Effect of monitoring and evaluation data management and use on Direct Health Facility Financing implementation effectiveness in urban and rural Tanzania: translating stakeholder perceptions of the DHFF M&E framework

Background Tanzanias Direct Health Facility Financing (DHFF) reform was introduced to strengthen primary health care through decentralized financing, autonomy, and accountability, but persistent weaknesses in monitoring and evaluation (M&E) data management and use continue to constrain implementation effectiveness, particularly in rural settings. Methods A convergent mixed-methods design was used to examine how M&E data management and use influence DHFF implementation effectiveness in an urban council (Kinondoni Municipal Council, KMC) and a rural council (Morogoro District Council, MDC), while also assessing the role of stakeholder perceptions of the DHFF M&E framework and contextual variation. Quantitative data were analyzed using descriptive statistics, relative importance indices, regression and ANOVA, while qualitative data from key informant interviews and focus group discussions were thematically analyzed and triangulated with quantitative results. Results Of 233 respondents analysed, 51.1% were from Morogoro District Council, 48.9% from Kinondoni Municipal Council, 51.2% worked in rural settings, 42.9% were from health centres, and 38.2% from dispensaries, providing an analytically useful spread across managerial and frontline contexts relevant to DHFF implementation. Descriptive statistics showed generally favourable perceptions across the five major constructs, with mean scores ranging from 3.09 for M&E capacity to 3.73 for urban-rural M&E practice context, while DHFF implementation effectiveness scored 3.71 overall. Data quality checks showed acceptable factor loadings above 0.4, reliability coefficients above 0.7, bivariate correlations of 0.34-0.76, and VIF values of 1.31-2.95, indicating that the dataset was screened, cleaned and analytically fit for regression and ANOVA modelling. In the aggregated model, the explanatory variables jointly accounted for about 52% of the variation in DHFF implementation effectiveness, with M&E data management and use, stakeholder perceptions of the DHFF M&E framework, and urban-rural context emerging as the most influential predictors. Qualitative testimonies clarified these patterns: one council respondent explained, "We have DHIS2... GoTHOMIS... FFARS... also PlanRep," while another facility respondent observed, "We only add up numbers for the monthly report--we dont really analyze what they mean," illustrating the contrast between data availability and meaningful local use. Conclusions DHFF implementation effectiveness in Tanzania depends substantially on robust M&E data management and use, supportive stakeholder perceptions of the M&E framework, and context-sensitive strategies that address persistent urban-rural inequities. Strengthening technical capacity, digital infrastructure, participatory governance and feedback systems is essential for sustaining DHFF gains and improving equitable service delivery.