Article

The Power of Predicting Extended PACU Stays

Length of stay is top of mind for almost every healthcare worker and administrator -- not only is it more expensive to care for patients in the hospital longer, research suggests that longer LOS leads to inferior patient outcomes. One area frequently challenged by length of stay is the post anesthesia care unit (PACU). Patients with extended PACU stays consume valuable resources and contribute to costly patient backlogs.

But what if healthcare providers could identify patients at increased risk for a longer PACU stay before scheduling those surgeries and staffing the recovery room? Researchers from the University of California at San Diego (UCSD) have developed a predictive model that would determine individuals at higher odds of a prolonged PACU stay,[1] advance knowledge that could optimize patient flow and recovery room staff assignments.

By analyzing a set of patient factors known prior to surgery, UCSD researchers identified five pre-operative predictors that would flag patients at risk for prolonged PACU length-of-stay: morbid obesity, hypertension, surgical specialty, primary anesthesia type, and scheduled case duration (time allotted for surgery).

To determine these predictors, researchers analyzed data from more than 4,000 patients that had undergone outpatient surgery in 2014 and 2015 at the University of California, San Diego (UCSD) Health system. Outpatient surgeries were defined as procedures allowing patients to be discharged directly home after adequate post-anesthesia monitoring. Only procedures requiring anesthesia were included in the retrospective study.

Researchers defined a prolonged PACU length of stay as one greater than or equal to the 75th percentile of the time spent in the PACU.

Researchers divided the cases into a training set (outpatient surgeries occurring before 2015) and a test group (procedures occurring in 2015). They then analyzed the following data for each outpatient surgery case: number of minutes in the PACU; sex; age (divided by less than, greater than or equal to 65 years of age); primary anesthesia type; body mass index (BMI) to identify morbidly obese patients; scheduled case duration (expected duration of operating room time); surgical category; non-English primary language; and the presence of any of thirteen common comorbidities including diabetes mellitus type 2, obstructive sleep apnea, coronary artery disease, chronic obstructive pulmonary disease, and a history of postoperative nausea and vomiting (PONV), among others.

The following list examines the rationale behind researchers’ five predictors of a prolonged PACU stay.:

  1. Morbid obesity: This population, at increased risk for sleep apnea, is at higher odds of postoperative airway obstruction, especially when opioids are utilized in anesthesia. Upper airway problems are a common PACU complication for which extended recovery room observation is advised.
  2. Hypertension: The presence of hypertension increased patients’ odds for extended PACU length of stay, most likely due to hemodynamic challenges faced in this population during recovery, researchers said.
  3. Surgical Specialty: Patients undergoing general or gynecological outpatient surgeries were more likely to require an extended PACU length of stay due to higher risks of postoperative nausea and vomiting (PONV). Conversely, subspecialty outpatient surgeries such as otolaryngology, gastroenterology and plastic surgery had decreased odds for extended PACU stays.
  4. Primary anesthesia type: The use of general anesthesia, which requires more anesthetic medication and usually longer postoperative periods of recovery than other anesthesia, was associated with extended PACU length of stay.
  5. Scheduled case duration: As determined by previous studies, longer scheduled case duration was associated with extended PACU length of stays. Researchers reason that longer anesthesia could be related to more complex surgeries and increased anesthetic utilization, thereby requiring additional recovery time.

Interestingly, while previous studies cited patient age as a factor in extended PACU stays, the UCSD study found that age alone did not necessarily predict prolonged recovery room time but rather the presence of associated age-related comorbidities. Effective patient monitoring across these five factors can enable a better prediction of extended PACU stay.

Researchers noted that during the complex, multi-step process of operating room management, there are many advantages to predicting cases at risk for prolonged recovery room length of stays. Administrators can leverage this knowledge to inform advance planning such as operating room allocation, case scheduling and staff assignments. The predictive model also can be valuable in optimizing day-of-surgery operations such as patient safety, operating room efficiency and patient wait times.

In general, minimizing the peak number of patients in the PACU can not only reduce the number of PACU admission delays through the day but also avoid costly end-of-day overutilization of nursing staff.

Researchers acknowledged several limitations to the predictive model, including difficult-to-anticipate factors such as transportation or providers’ availability for patient education or discharge orders. Additionally, other comorbidities not included in the UCSD predictive model may impact PACU length of stay. They emphasized that the goal of the predictive model is not to decrease PACU length of stay but rather identify patients with higher odds of an extended PACU stay prior to optimize case-sequencing and staffing.

Reference:

1. A Predictive Model for Extended Postanesthesia Care Unit Length of Stay in Outpatient Surgeries, Anesthesia & Analgesia, Accessed March 2019. https://journals.lww.com/anesthesia-analgesia/FullText/2017/05000/A_Predictive_Model_for_Extended_Postanesthesia.28.aspx