Abstract

BackgroundDemand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Uganda, the primary source of malaria surveillance data is the Health Management Information System (HMIS). However, HMIS data may be incomplete, inaccurate or delayed. Collaborative improvement (CI) is a quality improvement intervention developed in high-income countries, which has been advocated for low-resource settings. In Kayunga, Uganda, a pilot study of CI was conducted in five public health centres, documenting a positive effect on the quality of HMIS and malaria surveillance data. A qualitative evaluation was conducted concurrently to investigate the mechanisms of effect and unintended consequences of the intervention, aiming to inform future implementation of CI.MethodsThe study intervention targeted health workers, including brief in-service training, plus CI with ‘plan-do-study-act’ (PDSA) cycles emphasizing self-reflection and group action, periodic learning sessions, and coaching from a CI mentor. Health workers collected data on standard HMIS out-patient registers. The qualitative evaluation (July 2015 to September 2016) included ethnographic observations at each health centre (over 12–14 weeks), in-depth interviews with health workers and stakeholders (n = 20), and focus group discussions with health workers (n = 6).ResultsThe results suggest that the intervention did facilitate improvement in data quality, but through unexpected mechanisms. The CI intervention was implemented as planned, but the PDSA cycles were driven largely by the CI mentor, not the health workers. In this context, characterized by a rigid hierarchy within the health system of limited culture of self-reflection and inadequate training and supervision, CI became an effective form of high-quality training with frequent supervisory visits. Health workers appeared motivated to improve data collection habits by their loyalty to the CI mentor and the potential for economic benefits, rather than a desire for self-improvement.ConclusionsCI is a promising method of quality improvement and could have a positive impact on malaria surveillance data. However, successful scale-up of CI in similar settings may require deployment of highly skilled mentors. Further research, focusing on the effectiveness of ‘real world’ mentors using robust study designs, will be required to determine whether CI can be translated effectively and sustainably to low-resource settings.

Highlights

  • Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before

  • Collaborative improvement (CI) is a promising method of quality improvement and could have a positive impact on malaria surveillance data

  • CI is a promising approach to quality improvement, and could be applied to strengthen the quality of malaria surveillance data

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Summary

Introduction

Demand for high-quality surveillance data for malaria, and other diseases, is greater than ever before. In Kayunga, Uganda, a pilot study of CI was conducted in five public health centres, documenting a positive effect on the quality of HMIS and malaria surveillance data. In Uganda and elsewhere in Africa, data collected at health centres through the Health Management Information System (HMIS) form the backbone of malaria surveillance, and are vital for monitoring disease burden, assessing intervention coverage and impact, and guiding decision-making for programmes and policies. In Uganda, it has been estimated that less than 30% of malaria cases are captured in health facilities by HMIS [5] Such data may be inaccurate, incomplete or delayed, which limits the validity and utility of HMIS surveillance data [6] and may impact negatively on patient care. The US Government has become a major supporter of quality improvement initiatives for health care, including CI, funding multiple programmes in the health sector over the last decade [16]

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