Wilton C. Levine

A model for understanding the impacts of demand and capacity on waiting time to enter a congested recovery room.

Background:When a recovery room is fully occupied, patients frequently wait in the operating room after emerging from anesthesia. The frequency and duration of such delays depend on operating room case volume, average recovery time, and recovery room capacity. Methods:The authors developed a simple yet nontrivial queueing model to predict the dynamics among the operating and recovery rooms as a function of the number of recovery beds, surgery case volume, recovery time, and other parameters. They hypothesized that the model could predict the observed distribution of patients in recovery and on waitlists, and they used statistical goodness-of-fit methods to test this hypothesis against data from their hospital. Numerical simulations and a survey were used to better understand the applicability of the model assumptions in other hospitals. Results:Statistical tests cannot reject the prediction, and the model assumptions and predictions are in agreement with data. The survey and simulations suggest that the model is likely to be applicable at other hospitals. Small changes in capacity, such as addition of three beds (roughly 10% of capacity) are predicted to reduce waiting for recovery beds by approximately 60%. Conversely, even modest caseload increases could dramatically increase waiting. Conclusions:A key managerial insight is that there is a sensitive relationship among caseload and number of recovery beds and the magnitude of recovery congestion. This is typical in highly utilized systems. The queueing approach is useful because it enables the investigation of future scenarios for which historical data are not directly applicable.

Anesthesia for the elderly: selected topics.

Purpose of review With the graying of the Western population, there is a continuous increase in the proportion of elderly patients undergoing surgical procedures. Geriatric anesthesia is emerging from a ‘subspecialty’ to the mainstream of todays anesthesia and perioperative care. Much has been written on anesthesia for the elderly, but this review will concentrate on selected topics related to elderly care that represent current unresolved and pertinent issues for the care of the elderly surgical patient. Recent findings Postoperative cognitive dysfunction, cardiac diastolic dysfunction and prophylactic perioperative β-blockade in the process of major noncardiac surgery are three main topics that have recently attracted great interest in clinical practice and research, and have therefore been chosen as the selected topics for this current review. Summary Although age is a clear risk factor for postoperative cognitive dysfunction, the association of general anesthesia with cognitive dysfunction is less clear, as is the effect of anesthesia per se or surgery on long-term cognitive dysfunction. Cardiac diastolic dysfunction is a relatively new and evolving concept in anesthesia and perioperative medicine, yet clearly diastolic dysfunction even with a normal ejection fraction may have a significant effect on the perioperative outcome and management of elderly patients. Small, but powerful studies have shown significant outcome benefit with prophylactic perioperative β-blockade in high-risk patients undergoing major noncardiac surgery. Data from other studies, however, are still conflicting and the final verdict awaits larger scale outcome studies.

A computerized perioperative data integration and display system

AbstractObject The operating room is rich in digital data that must be rapidly gathered and integrated by caregivers, potentially distracting them from direct patient care. We hypothesized that current desktop computers could integrate enough electronically accessible perioperative data to present a unified, contextually appropriate snapshot of the patient to the operating room team without requiring any user intervention. Materials and methods We implemented a system that integrates data from surgical and anesthesia devices and information systems, as well as an active radiofrequency identification location tracking system, to create a comprehensive, unified, time-synchronized database of all digital data produced by these systems. Next, a human factors engineering approach was used to identify selected data to show on a large format display during surgery. Results A prototype system has been in daily use in a clinical operating room since August 2005. The system functions automatically without any user input, as the display system self-configures based on cues from the primary data. The system is vendor agnostic with respect to input data sources and display options. Conclusion Automatic integration and display of team-synchronizing data from medical devices and hospital information systems is now possible using software that runs on a personal computer.

Development and Validation of an Intraoperative Predictive Model for Unplanned Postoperative Intensive Care

Background:The allocation of intensive care unit (ICU) beds for postoperative patients is a challenging daily task that could be assisted by the real-time detection of ICU needs. The goal of this study was to develop and validate an intraoperative predictive model for unplanned postoperative ICU use. Methods:With the use of anesthesia information management system, postanesthesia care unit, and scheduling data, a data set was derived from adult in-patient noncardiac surgeries. Unplanned ICU admissions were identified (4,847 of 71,996; 6.7%), and a logistic regression model was developed for predicting unplanned ICU admission. The model performance was tested using bootstrap validation and compared with the Surgical Apgar Score using area under the curve for the receiver operating characteristic. Results:The logistic regression model included 16 variables: age, American Society of Anesthesiologists physical status, emergency case, surgical service, and 12 intraoperative variables. The area under the curve was 0.905 (95% CI, 0.900–0.909). The bootstrap validation model area under the curves were 0.513 at booking, 0.688 at 3 h before case end, 0.738 at 2 h, 0.791 at 1 h, and 0.809 at case end. The Surgical Apgar Score area under the curve was 0.692. Unplanned ICU admissions had more ICU-free days than planned ICU admissions (5 vs. 4; P < 0.001) and similar mortality (5.6 vs. 6.0%; P = 0.248). Conclusions:The authors have developed and internally validated an intraoperative predictive model for unplanned postoperative ICU use. Incorporation of this model into a real-time data sniffer may improve the process of allocating ICU beds for postoperative patients.

Thoracoabdominal aneurysm repair: anesthetic management.

