Bibliographic record
Abstract
The landmark 1999 Institute of Medicine report, To Err is Human, focused attention on unintentional harm and medical error. The report revealed that approximately 98,000 Americans die in hospitals each year due to preventable error.1 Since its publication, patient safety and quality improvement has assumed a central role in health care delivery. Yet despite decades of efforts, patients continue to suffer preventable harm. More recent reports indicate that upwards of 440,000 patients,2 each year suffer some type of preventable harm that contributes to their death, making medical errors the third leading cause of death in the United States behind heart disease and cancer. In orthopaedics, a 2009 American Association of Orthopaedic Surgeons members’ survey revealed that medical errors continue to pose a threat to patient safety, with equipment and communication errors representing the highest frequency of errors.3 Organizations in other highly complex and hazardous industries such as commercial aviation and nuclear power have attained the status of high-reliable organizations through achieving and sustaining remarkable levels of safety; however, health care still struggles to achieve this same level of reliability. Within orthopaedic surgery the complexity of perioperative care for each patient is remarkable, and the opportunity for errors to occur throughout an individual patients’ perioperative management are tremendous. In 1991 James Reason4 proposed the “Swiss Cheese Model” of system failure in which he describes that every step in a process has the potential for failure. As shown in Figure 1, when each step in a process fails to capture an error from the previous step, or when all of the “holes” align, this error has the potential to negatively impact the final outcome. Although we know that it is impossible to perfect human behavior and that humans are prone to error, the question becomes how to effectively implement processes and interventions while shrinking the holes through adding structure and communication to current practice (Fig. 1).FIGURE 1: Reason’s Swiss cheese model for errors.VARIABILITY: UNEXPLAINED VARIABILITY REFLECTS SUBOPTIMAL CARE Academic medical centers are often expected to discover the next breakthrough in medical knowledge and practice. Sometimes this may seem antithetical toward implementing structure to standardize care. However, when navigating this tension, it is important to differentiate between “mindful” variation and “mindless” variation. “Mindful” variation comes from the knowledge that each patient may be different and some treatments may not work and leads to a curiosity to learn and improve. “Mindless” variation comes without any reasoning, evidence, or lessons to learn. This type of variation is one of the biggest adversaries to optimal patient care. Our goal should be to dampen “mindless” variation while accelerating “mindful” variation and assessing its results. Although existing evidence should always be used to guide expert opinion and physician practices when available, there are existing gaps in the literature where evidence is unobtainable because of ethical concerns of appropriate study design. As a result, these gaps are filled-in based on the different training and expertise of the physician, naturally resulting in significant practice variability. A recent survey by the lead author of 25 expert pediatric orthopaedic surgeons assessing current practices of intraoperative neuromonitoring (IONM) uncovered significant variability in site-specific practices of IONM for patients undergoing spinal deformity surgery.5 Similarly, a recent study by Glotzbecker and colleagues6,7 revealed significant variability in preoperative infection prophylaxis for patients undergoing spinal deformity surgery and also significant variability in deep vein thrombosis prophylaxis. Even when existing evidence around certain procedures is high, variability in compliance exists. We know that hand hygiene is an effective method of reducing hospital-acquired infections and the Centers for Disease Control and Prevention, World Health Organization (WHO), Joint Commission, and Institute for Healthcare Improvement have all developed hand-hygiene compliance programs.8 Despite these efforts, compliance to hand-hygiene protocols continues to hover around 50% adherence.9 The nuclear and aviation industry have a compelling history of improving and sustaining safety from which health care could learn. These high-reliability organizations (HROs) “operate under very trying conditions all the time and yet manage to have fewer than their fair share of accidents.”10 In these industries, risk is a function of probability and consequence. By decreasing the probability of an accident, HROs have the ability to recast themselves from high-risk enterprises to merely a high-consequence enterprise. This can be achieved by addressing chaotic processes, where failure consists of >20% of opportunities and achieving high levels of reliability of <5 failures of 10000 opportunities (approximately 99% reliability), which is the philosophy behind philosophies and methods such as Lean Six Sigma.11 This requires a combination of process design, creating a culture of reliability and integrating human factors design. Process design consists of using best practices, or focusing and simplifying tasks to reduce ambiguity. Reliability culture can be generated by identifying and defining core values and vertical integration, setting behavioral expectations for all, being fair, and creating full accountability. Human factors design is implemented by creating intuitive design, and developing systems that make it impossible to do the wrong thing. INFRASTRUCTURE: CHAOTIC WORK ENVIRONMENT BENEFITS FROM STRUCTURE In an era of increased focus on quality and safety, checklists, standards, and other protocol tools have achieved real progress. Well-constructed checklists codify interventions, remove ambiguity, and increase reliability of care processes, thereby reducing mindless variability. Checklists are powerful tools for promoting and evaluating specific aspects of care or competence; they can translate best practices to the bedside. Redesigning tasks to eliminate needless complexity and ambiguity can decrease the learning curve for resident physicians. One of the greatest successes of the use of checklists was the WHO Safe Surgery Checklist, published in 2008, which significantly decreased complications and death following