You are here
Enhancing case ascertainment of Parkinson's disease using Medicare claims data in a population-based cohort: the Cardiovascular Health Study.
Thursday,2013-12-26 13:25 America/Los_Angeles — poolea2
| Title | Enhancing case ascertainment of Parkinson's disease using Medicare claims data in a population-based cohort: the Cardiovascular Health Study. |
| Publication Type | Journal Article |
| Year of Publication | 2014 |
| Authors | Ton, TGN, Biggs, MLou, Comer, D, Curtis, L, Hu, S-C, Thacker, EL, Nielsen, SSearles, Delaney, JA, Landsittel, D, Longstreth, WT, Checkoway, H, Jain, S |
| Journal | Pharmacoepidemiol Drug Saf |
| Volume | 23 |
| Issue | 2 |
| Pagination | 119-27 |
| Date Published | 2014 Feb |
| ISSN | 1099-1557 |
| Keywords | Aged, Aged, 80 and over, Algorithms, Antiparkinson Agents, Cohort Studies, Databases, Factual, Female, Hospitalization, Humans, Incidence, Logistic Models, Male, Medicare, Parkinson Disease, Prevalence, Prospective Studies, Smoking, Time Factors, United States |
| Abstract | <p><b>PURPOSE: </b>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.</p><p><b>METHODS: </b>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.</p><p><b>RESULTS: </b>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.</p><p><b>CONCLUSIONS: </b>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.</p> |
| DOI | 10.1002/pds.3552 |
| Alternate Journal | Pharmacoepidemiol Drug Saf |
| PubMed ID | 24357102 |
| PubMed Central ID | PMC3923620 |
| Grant List | U01 HL080295 / HL / NHLBI NIH HHS / United States HHSN268200800007C / HL / NHLBI NIH HHS / United States N01HC55222 / HL / NHLBI NIH HHS / United States N01HC85086 / HL / NHLBI NIH HHS / United States K23 NS070867 / NS / NINDS NIH HHS / United States HHSN268201200036C / HL / NHLBI NIH HHS / United States R01 HL080295 / HL / NHLBI NIH HHS / United States N01HC85082 / HL / NHLBI NIH HHS / United States N01HC85083 / HL / NHLBI NIH HHS / United States L30 NS052978 / NS / NINDS NIH HHS / United States HL080295 / HL / NHLBI NIH HHS / United States N01HC85079 / HL / NHLBI NIH HHS / United States R01 AG023629 / AG / NIA NIH HHS / United States N01HC85080 / HL / NHLBI NIH HHS / United States AG023629 / AG / NIA NIH HHS / United States R56 AG023629 / AG / NIA NIH HHS / United States N01HC85081 / HL / NHLBI NIH HHS / United States |