Susan Moffatt-Bruce

Risk factors for retained surgical items: a meta-analysis and proposed risk stratification system

BACKGROUNDnRetained surgical items (RSI) are designated as completely preventable never events. Despite numerous case reports, clinical series, and expert opinions few studies provide quantitative insight into RSI risk factors and their relative contributions to the overall RSI risk profile. Existing case-control studies lack the ability to reliably detect clinically important differences within the long list of proposed risks. This meta-analysis examines the best available data for RSI risk factors, seeking to provide a clinically relevant risk stratification system.nnnMETHODSnNineteen candidate studies were considered for this meta-analysis. Three retrospective, case-control studies of RSI-related risk factors contained suitable group comparisons between patients with and without RSI, thus qualifying for further analysis. Comprehensive Meta-Analysis 2.0 (BioStat, Inc, Englewood, NJ) software was used to analyze the following common factor variables compiled from the above studies: body-mass index, emergency procedure, estimated operative blood loss >500xa0mL, incorrect surgical count, lack of surgical count, >1 subprocedure, >1 surgical team, nursing staff shift change, operation afterhours (i.e., between 5 PM and 7 AM), operative time, trainee presence, and unexpected intraoperative factors. We further stratified resulting RSI risk factors into low, intermediate, and high risk.nnnRESULTSnDespite the fact that only between three and six risk factors were associated with increased RSI risk across the three studies, our analysis of pooled data demonstrates that seven risk factors are significantly associated with increased RSI risk. Variables found to elevate the RSI risk include intraoperative blood loss >500xa0mL (odds ratio [OR] 1.6); duration of operation (OR 1.7); >1 subprocedure (OR 2.1); lack of surgical counts (OR 2.5); >1 surgical team (OR 3.0); unexpected intraoperative factors (OR 3.4); and incorrect surgical count (OR 6.1). Changes in nursing staff, emergency surgery, body-mass index, and operation afterhours were not significantly associated with increased RSI risk.nnnCONCLUSIONSnAmong the common risk factors reported by all three case-control studies, seven synergistically show elevated RSI risk across the pooled data. Based on these results, we propose a risk stratification scheme and issue a call to arms for large, prospective, and multicenter studies evaluating effects of specific changes at the institutional level (i.e., universal surgical counts, radiographic verification of the absence of RSI, and radiofrequency labeling of surgical instruments and sponges) on the risk of RSI. Overall, our findings provide a meaningful foundation for future patient safety initiatives and clinical studies of RSI occurrence and prevention.

The limits of checklists: handoff and narrative thinking

Concerns about the role of communication failures in adverse events coupled with the success of checklists in addressing safety hazards have engendered a movement to apply structured tools to a wide variety of clinical communication practices. While standardised, structured approaches are appropriate for certain activities, their usefulness diminishes considerably for practices that entail constructing rich understandings of complex situations and the handling of ambiguities and unpredictable variation. Drawing on a prominent social science theory of cognition, this article distinguishes between two radically different modes of human thought, each with its own strengths and weaknesses. The paradigmatic mode organises context-free knowledge into categorical hierarchies that emphasise member-to-category relations in order to apply universal truth conditions. The narrative mode, on the other hand, organises context-sensitive knowledge into temporal plots that emphasise part-to-whole relations in order to develop meaningful, holistic understandings of particular events or identities. Both modes are crucial to human cognition but are appropriate responses for different kinds of tasks and situations. Many communication-intensive practices in which patient cases are communicated, such as handoffs, rely heavily on the narrative mode, yet most interventions assume the paradigmatic mode. Improving the safety and effectiveness of these practices, therefore, necessitates greater attention to narrative thinking.

Human Factors and Human Nature in Cardiothoracic Surgery

t 7:34 A.M. on September 11, 1974, Eastern Air Lines AFlight 212 from Charleston, SC, crashed in an open field 3.3 miles short of runway 36 at Douglas Municipal Airport in Charlotte, NC [1]. There was little or no wind, and the visibility was limited due to patchy dense ground fog. Of the 82 people on board, 11 survived. Notably, 5 flights preceded Flight 212 onto runway 36 without difficulty that morning. Partly based on the cockpit voice recorder, the National Transportation Safety Board determined that the likely cause of the crash was “the flight crew’s lack of altitude awareness at critical points during the approach due to poor cockpit discipline in that the crew did not follow prescribed procedures” [1]. Specific issues with discipline and prescribed procedures were as follows: “During the descent, until about 2 minutes and 30 seconds prior to the sound of impact, the flight crew engaged in conversations . . . (that) covered a number of subjects, from politics to used cars, and both crew members expressed strong views and mild aggravation concerning the subjects discussed. The Safety Board believes that these conversations were distractive and reflected a casual mood and lax cockpit atmosphere, which continued throughout the remainder of the approach and which contributed to the accident” [1]. In 1981, in response to aviation accidents, the Federal Aviation Administration imposed the “Sterile Cockpit Rule,” which states that pilots are to refrain from nonessential activities or conversations that could distract or interfere with their duties during critical phases of flight and operations below 10,000 feet [2]. Surgical errors and adverse events include wrong or delayed operations and judgment lapses that lead to incorrect procedures [3–7]. It is estimated that 54% of the adverse events in patients undergoing operations surgery are preventable [7]. In patients undergoing coronary artery bypass grafting, for whom the risk-adjusted mortality rate ranges from 1.3% to 3.1%, approximately one-third of associated deaths may be preventable, with most occurring in the operating room and intensive care unit [6]. Surgical outcomes are often attributed primarily to the technical skills of the surgeon: when errors are made, the surgeon’s competence is questioned [3, 4, 8–10]. The notion that the surgeon is often held solely accountable is

