title: Ability of nurse clinicians to predict unplanned returns to hospital within thirty days of discharge.
abstract: OBJECTIVE
  To evaluate the ability of nurse clinician discharge flow coordinators (DFCs) to identify medical patients at risk of unplanned return to the hospital emergency department within 30 days of discharge and whether a higher predicted risk of return was correlated with preventability.
  
  
  METHODS
  Prospective cohort study of patients discharged from medical wards at 2 hospital sites of the McGill University Health Center between September 1, 2011, and January 1, 2012.
  
  
  METHODS
  Univariate and multivariate analyses of factors including the ability of DFCs to predict 30-day unplanned returns to the hospital. Assessment of the preventability of returns to the hospital was performed by chart review using prespecified criteria. The ability of DFCs to predict returns was compared to the LACE criteria (length of stay, acute admission through the emergency department, comorbidities, and emergency department visits in the past 6 months).
  
  
  RESULTS
  We found that 25.0% (95% CI, 21.3-28.5) of our patients returned to the emergency department within 30 days. The DFC predictions were found to be significant in both univariate and multivariate analysis. Patient age, sex, and length of stay were not significant predictors in univariate or multivariate analysis; 13.9% (95% CI, 8.2-19.6) of returns were preventable and a further 25.8% (95% CI, 18.1-33.5) were potentially preventable with added services in the community. There was a trend toward more preventable or potentially preventable returns with higher predicted probability of return. In contrast the LACE criteria did not have a good predictive capacity in our patient population.
  
  
  CONCLUSIONS
  In a large urban center, experienced nurse clinician DFCs were able to predict 30-day emergency department returns with reasonable accuracy. They were also able to identify the returns to the hospital that were most likely to be preventable. Our data suggests that DFCs can be used to target patients identified as having an increased probability of return with interventions that may be able to reduce the burden of return to hospital.
authors.affiliation: Department of Internal Medicine, McGill University Health Centre, Montreal, Quebec, Canada.
authors.forename: Romina
authors.initials: R
authors.lastname: Pace
authors.forename: Rachel
authors.initials: R
authors.lastname: Spevack
authors.forename: Claudia
authors.initials: C
authors.lastname: Menendez
authors.forename: Maria
authors.initials: M
authors.lastname: Kouriambalis
authors.forename: Laurence
authors.initials: L
authors.lastname: Green
authors.forename: Dev
authors.initials: D
authors.lastname: Jayaraman
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002170:Canada; D015897:Comorbidity; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D005260:Female; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009720:Nurse Clinicians; D010351:Patient Discharge / Q000706:statistics & numerical data*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011446:Prospective Studies; D012737:Sex Factors