Predictors of correct treatment of children with fever seen at outpatient health facilities in the Central African Republic

Am J Epidemiol. 2000 May 15;151(10):1029-35. doi: 10.1093/oxfordjournals.aje.a010131.


To identify factors associated with improved performance of health care workers who treat ill children in developing countries, the authors analyzed a sample of consultations of children with malaria (defined as any fever) from a national health facility survey conducted in the Central African Republic from December 1995 to January 1996. Twenty-eight health care workers and 204 children were studied. A univariate analysis revealed the following significant predictors of correct treatment, as defined by the Central African malaria control program: high fever (odds ratio (OR) = 3.25, 95% confidence interval (CI): 1.47, 7.17); correct health care worker diagnosis (OR = 2.59, 95% CI: 1.39, 4.85); and the caregiver's reporting the child's fever to the health care worker (OR = 2.18, 95% CI: 1.32, 3.62). There was an unexpected inverse association between the presence of a fever treatment chart and correct treatment (OR = 0.19, 95% CI: 0.04, 0.91). Correct treatment was marginally associated with a longer consultation time (p value for trend = 0.058). Neither in-service training in the treatment of fever nor supervision was significantly associated with correct treatment. For child health programs to improve, targeted studies are needed to understand which factors, alone or in combination, improve health care worker performance.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Ambulatory Care / methods*
  • Analysis of Variance
  • Central African Republic
  • Child, Preschool
  • Cluster Analysis
  • Cross-Sectional Studies
  • Fever / parasitology*
  • Health Care Surveys
  • Humans
  • Infant
  • Inservice Training
  • Logistic Models
  • Malaria / complications
  • Malaria / diagnosis*
  • Malaria / drug therapy*
  • Predictive Value of Tests
  • Quality of Health Care*
  • Risk Factors
  • Time Factors