  Objectives: The fee-for-service approach to healthcare leads to the
management of a patient's conditions in an independent manner, inducing various
negative consequences. It is recognized that a bundled care approach to
healthcare-one that manages a collection of health conditions together-may
enable greater efficacy and cost savings. However, it is not always evident
which sets of conditions should be managed in a bundled program. Study Design:
Retrospective inference of clusters of health conditions from an electronic
medical record (EMR) system. A survey of healthcare experts to ascertain the
plausibility of the clusters for bundled care programs. Methods: We designed a
data-driven framework to infer clusters of health conditions via their shared
clinical workflows according to EMR utilization by healthcare employees. We
evaluated the framework with approximately 16,500 inpatient stays from a large
medical center. The plausibility of the clusters for bundled care was assessed
through a survey of a panel of healthcare experts using an analysis of variance
(ANOVA) under a 95% confidence interval. Results: The framework inferred four
condition clusters: 1) fetal abnormalities, 2) late pregnancies, 3) prostate
problems, and 4) chronic diseases (with congestive heart failure featuring
prominently). Each cluster was deemed plausible by the experts for bundled
care. Conclusions: The findings suggest that data from EMRs may provide a basis
for discovering new directions in bundled care. Still, translating such
findings into actual care management will require further refinement,
implementation, and evaluation.
