Andreas R. Seim

Real-Time Checking of Electronic Anesthesia Records for Documentation Errors and Automatically Text Messaging Clinicians Improves Quality of Documentation

INTRODUCTION:The quality of electronic anesthesia documentation is important for downstream communication and to demonstrate appropriate diligence to care. Documentation quality will also impact the success of reimbursement contracts that require timely and complete documentation of specific interventions. We implemented a system to improve completeness of clinical documentation and evaluated the results over time. METHODS:We used custom software to continuously scan for missing clinical documentation during anesthesia. We used patient allergies as a test case, taking advantage of a unique requirement in our system that allergies be manually entered into the electronic record. If no allergy information was entered within 15 min of the “start of anesthesia care” event, a one-time prompt was sent via pager to the person performing the anesthetic. We tabulated the daily fraction of cases missing allergy data for the 6 mo before activating the alert system. We then obtained the same data for the subsequent 9 mo. We tested for systematic performance changes using statistical process control methodologies. RESULTS:Before initiating the alert system, the fraction of charts without an allergy comment was slightly more than 30%. This decreased to about 8% after initiating the alerts, and was significantly different from baseline within 5 days. Improvement lasted for the duration of the trial. Paging was suspended on nights, weekends, and holidays, yet weekend documentation performance also improved, indicating that weekday reminders had far-reaching effects. DISCUSSION:Electronic anesthesia documentation performance can be rapidly managed and improved by using an automatic process monitoring and alerting system.

Statistical Process Control as a Tool for Monitoring Nonoperative Time

Background:Administrators need simple tools to quickly identify even small changes in the performance of perioperative systems. This applies both to established systems and to impact assessments of deliberate perioperative system design changes. Methods:Statistical process control was originally developed to detect nonrandom variation in manufacturing processes by continuous comparison to previous performance. The authors applied the technique to assess the nonoperative time performance between successive cases for same surgeon following themselves in a redesigned operating room. This operating room specifically implemented a new patient care pathway that improves throughput by reducing the nonoperative time. The authors tested how quickly statistical process control detected reductions in nonoperative time. They also tested the ability of statistical process control to detect successively smaller performance changes and investigated its utility for longitudinal process monitoring. Results:Statistical process control detected a clear reduction in nonoperative time after the new operating room had been used for only 2 days. The method could detect nonoperative time changes of between 5 and 10 min per case for a single operating room within one fiscal quarter. Nonoperative time for the new process was globally stable over the 31 months analyzed, but late in the analysis period, the authors detected small performance decrements, mostly attributable to factors external to the new operating room. Conclusions:Statistical process control is useful for detecting changes in perioperative system performance, represented in this study by nonoperative time. The technique is able to detect changes quickly and to detect small changes over time.

Causes of Cancellations on the Day of Surgery at Two Major University Hospitals

Cancellations of elective cases on the day of surgery waste valuable operating-room time. The authors studied cancellations at an American hospital and a Norwegian university hospital to test (a) whether the quality of hospital administrative data on cancellations is sufficient for meaningful comparative analysis and (b) whether causes of cancellations at these 2 major academic hospitals are comparable. Large retrospective cause-of-cancellation data sets were obtained from each hospital. The authors then prospectively established root causes of cancellations by on-site investigation and interviews of the hospital personnel involved. The surgical department at the Norwegian hospital cancelled 14.58% of cases in 2003 and 16.07% in 2004. The American hospital cancelled 16.52% of all cases between May 1, 2003, and April 30, 2004. Administrative data may give a rough picture of causes of cancellations. However, most findings at either of the hospitals do not translate easily to the other.

