Improving Anesthesia Start Time Documentation Through a Departmental Education Initiative at Yale New Haven Hospital, New Haven, United States

Background Reimbursement for anesthetic services in the United States utilizes a formula that incorporates procedural and patient factors with total anesthesia time. According to the Centers for Medicare & Medicaid Services and the American Society of Anesthesiologists, the period of billable time starts when the anesthesia practitioner assumes care of the patient and may include transport to the operating room from the preoperative holding area. In this report on a quality improvement effort, we implemented a departmental education initiative aimed at improving the accuracy of anesthesia start-time documentation. Methods Utilizing de-identified, internal data on surgical procedures at Yale New Haven Hospital (YNHH), New Haven, United States, the difference between documented anesthesia start and patient in-room time was determined for all cases. Those with a difference between 0-1 minute were assumed "likely underbilled," and the total revenue lost for these cases was estimated using a weighted average of institutional reimbursement per unit of time. A monthly, department-wide educational email was then introduced to inform practitioners about the guidelines around start-time documentation, and the percentage of "likely underbilled" cases and lost revenue estimates trended over a one-year period. Results Baseline data in December 2020 showed that of the 6,877 total surgical cases requiring anesthesia at YNHH, 55.1% (N=3,790) had an anesthesia start to in-room time of 0-1 minute, which were considered "likely underbilled." The average start-to-in-room time for properly recorded cases (44.9%, N=3,087) was 4.42 minutes. The baseline revenue lost in December 2020 for underbilled cases was estimated at $52,302. Over the one-year quality improvement initiative, the proportion of underbilled cases showed a downward trend, decreasing to 29.2% of total cases by November 2021. The estimate of revenue lost due to underbilling also showed a downward trend, decreasing to $29,300 in November 2021. Conclusion This quality improvement study demonstrated that a relatively simple, department-wide educational email sent monthly correlated with an improvement in anesthesia start-time documentation accuracy and a reduction in estimated revenue lost to underbilling over a one-year period.

Quality indicators and outcomes in ambulatory surgery

PURPOSE OF REVIEW

Quality indicators are used to monitor the quality and safety of care in ambulatory surgery, a specialty in which major morbidity and mortality remain low. As the demand for safe and cost-effective ambulatory surgical care continues to increase, quality indicators and metrics are becoming critical tools used to provide optimal care for these patients.

RECENT FINDINGS

Quality indicators are tools used by both regulatory agencies and surgical centers to improve safety and quality of ambulatory surgical and anesthetic care. These metrics are also being used to develop value-based payment models that focus on efficient, safe, and effective patient care. Patient reported outcome measures are a growing method of collecting data on the satisfaction and postoperative recovery period for ambulatory surgical patients. Monitoring of perioperative efficiency and utilization using quality metrics are important to the financial health of ambulatory surgical centers.

SUMMARY

Quality indicators will continue to play a growing role in the monitoring of quality and safety in ambulatory surgery, especially with the trend towards value-based reimbursement models and efficient, cost-effective surgical care. Additionally, quality indicators are useful tools to monitor postoperative patient outcomes and recovery pathways and the efficiency of operating room utilization and scheduling.

A Preoperative Cognitive Screening Test Predicts Increased Length of Stay in a Frail Population: A Retrospective Case-Control Study

BACKGROUND

Frailty is associated with adverse perioperative outcomes including major morbidity, mortality, and increased length of stay. We sought to elucidate the role that a preoperatively assessed Mini-Cog can play in assessing the risk of adverse perioperative outcomes in a population at high risk of frailty.

METHODS

In this retrospective case-control study, patients who were >60 years of age, nonambulatory, or had >5 documented medications were preoperatively assessed for handgrip strength, walking speed, and Mini-Cog score. The Emory University Clinical Data Warehouse was then used to extract this information and other perioperative data elements and outcomes data.

RESULTS

Data were available for 1132 patients undergoing a wide variety of surgical procedures. For the subset of 747 patients with data for observed-to-expected length of stay, an abnormal Mini-Cog was associated with an increased odds of observed-to-expected >1 (odds ratio, 1.52; 95% CI, 1.05-2.19; P = .025). There was no association of abnormal Mini-Cog with intensive care unit length of stay >3 days (P = .182) discharge to home with self-care (P = .873) or risk of readmission (P = .104). Decreased baseline hemoglobin was associated with increased risk of 2 of the 4 outcomes studied.

CONCLUSIONS

In a high-risk pool of patients, Mini-Cog may not be sensitive enough to detect significant differences for most adverse outcomes. Further work is needed to assess whether cognitive screens with greater resolution are of value in this context and to compare tools for assessing overall frailty status.

Substrate Supporting Disc Method for Confirmed Detection of Total Coliforms and E. coli in all Foods: Collaborative Study

The Coli Complete® substrate supporting disc (SSD) method for simultaneous confirmed total coliform count and Escherichia coli determination in all foods was compared with AOAC most probable number (MPN) methods, 966.23 and 966.24. Twenty-nine laboratories participated in this collaborative study in which 6 food types were analyzed. Four food types, raw ground beef, pork sausage, raw liquid milk, and nut meats, were naturally contaminated with coliform bacteria. Two foods, dry egg and fresh frozen vegetables, were seeded with coliforms. Three food types, ground beef, raw liquid milk, and pork sausage, were naturally contaminated with E. coli. Although pork sausage was naturally contaminated, the level was very low (<10/50 g); therefore, additional E. coli were inoculated into 1 lot of this food type. Three food types, nut meats, dry egg, and fresh frozen vegetables, were inoculated with E. coli. For naturally contaminated samples, duplicate determinations were made on 3 separate lots for each food type. For inoculated samples, low, medium, and high contamination levels plus uninoculated control samples were examined in duplicate. Data were analyzed separately for total coliform bacteria and for E. coli. Mean log MPN counts were determined by the SSD method and the appropriate AOAC MPN method. Results were then analyzed for repeatability, reproducibility, and mean log MPN statistical equivalence. Results were statistically equivalent for all total coliform levels in all food types except frozen vegetable and raw nut meat uninoculated control samples and 1 lot of pork sausage where the SSD method produced statistically significant greater numbers. For the E. coli determinations, results were statistically equivalent across all samples and all levels for each food type. The SSD method has been adopted first action by AOAC International for confirmed detection of total coliforms and E. coli in all foods.