Surgical repair of descending thoracic and thoracoabdominal aortic aneurysms (TAAs) presents one of the greatest challenges for the anesthesiologist. The challenge comes from the fine balance of complex medical issues in the setting of altered physiology that occurs during the perioperative period. Patients presenting for TAA repair usually have multiple preexisting comorbid conditions involving their cardiac, pulmonary, and renal systems; and aneurysm repair poses a direct and immediate threat to these systems in addition to the gastrointestinal and neurologic systems. To preserve proper function of these organ systems, the anesthesiologist must be adept at monitoring and manipulating rapid and extreme hemodynamic changes, maintaining adequate pulmonary function during one lung ventilation, and preserving metabolic and hematologic homeostasis after aortic crossclamping and unclamping in the setting of significant blood loss. In these high-risk patients, distal aortic perfusion, spinal cord preservation through cooling techniques, distal shunting procedures, and the use of motor-evoked potentials have all been used in attempt to decrease the risk of spinal cord and mesenteric ischemia. The recent development of endovascular stent graft repair is changing the practices of many institutions. Thoracoabdominal aneurysms are classified according to the Crawford classification depending on the extent of the aneurysm. Type I aneurysms extend from the left subclavian artery to the diaphragm. Type II aneurysms extend from the left subclavian artery to below the renal arteries. Type III aneurysms extend from the midthoracic descending aorta to below the

Medication Safety in the Perioperative Setting

Drug administration errors are a major cause of morbidity and mortality in hospitalized patients. These errors result in major harm and incur dramatic costs to the delivery of health care. This article highlights this problem, especially as it deals with patients in the perioperative setting.

Implementation of the Vocera Communication System in a Quaternary Perioperative Environment

In the hospital, fast and efficient communication among clinicians and other employees is paramount to ensure optimal patient care, workflow efficiency, patient safety and patient comfort. The implementation of the wireless Vocera® Badge, a hands-free wearable device distributed to perioperative team members, has increased communication efficiency across the perioperative environment at Massachusetts General Hospital (MGH). This quality improvement project, based upon identical pre- and post-implementation surveys, used qualitative and quantitative analysis to determine if and how the Vocera system affected the timeliness of information flow, ease of communication, and operating room noise levels throughout the perioperative environment. Overall, the system increased the speed of information flow and eased communication between coworkers yet was perceived to have raised the overall noise level in and around the operating rooms (ORs). The perceived increase in noise was outweighed by the closed-loop communication between clinicians. Further education of the system’s features in regard to speech recognition and privacy along with expected conversation protocol are necessary to ensure hassle-free communication for all staff.

Communication Patterns in the Perioperative Environment During Epic Electronic Health Record System Implementation

In April 2016, Massachusetts General Hospital (MGH) went live with the Epic electronic health records (EHR) system, replacing a variety of EHRs that previously existed in different departments throughout the hospital. At the time of implementation, the Vocera® Badge Communication System, a wireless hands-free communication device distributed to perioperative team members, had increased perioperative communication flow and efficiency. As a quality improvement effort to better understand communication patterns during an EHR go-live, we monitored our Vocera call volume and user volume before, during and after our go-live. We noticed that call volume and user volume significantly increased during our immediate go-live period and quickly returned to baseline levels. We also noticed that call volume increased during periods of unplanned EHR downtime long after our immediate go-live period. When planning the implementation of a new EHR, leadership must plan for and support this critical communication need at the time of the go-live and must also be aware of these needs during unplanned downtime.

Optimizing Endoscope Reprocessing Resources Via Process Flow Queuing Analysis

The Massachusetts General Hospital (MGH) is merging its older endoscope processing facilities into a single new facility that will enable high-level disinfection of endoscopes for both the ORs and Endoscopy Suite, leveraging economies of scale for improved patient care and optimal use of resources. Finalized resource planning was necessary for the merging of facilities to optimize staffing and make final equipment selections to support the nearly 33,000 annual endoscopy cases. To accomplish this, we employed operations management methodologies, analyzing the physical process flow of scopes throughout the existing Endoscopy Suite and ORs and mapping the future state capacity of the new reprocessing facility. Further, our analysis required the incorporation of historical case and reprocessing volumes in a multi-server queuing model to identify any potential wait times as a result of the new reprocessing cycle. We also performed sensitivity analysis to understand the impact of future case volume growth. We found that our future-state reprocessing facility, given planned capital expenditures for automated endoscope reprocessors (AERs) and pre-processing sinks, could easily accommodate current scope volume well within the necessary pre-cleaning-to-sink reprocessing time limit recommended by manufacturers. Further, in its current planned state, our model suggested that the future endoscope reprocessing suite at MGH could support an increase in volume of at least 90% over the next several years. Our work suggests that with simple mathematical analysis of historic case data, significant changes to a complex perioperative environment can be made with ease while keeping patient safety as the top priority.

Improving Operating Room Efficiency via Reduction and Standardization of Video-Assisted Thoracoscopic Surgery Instrumentation

Being the economic powerhouses of most large medical centers, operating rooms (ORs) require the highest levels of teamwork, communication, and efficiency in order to optimize patient safety and reduce hospital waste. A major component of OR waste comes from unused surgical instrumentation; instruments that are frequently prepared for procedures but are never touched by the surgical team still require a full reprocessing cycle at the conclusion of the case. Based on our own previous successes in the perioperative domain, in this work we detail an initiative that reduces surgical instrumentation waste of video-assisted thoracoscopic surgery (VATS) procedures by placing thoracotomy conversion instrumentation in a standby location and designing a specific instrument kit to be used solely for VATS cases. Our estimates suggest that this initiative will reduce at least 91,800 pounds of unnecessary surgical instrumentation from cycling through our ORs and reprocessing department annually, resulting in increased OR team communication without sacrificing the highest standard of patient safety.