Ramsey M Dallal1, Alfred Trang. 1. Albert Einstein Healthcare Network, Philadelphia, PA 19141, USA. dallalr@einstein.edu
Abstract
BACKGROUND: Hospital lengths of stay (LOS) and readmission rates often are used by third parties to measure quality of outcomes despite only a few published series that analyze risk-adjusted data and predictors of these events. METHODS: Single-institution retrospective multivariable analysis of consecutive Roux-en-Y gastric bypass (RYGB) patients was performed to determine variables that may influence LOS and the readmission rate. RESULTS: Between 2006 and 2010, 1,065 consecutive RYGB procedures were analyzed. The mean initial body mass index (BMI) of the patients was 48.4 kg/m(2) (range 35-108 kg/m(2)), and their mean age was 42 years (range 15-75 years). Of these patients, 42% were black and 31% were either Medicare or Medicaid beneficiaries. The average LOS was 1.8 days (range 1-59 days; median, 2 days). The hospital discharged 48% of these patients on postoperative day (POD) 1, 85% on POD 2, and 96% on POD 3. According to multivariable Poisson regression, the independent predictors of a longer LOS included longer procedure time, surgeon, BMI, black race, older age, and status as a Medicare/Medicaid beneficiary (all P < 0.01). Gender and measured comorbidities were not associated with LOS. However, this model was poorly predictive of LOS due to substantial unexplained variance (R (2) = 0.10). Complications were significantly associated with Medicare/Medicare status (odds ratio [OR] 2.0), older age (OR 1.03), and longer procedure time (OR 1.02) (P < 0.05). According to logistic regression, a 30-day readmission rate was predicted only by a LOS longer than 3 days for the primary procedure (P < 0.0005). CONCLUSIONS: Early discharge on postoperative day 1 is possible but nonmodifiable, and random patient factors challenge predictable discharge planning. Reliable discharge on postoperative day 1 is not likely with current technologies.
BACKGROUND: Hospital lengths of stay (LOS) and readmission rates often are used by third parties to measure quality of outcomes despite only a few published series that analyze risk-adjusted data and predictors of these events. METHODS: Single-institution retrospective multivariable analysis of consecutive Roux-en-Y gastric bypass (RYGB) patients was performed to determine variables that may influence LOS and the readmission rate. RESULTS: Between 2006 and 2010, 1,065 consecutive RYGB procedures were analyzed. The mean initial body mass index (BMI) of the patients was 48.4 kg/m(2) (range 35-108 kg/m(2)), and their mean age was 42 years (range 15-75 years). Of these patients, 42% were black and 31% were either Medicare or Medicaid beneficiaries. The average LOS was 1.8 days (range 1-59 days; median, 2 days). The hospital discharged 48% of these patients on postoperative day (POD) 1, 85% on POD 2, and 96% on POD 3. According to multivariable Poisson regression, the independent predictors of a longer LOS included longer procedure time, surgeon, BMI, black race, older age, and status as a Medicare/Medicaid beneficiary (all P < 0.01). Gender and measured comorbidities were not associated with LOS. However, this model was poorly predictive of LOS due to substantial unexplained variance (R (2) = 0.10). Complications were significantly associated with Medicare/Medicare status (odds ratio [OR] 2.0), older age (OR 1.03), and longer procedure time (OR 1.02) (P < 0.05). According to logistic regression, a 30-day readmission rate was predicted only by a LOS longer than 3 days for the primary procedure (P < 0.0005). CONCLUSIONS: Early discharge on postoperative day 1 is possible but nonmodifiable, and random patient factors challenge predictable discharge planning. Reliable discharge on postoperative day 1 is not likely with current technologies.
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