ABSTRACT
BACKGROUND: As healthcare payment and reimbursement begin to shift from a fee-for-service to a value-based model, ancillary providers including laboratories must incorporate this into their business strategy. Laboratory medicine, while continuing to support a transactional business model, should expand efforts to include translational data analytics, proving its clinical and economic valuation. Current literature in this area is limited. CONTENT: This article is a summary of how laboratory medicine can support value-based healthcare. Population health management is emerging as a method to support value-based healthcare by aggregating patient information, providing data analysis, and contributing to clinical decision support. Key issues to consider with a laboratory-developed population health management model are discussed, including changing reimbursement models, the use of multidisciplinary committees, the role of specialists in data analytics and programming, and barriers to implementation. Examples of data considerations and value are given. SUMMARY: Laboratory medicine is able to provide meaningful clinical diagnostic insights for population health initiatives that result in improved short- and long-term patient outcomes and drive cost-effective care. Opportunities include data analysis with longitudinal laboratory data, identification of patient-specific targeted interventions, and development of clinical decision support tools. Laboratories will need to leverage the skills and knowledge of their multidisciplinary staff, along with their extensive patient data sets, through innovative analytics to meet these objectives.
