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Abstract Background HIV/AIDS continues to be a significant contributor to illness and death, particularly in sub-Saharan Africa. In this study, we conducted a qualitative assessment to understand Client and Healthcare Provider Perspectives on Differential Service Delivery Models in Uganda. The purpose was to establish strengths and weaknesses within the services delivery models, inform policy and decision-making, and to facilitate context specific solutions. Methods Between February and April 2023, a qualitative cross-sectional study was utilised to gather insights from a targeted selection of individuals, including People Living with HIV (PLHIV), healthcare workers, HIV focal persons, community retail pharmacists, and various stakeholders. The data collection process included eleven in-depth interviews, nine key informant interviews, and eight focus group discussions carried out across eight districts in Central Uganda. The collected data was analyzed through inductive thematic analysis with the aid of Excel. Results The various Differentiated Service Delivery Models (DSDMs), notably Community-Client-Led Drug Distribution (CCLAD), Community Drug Distribution Point (CDDP), Community Retail Pharmacy Drug Distribution Point (CRPDDP), and the facility-based Facility Based Individual Model (FBIM), were reported to have several positive impacts. These included improved treatment adherence, efficient management of antiretroviral (ARV) supplies, reduced exposure to infectious diseases, enhanced healthcare worker hospitality, minimized travel time for ART refills, stigma reduction, and decreased waiting times. Concern was raised about the lack of improvement in HIV status disclosure, opportunistic infection treatment, adherence to seasonal appointments, and sustainability due to the overreliance of the DSDMs on donor funding, suggesting potential discontinuation without funding. Doubts about health workers’ commitment surfaced. Notably, the CCLAD model displayed self-sustainability, with clients financially supporting group members to collect medicines. Conclusion Community-based DSDMs, such as CCLAD and CDDP, improve ART refill convenience, social support, and client experiences. These models reduce travel and waiting times, lowering infection risks. Addressing challenges and enhancing facility-based models is vital. In order to maintain funding after donor funding ends, sustainability measures like cross-subsidization can be used. If well implemented, the DSDMs have the potential to produce better or comparable ART outcomes compared to the FBIM model.

Abstract Background Continuous quality improvement processes in health care were developed for use at health facility level, and that is where they have been used the most, often addressing defined care processes. However, in different settings different factors have been important to support institutionalization. This study explores how continuous quality improvement processes were institutionalized at the district level and at the health facility level in Uganda. Methods This qualitative study was carried out in seven districts in Uganda. Semi-structured interviews with key informants from the district health management teams and document review were conducted. Thematic analysis was used to analyze the data. Results All districts that participated in the study formed Continuous Quality Improvement (CQI) teams both at the district level and at the health facilities. The district CQI teams comprised of members from different departments within the district health office. District level CQI teams were mandated to take the lead in addressing management gaps and follow up CQI activities at the health facility level. Acceptability of quality improvement processes by the district leadership was identified across districts as supporting the successful implementation of CQI. However, high turnover of staff at health facility level was also reported as a detrimental to the successful implementation of quality improvement processes. Also the district health management teams did not engage much in addressing their own roles using continuous quality improvement. Conclusion The leadership and management provided by the district health management team was an important factor for the use of Continuous Quality Improvement principles within the district. The key roles of the district health team revolved around the institutionalisation of CQI at different levels of the health system, monitoring results of continuous quality improvement implementation, mobilising resources and health care delivery hence promoting the culture of quality, direct implementation of CQI, and creating an enabling environment for the lower-level health facilities to engage in CQI. High turnover of staff at health facility level was also reported as one of the challenges to the successful implementation of continuous quality improvement. The DHT did not engage much in addressing gaps in their own roles using continuous quality improvement.

Abstract Background General hospitals provide a wide range of primary and secondary healthcare services. They accounted for 38% of government funding to health facilities, 8.8% of outpatient department visits and 28% of admissions in Uganda in the financial year 2016/17. We assessed the levels, trends and determinants of technical efficiency of general hospitals in Uganda from 2012/13 to 2016/17. Methods We undertook input-oriented data envelopment analysis to estimate technical efficiency of 78 general hospitals using data abstracted from the Annual Health Sector Performance Reports for 2012/13, 2014/15 and 2016/17. Trends in technical efficiency was analysed using Excel while determinants of technical efficiency were analysed using Tobit Regression Model in STATA 15.1. Results The average constant returns to scale, variable returns to scale and scale efficiency of general hospitals for 2016/17 were 49% (95% CI, 44–54%), 69% (95% CI, 65–74%) and 70% (95% CI, 65–75%) respectively. There was no statistically significant difference in the efficiency scores of public and private hospitals. Technical efficiency generally increased from 2012/13 to 2014/15, and dropped by 2016/17. Some hospitals were persistently efficient while others were inefficient over this period. Hospital size, geographical location, training status and average length of stay were statistically significant determinants of efficiency at 5% level of significance. Conclusion The 69% average variable returns to scale technical efficiency indicates that the hospitals could generate the same volume of outputs using 31% (3439) less staff and 31% (3539) less beds. Benchmarking performance of the efficient hospitals would help to guide performance improvement in the inefficient ones. There is need to incorporate hospital size, geographical location, training status and average length of stay in the resource allocation formula and adopt annual hospital efficiency assessments.