Health system measurement: Harnessing machine learning to advance global health.
Journal:
PloS one
Published Date:
Oct 5, 2018
Abstract
BACKGROUND: Further improvements in population health in low- and middle-income countries demand high-quality care to address an increasingly complex burden of disease. Health facility surveys provide an important but costly source of information on readiness to provide care. To improve the efficiency of health system measurement, we applied unsupervised machine learning methods to assess the performance of the service readiness index (SRI) defined by the World Health Organization and compared it to empirically derived indices.