ArticlePloS one2016
Impact of Health System Inputs on Health Outcome: A Multilevel Longitudinal Analysis of Botswana National Antiretroviral Program (2002-2013).
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The role of individual and regional environment factors on levels of a cardiovascular risk predictor in middle-aged and older Chinese adults.Journal of global health · 2025Article
- Practice environment determinants of job satisfaction among midwives at healthcare facilities in Accra Metropolis: A multicentre study.PloS one · 2023Article
- Improving identification of symptomatic cancer at primary care clinics: A predictive modeling analysis in Botswana.International journal of cancer · 2022Article
- A Non-Linear Biostatistical Graphical Modeling of Preventive Actions and Healthcare Factors in Controlling COVID-19 Pandemic.International journal of environmental research and public health · 2021Article
- Healthcare system inputs and patient-reported outcomes: a study in adults with congenital heart defect from 15 countries.BMC health services research · 2020Observational
- Building Health System Capacity through Medical Education: A Targeted Needs Assessment to Guide Development of a Structured Internal Medicine Curriculum for Medical Interns in Botswana.Annals of global health · 2018Article
- Strengthening medical training programmes by focusing on professional transitions: a national bridging programme to prepare medical school graduates for their role as medical interns in Botswana.BMC medical education · 2017Article
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Authors and funding
14 authors.
Funding
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Abstract
objectiveTo measure the association between the number of doctors, nurses and hospital beds per 10,000 people and individual HIV-infected patient outcomes in Botswana.
designAnalysis of routinely collected longitudinal data from 97,627 patients who received ART through the Botswana National HIV/AIDS Treatment Program across all 24 health districts from 2002 to 2013. Doctors, nurses, and hospital bed density data at district-level were collected from various sources.
methodsA multilevel, longitudinal analysis method was used to analyze the data at both patient- and district-level simultaneously to measure the impact of the health system input at district-level on probability of death or loss-to-follow-up (LTFU) at the individual level. A marginal structural model was used to account for LTFU over time.
resultsIncreasing doctor density from one doctor to two doctors per 10,000 population decreased the predicted probability of death for each patient by 27%. Nurse density changes from 20 nurses to 25 nurses decreased the predicted probability of death by 28%. Nine percent decrease was noted in predicted mortality of an individual in the Masa program for every five hospital bed density increase.
conclusionConsiderable variation was observed in doctors, nurses, and hospital bed density across health districts. Predictive margins of mortality and LTFU were inversely correlated with doctor, nurse and hospital bed density. The doctor density had much greater impact than nurse or bed density on mortality or LTFU of individual patients. While long-term investment in training more healthcare professionals should be made, redistribution of available doctors and nurses can be a feasible solution in the short term.
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