An overview and critique of the use of cumulative sum methods with surgical learning curve data.

Cumulative sum (CUSUM) plots and methods have wide-ranging applications in healthcare. We review and discuss some issues related to the analysis of surgical learning curve (LC) data with a focus on three types of CUSUM statistical approaches. The underlying assumptions, benefits, and weaknesses of each approach are given. Our primary conclusion is that two types of CUSUM methods are useful in providing visual aids, but are subject to overinterpretation due to the lack of well-defined decision rules and performance metrics. The third type is based on plotting the CUSUM of the differences between observations and their average value. We show that this commonly applied retrospective method is frequently interpreted incorrectly and is thus unhelpful in the LC application. Curve-fitting methods are more suitable for meeting many of the goals associated with the study of surgical LCs.

Dynamic probability control limits for risk-adjusted CUSUM charts based on multiresponses.

For a patient who has survived a surgery, there could be several levels of recovery. Thus, it is reasonable to consider more than two outcomes when monitoring surgical outcome quality. The risk-adjusted cumulative sum (CUSUM) chart based on multiresponses has been developed for monitoring a surgical process with three or more outcomes. However, there is a significant effect of varying risk distributions on the in-control performance of the chart when constant control limits are applied. To overcome this disadvantage, we apply the dynamic probability control limits to the risk-adjusted CUSUM charts for multiresponses. The simulation results demonstrate that the in-control performance of the charts with dynamic probability control limits can be controlled for different patient populations because these limits are determined for each specific sequence of patients. Thus, the use of dynamic probability control limits for risk-adjusted CUSUM charts based on multiresponses allows each chart to be designed for the corresponding patient sequence of a surgeon or a hospital and therefore does not require estimating or monitoring the patients' risk distribution. Copyright © 2017 John Wiley & Sons, Ltd.

Improved implementation of the risk-adjusted Bernoulli CUSUM chart to monitor surgical outcome quality.

METHODOLOGY ISSUE: The traditional implementation of the risk-adjusted Bernoulli cumulative sum (CUSUM) chart for monitoring surgical outcome quality requires waiting a pre-specified period of time after surgery before incorporating patient outcome information. PROPOSED SOLUTION: We propose a simple but powerful implementation of the risk-adjusted Bernoulli CUSUM chart that incorporates outcome information as soon as it is available, rather than waiting a pre-specified period of time after surgery. EVALUATION: A simulation study is presented that compares the performance of the traditional implementation of the risk-adjusted Bernoulli CUSUM chart to our improved implementation. We show that incorporating patient outcome information as soon as it is available leads to quicker detection of process deterioration. ADVICE TO PRACTITIONERS: Deterioration of surgical performance could be detected much sooner using our proposed implementation, which could lead to the earlier identification of problems.

Debate: what is the best method to monitor surgical performance?

BACKGROUND: There is considerable recent interest in the monitoring of individual surgeon or hospital surgical outcomes. If one aggregates data over time and assesses performance with a funnel plot, then the detection of any process deterioration or improvement could be delayed. The variable life adjusted display (VLAD) is widely used for monitoring on a case-by-case basis, but we show that use of the risk-adjusted Bernoulli cumulative sum (RA-CUSUM) chart leads to much better performance. DISCUSSION: We use simulation to illustrate that the RA-CUSUM chart has better performance than the VLAD in detecting changes in the rates of adverse events. We recommend the RA-CUSUM approach over the VLAD approach for monitoring surgical performance. If the VLAD is used, we recommend running the RA-CUSUM chart in the background to generate signals that the process performance has changed.

Dynamic probability control limits for risk-adjusted Bernoulli CUSUM charts.

