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Using Simulation to Improve Systems-Based Practices
ARTICLE IN PRESS The Joint Commission Journal on Quality and Patient Safety 2017; ■■:■■–■■
Using Simulation to Improve Systems-Based Practices Aimee K. Gardner, PhD; Maximilian Johnston, MRCS; James R. Korndorffer, Jr., MD; Imad Haque, MD; John T. Paige, MD
Background: Ensuring the safe, effective management of patients requires efficient processes of care within a smoothly operating system in which highly reliable teams of talented, skilled health care providers are able to use the vast array of high-technology resources and intensive care techniques available. Simulation can play a unique role in exploring and improving the complex perioperative system by proactively identifying latent safety threats and mitigating their damage to ensure that all those who work in this critical health care environment can provide optimal levels of patient care. Methods: A panel of five experts from a wide range of institutions was brought together to discuss the added value of simulation-based training for improving systems-based aspects of the perioperative service line. Panelists shared the way in which simulation was demonstrated at their institutions. The themes discussed by each panel member were delineated into four avenues through which simulation-based techniques have been used. Results: Simulation-based techniques are being used in (1) testing new clinical workspaces and facilities before they open to identify potential latent conditions; (2) practicing how to identify the deteriorating patient and escalate care in an effective manner; (3) performing prospective root cause analyses to address system weaknesses leading to sentinel events; and (4) evaluating the efficiency and effectiveness of the electronic health record in the perioperative setting. Conclusion: This focused review of simulation-based interventions to test and improve components of the perioperative microsystem, which includes literature that has emerged since the panel’s presentation, highlights the broad-based utility of simulation-based technologies in health care.
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imulation involves re-creating medical tasks and environments to allow learners to develop and hone both technical and nontechnical skills. Work demonstrating the success of simulation-based curricula has not only led to requirements of its inclusion in residency training curricula,1 but simulation has also been chosen as the modality for national certification exams in surgery.2,3 Outside its role within training programs, though, simulation can be a critical tool to better understand and refine the larger health care system. Simulation is particularly conducive to helping address challenges in this way because it re-creates rare, yet high-risk events and conditions in which providers can practice their responses;4 it provides a safe learning environment in which learners can try and fail without consequences to patients; and—because of its experiential nature—it creates an immersive learning environment in which learners can suspend disbelief, allowing for better retention of knowledge, skills, and attitudes learned in the setting. Simulation likely has unique value in improving complex systems, such as perioperative pathways. The perioperative clinical microsystem is a highly dynamic, fast-paced work environment in which multiple professions and disciplines come together to care for patients with a wide array of acuity
1553-7250/$-see front matter © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jcjq.2017.05.006
levels, ranging from outpatient walk-ins to the critically ill in multisystem organ failure (Figure 1). Ensuring the safe, effective management of this wide range of patients requires efficient processes of care within a smoothly operating system in which highly reliable teams of talented, skilled health care providers are able to use the vast array of high-technology resources and intensive care techniques available. Unfortunately, the perioperative microsystem does not always function in this ideal manner, leading to breakdowns at the service line and system level that can produce catastrophic failures and patient harm. These breakdowns are particularly difficult to identify because the latent safety threats5—those errors in design, organization, training, or maintenance that may contribute to medical errors—that predispose them are often masked by the workings of the system itself, only exposed at the last minute before an adverse event.6 Simulation can be used in diverse ways to proactively identify these threats and mitigate their damage to ensure that all those who work in this critical health care environment can provide optimal levels of patient care. Unfortunately, though, comprehensive review of how simulation can be used in this way has occurred in a piecemeal fashion, with published studies serving as single-institution case reports that describe how simulation helped fill a specific gap. To provide a broader perspective on this topic, an international group of five experts joined together on a panel, moderated by one of the authors [J.T.P.], at an international simulation conference in 2015 to discuss their own experiences
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Interactions Within the Perioperative Microsystem
Figure 1: Interactions of clinical areas that contribute to the complex perioperative microsystem are shown. Each of these interactions reflects situations in which health care providers from numerous specialties must join together to care for patients with varying acuity levels. Intensive Care Units refer to postanesthesia care unit and surgical intensive care unit.
