1. Predictors of 30-Day Readmission in Gynecologic Oncology
Sahar Gowani; Shitanshu Uppal, MD
Background:
 The Centers for Medicare and Medicaid Services (CMS)
plans to include surgical procedures as it expands its
Readmission Penalty Program.
 The Readmission Penalty Program requires CMS to
reduce payments to hospitals with exceptionally high
readmission rates
 Hospital readmission is a persistent and costly
occurrence. A study of Medicare beneficiaries hospitalized
in 2009 reported a 30-day readmission rate of 12.7% for
surgical patients and 16.1% for medical patients and
unplanned hospital readmissions were estimated to cost
Medicare $17.4 billion in 2004.
Objectives:
 PRIMARY OBJECTIVE: Identify predictors of 30-day
readmission for patients undergoing surgery for
gynecologic malignancies
 SECONDARY OBJECTIVE: Establish a readmission
prediction scoring system with information available at the
time of discharge to categorize risk of readmission
Results:
 Overall readmission rate was 7.4% (339/4581 patients)
 Variables found to be significant for predicting
readmission at the time of discharge on logistic regression
modeling were
• Occurrence of at least one complication prior
to discharge
• Wide spread cancer
• Non-laparoscopic surgery
 Patients experiencing post-discharge complications were
20 times more likely to be readmitted
 Exploratory analysis of post-discharge complications
revealed 124 (36.5%) of patients readmitted had developed
infectious complications
• 32 (9.4%) were admitted with septic shock
• 25 (7.3%) had thromboembolic complications
Readmission Prediction Score (RPS)
Methods:
 Patients included in the National Surgical Quality
Improvement Program (NSQIP) for the years 2011 & 2012
with a final diagnosis of gynecologic malignancy were
identified.
 Exploratory analysis and logistic regression modeling
were performed on the patients included in 2012
 Readmission prediction score (RPS) was developed on
2012 file and validated on the 2011 file
Variable Score
Wide spread cancer 2
Non-laparoscopic surgery 2
Any one pre-discharge
complication
2
High complexity surgery
(Total relative value units >35)
1
Score Readmission
Risk
Example
0–1 <5% Woman who underwent a high complexity
surgery
2–3 5–7.5% Woman who underwent a non-laparoscopic
surgery
Woman who underwent a high complexity
surgery and had one pre-discharge complication
≥4 >15% Woman who underwent non-laparoscopic
surgery and has wide spread cancer
Validation on 2011 NSQIP patients
Low risk
Intermediate risk
High risk
1/5th of total patient identified as high risk by RPS had readmission rate of 14.5%
This population needs targeted efforts to reduce readmissions.
Conclusion:
 Our readmission prediction scoring system can identify
patients at a high risk of readmission (~15%)
 The high-risk categories identify patients who should be
targeted for prospective interventions that will prevent
readmissions
 Interventions by home health care and social workers as
well as early post-operative visits may decrease the overall
healthcare resource utilization by preventing re-
hospitalization