Quantile regression forests for individualized surgery scheduling.

Determining the optimal surgical case start times is a challenging stochastic optimization problem that shares a key feature with many other healthcare operations problems. Namely, successful problem solutions require using a vast array of available historical data to create distributions that accurately capture a case duration's uncertainty for integration into an optimization model. Distribution fitting is the conventional approach to generate these distributions, but it can only employ a limited, aggregate portion of the detailed patient features available in Electronic Medical Records systems today. If all the available information can be taken advantage of, then distributions individualized to every case can be constructed whose precision would support higher quality solutions in the presence of uncertainty. Our individualized stochastic optimization framework shows how the quantile regression forest (QRF) method predicts individualized distributions that are integrable into sample-average approximation, robust optimization, and distributionally robust optimization models for problems like surgery scheduling. In this paper, we present some related theoretical performance guarantees for each formulation. Numerically, we also study our approach's benefits relative to three other traditional models using data from Memorial Sloan Kettering Cancer Center in New York, NY, USA.

Integrating autonomously navigating assistance systems into the clinic: guiding principles and the ANTS-OR approach.

PURPOSE: Autonomously self-navigating clinical assistance systems (ASCAS) seem highly promising for improving clinical workflows. There is great potential for easing staff workload and improving overall efficiency by reducing monotonous and physically demanding tasks. However, a seamless integration of such systems into complex human-supervised clinical workflows is challenging. As of yet, guiding principles and specific approaches for solving this problem are lacking. METHODS: We propose to treat ASCAS orchestration as a scheduling problem. However, underlying objectives and constraints for this scheduling problem differ considerably from those found in other domains (e.g., manufacturing, logistics). We analyze the clinical environment to deduce unique needs and conclude that existing scheduling approaches are not sufficient to overcome these challenges. RESULTS: We present four guiding principles, namely human precedence, command structure, emergency context and immediacy, that govern the integration of self-navigating assistance systems into clinical workflows. Based on these results, we propose our approach, namely Auto-Navigation Task Scheduling for Operating Rooms (ANTS-OR), for solving the ASCAS orchestration problem in a surgical application scenario, employing a score-based scheduling strategy. CONCLUSION: The proposed approach is a first step toward addressing the ASCAS orchestration problem for the OR wing. We are currently advancing and validating our concept using a simulation environment and aim at realizing a dynamic end-to-end ASCAS orchestration platform in the future.

Operational Efficiency and Productivity Improvement Initiatives in a Large Cardiac Catheterization Laboratory.

OBJECTIVES: This study sought to report outcomes from an efficiency improvement project in a large cardiac cath lab. BACKGROUND: Operational inefficiencies are common in the cath lab, yet solutions are challenging. A detailed report describing and providing solutions for these inefficiencies may be valuable in guiding improvements in productivity. METHODS: In this observational study, the authors report metrics of efficiency before and after a cath lab quality improvement program in June 2014. Main outcomes included lab room start times, room turnaround times, laboratory use, and employee satisfaction. Time series analysis was used to assess trend over time. Chi-square testing and analysis of variance were used to assess change before and after the initiative. RESULTS: The principal changes included implementation of a pyramidal nursing schedule, increased use of an electronic scheduling system, and increased utilization of a preparation and recovery area. Comparing before with after the program, start times improved an average of 17 min, and on-time starts improved from 61.8% to 81.7% (p = 0.0024). Turnaround times improved from 20.5 min to 16.4 min (trend p < 0.0001), and the proportion of days at full lab utilization improved from 7.7% to 77.3% (p < 0.00001). There were no increases in overtime, night, or weekend cases. There was a reduction in full time employees from 36.1 in 2013 to 29.6 in 2016, with an improvement in employee satisfaction. CONCLUSIONS: A systematic approach to reducing inefficiencies can improve cath lab start times, turnaround times, and overall productivity. This knowledge may be helpful in assisting other cath labs in similar efficiency improvement initiatives.

A Real-Time Decision Support System for Anesthesiologist End-of-Shift Relief.

