title: Risk factors for hospitalization among community-dwelling primary care older patients: development and validation of a predictive model.
abstract: BACKGROUND
  Unplanned hospitalization often represents a costly and hazardous event for the older population.
  
  
  OBJECTIVE
  To develop and validate a predictive model for unplanned medical hospitalization from administrative data.
  
  
  METHODS
  Model development and validation.
  
  
  METHODS
  A total of 3919 patients aged > or =70 years who were followed for at least 1 year in primary care clinics of an academic medical center.
  
  
  METHODS
  Risk factor data and the primary outcome of unplanned medical hospitalization were obtained from administrative data.
  
  
  RESULTS
  Of 1932 patients in the development cohort, 299 (15%) were hospitalized during 1 year follow up. Five independent risk factors were identified in the preceding year: Deyo-Charlson comorbidity score > or =2 [adjusted relative risk (RR) = 1.8; 95% confidence interval (CI): 1.4-2.2], any prior hospitalization (RR = 1.8; 95% CI: 1.5-2.3), 6 or more primary care visits (RR = 1.6; 95% CI: 1.3-2.0), age > or =85 years (RR = 1.4; 95% CI: 1.1-1.7), and unmarried status (RR = 1.4; 95% CI: 1.1-1.7). A risk stratification system was created by adding 1 point for each factor present. Rates of hospitalization for the low- (0 factor), intermediate- (1-2 factors), and high-risk (> or =3 factors) groups were 5%, 15%, and 34% (P < 0.0001). The corresponding rates in the validation cohort, where 328/1987 (17%) were hospitalized, were 6%, 16%, and 36% (P < 0.0001).
  
  
  CONCLUSIONS
  A predictive model based on administrative data has been successfully validated for prediction of unplanned hospitalization. This model will identify patients at high risk for hospitalization who may be candidates for preventive interventions.
authors.affiliation: Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Sharon K
authors.initials: SK
authors.lastname: Inouye
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.forename: Richard N
authors.initials: RN
authors.lastname: Jones
authors.forename: Peilin
authors.initials: P
authors.lastname: Shi
authors.forename: L Adrienne
authors.initials: LA
authors.lastname: Cupples
authors.forename: Harold N
authors.initials: HN
authors.lastname: Calderon
authors.forename: Edward R
authors.initials: ER
authors.lastname: Marcantonio
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D004636:Emergency Service, Hospital; D005260:Female; D005544:Forecasting; D005853:Geriatrics; D006760:Hospitalization / Q000639:trends; D006801:Humans; D008297:Male; D008404:Massachusetts; D008962:Models, Theoretical; D011446:Prospective Studies; D012017:Referral and Consultation / Q000639:trends; D012307:Risk Factors