title: Using hospital outcomes to predict 30-day mortality among injured patients insured by Medicare.
abstract: OBJECTIVE
  Survival until a fixed time after injury is a more useful outcome variable than survival until hospital discharge.
  
  
  METHODS
  We sought to determine whether 30-day survival could be accurately predicted by hospital discharge status.
  
  
  METHODS
  Academic research.
  
  
  METHODS
  We analyzed Medicare fee-for-service records for patients 65 years or older admitted with a principal diagnosis of injury (International Classification of Diseases, Ninth Revision, Clinical Modification codes 800-959, excluding 905-909, 930-939, and 958).
  
  
  METHODS
  Patients were classified by maximum Abbreviated Injury Score (range, 1-5) and Charlson comorbidity score (0, 1, 2, or ≥ 3). We modeled the conditional probability of survival at 30 days given hospitalization survival (P[S30SH]) as a function of census region, age, sex, maximum Abbreviated Injury Score, Charlson comorbidity score, length of stay, and discharge home or not.
  
  
  RESULTS
  A total of 436 104 patients met inclusion criteria, and a model was created using half the sample. For northeastern women aged 65 to 69 years with a maximum Abbreviated Injury Score of less than 3, Charlson comorbidity score of 0, and discharge home with length of stay less than 3 days, the model predicted P (S30SH) to be 0.998. The P (S30SH) was lower for other census regions, male sex, older age, more severe injury, and greater comorbidity. The equation had modest predictive ability when applied to individuals in the other half of the sample (area under the receiver operating characteristic curve, 0.75) and closely predicted P (S30SH) within numerous subpopulations.
  
  
  CONCLUSIONS
  For injured patients insured by Medicare, P (S30SH) can be estimated using administrative data known at the time of hospital discharge.
authors.affiliation: Department of Surgery, Maine Medical Center, 887 Congress St, Portland, ME 04102, USA.
authors.forename: Adam S
authors.initials: AS
authors.lastname: Gorra
authors.forename: David E
authors.initials: DE
authors.lastname: Clark
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Mullins
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D018588:Fee-for-Service Plans / Q000706:statistics & numerical data*; D005260:Female; D017052:Hospital Mortality / Q000639:trends; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data*; D011379:Prognosis; D015203:Reproducibility of Results; D012189:Retrospective Studies; D015996:Survival Rate / Q000639:trends; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000191:economics / Q000401:mortality*