Improving Medication Administration Safety in Solid Organ Transplant Patients Through Barcode-Assisted Medication Administration

Solid organ transplant recipients are prescribed a high number of medications, increasing the potential for medication errors. Barcode-assisted medication administration (BCMA) is technology that reduces medication administration errors. An observational study was conducted at an academic medical center solid organ transplant unit before and after BMCA implementation. Medication accuracy was determined and administration errors were categorized by type and therapeutic class of medication. A baseline medication administration error rate of 4.8% was observed with wrong dose errors representing 78% of the errors. During the post-BCMA period the medication administration error rate was reduced by 68% to 1.5% (P = .0001). Wrong dose errors were reduced by 67% (P = .001), and unauthorized medication administrations were reduced by 73%. Steroids were associated with the highest error rate. The results of this study suggest that routinely adopting BCMA has the potential to reduce medication administration errors in transplant patients.

Navigating a ship with a broken compass: evaluating standard algorithms to measure patient safety.

Objective: Agency for Healthcare Research and Quality (AHRQ) software applies standardized algorithms to hospital administrative data to identify patient safety indicators (PSIs). The objective of this study was to assess the validity of PSI flags and report reasons for invalid flagging. Material and Methods: At a 6-hospital academic medical center, a retrospective analysis was conducted of all PSIs flagged in fiscal year 2014. A multidisciplinary PSI Quality Team reviewed each flagged PSI based on quarterly reports. The positive predictive value (PPV, the percent of clinically validated cases) was calculated for 12 PSI categories. The documentation for each reversed case was reviewed to determine the reasons for PSI reversal. Results: Of 657 PSI flags, 185 were reversed. Seven PSI categories had a PPV below 75%. Four broad categories of reasons for reversal were AHRQ algorithm limitations (38%), coding misinterpretations (45%), present upon admission (10%), and documentation insufficiency (7%). AHRQ algorithm limitations included 2 subcategories: an “incident” was inherent to the procedure, or highly likely (eg, vascular tumor bleed), or an “incident” was nonsignificant, easily controlled, and/or no intervention was needed. Discussion: These findings support previous research highlighting administrative data problems. Additionally, AHRQ algorithm limitations was an emergent category not considered in previous research. Herein we present potential solutions to address these issues. Conclusions: If, despite poor validity, US policy continues to rely on PSIs for incentive and penalty programs, improvements are needed in the quality of administrative data and the standardized PSI algorithms. These solutions require national motivation, research attention, and dissemination support.

Establishing an instrumented training environment for simulation-based training of health care providers: An initial proof of concept

Objective: Several decades of armed conflict at a time of incredible advances in medicine have led to an acknowledgment of the importance of cognitive workload and environmental stress in both war and the health care sector. Recent advances in portable neurophysiological monitoring technologies allow for the continuous real-time measurement and acquisition of key neurophysiological signals that can be leveraged to provide high-resolution temporal data indicative of rapid changes in functional state, (i.e., cognitive workload, stress, and fatigue). Here, we present recent coordinated proof of concept pilot project between private industry, the health sciences, and the USA government where a paper-based self-reporting of workload National Aeronautics and Space Administration Task Load Index Scale (NASA TLX) was successfully converted to a real-time objective measure through an automated cognitive load assessment for medical staff training and evaluation (ACLAMATE). Methods: These real-time objective measures were derived exclusively through the processing and modeling of neurophysiological data. This endeavor involved health care education and training with real-time feedback during high fidelity simulations through the use of this artificial modeling and measurement approach supported by Aptima Corporations FuSE2, SPOTLITE, and PM Engine technologies. Results: Self-reported NASA TLX workload indicators were converted to measurable outputs through the development of a machine learning-based modeling approach. Workload measurements generated by this modeling approach were represented as a NASA TLX anchored scale of 0–100 and were displayed on a computer screen numerically and visually as individual outputs and as a consolidated team output. Conclusions: Cognitive workloads for individuals and teams can be modeled through use of feed forward back-propagating neural networks thereby allowing healthcare systems to measure performance, stress, and cognitive workload in order to enhance patient safety, staff education, and overall quality of patient care. The following core competencies are addressed in this article: Medical Knowledge, Interpersonal Skills, Patient Care, and Professionalism.