surgical procedures.12 A consistent finding, however has been that these “technical” solutions are not just linked to, but rely on, “adaptive” change. Addressing and tailoring interventions to local culture and context is a barrier that must overcome on the path to scalable, sustainable quality improvement. Checklists are used—and useful—only if the staff believes that they will truly change care and improve the outcome. Simply mandating use of the WHO Safe Surgery Checklist in 133 surgical hospitals in Ontario did not improve outcomes.13 It is also essential that health care professionals do not become slaves to checklists, which should act as aids and not burdens. For example, most improvement efforts focus on one type of harm, but patients are at risk for multiple harms. Each harm type needs a checklist; each checklist needs multiple items; and some of these items may need to be performed multiple times a day. This creep would require an unwieldy checklist, relying on the heroism of clinicians to manage it, when it would be more reliable to design safer systems. Equally important to the development of safest practices is the creation of a culture of safety. Widespread deployment of checklists without an appreciation of how or why they work will fail to move the needle far enough. Checklists help users perform a task by reducing ambiguity about what to do. However, the assumption that a technical solution (checklists) can solve an adaptive (sociocultural) problem may be dangerous. Without attention to adaptive work, checklists could suffer similar fate as guidelines—often left unused, even when robust. Initiatives such as the Michigan Keystone study,14 in which a collaborative of intensive care units in Michigan used an adaptive checklist to reduce central-line–associated blood stream infections provide valuable lessons on how to achieve results in a wider context of Pediatric Orthopaedics: recruit advocates within the organization, keep the team focused on goals, create an alliance with administration to secure resources if necessary, shift power relations, create social and reputational incentives for cooperation, open channels of communications with centers that face the same challenges, and use audit and feedback as a data-driven approach. The checklists are a component of a complex, culture, and organizational change effort. Conferring legitimacy and securing buy-in is also essential. This can be achieved by allowing teams to customize implementation locally and modify checklists to fit their unique barriers and culture. This can change workers’ motives for cooperation so that they internalize new norms. Proper implementation of these interventions is dependent on a culture geared toward patient safety. Training in teamwork can be a powerful tool. Much has been written recently about optimizing the function of the team. Key to this is efforts to decrease the perception of hierarchy so that “The Power of the Crowd” may surface. Some work remains to be done here. In 2000, Sexton et al15 discovered that attending surgeons rated their teamwork level as “high” as opposed to opposite reactions from nurses and anesthesia residents. Studies from the Joint Commission have found that communication breakdown contributed to nearly 70% of all sentinel events reported.16 In their results, 55% of surveys cited organizational culture as a barrier to effective communication.16 In an effort to borrow concepts from various HRO, techniques such as crew resource management can be promoted to improve communication. Crew resource management promotes 3 essential concepts: active participation across the team, challenges and responses, and leveling the playing field so all can speak up. TeamSTEPPS (http://teamstepps.ahrq.gov/), developed by the Department of Defense and Agency for Healthcare Research and Quality is yet another structured communication protocol. TeamSTEPPS revolves around 4 core principles designed to enhance performance: leadership, communication, situation monitoring, and mutual support. Effective orthopaedic surgeons should organize their team, articular clear goals, make decisions through collective input of members, empower members to speak up and challenge them when appropriate, actively promote and facilitate good teamwork, and become skillful at conflict resolution. Situation monitoring consists of continually scanning and assessing the environment to maintain situational awareness. This could include the status of patient, team members, the environment, and progress toward the goal. CONSENSUS: BETTER DECISIONS ARE USUALLY MADE IN GROUPS While the first step in combating practice variability is the development of guidelines, the availability of evidence to create the infrastructure needed is not always available. A systematic review by Glotzbecker et al17 regarding risk factors and preventive strategies for surgical site infection (SSI) following pediatric spine surgery found that there was no grade A evidence for patient-related risk factors in pediatric scoliosis surgery, sparse grade A evidence for perioperative interventions in scoliosis surgery, and that many interventions had insufficient evidence. In the face of the lack of evidence, orthopaedic surgeons can either rely on the best available evidence or choose to develop consensus-driven best practice guidelines (BPG). This can be accomplished via the shared experience and opinions of top experts using formal methods of consensus development including the Delphi method and nominal group process.18 Internally motivated efforts may be better in changing communities and social norms. Relying on financial incentives only work when there is limited motivation to improve quality. However, sufficient motivation already exists in Pediatric Orthopaedics. Regulation has also done little and risks creating a punitive culture within health care. Solely relying on financial incentives and regulation has also done little to move the needle in terms of quality, as seen by the large volume of preventable medical errors that still occur every year. The “wisdom of crowds” also has the ability to affect surgical decision making. At the lead author’s institution, all preoperative patients are discussed in weekly indication conferences, where surgical plans can be debated, including topics such as surgical levels, construct choices, staging of surgeries, traction, additional procedures, and the use of growing constructs versus fusion. Case Study 1: The Development of a BPG for