and efficient supply chain management". In Uganda, a functional real-time ARV Stock Status (RASS) monitoring system and dashboard was developed to provide real-time intelligent data and reliable and accurate information on antiretroviral drugs and other HIV commodities. This integrates data from different information systems for timely decision-making and supports evidence-based ARV commodities supply chain management solutions. This study aimed to identify the factors influencing the quality and reporting rate for Real-Time ARV Stock Status (RASS) weekly reporting in public health facilities in the West Acholi sub-region of Uganda.
Methods: A mixed-methods cross-sectional study was conducted in six public health facilities of the West Acholi sub-region. Quantitative data involved a review of 312 reports for the reporting rate. The available 180 RASS reports were reviewed for data quality; supplemental qualitative data was gathered through key informant interviews with 11 healthcare workers and stakeholders. Quantitative data was then cleaned using EPI data, and all the variables were coded and analyzed using SPSS version 21. The tables were then computed using the analyzed data from the software, and the pie charts were constructed using the Excel 2019 version. Thematic analysis was done for the key informant qualitative interviews.
Results: Analysis of RASS reports revealed a mixed level of quality, with only 40 reports (22%) categorized as good quality. The overall reporting rate was slightly more than half, with only 180 reports (57.7%) of the expected reports. Key factors influencing data quality were infrastructural limitations, such as unreliable internet, lack of proper equipment, and staff transfers. Lack of training on RASS and limited leadership support were documented to influence the data quality and RASS reporting rate.
Conclusion: The quality of RASS reports could have been better than the national set targets. The reporting rate was slightly above average but far below the national set targets. Several factors affecting both the reporting rate and quality of reports were cited. These include staff attitude, knowledge gap, Staff transfers, poor internet connectivity, and lack of internet data bundles.

Keywords

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