A decision support system using recent data about work hours and real-time data about relief events was developed to guide anesthesiologist end-of-shift relief decisions in an effort to promote a relief order that prioritized relief for those who had recently worked later than others. After system implementation, there were fewer deviations from this idealized order of relief, and early relief was more evenly distributed.

Implications of Perioperative Team Setups for Operating Room Management Decisions.

BACKGROUND: Team performance has been studied extensively in the perioperative setting, but the managerial impact of interprofessional team performance remains unclear. We hypothesized that the interplay between anesthesiologists and surgeons would affect operating room turnaround times, and teams that worked together over time would become more efficient. METHODS: We analyzed 13,632 surgical cases at our hospital that involved 64 surgeons and 48 anesthesiologists. We detrended and adjusted the data for potential confounders including age, American Society of Anesthesiologists physical status, and surgical list (scheduled cases of specific surgical specialties). The surgical lists were categorized as ear, nose, and throat surgery; trauma surgery; general surgery; and gynecology. We assessed the relationship between turnaround times and assignment of different anesthesiologists to specific surgeons using a Monte Carlo simulation. RESULTS: We found significant differences in team performances among the different surgical lists but no team learning. We constructed managerial decision tables for the assignment of anesthesiologists to specific surgeons at our hospital. We defined a decision algorithm based on these tables. Our analysis indicated that had this algorithm been used in staffing the operating room for the surgical cases represented in our data, median turnaround times would have a reduction potential of 6.8% (95% confidence interval 6.3% to 7.1%). CONCLUSIONS: A surgeon is usually predefined for scheduled surgeries (surgical list). Allocation of the right anesthesiologist to a list and to a surgeon can affect the team performance; thus, this assignment has managerial implications regarding the operating room efficiency affecting turnaround times and thus potentially overutilized time of a list at our hospital.

Resident Physicians Improve Nontechnical Skills When on Operating Room Management and Leadership Rotation.

BACKGROUND: Anesthesiology residency primarily emphasizes the development of medical knowledge and technical skills. Yet, nontechnical skills (NTS) are also vital to successful clinical practice. Elements of NTS are communication, teamwork, situational awareness, and decision making. METHODS: The first 10 consecutive senior residents who chose to participate in this 2-week elective rotation of operating room (OR) management and leadership training were enrolled in this study, which spanned from March 2013 to March 2015. Each resident served as the anesthesiology officer of the day (AOD) and was tasked with coordinating OR assignments, managing care for 2 to 4 ORs, and being on call for the trauma OR; all residents were supervised by an attending AOD. Leadership and NTS techniques were taught via a standardized curriculum consisting of leadership and team training articles, crisis management text, and daily debriefings. Resident self-ratings and attending AOD and charge nurse raters used the Anaesthetists' Non-Technical Skills (ANTS) scoring system, which involved task management, situational awareness, teamwork, and decision making. For each of the 10 residents in their third year of clinical anesthesiology training (CA-3) who participated in this elective rotation, there were 14 items that required feedback from resident self-assessment and OR raters, including the daily attending AOD and charge nurse. Results for each of the items on the questionnaire were compared between the beginning and the end of the rotation with the Wilcoxon signed-rank test for matched samples. Comparisons were run separately for attending AOD and charge nurse assessments and resident self-assessments. Scaled rankings were analyzed for the Kendall coefficient of concordance (ω) for rater agreement with associated χ and P value. RESULTS: Common themes identified by the residents during debriefings were recurrence of challenging situations and the skills residents needed to instruct and manage clinical teams. For attending AOD and charge nurse assessments, resident performance of NTS improved from the beginning to the end of the rotation on 12 of the 14 NTS items (P < .05), whereas resident self-assessment improved on 3 NTS items (P < .05). Interrater reliability (across the charge nurse, resident, and AOD raters) ranged from ω = .36 to .61 at the beginning of the rotation and ω = .27 to .70 at the end of the rotation. CONCLUSIONS: This rotation allowed for teaching and resident assessment to occur in a way that facilitated resident education in several of the skills required to meet specific milestones. Resident physicians are able to foster NTS and build a framework for clinical leadership when completing a 2-week senior elective as an OR manager.

