A scoring system to predict readmission of patients with acute pancreatitis to the hospital within thirty days of discharge.
OBJECTIVE
Reducing rapid readmission of patients after discharge could improve quality of treatment and reduce costs. Little is known about clinical predictors of early readmission for acute pancreatitis (AP). We developed a strategy to identify and stratify patients with AP at risk for readmission within 30 days of discharge.


METHODS
We derived and validated a model in a cohort of patients hospitalized with AP from June 2005-October 2009. Early readmission was defined as admission to the hospital or reevaluation in the emergency department within 30 days of discharge. The cohort was divided into a derivation cohort (admitted June 2005-December 2007, n = 248) and a validation cohort (admitted January 2008-October 2009, n = 198). A weighted scoring system was developed using logistic regression for the prediction of early readmission. Accuracy was assessed by area under the receiver-operator characteristic (ROC) curve analysis.


RESULTS
Of the total patients, 21% (92/446) had early readmission. Multivariable analysis identified the following discharge characteristics as independent risk factors for early readmission: gastrointestinal symptoms, eating less than a solid diet, pancreatic necrosis, treatment with antibiotics, and pain (P < .05). Weighted risk scores stratified patients into groups of low, moderate, and high risk for early readmission: 4%, 15%, and 87%, respectively, in the derivation cohort and 5%, 18%, and 68%, respectively, in the validation cohort. Area under the ROC curve demonstrated an accurate prediction (c-statistic = 0.83).


CONCLUSIONS
We created a scoring system that accurately predicts which patients with AP have high and low risk of readmission within 30 days of discharge.
Whitlock
Tom L
TL
Division of Gastroenterology, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA. Tom_Whitlock@post.harvard.edu
Tignor
April
A
Webster
Emily M
EM
Repas
Kathryn
K
Conwell
Darwin
D
Banks
Peter A
PA
Wu
Bechien U
BU
D000328:Adult; D000368:Aged; D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000627:therapeutic use; D015331:Cohort Studies; D003967:Diarrhea / Q000453:epidemiology; D004032:Diet; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008404:Massachusetts / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D009325:Nausea / Q000453:epidemiology; D009336:Necrosis; D010146:Pain / Q000453:epidemiology; D010179:Pancreas / Q000473:pathology; D010195:Pancreatitis / Q000453:epidemiology*; D010351:Patient Discharge; D010359:Patient Readmission; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D014839:Vomiting / Q000453:epidemiology
D000900:Anti-Bacterial Agents