The Development of a Post Anesthesia Care Unit Patient Quantitative Assessment/Predictive Tool to Manage Post-Operative Health Alterations

Abstract

Purpose: Post anesthesia care units (PACUs) play an important role in the provision of safe patient care. Patients that possess comorbidities may have exacerbated medical conditions when exposed to surgical intervention and anesthesia. Physiologic changes related to surgery alter a patient’s baseline physical state. Medical and nursing interventions are often needed to return patients to their pre-procedure health. American Society of Anesthesiologists (ASA) physical status classification may be a poor predictor of post-surgical complication. Nearly 20% of all PACU admissions require anesthesia intervention. Determining patient’s acuity and staffing PACU appropriately maybe challenging. Recovery room workload responsibilities are different from other hospital units. Patient census can vary widely based on time of day, types of surgeries and whether scheduled/emergent. Nurses may care for more than one patient at varying degrees of recovery. The aim of the study was to develop a simple and reliable scoring tool [Rapid System Review (RSR) score] for recovery room nurses, that can predict the number of nursing interventions a patient may require during their stay in PACU.

Methods: This prospective, non-randomized, observational pilot study was conducted in the Post Anesthesia Care Unit (PACU) at the Veterans Affairs Medical Center, Oklahoma City. The pilot clinical evaluation tool was evaluated during a 4-month pilot period. A total of 100 patients were enrolled in the data collection. All data were entered on a form, and completed forms were collected for data entry and analysis, using Microsoft Excel. Pearson Correlation Coefficient was completed to evaluate trend, and the two-tailed unpaired t test with p values to evaluate significance. Graph Pad Prism (Version 7) and Pearson Correlation was used to calculate statistics. Significance was defined as (p <0.05).

Results: The primary outcome was to predict the amount of interventions needed, to achieve a baseline health score for a patient admitted to the PACU, at the time of discharge. The secondary outcome was to evaluate if these patients achieved their baseline ideal score, or better at discharge. The Pearson Correlation Coefficient between the RSR high score, and actual interventions were 0.908 and p value was 0.000. The Pearson Correlation Coefficient between the ASA class and actual interventions was 0.273 and p value was 0.006. The mean patient ideal score was 9.57 ± 0.99752218, and the mean discharge score was 9.96 ± 0.695149. The two-tailed unpaired t test p-value was 0.0016 with a 95% confidence interval of difference. The RSR highest score (mean=5.3636 ± 3.14471576) and the RSR discharge score (mean=3.82716 ± 2.58742) were compared. The two-tailed unpaired t test p-value was 0.0002 with a 95% confidence interval of difference.

Conclusion: The pilot RSR tool had a strong positive relationship between the RSR scores, and the number of medical/nursing interventions. The RSR scoring system is more specific, and accurate, compared to the ASA physical status when determining PACU patient’s needs. Patients discharged from the PACU achieved their preoperative ideal score or better.

Keywords: Rapid System Review, RSR score, Post anesthesia care units, PACU, predictive tool, anesthesia