African Biodiversity Research (Environmental/Earth Science) | 20 April 2009
Operationalization and Patient Satisfaction Analysis of Mobile Health Clinics for Malaria Diagnosis in Rural Mozambique Over One Year
S, h, i, r, l, e, y, M, a, p, a, n, d, a, ,, F, r, a, n, c, i, s, C, h, i, p, a, m, b, a, ,, T, e, r, e, s, a, C, h, i, k, w, a, w, a, a, ,, N, e, l, s, o, n, C, a, n, g, o, m, a
Abstract
Mobile health clinics (MHCs) have been increasingly used in rural areas to provide timely access to healthcare services, particularly for malaria diagnosis and treatment. In Mozambique, rural populations often face significant barriers such as geographical isolation and limited infrastructure. A mixed-methods approach combining quantitative surveys with qualitative interviews was employed to gather data from participants who utilised the MHCs. Patient satisfaction scores were calculated based on Likert scale responses, while retention rates were determined through follow-up assessments after one year of initial service use. Patient satisfaction levels averaged at 85% with a significant majority (70%) indicating that the MHC services significantly improved their access to healthcare. A notable theme emerging from qualitative interviews was the convenience and accessibility offered by these clinics, especially for those living in remote areas. The operationalization of MHCs has been successful in enhancing malaria diagnosis and treatment availability in rural Mozambique, with high patient satisfaction levels observed over a one-year period. Future research could explore scalability and long-term sustainability of this model. Further studies should investigate the potential for scaling up these MHC services to other regions within Mozambique while considering additional factors such as health workforce training and community engagement strategies. Mobile Health Clinics, Malaria Diagnosis, Patient Satisfaction, Retention Rates, Rural Healthcare Treatment effect was estimated with $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.