Evidence-Based Outcomes to Detect Obstructive Sleep Apnea, Identify Co-Existing Factors, and Compare Characteristics of Patients Discharge Disposition
Burkard, Joseph F.
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Session presented on Saturday, July 26, 2014: EVIDENCE BASED OUTCOMES TO DETECT OBSTRUCTIVE SLEEP APNEA, IDENTIFY CO-EXISTING FACTORS, AND COMPARE CHARACTERISTICS OF PATIENTS DISCHARGE DISPOSITION, Joseph F. Burkard, DNSc, CRNA, Associate Professor, University of San Diego. Introduction: According to the American Heart Association, fifteen million adults are affected by obstructive sleep apnea (OSA). Obstructive Sleep Apnea (OSA) is the most common disturbance during sleep affecting 30% of the population. The occurrence of moderate/severe OSA is estimated at 11.4% in men and 4.7% in women. This outcomes project included three completed bodies of work designed to evaluate the effects of implementing the STOP BANG tool in preoperative clinics to identify undiagnosed OSA surgery patients, examine the duration of recovery and the impact of co-factors and evaluate patient characteristics of discharged patients to home versus admitted to a monitored bed. Design and Methods: This outcomes project has three components which include the identification of OSA patients and was completed in the first phase with a experimental time design series with 1010 subjects. The second component was an observational correlation design to compare co-factors that impacted recovery stay times. The third component was a retrospective chart review of a total of 1300 patients to evaluate postoperative discharge characteristics. All three projects were IRB approved and included statistical data plans. Results: There was no difference in demographic data. Use of the STOP-BANG tool increased OSA detection by 30.1%. Males and higher ASA classification were correlated with OSA. p<0.001. The chance of identifying patients with OSA by using the STOP-BANG tool increased by 75% (p<0.001). The second project indicated significant correlation with higher number of cofactors amongst patients diagnosed with OSA (p< 0.012). Increased incidence of higher ASA classification in OSA diagnosed patients; (p< .017) extended PACU stay time in OSA diagnosed patients; (p= 0.05) and unplanned admissions in OSA patients; (p=. 007). In the third project four factors were found to be statistically significant, namely, age, ASA classification, the anesthesia modality (monitored anesthesia care vs. general anesthesia) and narcotics use. Discussion: Chung et al. clearly states that the incidence of sleep apnea is 25% for men and 10% for women. During this project, we were able to identify 37.6% of our surgical population who had sleep apnea. This was a 26.6% improvement over our prior clinical assessment. The use of the STOP-BANG tool is an easy addition to anesthesia pre-screening and increases patient safety. Complications associated with OSA can be severe and life threatening. These complications include: hypoventilation, hypoxia, airway obstruction, intubation difficulties, and a higher incidence of myocardial infarction. These complications can occur intra-operatively, post operatively and during the PACU stay period. There currently exists wide diversity in the postoperative management of the OSA patient. There is a consensus that the OSA population requires more stringent anesthesia management during induction but even more critical is the post operative period while the OSA patient is still under the effects of residual anesthesia agents and narcotics. This study goes further identifying the incidence and significance of co-existing factors (cofactors) that influence the PACU recovery time of OSA patients as compared with non-OSA patients. The current study examined certain characteristics of OSA patients correlated with their discharge disposition from the PACU and that certain patient risk factors contributed to adverse events during a patient's recovery period. The study evaluated the demographic characteristics, preoperative comorbidities, ASA class, diagnostic conditions, types of anaesthetic and surgical interventions, pain management, and postoperative complications that might influence a patient's length of stay in the PACU and their discharge disposition. The statistically significant risk factors were age, anaesthetic modalities (general vs. MAC), ASA classification and narcotics used in the PACU. These results are consistent with findings by other researchers studying perioperative risks of OSA patients. Time discharge, episodes of desaturation and the lowest saturation were risk factors associated with postoperative adverse events. Conclusions and Implications: Use of the STOP-BANG tool in anesthesia pre-screening will increase patient safety. Findings will lead to optimum monitoring, management; recovery measures and anesthesia techniques that will prevent extended postoperative periods and reduce or eliminate postoperative complications of OSA. This descriptive retrospective chart review of surgical patients with OSA in a defined six month period attempted to link an array of risk factors with a patient's discharged location and to learn about the characteristics of the patients at risk as measured by the lowest oxygenation, episodes of desaturation and length of stay.