Decreasing the Hours That Anesthesiologists and Nurse Anesthetists Work Late by Making Decisions to Reduce the Hours of Over-Utilized Operating Room Time.

In this special article, we evaluate how to reduce the number of hours that anesthesiologists and nurse anesthetists work beyond the end of their scheduled shifts. We limit consideration to surgical suites where the hours of cases in each operating room (OR) average 8 hours or more per day. Let "allocated hours" refer to the hours into which cases are scheduled, calculated months in advance for each combination of service and day of the week. Over-Utilized time is the OR workload exceeding allocated time. Reducing Over-Utilized time is the key to reducing the hours that anesthesia providers work late. Certain decisions that reduce Over-Utilized time and reduce the hours that anesthesiologists and nurse anesthetists work late are made by the surgical committee or perioperative medical director months in advance. Such decisions include increasing the number of first case starts and planning staffing for turnovers and lunch breaks during the busiest times of the day. However, most decisions substantively influencing Over-Utilized OR time are made within 1 workday before the day of surgery and on the day of surgery, because only then are ORs sufficiently full that changes can be made to minimize Over-Utilized time. Decisions to reduce Over-Utilized time on the day of surgery include targeting ORs with expected Over-Utilized time and taking steps to reduce it, including making effective staff assignments and appropriately scheduling add-on cases.

Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery.

BACKGROUND: The American Society of Anesthesiologists has embraced the concept of the Perioperative Surgical Home as a means through which anesthesiologists can add value to the health systems in which they practice. One key listed element of the Perioperative Surgical Home is to support "scheduling initiatives to reduce cancellations and increase efficiency." In this study, we explored the potential benefits of the Perioperative Surgical Home with respect to inpatient cancellations and add-on case scheduling. We evaluated 6 hypotheses related to the timing of inpatient cancellations and preoperative anesthesia evaluations. METHODS: Inpatient cancellations were studied during 26 consecutive 4-week intervals between July 2012 and June 2014 at a tertiary care academic hospital. All timestamps related to scheduling, rescheduling, and cancellation activities were retrieved from the operating room (OR) case scheduling system. Timestamps when patients were seen by anesthesia residents were obtained from the preoperative evaluation system database. Batch mean methods were used to calculate means and SE. For cases cancelled, we determined whether, for "most" (>50%) cancellations, a subsequent procedure (of any type) was performed on the patient within 7 days of the cancellation. Comparisons with most and other fractions were assessed using the 1 group, 1-sided Student t test. We evaluated whether a few procedures were highly represented among the cancelled cases via the Herfindahl (Simpson's) index, comparing it with <0.15. The rate of scheduling activity was assessed by computing the number of OR scheduling office decisions in each 1-hour bin between 6:00 AM and 3:59 PM. These values were compared with ≥1 decision per hour at the study hospital. RESULTS: Data from 24,735 scheduled inpatient cases were assessed. Cases cancelled after 7 AM on the day before or at any time on the scheduled day of surgery accounted for 22.6% ± 0.5% (SE) of the scheduled minutes all scheduled cases, and 26.8% ± 0.4% of the case volume (i.e., number of cases). Most (83.1% ± 0.6%, P < 10) cases performed were evaluated on the day before surgery. Most (67.6% ± 1.6%, P < 10) minutes of cancelled cases were evaluated on the day before surgery. Most (62.3% ± 1.5%, P < 10) cases were seen earlier than 6:00 PM of the day before surgery. The Herfindahl index among cancelled procedures was 0.021 ± 0.001 (P < 10 compared not only to <0.15 but also to <0.05), showing large heterogeneity among the cancelled procedures. A subsequent procedure was not performed for most cancelled cases (50.6% ± 0.9% compared with >50%, P = 0.12), implying that the indication for the cancelled procedure no longer existed or the patient/family decided not to proceed with surgery. When only cancellations on the scheduled day of surgery were considered, the cancellation rate was 14.0% ± 0.3% of scheduled inpatient minutes and 11.8% ± 0.2% of scheduled inpatient cases. There were 0.59 ± 0.02 OR schedule decisions per hour per 10 ORs between 6:00 AM and 3:59 PM (P < 10, corresponding to ≥1 decision per hour at the 36 OR study hospital). CONCLUSIONS: The study hospital had a high inpatient cancellation rate, despite the fact that most patients whose cases were cancelled were seen by an anesthesia resident by 6:00 PM of the day before surgery. This finding suggests that further efforts to reduce the cancellations by seeing patients sooner on the day before surgery, or seeing even more patients the day before surgery, would not be an economically useful focus of the Perioperative Surgical Home. The wide heterogeneity among cancelled cases indicates that focusing on a few procedures would not materially affect the overall cancellation rate. The relatively low rate of subsequent performance of a procedure on patients whose cases had been cancelled suggests that trying to decrease the cancellation rate might be medically counterproductive. The hourly rate of decisions in the scheduling office during regular work hours on the day of surgery highlights the importance of decisions made at the OR control desk and scheduling office throughout the day to reduce the hours of overused OR time. These data suggest that efforts of the Perioperative Surgical Home related to inpatient cancellations should focus on management decision-making to mitigate the disruptions to the planned OR schedule caused by inpatient case cancellations and add-on cases, more so than on efforts to reduce inpatient cancellation rates.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

