Botswana's integration of data quality assurance into standard operating procedures: Adaption of the routine data quality assessment tool
Wednesday, November 6, 2013
This session describes the collaborative process between MEASURE Evaluation and the Botswana Ministry of Health (MoH) for developing a national procedure for routine monitoring of data quality across program areas, as well as highlights resources required to support this process and describes lessons learned for future country adaptations. Information is a key building block of a health system, thus efforts to improve data quality directly support improvements in a country's health information system (HIS). The ability of health system stewards to make strategic decisions is impacted by the quality of health data. To support improved data quality throughout the health system, the Botswana MoH and MEASURE Evaluation developed standard operating procedures (SOPs) for data quality that included defining responsibilities for data quality at every level of the HIS, adapted a global Routine Data Quality Assessment (RDQA) tool to the Botswana context, and developed and implemented a training curriculum to support dissemination of the SOPs and RDQA tool. The protocols emphasize repeated assessment of data quality performance indicators as part of routine supervision and the ability to monitor those performance indicators over time and respond where needed. Results of regular system assessments and routine data verification exercises will be analyzed in the future to evaluate the impact of the SOPs and use of the RDQA process. With growing interest and investment in health system strengthening measures, the Botswana adaptation of global data quality tools operationalizes a system for HIS improvements that could be adopted by other countries facing data quality challenges.
Other professions or practice related to public health
Public health or related organizational policy, standards, or other guidelines
Identify dimensions of data quality that could be monitored on a routine basis.
Describe six key functional components of an M&E system needed to ensure data quality.
Formulate a plan to implement routine data quality assessments.
Describe how to formalize routine data quality assurance techniques into standard operating procedures.
Keyword(s): Quality Assurance, Health Information
Presenting author's disclosure statement:
Qualified on the content I am responsible for because: I have been a senior monitoring and evaluation advisor on federally funded HIV projects specializing in data management, particularly in the area of data quality. My focus has been on survey design and data analysis, data quality assurance, capacity building, and data demand and use.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.