title: Abstraction of core measure data:  creating a process for interrater reliability.
abstract: Health care facilities are challenged with an ever-increasing demand for producing accurate quality data to be used for guiding internal improvement initiatives as well as for reimbursement. It is essential that data abstraction be reliable and valid. In this article, we describe an interrater reliability process of data abstraction using the Centers for Medicare and Medicaid Services core measures that successfully reduced variability between abstractors and produced higher quality data.
authors.affiliation: Value Performance, Measurement and Patient Safety Department at Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA. holly.a.george@hitchcock.org
authors.forename: Holly A
authors.initials: HA
authors.lastname: George
authors.forename: Shelly L
authors.initials: SL
authors.lastname: Davis
authors.forename: Cynthia F
authors.initials: CF
authors.lastname: Mitchell
authors.forename: Naomi M
authors.initials: NM
authors.lastname: Moyer
authors.forename: Claire G
authors.initials: CG
authors.lastname: Toner
mesh_terms: D003625:Data Collection / Q000592:standards; D016208:Databases, Factual / Q000592:standards*; D006801:Humans; D008484:Medicaid / Q000458:organization & administration / Q000592:standards; D006278:Medicare / Q000458:organization & administration / Q000592:standards; D015588:Observer Variation; D010043:Outcome and Process Assessment, Health Care / Q000379:methods* / Q000592:standards* / Q000706:statistics & numerical data; D011787:Quality of Health Care / Q000458:organization & administration* / Q000592:standards*; D015203:Reproducibility of Results; D019035:Rural Health Services / Q000458:organization & administration / Q000592:standards / Q000706:statistics & numerical data; D014481:United States