The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, the use of a fixed control limit for the chart leads to a quite variable in-control average run length performance for patient populations with different risk score distributions. To overcome this problem, we determine simulation-based dynamic probability control limits (DPCLs) patient-by-patient for the risk-adjusted Bernoulli CUSUM charts. By maintaining the probability of a false alarm at a constant level conditional on no false alarm for previous observations, our risk-adjusted CUSUM charts with DPCLs have consistent in-control performance at the desired level with approximately geometrically distributed run lengths. Our simulation results demonstrate that our method does not rely on any information or assumptions about the patients' risk distributions. The use of DPCLs for risk-adjusted Bernoulli CUSUM charts allows each chart to be designed for the corresponding particular sequence of patients for a surgeon or hospital.

The impact of varying patient populations on the in-control performance of the risk-adjusted CUSUM chart.

OBJECTIVE: This research is designed to examine the impact of varying patient population distributions on the in-control performance of the risk-adjusted Bernoulli CUSUM chart. DESIGN: The in-control performance of the chart is compared based on sampling the Parsonnet scores with replacement from five realistic subsets of a given distribution. SETTINGS: Five patient mixes with different Parsonnet score distributions are created from a real patient population. MAIN OUTCOME MEASURES: The outcome measures for this research are the in-control average run lengths (ARLs) given varying patient populations. RESULTS: Our simulation results show that the in-control ARLs of the risk-adjusted Bernoulli CUSUM chart with fixed control limits and a given risk-adjustment equation vary significantly for different patient population distributions, and the in-control ARLs decrease as the mean of the Parsonnet scores increases. CONCLUSIONS: The simulation results imply that the control limits should vary based on the particular patient population of interest in order to control the in-control performance of the risk-adjusted Bernoulli CUSUM method.

Evaluation of donor factors contributing to plateletpheresis yields among apheresis platelet donors.

BACKGROUND: The University of California, Irvine Blood Donor Center operates a plateletpheresis donor program utilizing the Amicus Cell Separator. Plateletpheresis donors may donate one or more apheresis platelet (PLT) units per collection event. This study seeks to characterize UC Irvine's donor pool by identifying biometric and demographic attributes predictive of double product (DP) collections. STUDY DESIGN AND METHODS: Biometric, demographic and procedural data from 1,786 apheresis donors were collected and entered into Excel spreadsheets. Of the 1,786 successful plateletpheresis procedures performed from January 2009 to April 2012, 1,442 of the donations were performed using double-needle (DN) kits. Only data from DN-kit collections were used for statistical analyses. The Classification And Regression Tree (CART) algorithm was used to help identify variables predictive of donating multiple PLT units in a single collection event. RESULTS: Donors weighing 75.7 kg or greater appear to be twice as likely to donate DPs as those weighing less than 75.7 kg. For donors weighing less than 75.7 kg, females appear to be twice as likely to donate DPs as males. Donors exhibiting platelet counts of 216.5 K/mcL or greater appear to be twice as likely to donate DPs as those with platelet counts fewer than 216.5 K/mcL. CONCLUSION: Weight, sex, and PLT count were identified as the most predictive donor attributes that separate UCI donors into DP donors and non-DP donors. Greater weights, greater PLT counts, and female sex confer to greater PLT yields per given amount of time.

Effect of nicotine replacement therapy on quitting by young adults in a trial comparing cessation services.

