Integrating family planning data in Uganda’s Health Management Information System
Wandera, Stephen Ojiambo
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Background: Uganda’s health management information system (HMIS) was established in 1985 to collect and analyze national data on morbidity from communicable and noncommunicable diseases, reproductive health, family planning (FP), and immunization (Kintu, et al., 2004). The routine health data reporting system has evolved to the current platform known as the district health information system, version 2 (DHIS 2), which began in 2011 in a few districts and was rolled out to all districts in Uganda in 2012 (Kiberu, et al., 2014). Few studies have explored the mechanisms for integrating FP data from the public and private health sectors in Uganda’s national HMIS. This study aimed to investigate the barriers, facilitators, and best practices of integrating these FP data in the district and national HMIS in Uganda. Methods: We conducted a qualitative study in Kampala, Jinja, and Hoima Districts. Primary data were collected from 16 key informant interviews (KIIs) and a multi-stakeholder dialogue (MSD) workshop comprised of 11 participants. The KIIs included three Ministry of Health (MOH) officers, three HMIS focal persons at nongovernmental organizations, four HMIS focal persons who were district biostatisticians or medical records officers, and six providers who were medical records officers at public and private health facilities. We conducted a systematic review of the HMIS in sub-Saharan African countries that are FP priorities for the United States Agency for International Development (USAID). The systematic literature review covered 2008–2016. Results: The technical facilitators for integrating FP data from public and private facilities in the national and district HMIS were user-friendly software; web-based and standardized reporting; government support for FP; availability of resources, including computers; and stakeholder engagement in HMIS design. Organizational facilitators were prioritizing FP data, training staff in HMIS, supportive supervision, and quarterly performance review meetings. Key behavioral facilitators were motivation and competence of HMIS staff. Collaborative networks with donor-funded implementing partners, such as the United Nations Population Fund and Marie Stopes Uganda, that can provide training, financial support, and technical assistance in designing HMIS forms are essential for improved performance and sustainability of the HMIS. Notable best practices of HMIS implementation in Uganda were an integrated reporting system, routine performance reviews, compliance enforcement, stakeholder engagement in designing HMIS forms, and review and collaboration by the MOH and implementing partners. The most substantial technical barriers were limited supply of computers at lower health facilities, complex HMIS forms, double entry of HMIS data, and web-reporting challenges. Organizational barriers were limited HMIS human resources, high levels of staff attrition in private facilities, limited training, poor culture of information, and stockouts of paper-based HMIS forms. Behavioral barriers were low motivation of healthcare providers to collect FP data, low use of FP data for planning purposes by district and health facility staff, and low motivation of staff to ensure data quality. Conclusion: Family planning data collection and reporting are integrated in Uganda’s district and national HMIS (DHIS 2). However, limited priority and attention is given to FP data collection at the facility and national levels. Data are not used by the health facilities that collect them. We recommend reviewing and strengthening HMIS data collection forms and FP commodities, ensuring forms are available at health facilities, and training all staff involved in HMIS data reporting so they can support their units and track FP data inclusion. It is important to encourage HMIS staff and health facility incharges to use FP data for decision making.