Efficient Postoperative Disposition Selection in Pediatric Otolaryngology Patients: A Novel Approach

Laryngoscope. 2021 Jan:131 Suppl 1:S1-S10. doi: 10.1002/lary.28760. Epub 2020 May 21.

Abstract

Objective: Pediatric patients undergoing surgery on the aerodigestive tract require a wide range of postoperative airway support that may be difficult predict in the preoperative period. Inaccurate prediction of postoperative resource needs leads to care inefficiencies in the form of unanticipated intensive care unit (ICU) admissions, ICU bed request cancellations, and overutilization of ICU resources. At our hospital, inefficient utilization of pediatric intensive care unit (PICU) resources was negatively impacting safety, access, throughput, and finances. We hypothesized that actionable key drivers of inefficient ICU utilization at our hospital were operative scheduling errors and the lack of predictability of intermediate-risk patients and that improvement methodology could be used in iterative cycles to enhance efficiency of care. Through testing this hypothesis, we aimed to provide a framework for similar efforts at other hospitals.

Study design: Quality improvement initiative.

Methods: Plan, Do, Study, Act methodology (PDSA) was utilized to implement two cycles of change aimed at improving level-of-care efficiency at an academic pediatric hospital. In PDSA cycle 1, we aimed to address scheduling errors with surgical order placement restriction, creation of a standardized list of surgeries requiring PICU admission, and implementation of a hard stop for postoperative location in the electronic medical record surgical order. In the PDSA cycle 2, a new model of care, called the Grey Zone model, was designed and implemented where patients at intermediate risk of airway compromise were observed for 2-5 hours in the post-anesthesia care unit. After this observation period, patients were then transferred to the level of care dictated by their current status. Measures assessed in PDSA cycle 1 were unanticipated ICU admissions and ICU bed request cancellations. In addition to continued analysis of these measures, PDSA cycle 2 measures were ICU beds avoided, safety events, and secondary transfers from extended observation to ICU.

Results: In PDSA cycle 1, no significant decrease in unanticipated ICU admissions was observed; however, there was an increase in average monthly ICU bed cancellations from 36.1% to 45.6%. In PDSA cycle 2, average monthly unanticipated ICU admissions and cancelled ICU bed requests decreased from 1.3% to 0.42% and 45.6% to 33.8%, respectively. In patients observed in the Grey Zone, 229/245 (93.5%) were transferred to extended observation, avoiding admission to the ICU. Financial analysis demonstrated a charge differential to payers of $1.1 million over the study period with a charge differential opportunity to the hospital of $51,720 for each additional hospital transfer accepted due to increased PICU bed availability.

Conclusions: Implementation of the Grey Zone model of care improved efficiency of ICU resource utilization through reducing unanticipated ICU admissions and ICU bed cancellations while simultaneously avoiding overutilization of ICU resources for intermediate-risk patients. This was achieved without compromising safety of patient care, and was financially sound in both fee-for-service and value-based reimbursement models. While such a model may not be applicable in all healthcare settings, it may improve efficiency at other pediatric hospitals with high surgical volume and acuity.

Level of evidence: N/A Laryngoscope, 131:S1-S10, 2021.

Keywords: Healthcare efficiency; adenotonsillectomy; aerodigestive surgery; intensive care unit; pediatrics; quality and safety.

MeSH terms

  • Child
  • Health Care Rationing / economics
  • Health Care Rationing / methods*
  • Health Care Rationing / statistics & numerical data
  • Health Plan Implementation / organization & administration
  • Hospitals, Pediatric / economics
  • Hospitals, Pediatric / organization & administration*
  • Hospitals, Pediatric / statistics & numerical data
  • Humans
  • Intensive Care Units, Pediatric / economics
  • Intensive Care Units, Pediatric / organization & administration*
  • Intensive Care Units, Pediatric / statistics & numerical data
  • Otorhinolaryngologic Diseases / economics
  • Otorhinolaryngologic Diseases / surgery*
  • Otorhinolaryngologic Surgical Procedures*
  • Postoperative Care / economics*
  • Postoperative Care / statistics & numerical data
  • Program Evaluation
  • Quality Improvement