What is optimal timing for trauma team alerts? A retrospective observational study of alert timing effects on the initial management of trauma patients

Background Trauma teams improve the initial management of trauma patients. Optimal timing of trauma alerts could improve team preparedness and performance while also limiting adverse ripple effects throughout the hospital. The purpose of this study was to evaluate how timing of trauma team activation and notification affects initial in-hospital management of trauma patients. Methods Data from a single hospital trauma care quality registry were matched with data from a trauma team alert log. The time from patient arrival to chest X-ray, and the emergency department length of stay were compared with the timing of trauma team activations and whether or not trauma team members received a preactivation notification. Results In 2009, the trauma team was activated 352 times; 269 times met the inclusion criteria. There were statistically significant differences in time to chest X-ray for differently timed trauma team activations (P = 0.003). Median time to chest X-ray for teams activated 15–20 minutes prearrival was 5 minutes, and 8 minutes for teams activated <5 minutes before patient arrival. Timing had no effect on length of stay in the emergency department (P = 0.694). We found no effect of preactivation notification on time to chest X-ray (P = 0.474) or length of stay (P = 0.684). Conclusion Proactive trauma team activation improved the initial management of trauma patients. Trauma teams should be activated prior to patient arrival.

Shaping the operating room and perioperative systems of the future: innovating for improved competitiveness.

Purpose of review To review the current state of anesthesiology for operative and invasive procedures, with an eye toward possible future states. Recent findings Anesthesiology is at once a mature specialty and in a crisis – requiring breakthrough to move forward. The cost of care now approaches reimbursement, and outcomes as commonly measured approach perfection. Thus, the cost of further improvements seems ready to topple the field, just as the specialty is realizing that seemingly innocuous anesthetic choices have long-term consequences, and better practice is required. Summary Anesthesiologists must create more headroom between costs and revenues in order to sustain the academic vigor and creativity required to create better clinical practice. We outline three areas in which technological and organizational innovation in anesthesiology can improve competitiveness and become a driving force in collaborative efforts to develop the operating rooms and perioperative systems of the future: increasing the profitability of operating rooms; increasing the efficiency of anesthesia; and technological and organizational innovation to foster improved patient flow, communication, coordination, and organizational learning.

Implementation of a Direct-From-Recovery-Room Discharge Pathway: A Process Improvement Effort

Background. The authors describe a process improvement effort to achieve direct-from-recovery-room discharge for elective laparoscopic cholecystectomy patients— without prior patient selection. Methods. The authors developed and implemented a new pathway, and then measured the learning curve (ie, success rate over time for direct discharge) and compared patients achieving direct discharge with patients admitted after surgery. Results. The learning curve between the first patient and steady-state performance was 56 patients. A total of 80% of patients achieved direct discharge. Directly discharged patients were younger (P < .001), had lower ASA physical status classifications (P < .005), and left the recovery room earlier in the day (P < .0001). However, elderly patients and those with high ASA scores frequently could be directly discharged from the recovery room. Conclusions. Through small team based rapid cycle process improvement, direct-from-recovery-room discharge of laparoscopic cholecystectomy patients can be achieved in an unselected patient population with a short learning curve.

The Effect of Direct-From-Recovery Room Discharge of Laparoscopic Cholecystectomy Patients on Recovery Room Workload

Ambulatory laparoscopic cholecystectomy pathways move patients through the hospital without encountering delays caused by congested inpatient bed units. However, redirecting patients to a direct discharge pathway might not be beneficial if recovery capacity is further taxed by additional workload. In this study, we attempt to assess the operational impact on recovery room workload of directly discharging laparoscopic cholecystectomy patients to home. We conducted a retrospective case-control review of recovery room flow sheets to determine recovery room time and effort required for laparoscopic cholecystectomy patients. The study was restricted to patients of a single surgeon to minimize confounds from surgical technique. Fifty-seven case patients (May 1, 2004, through November 30, 2004), all managed with intent to directly discharge from the recovery room, were compared with control patients (n = 81) from the corresponding 6 months in the year before the direct-discharge plan. The times (mean; 95% confidence interval) to meet objective criteria for adequate pain control (3.5 minutes [2.1 to 5.9] versus 4.0 minutes [2.6 to 6.1]) and readiness for discharge from phase 1 recovery (8.1 minutes [4.8 to 13.6] versus 6.1 minutes [4.0 to 9.5]) were not different between the groups. The number and distribution of interventions documented in the recovery process were not different between groups, nor was there a difference in recovery room length of stay (158 minutes [138 to 182] versus 149 minutes [132 to 167]). In our study, recovery room records reveal little if any increased workload associated with the direct-to-home discharge of laparoscopic cholecystectomy patients.