CONTEXT: Young adult smokers have the highest smoking prevalence among all US age groups but are least likely to use evidence-based cessation counseling or medication to quit. OBJECTIVE: Use and effectiveness of nicotine patch were explored in a randomized trial evaluating smoking cessation interventions with this population. PARTICIPANTS: Smokers aged 18 to 30 (n = 3094) were recruited through online and off-line methods and from telephone quit lines and analyzed. DESIGN: Smokers were enrolled in a pretest-posttest trial, and randomized to 1 of 3 cessation services. SETTING: Trial delivering counseling services by self-help booklet, telephone quit lines, or online expert system in the 48 continental United States. INTERVENTION: Smokers could request a free 2-week course of nicotine replacement therapy (NRT) patches from the project. MAIN OUTCOME MEASURE: Follow-up surveys at 12 and 26 weeks assessed smoking abstinence, use of NRT, counseling, and other cessation medications, and smoking-related variables. RESULTS: Overall, 69.0% of smokers reported using NRT (M = 3.2 weeks) at 12 weeks and 74.8% (M = 3.3 weeks) at 26 weeks. More smokers who were sent the free nicotine patches (n = 1695; 54.8%) reported using NRT than those who did not receive them (12 weeks: 84.3% vs 41.9%, P < .001; 26 weeks: 87.6% vs 51.1%, P < .001). The use of NRT was associated with greater smoking abstinence at 12 weeks (P < .001) and 26 weeks (P < .05), especially if used for more than 2 weeks (P < .001). Smokers assigned to a self-help booklet or cessation Web site and heavier smokers were most likely to use NRT (P < .05), whereas those reporting marijuana use and binge drinking used NRT less (P < .05). CONCLUSIONS: Many young adults were willing to try NRT, and it appeared to help them quit in the context of community-based cessation services. Strategies should be developed to make NRT available to this age group and support them in using it to prevent lifelong smoking.

Industry payments to academic neurosurgeons in 2021: an open payments cross-sectional analysis.

OBJECTIVE: The Open Payments Program (OPP) was a database started in 2013 by the US government to report payments made by the medical device and pharmaceutical industry to physicians. Neurosurgery is a technologically advanced field that relies heavily on the latest innovations for complex treatment of its patient population. This study sought to explore the financial relationship between academic neurosurgeons and the industry. METHODS: OPP data were reviewed for the year 2021 of all faculty neurosurgeons affiliated with a neurosurgery residency program. Trends related to general payments, research payments, associated research funding, ownership and investment interest, name of the companies making payments, monetary amount of payments per company, and number of payments per company were analyzed. RESULTS: Industry payments to 1151 US academic neurosurgeons were reviewed. These neurosurgeons received $121.4 million in payments. Three hundred thirty-two companies made 18,466 payments. The average payment per neurosurgeon was approximately six-fold higher than that of all other physicians. Vascular and spine subspecialties received the highest payments. A higher proportion of research money was allocated to the Pacific division, while all other categories (including total amount) were higher in the Eastern US. Most financial contributions were made by a small number of companies. CONCLUSIONS: Neurosurgery has been rated by many as a field fueled by research, innovation, and technology. In 2021, academic neurosurgeons had a strong relationship with the medical device and pharmaceutical industry as reflected in the OPP data. While the true impact on patient care cannot be directly measured, the advancement of the field relies heavily on these collaborations.

Does Extended Reality Simulation Improve Surgical/Procedural Learning and Patient Outcomes When Compared With Standard Training Methods?: A Systematic Review.

INTRODUCTION: The use of extended reality (XR) technologies, including virtual, augmented, and mixed reality, has increased within surgical and procedural training programs. Few studies have assessed experiential learning- and patient-based outcomes using XR compared with standard training methods. METHODS: As a working group for the Society for Simulation in Healthcare, we used Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and a PICO strategy to perform a systematic review of 4238 articles to assess the effectiveness of XR technologies compared with standard training methods. Outcomes were grouped into knowledge, time-to-completion, technical proficiency, reactions, and patient outcomes. Because of study heterogeneity, a meta-analysis was not feasible. RESULTS: Thirty-two studies met eligibility criteria: 18 randomized controlled trials, 7 comparative studies, and 7 systematic reviews. Outcomes of most studies included Kirkpatrick levels of evidence I-III (reactions, knowledge, and behavior), while few reported level IV outcomes (patient). The overall risk of bias was low. With few exceptions, included studies showed XR technology to be more effective than standard training methods in improving objective skills and performance, shortening procedure time, and receiving more positive learner ratings. However, XR use did not show significant differences in gained knowledge. CONCLUSIONS: Surgical or procedural XR training may improve technical skill development among trainees and is generally favored over standard training methods. However, there should be an additional focus on how skill development translates to clinically relevant outcomes. We recommend longitudinal studies to examine retention and transfer of training to clinical settings, methods to improve timely, adaptive feedback for deliberate practice, and cost analyses.