OBJECTIVES: Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. METHOD: A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. RESULTS: The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in individual maximum overtime (OT); and (4) an 42% reduction in the total OT of nurses. Comparison results with the real 10-workday hospital scheduling further show the advantage of the ACO in several measurements. Instead of assigning all surgeries by a surgeon to only one OR and the same nurses by traditional manual approach in hospital, ACO realizes a more balanced surgery arrangement by assigning the surgeries to different ORs and nurses. It eventually leads to shortening the end time within the confidential interval of [7.4%, 24.6%] with 95% confidence level. CONCLUSION: The ACO approach proposed in this paper efficiently solves the surgery scheduling problem with daily nurse roster while providing a shortened end time and relatively balanced resource allocations. It also supports the advantage of integrating the surgery scheduling with the nurse scheduling and the efficiency of systematic optimization considering a complete three-stage surgery flow and resources involved.

Patients' adoption of the e-appointment scheduling service: A case study in primary healthcare.

The aim of this study is to investigate patients' initial acceptance and ongoing use of a simple but typical type of consumer e-health service - an e-appointment scheduling (EAS) system - in order to identify facilitators and barriers for patients' adoption of e-health services in primary healthcare. In-depth, semi-structured interviews were conducted to gather patients' background information, their awareness of the system, their feedbacks on the characteristics of the system, and their reasons for use or not use the system. A total of 125 patients aged between 17 and 74 were interviewed. Study results show that 89% of the interviewed patients had shown reluctance to adopt this online service. The identified barriers for acceptance include many patients' lack of access to the internet, lack of awareness of the service, low computer skills and incompatibility of the online appointment service with many patients' habits of face-to-face or phone-call based medical appointment making. Health service providers need to consider the general public's acceptance for online services before implementing consumer e-health systems.

Explanation for the near-constant mean time remaining in surgical cases exceeding their estimated duration, necessary for appropriate display on electronic white boards.

