title: Understanding meaningful outcomes.
abstract: This commentary is meant to set the stage for further discussion about how the objective of a learning healthcare system can be advanced through better specifying requirements to support secondary data use. Recent federal initiatives seek to foster widespread health information technology adoption in the hopes of improving the efficiency and efficacy of our nation's health system. Development of a framework for codifying clinical outcomes would support those objectives primarily though making it easier to uncover associative patterns in patient care data. Put simply, the explicit classification of patient outcomes at the point of care seems to be a prerequisite to foster the most rapid exploration of achievable outcomes and their determinants. Considerations in such an endeavor include attributional validity, accounting for treatment appropriateness, incorporating patient perspectives, and evaluating the impacts of linkages to pay-for-performance programs.
authors.affiliation: Altarum Institute, Ann Arbor, MI 48105-1566, USA. dan.armijo@altarum.org
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Armijo
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Lammers
authors.forename: Dean G
authors.initials: DG
authors.lastname: Smith
mesh_terms: D057286:Electronic Health Records; D006801:Humans; D038801:International Classification of Diseases; D008490:Medical Informatics / Q000379:methods* / Q000592:standards; D010043:Outcome and Process Assessment, Health Care / Q000592:standards*; D017060:Patient Satisfaction; D019095:Point-of-Care Systems