and the associated opportunities, challenges, and considerations of using simulation in this manner.7 In this article we provide an overview of the themes discussed by each panel member, which we have delineated into four avenues through which simulation-based techniques have been used to improve systems-based aspects of the perioperative service line, as follows: 1. Simulation for Workplace Readiness: Testing new clinical workspaces and facilities before they open to identify potential latent conditions [A.K.G.] 2. Simulation to Improve Escalation of Care: Practicing how to identify the deteriorating patient and escalate care in an effective manner [M.J.] 3. Simulation to Re-Create Adverse Outcomes: Performing prospective root cause analyses (RCAs) to address system weaknesses leading to sentinel events [J.R.K.] 4. Simulation to Evaluate Negative Impacts of the EHR: Evaluating the efficiency and effectiveness of the electronic health record (EHR) in the perioperative setting [I.H.]. Literature that has emerged since the panel’s presentation is cited in this article, as appropriate. AVENUE 1. SIMULATION FOR WORKSPACE READINESS “Error-Proofing” of New Clinical Workspace
Making the transition to a new clinical workspace can be an extremely challenging endeavor. In situ simulation (that is, simulation activities that occur within an actual clinical
Simulation for Systems
space), though, can be invaluable for this process. By realistically playing out patient care scenarios in the actual clinical environment before it opens, a unique opportunity emerges to systematically analyze human, technical, and system performance. Simulation-based training (SBT) can not only make health care workers more comfortable with their new setting but can help hospital staff preemptively identify weaknesses in technologies or processes that may otherwise lie dormant until facility opening. The use of SBT for error-proofing has been studied in a number of ways. The beginning of this application of simulation began with a group of emergency medicine physicians who sought to investigate if workers who actually participated in SBT within a new workspace would benefit more than individuals who participated in a standard facility orientation to the new space.8 The researchers had a small group of emergency department (ED) staff participate in a medical resuscitation scenario four days before opening, and they evaluated the following: (1) the SBT group’s preparedness reactions compared to those individuals who only participated in the standard orientation, and (2) latent safety threats identified by the SBT participants who completed the simulated scenario. From this exercise, they were able to identify 18 latent safety threats from this one SBT activity and were able to correct most of them within the next few days before the facility opened. The threats identified ranged from seemingly small issues such as not knowing the location of switches within the space and less-thanideal placement of monitors to more serious concerns such as a faulty communication system that was for all intents and purposes unusable. More recently, another group of researchers assessed the readiness of two new trauma bays within another workspace by placing ED and surgery staff in a situation in which they had to manage a critically ill patient with trauma (patient simulator) who presented with multisystem injuries and then regroup to distribute resources and personnel to manage another arriving patient (standardized patient actor) complaining of severe, crushing chest pain.9 From this work, the researchers were able to recognize quickly that the trauma bays were lacking crucial components that could have a significant effect on actual patient care if the bays were used to treat trauma victims. For example, the researchers noted that lights were striking team members in the head, resuscitation equipment was absent, monitors were missing, and paths to the operating room (OR) were unmarked and unclear. In addition to identifying these important latent safety threats, the researchers were able to demonstrate that in situ SBT enhanced perceptions of readiness, self-efficacy, communication, and workspace satisfaction among the staff. Of note, these SBT exercises took place after a standard staff orientation and a “scavenger hunt” of the new workspace, typical standard techniques to familiarize workers to a new workspace. Thus, these improvements demonstrate that in situ SBT for new workspaces contributes unique value to clinical workers above
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and beyond what typical orientation approaches may offer. More recently, Medwid et al.10 examined the readiness of a new ED by rotating multidisciplinary teams through 15 in-situ simulations involving patients presenting as a cardiac arrest, stroke, septic shock, trauma, pediatric respiratory distress, and a precipitous labor and delivery. These researchers, much like those in the other cited studies, were able to uncover numerous (35) latent safety threats before opening the new facility. They also used this methodology to introduce and examine the efficacy of new process changes, including a new registration system, a new alert system for bedside triage, and a new process for medication distribution. By assigning each simulated patient a health record number, the researchers were able to register each patient in the computer system to allow for tracking and testing of these systems changes. Whereas the aforementioned studies assessed the impact of in situ simulation in a relatively short time span, Kerner et al.11 implemented in situ simulations during the course of three weeks to orient experienced clinicians to a new ED. This simulation curriculum was purposefully broad, including simulation for mass emergency and disaster preparedness, cadaveric tissue for technical skills refresher/training, and simulation with standardized patients and hybrid scenarios, to stress-test the new workspace. From these activities, this group was able to identify a number of latent safety threats related to patient flow, physical design/layout, community access, and transfer of deceased patients. In addition, issues related to culture, including how the health care teams managed errors and an overall feeling of distrust in the true purpose of the simulations, emerged from these activities. The authors were thus able to explore and manage a number of hidden psychosocial issues within their team debriefings as well. Evaluation of Workspace Readiness
In addition to assessing newly constructed clinical settings, SBT can be instrumental in evaluating the readiness of clinical spaces that are rarely, if ever, used, such as decontamination suites. The integrity and readiness of these facilities are crucial during outbreaks, such as the 2014 Ebola virus epidemic. As noted by Gaba,12 SBT can be a critical resource in these situations. Hospitals can use simulation to stress-test various hospital protocols and the functionality of decontamination suites. A common approach to identify latent safety threats in this context is to dust standardized patients with an ultraviolet substance designed to simulate the Ebola virus and present them to the clinical staff in the ED.13 Staff then perform simulated procedures and are scanned with an ultraviolet light after doffing or degowning their equipment to investigate any breaks in technique. Thus, in situ SBT can be used not only to identify latent safety threats of the space itself but also to detect potential gaps in education and training of protocols.