BACKGROUND: Consider a case that has been ongoing for longer than the scheduled duration. The anesthesiologist estimates that there is 1 hour remaining. Forty-five minutes later the case has not yet finished, and closure has not yet started. We showed previously that the mean (expected) time remaining is approximately 1 hour, not 15 minutes. The relationship is a direct mathematical consequence of the log-normal probability distributions of operating room (OR) case durations. We test the hypothesis that, with an accurate probabilistic model, until closure begins the estimated mean time remaining would be the mean time from the start of closure to OR exit. METHODS: Among the 311,940 OR cases in a 7-year time series from 1 hospital, there were 3962 cases for which (1) there had been previously at least 30 cases of the same combination of scheduled procedure(s), surgeon, and type of anesthetic and (2) the actual OR time exceeded the 0.9 quantile of case duration before the case started. A Bayesian statistical method was used to calculate the mean (expected) minutes remaining in the case at the 0.9 quantile. The estimate was compared with the actual minutes from the time of the start of closure until the patient exited the OR. RESULTS: The mean ± standard error of the pairwise difference was 0.2 ± 0.4 minutes. The Bayesian estimate for the 0.9 quantile was exceeded by 10.2% ± 0.01% of cases (i.e., very close to the desired 10.0% rate). CONCLUSIONS: If a case is taking longer than the expected (scheduled) duration, closure has not yet started, and someone in the OR is asked how much time the case likely has remaining, the value recorded on a clipboard for viewing later should be the estimated time remaining (e.g., "1 hour") not an end time (e.g., "5:15 pm"). Electronic whiteboard displays should not show that the estimated time remaining in the case is less than the mean time from start of closure to OR exit. Similarly, if closure has started, the expected time remaining that is displayed should not be longer than the mean time from closure to OR exit. Finally, our results match previous reports that, before a case starts, statistical methods can reliably be used to assist in decisions involving the longest amount of time that cases may take (e.g., conflict checking for resources, filling holes in the OR schedule, and preventing holes in the schedule).

Decision support using anesthesia information management system records and accreditation council for graduate medical education case logs for resident operating room assignments.

Our goal in this study was to develop decision support systems for resident operating room (OR) assignments using anesthesia information management system (AIMS) records and Accreditation Council for Graduate Medical Education (ACGME) case logs and evaluate the implementations. We developed 2 Web-based systems: an ACGME case-log visualization tool, and Residents Helping in Navigating OR Scheduling (Rhinos), an interactive system that solicits OR assignment requests from residents and creates resident profiles. Resident profiles are snapshots of the cases and procedures each resident has done and were derived from AIMS records and ACGME case logs. A Rhinos pilot was performed for 6 weeks on 2 clinical services. One hundred sixty-five requests were entered and used in OR assignment decisions by a single attending anesthesiologist. Each request consisted of a rank ordered list of up to 3 ORs. Residents had access to detailed information about these cases including surgeon and patient name, age, procedure type, and admission status. Success rates at matching resident requests were determined by comparing requests with AIMS records. Of the 165 requests, 87 first-choice matches (52.7%), 27 second-choice matches (16.4%), and 8 third-choice matches (4.8%) were made. Forty-three requests were unmatched (26.1%). Thirty-nine first-choice requests overlapped (23.6%). Full implementation followed on 8 clinical services for 8 weeks. Seven hundred fifty-four requests were reviewed by 15 attending anesthesiologists, with 339 first-choice matches (45.0%), 122 second-choice matches (16.2%), 55 third-choice matches (7.3%), and 238 unmatched (31.5%). There were 279 overlapping first-choice requests (37.0%). The overall combined match success rate was 69.4%. Separately, we developed an ACGME case-log visualization tool that allows individual resident experiences to be compared against case minimums as well as resident peer groups. We conclude that it is feasible to use ACGME case-log data in decision support systems for informing resident OR assignments. Additional analysis will be necessary to assess the educational impact of these systems.

Introducing the productive operating theatre programme in urology theatre suites.

BACKGROUND: The Productive Operating Theatre (TPOT) is a theatre improvement programme designed by the UK National Health Service. The aim of this study was to evaluate the implementation of TPOT in urology operating theatres and identify obstacles to running an ideal operating list. METHOD: TPOT was introduced in two urology operating theatres in September 2010. A multidisciplinary team identified and audited obstacles to the running of an ideal operating list. A brief/debrief system was introduced and patient satisfaction was recorded via a structured questionnaire. The primary outcome measure was the effect of TPOT on start and overrun times. RESULTS: Start times: 39-41% increase in operating lists starting on time from September 2010 to June 2011, involving 1,365 cases. Overrun times: Declined by 832 min between March 2010 and March 2011. The cost of monthly overrun decreased from September 2010 to June 2011 by GBP 510-3,030. Patient experience: A high degree of satisfaction regarding level of care (77%), staff hygiene (71%) and information provided (72%), while negative comments regarding staff shortages and environment/facilities were recorded. CONCLUSIONS: TPOT has helped identify key obstacles and shown improvements in efficiency measures such as start/overrun times.