Robotic lobectomy has the greatest benefit in patients with marginal pulmonary function

BackgroundPatients with limited pulmonary function have a high risk for pulmonary complications following lobectomy. Robotic approach is currently the least invasive approach. We hypothesized that robotic lobectomy may be of particular benefit in high-risk patients.MethodsWe reviewed our institutional Society of Thoracic Surgeons (STS) data on lobectomy patients from 2012 to 2017. Postoperative outcomes were compared between robotic and open lobectomy groups. High-risk patients were identified by pulmonary function test. Risk of pulmonary complication was assessed by binary logistic regression analysis.ResultsA total of 599 patients underwent lobectomy by robotic (nu2009=u2009287), or by open (nu2009=u2009312) approach, including 189 high-risk patients. Robotic lobectomy patients had a lower rate of prolonged air leak (6% vs. 10%, pu2009=u20090.047), less atelectasis requiring bronchoscopy (6% vs. 16%, pu2009=u20090.02), pneumonia (3% vs. 8%, pu2009=u20090.01), and shorter length of stay (4 vs. 6xa0days, pu2009=u20090.001). Overall pulmonary complication rate was significantly lower after robotic lobectomy in high-risk patients (28% vs. 45%, pu2009=u20090.02), less in intermediate or low risk patients. No significant difference was seen relative to major complication rate (12% vs. 17%, pu2009=u20090.09). After multivariate analysis, when adjusting for age, gender, smoking history, FEV1, DLCO, cardiopulmonary comorbidities, and prior chest surgery, the robotic approach remained independently associated with decreased pulmonary complications (odds ratio 0.54, 95% confidence interval [0.34–0.85], pu2009=u20090.008).ConclusionsRobotic lobectomy has the potential to decrease the risk of postoperative pulmonary complication as compared with traditional open thoracotomy. In particular, patients with limited pulmonary function derive the most benefit from a robotic approach.

From ideas to institute for the design of environments aligned for patient safety (IDEA4PS): The reality of research and the keys to making it work

When starting to develop a research program, the first important order of business is to define what research actually is. Research is not quality improvement; one is not a synonymous with the other. Quality means improving your outcomes, reducing the causes of variation, aligning to best practice, and success is standardization. Quality improvement is about figuring out what works for you as a practitioner, a hospital, or even a healthcare system. Research on the other hand implies improving (or at least attempting to) the outcomes of others, identifying the causes of variation, and building and informing best practice, with the ultimate success being innovation. Research is generalizable and therefore inherently fundable. Research has rules and these rules are very important. First, you cannot build research on bad process. Before a health system can research a process or an idea, they need to have their shop in order. Second, the best research is what you are already planning to do. Do not recreate the wheel. Invest research time in what is important to the institution as well as the patients and providers. Third, remember that research is a bit about opportunity and a lot about relationships. Reach out and get to know who is doing research in your local environment or even nationally and who might want to partner. Finally, there are what you say and what you do. If you are keen to do research, you will have to spend time and commit. The grants do not materialize on their own. They take time, tedious attention to detail, and continuous improvement of submissions.

What is new in critical illness and injury science? Patient safety amidst chaos: Are we on the same team during emergency and critical care interventions?

© 2015 International Journal of Critical Illness and Injury Science | Published by Wolters Kluwer Medknow More than a decade ago, the Institute of Medicine released its famous report To Err Is Human, which set an ambitious agenda for the world to reduce the number of patients harmed by medical errors.[1] In response, a number of new initiatives were launched, including electronic medical records, limited resident and faculty work hours, and implementation of evidence‐based care bundles and checklists.[2] Additionally, federal entities such as the Agency for Healthcare Research and Quality established funding for patient safety research helped to develop patient safety organizations and a set of nationally vetted Patient Safety Goals via the National Quality Forum. In short, much of this work was focused on mitigating the risk of the human element in chaotic healthcare environments.[3] The current issue of the International Journal of Critical Illness and Injury Sciences focuses on complications associated with procedures performed in the intensive care and trauma setting.[4‐10] It is imperative that all key aspects of patient safety should be maintained and observed during any routine and non‐routine invasive procedures, especially those performed outside of the standardized, controlled environment of the operating room.

A qualitative analysis of clinical decompensation in the surgical patient: Perceptions of nurses and physicians.

Background: There is little knowledge on how health care providers individually interpret and communicate early warning signs to other providers. The aim of the study described here was to qualitatively assess the similarities and differences in how nurses and physicians perceive early warning signs that potentially predict clinical decompensation, changes in clinical acuity in surgical patients, and need for escalation of care. Methods: Ethnographic interviews were conducted with nurses, surgical residents, and attending surgeons on an acute care medical–surgical unit. Constant comparative analysis was used to analyze and draw conclusions from the interview data. Results: There were many areas of strong agreement across all care providers including the same data analyzed, importance of temporal trends, and lower acuity level for an established patient. However, physicians differed from nurses in that their primary indicator of patient stability was their level of confidence in the current diagnosis. Nurses, however, deemed patients to be stable only when their symptoms resolved. Other differences were the methods and frequency they used to monitor unstable patients. Conclusion: Differences in the type of communication and clinicians mental models of acuity and stability could lead to coordination failures and adverse events. Understanding and addressing these differences has the potential to improve outcomes.