Improved Compliance With Anesthesia Quality Measures After Implementation of Automated Monthly Feedback

Abstract

PURPOSE: Minimization of postoperative complications is important in patients with cancer. We wished to improve compliance with anesthesiology quality measures through staff education reinforced with automated monthly feedback. METHODS: The anesthesiology department implemented a program to capture and report quality metrics. After staff education, monthly e-mail reports were sent to each anesthesiology physician and nurse anesthetist to detail individual compliance rates for a set of quality measures. For each measure, the proportion of patient cases that passed the measure before and after implementation of the program was compared using a two-sample proportion test. RESULTS: After exclusions, we analyzed 15 of 23 quality measures. Of the 15 measures, 11 were process measures, and four were outcome measures. Of the 11 process measures, seven demonstrated statistically significant improvements ( P < .01). The most improved measure was TEMP-02 (core temperature measurement), which increased from 69.6% to 85.7% (16.1% difference; P < .001). Also improved were PUL-02 (low tidal volume, less than 8 mL/kg ideal body weight; 15.4% difference; P < .001) and NMB-01 (train of four taken; 12.2% difference; P < .001). The outcome measure TEMP-03 (perioperative temperature management) had a statistically significant increase of a small magnitude (0.2% difference; P < .001). No other outcome measures showed statistically significant improvement. CONCLUSION: After implementation of a comprehensive quality improvement program, our group observed significant improvements in anesthesia quality measure compliance for several process measures. Future work is needed to determine if this initial success can be preserved and associated with improved outcomes.

Making Sense of Big Data to Improve Perioperative Care: Learning Health Systems and the Multicenter Perioperative Outcomes Group

“…To improve stewardship of big data, considerations first must be given to the multiple levels of large-scale perioperative EHR data available, each serving unique functions. In its most granular form, perioperative EHR data are available at the individual case level, providing clinicians with personalized feedback on cases performed 5 and supplying local quality improvement programs with objective data for individual provider performance review and peer-to-peer comparisons. These data also can be used for quality improvement initiatives, such as development of real-time clinical decision support 4 and opportunities for obtaining Maintenance of Certification in Anesthesiology Part 4 credits.…”

Institution of Monthly Anesthesia Quality Reports Does Not Reduce Postoperative Complications despite Improved Metric Compliance

“…In our prior work we showed that the implementation of a quality improvement plan centered around a monthly quality report card was associated with improvement in several process metrics, but no improvement in outcome metrics. [8] In this study we looked at the effects of this program on postoperative complications in an inpatient cohort. We found no change in overall complication rate but did find a decrease in wound infection rate.…”

“…[7] In a previous article our group demonstrated that quality metric performance improved with the institution of this quality program. [8] In this study we hypothesize that improved compliance with process-oriented quality metrics translates into improved patient care by a reduction in the rate of any complication in the post-operative period.…”

Geospatial analysis of patients’ social determinants of health for health systems science and disparity research

“…MPOG does contain demographic data, including patient race/ethnicity, insurance status, but generally SDOH in MPOG are sparse and mostly at the level of the individual patient, not the community or built environment the patient originates from, or is exposed to. The MPOG has a well-established quality improvement arm called ASPIRE 55,56. ASPIRE could be leveraged also to address perioperative process equity.…”