J D Piette1, P G Barnett, R H Moos. 1. Center for Health Care Evaluation, Department of Veterans Affairs Palo Alto Health Care System, Menlo Park, California 94025, USA.
Abstract
OBJECTIVE: We estimated the rate of first-time hospital admission over 10 years with alcohol-related medical problems among a large national sample of patients with diagnosed alcohol abuse disorders. METHOD: We identified a nationwide cohort of all patients (N = 46,680) discharged in 1980 from all Department of Veterans Affairs (VA) medical centers with alcohol-related diagnoses. Two comparison cohorts also were identified: patients with musculoskeletal disorders (N = 18,231) and a random sample of nonalcoholic patients (N = 45,204). Using secondary databases, ICD-9-CM coded diagnostic information was collected for all VA inpatient admissions these patients experienced over the decade following their index hospitalizations. Admission rates within age strata and age/race standardized rates were computed. Adjusted rate ratios were estimated using Poisson regression. RESULTS: Alcoholic patients were at substantial risk of admission for multiple medical disorders. Admission rates varied for patients of different ages. Those who were between 50 and 59 years of age during their index hospital stay were at the highest risk of admission with an alcohol-related medical disease over the subsequent decade. CONCLUSIONS: The admission rates for these medical disorders among alcoholic patients provide an important baseline estimate of individual patients' risk profiles and may help providers set priorities among diagnostic tests.
OBJECTIVE: We estimated the rate of first-time hospital admission over 10 years with alcohol-related medical problems among a large national sample of patients with diagnosed alcohol abuse disorders. METHOD: We identified a nationwide cohort of all patients (N = 46,680) discharged in 1980 from all Department of Veterans Affairs (VA) medical centers with alcohol-related diagnoses. Two comparison cohorts also were identified: patients with musculoskeletal disorders (N = 18,231) and a random sample of nonalcoholic patients (N = 45,204). Using secondary databases, ICD-9-CM coded diagnostic information was collected for all VA inpatient admissions these patients experienced over the decade following their index hospitalizations. Admission rates within age strata and age/race standardized rates were computed. Adjusted rate ratios were estimated using Poisson regression. RESULTS:Alcoholicpatients were at substantial risk of admission for multiple medical disorders. Admission rates varied for patients of different ages. Those who were between 50 and 59 years of age during their index hospital stay were at the highest risk of admission with an alcohol-related medical disease over the subsequent decade. CONCLUSIONS: The admission rates for these medical disorders among alcoholicpatients provide an important baseline estimate of individual patients' risk profiles and may help providers set priorities among diagnostic tests.
Authors: Kathleen A McGinnis; Amy C Justice; Kevin L Kraemer; Richard Saitz; Kendall J Bryant; David A Fiellin Journal: Alcohol Clin Exp Res Date: 2012-10-10 Impact factor: 3.455
Authors: Amy C Justice; Rachel V Smith; Janet P Tate; Kathleen McGinnis; Ke Xu; William C Becker; Kuang-Yao Lee; Kevin Lynch; Ning Sun; John Concato; David A Fiellin; Hongyu Zhao; Joel Gelernter; Henry R Kranzler Journal: Addiction Date: 2018-08-01 Impact factor: 6.526
Authors: Henry R Kranzler; Hang Zhou; Rachel L Kember; Rachel Vickers Smith; Amy C Justice; Scott Damrauer; Philip S Tsao; Derek Klarin; Aris Baras; Jeffrey Reid; John Overton; Daniel J Rader; Zhongshan Cheng; Janet P Tate; William C Becker; John Concato; Ke Xu; Renato Polimanti; Hongyu Zhao; Joel Gelernter Journal: Nat Commun Date: 2019-04-02 Impact factor: 14.919
Authors: P V AshaRani; Mohamed Zakir Karuvetil; Tan Yeow Wee Brian; Pratika Satghare; Kumarasan Roystonn; Wang Peizhi; Laxman Cetty; Noor Azizah Zainuldin; Mythily Subramaniam Journal: Int J Ment Health Addict Date: 2022-01-23 Impact factor: 11.555