Impact of Obesity on Anterior Cervical Discectomy and Fusion (ACDF): Postoperative Morbidity and Mortality.

AIM: To investigate the impact of obesity on postoperative morbidity and mortality in patients who underwent anterior cervical discectomy and fusion (ACDF). MATERIAL AND METHODS: The American College of Surgeons' National Surgical Quality Improvement Project (NSQIP) files from 2006 to 2019 were queried for all patients who underwent an ACDF. Fisher exact tests were used in analyzing univariate differences in preoperative comorbidities and postoperative morbidity and mortality between patients with and without obesity (BMI ?30 kg/ m < sup > 2 < /sup > ). Results with a p value < 0.05 were considered statistically significant. Multivariable logistic regression models were used in determining the independent impact of obesity on ACDF postoperative morbidity and mortality. A p value < 0.017 was required for multivariate statistical significance. RESULTS: There were 96,882 patients who underwent an ACDF from 2006 to 2019 found. 53.77% had non-obese BMI. Patients had statistically significant differences in most perioperative comorbidities and postoperative outcomes on univariate analysis. On multivariate analysis, patients with obesity has decreased adjusted odds of wound infections (aOR=0.7208, CI 0.574-0.9075, p=0.0053), pulmonary events (aOR=0.7939, CI 0.6903-0.9129, p=0.0012), sepsis (aOR=0.5670, CI 0.4359-0.7374, p=2.32E-05), transfusion requirements (aOR=0.5396, CI 0.4498-0.6473, p=3.04E-11), return to operating room (aOR=0.7537, CI 0.6727-0.8447, p=1.17E-06), and length of stay > 10 days (aOR=0.7061, CI 0.6438-0.7744, p=1.49E-13). CONCLUSION: Obesity is a protective factor toward ACDF postoperative complications. Obesity as a marker of patient selection criteria for ACDF procedures should not be used by spine surgeons.

Occupational therapy practitioners' perceptions of important competencies for handwriting evaluation and intervention in school-aged children.

OBJECTIVE: The primary purpose of this study was to identify the practitioner competencies that occupational therapists perceive as important for handwriting evaluation and intervention in school-aged children. A secondary purpose was to compare the practitioner perceptions of those in school-based practice with those from other primary practice settings. METHOD: A stratified random sample of 376 occupational therapists recruited from a national professional organization database participated by completing a survey instrument containing 80 competency items. RESULTS: A majority of the 80 practitioner competency items were perceived to be of high importance to the respondent groups. A significance difference in perception when comparing the school-based practitioners to all other practitioners was revealed in only 3-12 competency summary categories. CONCLUSION: Practitioner competency survey items were perceived to be of high importance to the participants. School-based practitioner perceptions of competency were, for the most part, mainly similar to those in other primary practice settings.

Learning curve for completely thoracoscopic anatomic sublobar resection.

BACKGROUND: Minimally invasive anatomic sublobar resection is increasingly being considered as an alternative to lobectomy in selected cases. However, this remains a technically challenging procedure and only 5 studies evaluating learning curves have been published to date. The aim of this study was to evaluate a single surgeon's learning curve for completely thoracoscopic anatomic sublobar resection. METHODS: A retrospective review was conducted of all thoracoscopic anatomic sublobar resections by one surgeon proficient in VATS lobectomy between January 2015 and January 2020. The primary outcome was operative time. Secondary outcomes were perioperative complications, duration of chest tube drainage and length of stay. RESULTS: There were 67 thoracoscopic anatomic sublobar resections performed in 66 patients. A Time-series plot and Cumulative Sum analysis of operative times showed a drop off after case 32, suggesting achievement of competency. After case 32, mean operative times were decreased (128.59±32.42 min. vs. 153.63±40.16 min, P=0.013) and there was a trend toward decreased blood loss (124.26±76.0 vs. 175.0±141.99 mL, P=0.073). A percentage 13.6% of patients had postoperative complications other than air leak and 88,9% of these were Clavien-Dindo class 1-2; postoperative complications were evenly distributed before and after case 32. Cumlulative Sum curves for the duration of chest tube drainage and length of stay did not show any significant change during the study period. CONCLUSIONS: This study suggests that for a surgeon proficient in VATS lobectomy, competency in completely thoracoscopic anatomic sublobar resection can be achieved after 32 cases and can be accomplished in a way that does not compromise perioperative outcomes.

