Abstract

Globally, weak pharmaceutical information systems (PIS) negatively affect universal health coverage and outcomes. Few studies in sub-Saharan Africa qualitatively and quantitatively assess drivers and utility of data from PIS in public healthcare. A nationwide cross-sectional descriptive study interviewed PIS focal persons in all 14 regions of Namibia. The primary outcome was extent and predictors of utility of PIS data. The extent of utility of PIS data was determined using descriptive statistics and predictors by logistic regression in SPSSv24 or thematic analysis for qualitative data. The study recruited 58 key informants at facility-based 56 (96.6%) and national 2 (3.4%) levels. Of the 56 facility-based respondents, 29 (51.8%) were female and 27 (48.2%) pharmacists. The mean age and PIS work experience were 33.5±7.6years and 4.5±3.3years respectively. The utility level of PIS data was 34 (60.7%) (target >80%). A total of 103 uses of PIS data were cited; of which 38 (36.9%) were informing decisions on rational medicine use, 27 (26.2%) on pharmaceutical stock management and 24 (23.3%) on strengthening pharmacy workforce. The utility of PIS data significantly decreased with lack of systems on routine reporting by health facility in-charge (cOR=0.25, 95%CI: 0.06,0.90, p=0.035). Longer work experience (cOR=1.05, 95%CI: 0.88,1.25, p=0.58), formal consultations (cOR=1.29, 95%CI: 0.14,11.54, p=0.82), and availability of feedback systems (cOR=1.08, 95%CI: 0.33,3.56, p=0.89) appeared to increase utility of PIS data. Two thematic drivers of utility of PIS data were programmatic "feedback and action on PIS; structures,technical supportfor PIS discussion"; technical "training/technical capacity of staff; tools and resources for data collection and utilization"; and human-resource "staff availability and workload; attitude and commitment". The nationwide study shows sub-optimal utility of PIS data in public healthcare in Namibia, which negatively affects delivery of pharmaceutical services. This calls for action to enhance capabilities for utilization of automated real-time pharmaceutical information decision support systems to enhance real-time analysis and feedback on medicines data in resource-limited settings.

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