Most of the variation in length of stay in emergency general surgery is not related to clinical factors of patient care

J Trauma Acute Care Surg. 2019 Aug;87(2):408-412. doi: 10.1097/TA.0000000000002279.

Abstract

Background: Hospital length of stay (LOS) is currently recognized as a key quality indicator. We sought to investigate how much of the LOS variation in the high-risk group of patients undergoing Emergency general surgery could be explained by clinical versus nonclinical factors.

Methods: Using the 2007 to 2015 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, we included all patients who underwent an emergency appendectomy, cholecystectomy, colectomy, small intestine resection, enterolysis, or hernia repair. American College of Surgeons National Surgical Quality Improvement Program defines emergency surgery as one that is performed no later than 12 hours after admission or symptom onset. Using all the ACS-NSQIP demographic, preoperative (comorbidities, laboratory variables), intraoperative (e.g., duration of surgery, wound classification), and postoperative variables (i.e., complications), we created multivariable linear regression models to predict LOS. LOS was treated as a continuous variable, and the degree to which the models could explain the variation in LOS for each type of surgery was measured using the coefficient of determination (R).

Results: A total of 215,724 patients were included. The mean age was 47.1 years; 52.0% were female. In summary, the median LOS ranged between 1 day for appendectomies (n = 124, 426) and cholecystectomies (n = 21,699) and 8 days for colectomies (n = 19,557) and small intestine resections (n = 7,782). The R for all clinical factors ranged between 0.28 for cholecystectomy and 0.44 for hernia repair, suggesting that 56% to 72% of the LOS variation for each of the six procedures studied cannot be explained by the wide range of clinical factors included in ACS-NSQIP.

Conclusion: Most of the LOS variation is not explained by clinical factors and may be explained by nonclinical factors (e.g., logistical delays, insurance type). Further studies should evaluate these nonclinical factors to identify target areas for quality improvement.

Levels of evidence: Epidemiological study, level III.

MeSH terms

  • Emergencies
  • Female
  • Humans
  • Length of Stay / statistics & numerical data*
  • Male
  • Middle Aged
  • Quality Indicators, Health Care / statistics & numerical data
  • Surgical Procedures, Operative / statistics & numerical data*