Creating a transparent and dynamic view of staffing as a foundation for improving quality and efficiency.

As the United States moves into health care reform, there will be renewed debate on staffing models and ratios. The state of Massachusetts has developed a dashboard that will prepare them for nursing care models of the future while demonstrating that a variety of staffing templates can result in quality patient care today. Nursing leaders, legislators, and the public have access to information that demonstrates that staffing is complex and cannot be based on precise nursing ratios in all hospital settings.

Oral health workforce planning. Part 1: Data available in a sample of FDI member countries.

BACKGROUND & AIM: Workforce planning is a resource to measure and compare current versus future workforce. Organised dentistry needs to focus on the benefits and the determinants and various systems of workforce planning together with the challenges, new trends and threats. The aim of the study was to identify data sources from countries relating to a selection of oral health indicators in a sample of FDI member countries. The potential for differences between developed and developing countries was also examined. METHODS: A cross-sectional survey study was carried out among FDI member countries classified in developed and developing countries between October 2011 and January/February 2012. A questionnaire was developed addressing the availability of 40 selected indicators distributed in four domains. Mann-Whitney U-tests to identify differences between developed and developing countries and chi-square tests for the degree of information regularly available were carried out. RESULTS: There is an important lack of information about indicators relevant to oral health between FDI participating countries regardless of their level of economic development. Although not significant, the availability of indicators for developing countries showed higher variability and minimum values of zero for all domains. Surveys were the source of information more frequently reported. DISCUSSION: Standardised and reliable methodologies are needed to gather information for successful workforce planning. It is of utmost importance to increase the awareness and understanding of the member National Dental Associations regarding the role, basic elements, benefits, challenges, models and critical elements of an ideal workforce planning system.

Lack of value of scheduling processes to move cases from a heavily used main campus to other facilities within a health care system.

BACKGROUND: Economically, the most important anesthesia group and operating room (OR) management decision is the choice made months before surgery of the allocated OR time (duration of the workday) for each service. Consider a health system with surgeons who practice at multiple hospitals and ambulatory surgery centers. The main campus' ORs are busy, with nearly 8 h of cases, including turnovers, per anesthetizing location per workday. The other (regional) facilities have substantial underutilized time. A surgeon wants to do one 3-hour case at the main campus and have an afternoon start. The anesthesia group's OR director could use the health systems' common OR information system to examine the surgeons' schedules at all facilities. In this study, we quantify the percentage of OR hours that can practically be off-loaded from a main campus with long duration workdays. METHODS: One year of cases were evaluated from a health system with a busy main campus, multiple (11) regional facilities with low workload per OR per day, and a common OR information system. RESULTS: The OR time was summed among surgeons meeting the following criteria: no first case start at the main campus that day; performing <4 hour of elective cases at the main campus that day; and doing at least 1 case at any of the regional facilities within the preceding or following week. The OR time potentially moveable was <0.8% (95% CI, 0.7% to 0.8%) of the total OR time used by all surgeons operating at the main campus, considerably less than the managerially important threshold of "≥ 5.0%" (P < 0.0001). The principal reason for the result was that few (10%) OR hours at the main campus were used by surgeons performing <4 hour of cases that day. To understand why so little OR time could be moved, we performed secondary analysis of different data from 21 facilities nationwide. Larger hours of cases per OR per workday (e.g., 7.8 hour at the main facility) were commonly associated with larger percentages of workdays for which single surgeons filled an OR for the day (r = 0.87 ± 0.05). CONCLUSIONS: For many health systems, investing in the software and personnel to coordinate case scheduling among facilities is unlikely to be of benefit, either operationally or financially.