Health system measurement: Harnessing machine learning to advance global health.

A facility readiness measure developed by global health experts performed poorly in capturing the totality of readiness information collected during facility surveys. Using a machine learning approach with sequential selection and cross-validation to identify the most informative items dramatically improved performance. Such approaches can make assessment of health facility readiness more efficient. Further improvements in measurement will require identification of external criteria-such as patient outcomes-to guide and validate measure development.