title: Using the past to predict the future: latent class analysis of patterns of health service use of older adults in the emergency department.
abstract: OBJECTIVE
  To classify older adults in the emergency department (ED) according to healthcare use and to examine associations between group membership and future ED visits and hospital admissions.
  
  
  METHODS
  Secondary analysis.
  
  
  METHODS
  Medicare Current Beneficiary Survey.
  
  
  METHODS
  Adults aged 65 and older with at least one treat-and-release ED visit between January 1, 2000, and September 30, 2007 (N = 4,964).
  
  
  METHODS
  Measures of health service use included primary care visits, treat-and-release ED visits, and hospital days in the 12 months preceding the index ED visit.
  
  
  RESULTS
  Five groups of individuals in the ED with distinct patterns of health service use were identified. "Primary Carederly" (39%) had low rates of ED and hospital use and a high mean number of primary care visits. "Wellderly" (34%) had fewer visits of all types than other groups. "Chronically Illderly" (14%) had the highest mean number of primary care visits and hospital days. "Acute Carederly" (9.8%) had lowest mean number of primary care visits but higher ED visits and hospital days than all other groups except the "Sickest Elderly." Sickest Elderly (3.2%) had the highest number of ED visits; mean number of hospital days was more than four times that of any other group. Primary Carederly and Wellderly had a lower risk of hospital admission within 30 days of the index ED visit than the other groups.
  
  
  CONCLUSIONS
  In older adults released from an ED, group membership was associated with future health services use. Classification of individuals using readily available previous visit data may improve targeting of interventions to improve outcomes.
authors.affiliation: Center for Health Services Research in Primary Care, Veterans Affairs Medical Center, Durham, North Carolina; Geriatrics Research, Education and Clinical Center, Veterans Affairs Medical Center, Durham, North Carolina; Ambulatory Care Service, Veterans Affairs Medical Center, Durham, North Carolina; Division of Geriatrics, Department of Medicine, Duke University, Durham, North Carolina; Center for the Study of Aging and Human Development, Duke University, Duke University School of Medicine, Durham, North Carolina.
authors.forename: S Nicole
authors.initials: SN
authors.lastname: Hastings
authors.forename: Heather E
authors.initials: HE
authors.lastname: Whitson
authors.forename: Richard
authors.initials: R
authors.lastname: Sloane
authors.forename: Lawrence R
authors.initials: LR
authors.lastname: Landerman
authors.forename: Carolyn
authors.initials: C
authors.lastname: Horney
authors.forename: Kimberly S
authors.initials: KS
authors.lastname: Johnson
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016208:Databases, Factual; D004636:Emergency Service, Hospital / Q000191:economics / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D006278:Medicare / Q000706:statistics & numerical data; D017063:Outcome Assessment, Health Care; D012189:Retrospective Studies; D013997:Time Factors; D014481:United States
keywords: emergency department; latent class analysis; older adults