Robot Operating System 2: Design, architecture, and uses in the wild.

The next chapter of the robotics revolution is well underway with the deployment of robots for a broad range of commercial use cases. Even in a myriad of applications and environments, there exists a common vocabulary of components that robots share-the need for a modular, scalable, and reliable architecture; sensing; planning; mobility; and autonomy. The Robot Operating System (ROS) was an integral part of the last chapter, demonstrably expediting robotics research with freely available components and a modular framework. However, ROS 1 was not designed with many necessary production-grade features and algorithms. ROS 2 and its related projects have been redesigned from the ground up to meet the challenges set forth by modern robotic systems in new and exploratory domains at all scales. In this Review, we highlight the philosophical and architectural changes of ROS 2 powering this new chapter in the robotics revolution. We also show through case studies the influence ROS 2 and its adoption has had on accelerating real robot systems to reliable deployment in an assortment of challenging environments.

Comparison of the early aberration reporting system (EARS) W2 methods to an adaptive threshold method.

In this paper we examine some of the methodologies implemented by the Centers for Disease Control and Prevention's (CDC) BioSense program. The program uses data from hospitals and public health departments to detect outbreaks using the Early Aberration Reporting System (EARS). The EARS method W2 allows one to monitor syndrome counts (W2count) from each source and the proportion of counts of a particular syndrome relative to the total number of visits (W2rate). We investigate the performance of these methods, which are designed using an empiric recurrence interval (RI), with simulated parametric data. Counts from the Poisson and negative binomial distributions are generated, and used to examine W2 properties. An adaptive threshold monitoring method is introduced based on fitting sample data to the above distributions, then converting the current value to a Z-score through a p-value. We compare the thresholds required to obtain given values of the RI for different sets of parameter values. We then simulate 1-week outbreaks in our data and calculate the proportion of times these methods correctly signal an outbreak using Shewhart and exponentially weighted moving average (EWMA) charts. Our results indicate that the adaptive threshold method gives more consistent statistical performance across different parameter sets and amounts of baseline historical data used for computing the statistics. For the sensitivity analysis, the EWMA chart is superior to its Shewhart counterpart in nearly all cases and the adaptive threshold methods tend to outperform the W2 methods. Copyright © 2011 John Wiley & Sons, Ltd.

Spatiotemporal surveillance methods in the presence of spatial correlation.

Health surveillance involves collecting public health data on chronic and infectious diseases to detect changes in disease incidence rates in order to improve public health. Timely detection of disease clusters is essential in prospective public health surveillance. Most existing health surveillance research is based on the assumption that observations from different regions are independent. This paper proposes a set of multivariate surveillance schemes generalized from well-known detection methods in multivariate statistical process control based on likelihood ratio tests. We use Monte Carlo simulations to compare these methods for health surveillance in the presence of spatial correlations. By taking advantage of correlations among regions,the proposed schemes are able to perform better than existing surveillance methods and provide faster and more accurate detection of outbreaks. An example of breast cancer in New Hampshire is presented to demonstrate the application of these methods when observations are spatially correlated counts.

Can long-term historical data from electronic medical records improve surveillance for epidemics of acute respiratory infections? A systematic evaluation.