Infection Prevention in Spine Deformity Surgery During the third quarter of 2008, an unexpected increase in the rate SSIs following scoliosis surgery was noted at the lead investigator’s institution. Previously, the average quarterly SSI rate was 7%; however, during the infection spike, the SSI rate for posterior scoliosis surgery rose to over 23% (Fig. 2).FIGURE 2: Run chart with increase in surgical site infections (SSIs) in Q3 2008.This prompted an in-depth review of the infection-prevention protocol by an interdisciplinary team of pediatric orthopaedic surgeons, infectious disease experts, and operating room nursing and staff. This effort revealed that there were deficiencies in the timing of prophylactic antibiotics, knowledge of the support staff of proper infection-prevention measures, uniform surgical techniques for wound lavage, and a higher percentage of gram-negative infections than traditionally demonstrated in the literature. This in-depth analysis led to the development and implementation of a new standardized multimodal SSI prevention protocol at the end of 2009 that included: An antibiotic prophylaxis educational program to ensure correct preincision timing and correct dose. Addition of tobramycin to the perioperative prophylaxis regimen for pediatric spine patients based on the susceptibility of pathogens associated with SSIs at our institution. Required preoperative chlorhexidine gluconate bathing for all patients. Mandatory 3 L of warmed saline lavage before closure for all spine cases. In the 12 months after initiating the new protocol, zero cases of infection were observed (Fig. 3).FIGURE 3: Run chart depicting results of standardization of surgical site infection (SSI) prevention protocols.More often than not, areas of practice variability exist where there is little or no evidence to guide clinical judgment and decision making. In the area of infection prevention in spine surgery, a systematic literature review assessing evidence for risk factors and preventative strategies for SSI after spine surgery found poor evidence for patient-related risk factors and perioperative interventions, and found that many currently used interventions have insufficient evidence for their use. Even further, a survey of infection-prevention measures of all POSNA members who perform spine surgery revealed significant variability in infection-prevention practices. In March of 2011, with an aim at broadening our experience in decreasing infection rates through a multidisciplinary approach, we organized a consensus group of 20 leading spine surgeons and 3 infectious disease specialists from across the country with the aim of developing a BPG for infection prevention in high-risk spine deformity surgery. Consensus group members were presented with several interventions to be included in the guideline, including the results of a current practices survey completed by all group members and the results of a systematic literature review. Utilizing the Delphi and Nominal Group Technique18 through iterative surveys and several face-to-face discussions, a guideline consisting of 14 interventions was finalized in March of 2012 based on the expertise and consensus of all members involved19 (Fig. 4).FIGURE 4: Consensus results of Delphi process for the Best Practice Guidelines for infection prevention in high-risk spine deformity surgery.A recent survey of all sites involved in the creation of the guideline revealed that after 1 year of implementing the guideline at their respective institutions, rates of adherence to the checklist were high and infection rates for high-risk spine deformity surgeries remained stable or decreased almost universally. Case Study 2: IONM Checklist After the successful creation of the BPG for infection prevention, we used our experience to focus on another area of spine deformity surgery with poor evidence and significant variability, the response to changes in IONM. Drawing upon the same study design used previously, a consensus group of orthopaedic spine surgeons, neurosurgeons specializing in spine deformity surgery, neurologists, and monitoring technologists was formed with the goal of developing a consensus-based checklist for responding to IONM changes in patients with a stable spine. Beginning in March 2013, using the Delphi and Nominal Group Technique,18 a literature review of neuromonitoring in spine deformity surgery and several rounds of surveys aimed at developing consensus on items to be included in the final checklist were administered to consensus group participants. Following several rounds of surveys and 2 face-to-face meetings, a preliminary checklist was created and all participants agreed to a 4-month trial of the checklist aimed at optimizing the checklist through its use in real-time. In January of 2014, utilizing feedback received from the real-time optimization of the checklist a final survey was administered to consensus group participants. Finally, in February 2014 at the final face-to-face meeting, 100% agreement was reached on the final version of the IONM checklist5 (Fig. 5).FIGURE 5: Checklist for the response to intraoperative neuromonitoring changes in patients with a stable spine.SUSTAINABLY MAKING CARE BETTER Beyond imparting technical skills, we need to model care and engage colleagues at the deepest and most positive levels. We need less of a stream of praise for behavior but a mindset that encourages all of us to turn inward and access our own as who to improve. the of quality on that of quality is It is with the of our patients and for orthopaedic surgery that we aim to decrease variability through the use of consensus-driven and We also to use these guidelines to create infrastructure and use in a more to make sustainable and developed as a of these include guidelines, and based on the consensus-based to are also quarterly report for quality, safety, and a structure to improve communication during a team toward and checklists to engage all team members, from the surgeons to the and more important the and patients. an SSI a cause analysis is also done so that is to potential risks and learn about areas for improvement. In this we to standardize improve communication, and create a and highly reliable culture, all by is no that health care has often the to quality and best practices. to a group that is to The in and pediatric surgical care has not yet the same as our is the time to act to quality, safety, and for before the
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".