title: Enhancing case ascertainment of Parkinson's disease using Medicare claims data in a population-based cohort: the Cardiovascular Health Study.
abstract: OBJECTIVE
  We sought to improve a previous algorithm to ascertain Parkinson's disease (PD) in the Cardiovascular Health Study by incorporating additional data from Medicare outpatient claims. We compared our results to the previous algorithm in terms of baseline prevalence and incidence of PD, as well as associations with baseline smoking characteristics.
  
  
  METHODS
  Our original case ascertainment used self-reported diagnosis, antiparkinsonian medication, and hospitalization discharge International Classification of Diseases-Ninth version code. In this study, we incorporated additional data from fee-for-service Medicare claims, extended follow-up time, review of hospitalization records, and adjudicated cause of death. Two movement disorders specialists adjudicated final PD status. We used logistic regression models and controlled for age, sex, African American race, and education.
  
  
  RESULTS
  We identified 75 additional cases but reclassified 80 previously identified cases as not having PD. We observed significant inverse association with smoking status (odds ratio = 0.42; 95% confidence interval (CI) = 0.22, 0.79), and inverse linear trends with pack-years (p = 0.005), and cigarettes per day (p = 0.019) with incident PD. All estimates were stronger than those from the previous algorithm.
  
  
  CONCLUSIONS
  Our enhanced method did not alter prevalence and incidence estimates compared with our previous algorithm. However, our enhanced method provided stronger estimates of association, potentially due to reduced level of disease misclassification.
authors.affiliation: Department of Neurology, School of Medicine, University of Washington, Seattle, WA, USA.
authors.forename: Thanh G N
authors.initials: TG
authors.lastname: Ton
authors.forename: Mary Lou
authors.initials: ML
authors.lastname: Biggs
authors.forename: Diane
authors.initials: D
authors.lastname: Comer
authors.forename: Lesley
authors.initials: L
authors.lastname: Curtis
authors.forename: Shu-Ching
authors.initials: SC
authors.lastname: Hu
authors.forename: Evan L
authors.initials: EL
authors.lastname: Thacker
authors.forename: Susan
authors.initials: S
authors.lastname: Searles Nielsen
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Delaney
authors.forename: Douglas
authors.initials: D
authors.lastname: Landsittel
authors.forename: William T
authors.initials: WT
authors.lastname: Longstreth
authors.forename: Harvey
authors.initials: H
authors.lastname: Checkoway
authors.forename: Samay
authors.initials: S
authors.lastname: Jain
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000978:Antiparkinson Agents / Q000627:therapeutic use*; D015331:Cohort Studies; D016208:Databases, Factual / Q000706:statistics & numerical data; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D006278:Medicare; D010300:Parkinson Disease / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology*; D015995:Prevalence; D011446:Prospective Studies; D012907:Smoking / Q000453:epidemiology*; D013997:Time Factors; D014481:United States / Q000453:epidemiology
chemical_list: D000978:Antiparkinson Agents
keywords: ICD-9; Parkinson's disease; cardiovascular disease; cardiovascular health study; epidemiology; medical records; pharmacoepidemiology