BACKGROUND: As the deployment of electronic medical records (EMR) expands, so is the availability of long-term datasets that could serve to enhance public health surveillance. We hypothesized that EMR-based surveillance systems that incorporate seasonality and other long-term trends would discover outbreaks of acute respiratory infections (ARI) sooner than systems that only consider the recent past. METHODS: We simulated surveillance systems aimed at discovering modeled influenza outbreaks injected into backgrounds of patients with ARI. Backgrounds of daily case counts were either synthesized or obtained by applying one of three previously validated ARI case-detection algorithms to authentic EMR entries. From the time of outbreak injection, detection statistics were applied daily on paired background+injection and background-only time series. The relationship between the detection delay (the time from injection to the first alarm uniquely found in the background+injection data) and the false-alarm rate (FAR) was determined by systematically varying the statistical alarm threshold. We compared this relationship for outbreak detection methods that utilized either 7 days (early aberrancy reporting system (EARS)) or 2-4 years of past data (seasonal autoregressive integrated moving average (SARIMA) time series modeling). RESULTS: In otherwise identical surveillance systems, SARIMA detected epidemics sooner than EARS at any FAR below 10%. The algorithms used to detect single ARI cases impacted both the feasibility and marginal benefits of SARIMA modeling. Under plausible real-world conditions, SARIMA could reduce detection delay by 5-16 days. It also was more sensitive at detecting the summer wave of the 2009 influenza pandemic. CONCLUSION: Time series modeling of long-term historical EMR data can reduce the time it takes to discover epidemics of ARI. Realistic surveillance simulations may prove invaluable to optimize system design and tuning.

The effect of temporal aggregation level in social network monitoring.

Social networks have become ubiquitous in modern society, which makes social network monitoring a research area of significant practical importance. Social network data consist of social interactions between pairs of individuals that are temporally aggregated over a certain interval of time, and the level of such temporal aggregation can have substantial impact on social network monitoring. There have been several studies on the effect of temporal aggregation in the process monitoring literature, but no studies on the effect of temporal aggregation in social network monitoring. We use the degree corrected stochastic block model (DCSBM) to simulate social networks and network anomalies and analyze these networks in the context of both count and binary network data. In conjunction with this model, we use the Priebe scan method as the monitoring method. We demonstrate that temporal aggregation at high levels leads to a considerable decrease in the ability to detect an anomaly within a specified time period. Moreover, converting social network communication data from counts to binary indicators can result in a significant loss of information, hindering detection performance. Aggregation at an appropriate level with count data, however, can amplify the anomalous signal generated by network anomalies and improve detection performance. Our results provide both insights on the practical effects of temporal aggregation and a framework for the study of other combinations of network models, surveillance methods, and types of anomalies.

Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial.

OBJECTIVE: This study evaluated a new insulin delivery system designed to reduce insulin delivery when trends in continuous glucose monitoring (CGM) glucose concentrations predict future hypoglycemia. RESEARCH DESIGN AND METHODS: Individuals with type 1 diabetes (n = 103, age 6-72 years, mean HbA1c 7.3% [56 mmol/mol]) participated in a 6-week randomized crossover trial to evaluate the efficacy and safety of a Tandem Diabetes Care t:slim X2 pump with Basal-IQ integrated with a Dexcom G5 sensor and a predictive low-glucose suspend algorithm (PLGS) compared with sensor-augmented pump (SAP) therapy. The primary outcome was CGM-measured time <70 mg/dL. RESULTS: Both study periods were completed by 99% of participants; median CGM usage exceeded 90% in both arms. Median time <70 mg/dL was reduced from 3.6% at baseline to 2.6% during the 3-week period in the PLGS arm compared with 3.2% in the SAP arm (difference [PLGS - SAP] = -0.8%, 95% CI -1.1 to -0.5, P < 0.001). The corresponding mean values were 4.4%, 3.1%, and 4.5%, respectively, represent-ing a 31% reduction in the time <70 mg/dL with PLGS. There was no increase in mean glucose concentration (159 vs. 159 mg/dL, P = 0.40) or percentage of time spent >180 mg/dL (32% vs. 33%, P = 0.12). One severe hypoglycemic event occurred in the SAP arm and none in the PLGS arm. Mean pump suspension time was 104 min/day. CONCLUSIONS: The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control.