title: Functional Status Outperforms Comorbidities in Predicting Acute Care Readmissions in Medically Complex Patients.
abstract: OBJECTIVE
  To examine functional status versus medical comorbidities as predictors of acute care readmissions in medically complex patients.
  
  
  METHODS
  Retrospective database study.
  
  
  METHODS
  U.S. inpatient rehabilitation facilities.
  
  
  METHODS
  Subjects included 120,957 patients in the Uniform Data System for Medical Rehabilitation admitted to inpatient rehabilitation facilities under the medically complex impairment group code between 2002 and 2011.
  
  
  METHODS
  A Basic Model based on gender and functional status was developed using logistic regression to predict the odds of 3-, 7-, and 30-day readmission from inpatient rehabilitation facilities to acute care hospitals. Functional status was measured by the FIM(®) motor score. The Basic Model was compared to six other predictive models-three Basic Plus Models that added a comorbidity measure to the Basic Model and three Gender-Comorbidity Models that included only gender and a comorbidity measure. The three comorbidity measures used were the Elixhauser index, Deyo-Charlson index, and Medicare comorbidity tier system. The c-statistic was the primary measure of model performance.
  
  
  METHODS
  We investigated 3-, 7-, and 30-day readmission to acute care hospitals from inpatient rehabilitation facilities.
  
  
  RESULTS
  Basic Model c-statistics predicting 3-, 7-, and 30-day readmissions were 0.69, 0.64, and 0.65, respectively. The best-performing Basic Plus Model (Basic+Elixhauser) c-statistics were only 0.02 better than the Basic Model, and the best-performing Gender-Comorbidity Model (Gender+Elixhauser) c-statistics were more than 0.07 worse than the Basic Model.
  
  
  CONCLUSIONS
  Readmission models based on functional status consistently outperform models based on medical comorbidities. There is opportunity to improve current national readmission risk models to more accurately predict readmissions by incorporating functional data.
authors.affiliation: Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA.|Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Shirley L
authors.initials: SL
authors.lastname: Shih
authors.affiliation: New England Rehabilitation Hospital of Portland, Portland, ME, USA.
authors.forename: Paul
authors.initials: P
authors.lastname: Gerrard
authors.affiliation: Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Richard
authors.initials: R
authors.lastname: Goldstein
authors.affiliation: Uniform Data System for Medical Rehabilitation, Amherst, NY, USA.
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Mix
authors.affiliation: Sumner Redstone Burn Center, Surgical Services, Massachusetts General Hospital, Boston, MA, USA.|Shriners Hospital for Children®-Boston, Boston, MA, USA.
authors.forename: Colleen M
authors.initials: CM
authors.lastname: Ryan
authors.affiliation: Uniform Data System for Medical Rehabilitation, Amherst, NY, USA.|Daemen College, Health Care Studies Department, Amherst, NY, USA.
authors.forename: Paulette
authors.initials: P
authors.lastname: Niewczyk
authors.affiliation: Department of Health Policy and Management, Boston University School of Public Health, Boston, MA, USA.
authors.forename: Lewis
authors.initials: L
authors.lastname: Kazis
authors.affiliation: Department of Internal Medicine, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Jaye
authors.initials: J
authors.lastname: Hefner
authors.affiliation: Department of Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.|Department of Medicine and Department of Health Care Policy, Harvard Medical School, Boston, MA, USA.
authors.forename: D Clay
authors.initials: DC
authors.lastname: Ackerly
authors.affiliation: Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA.|Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
authors.forename: Ross
authors.initials: R
authors.lastname: Zafonte
authors.affiliation: Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA. jcschneider@partners.org.|Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. jcschneider@partners.org.
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Schneider
mesh_terms: D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D004185:Disability Evaluation; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011379:Prognosis; D012047:Rehabilitation Centers; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D014481:United States
keywords: care transitions; functional status; outcomes; risk assessment; statistical modeling