title: Informatics in action: lessons learned in comparative effectiveness research.
abstract: Comparative effectiveness research (CER) is meant to provide evidence about the relative risks and benefits of different treatment options. It is gaining visibility as a tool to address the evidence gaps that clinicians struggle with every day; however, CER is particularly challenging in oncology as there is great variability in how individuals respond to interventions, and a wide range of drugs and procedures are available. In order to overcome these obstacles and conduct reliable CER studies, it is critical to create a robust data infrastructure to support it.The Center for Medical Technology Policy held its first annual CER Summit in November 2010, with a particular focus on oncology. A number of critical informatics themes emerged including the need for consistent data standards, registry reform, tools to assist trial accrual, and data to integrate into value deliberations. Addressing the data issues highlighted in this report will provide a significant opportunity to improve the health of our medical system.
authors.affiliation: Duke Cancer Institute, Duke Cancer Care Research Program, Durham, NC, USA. bradford.hirsch@duke.edu
authors.forename: Bradford R
authors.initials: BR
authors.lastname: Hirsch
authors.forename: Robert B
authors.initials: RB
authors.lastname: Giffin
authors.forename: Laura C
authors.initials: LC
authors.lastname: Esmail
authors.forename: Sean R
authors.initials: SR
authors.lastname: Tunis
authors.forename: Amy P
authors.initials: AP
authors.lastname: Abernethy
authors.forename: Sharon B
authors.initials: SB
authors.lastname: Murphy
mesh_terms: D057186:Comparative Effectiveness Research; D003362:Cost-Benefit Analysis / Q000191:economics; D057286:Electronic Health Records; D006801:Humans; D008490:Medical Informatics / Q000639:trends*; D008495:Medical Oncology / Q000592:standards*; D016347:Medical Records Systems, Computerized / Q000592:standards; D012306:Risk; D016896:Treatment Outcome