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AVENUE 2. SIMULATION TO IMPROVE ESCALATION OF CARE Defining Escalation of Care and Its Importance
The recognition and communication of patient deterioration to a senior colleague who responds promptly to implement definitive treatment is termed “escalation of care.”14 Escalation of care differs from the handoff (handover) process, as it is usually unplanned, unstructured, and pressured. This places a great deal of importance on “getting it right the first time.” When professionals are unable to save patients who develop complications, it is termed “failure to rescue.”15 Unfortunately, delays in escalation of care and failure to rescue are frequent and deadly. For example, in a global systematic review of escalation of care, between one fifth to one half of deteriorating patients were subjected to delays in care.16 Whereas hospital volume, equipment availability, and other organizational factors affect patient outcome in these scenarios,17–19 one of the most worrying contributors to both failed escalation of care and failure to rescue is the inexperience of junior clinicians and nursing staff in the diagnosis and management of critical illness.20 Other contributors include workload, outdated communication systems, hierarchical barriers, and a lack of protocol-driven care.21,22 Simulation has been offered as a methodology to resolve the systems-related causes of these occurrences. By re-creating the systems requirements that need to be in place for successful escalation of care, researchers are able to narrow in on all three phases of the escalation of care process—(1) recognition of patient deterioration, (2) communication, and (3) response. As shown in Figure 2, the efficacy of each of these processes can be further dissected and examined by researchers.
Key Factors and Contributors Needed for Successful Escalation of Care Communication 1. Skills
2. Technology Recognition
Response
1. Prioritization
1. Prioritization
2. Assessment
2. Management
Escalation of care
Figure 2: The key factors and contributors that are needed for successful escalation of care are shown. For timely and effective escalation of care, all factors must be present. These areas are prime for further research and education.
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Recognition of Patient Deterioration 23
Pucher et al. have successfully used simulation to assess trainee ability to recognize a deteriorating patient. This group had surgery residents participate in simulated ward rounds in which they encountered three patients: a postoperative elderly man demonstrating signs of sepsis, a young woman with right iliac fossa pain, and a middle-aged woman with epigastric pain and blood results suggestive of pancreatitis. From these simulation activities, these researchers were able to assess diagnostic ability, clinical management skills, teamwork, leadership, and communication, by adapting a previously developed clinical handoff checklist24 and nontechnical assessment tool.25 Another group of researchers developed a comprehensive, expert-derived toolkit to assess ward care ability, which includes a Clinical Skills Assessment for Ward Care, a Teamwork Skills Assessment for Ward Care, and a Physician-Patient Interaction Global Rating Scale.26 This group, which placed 185 residents through 38 simulated scenarios involving a rapidly deteriorating patient, was able to demonstrate excellent interrater reliability and convergent validity between the three tools. Finally, through a randomized controlled trial, researchers have been able to demonstrate the value of using simulation to evaluate the effectiveness of interventions to improve the process of escalation of care in the surgical ward setting, with evidence of some success in improving the interaction between the various health care providers involved in the escalation of care.27 Communication Process
The second facet of Figure 2, the communication process, has also received some attention from simulation researchers. Specifically, the creation and use of escalation protocols to help health care workers structure their communication, such as use of the SBAR (Situation, Background, Assessment, Recommendation) tool, has been suggested as one solution to improve escalation of care.28 This tool has been used to attempt to improve telephone referral skills of junior residents but has been an unsuccessful intervention for improving the quality of information transferred.29 This work led to the development of the QUality of Information Transfer (QUIT) tool, which was developed through literature review and semistructured interviews, and has demonstrated validity in both simulated and real-time clinical environments to assess information transfer of deteriorating surgical patients.30 Response Phase
The final component of the escalation of care, the response phase, has received less simulation attention. The majority of these studies have arisen from the critical care and nursing literature. A group in Amsterdam found that nurses who were previously trained on using the SBAR communication tool and the Modified Early Warning Score
Simulation for Systems
(MEWS) vital measurement tool were better able to identify a deteriorating simulated patient but failed to use the escalation protocol tools available to them.31 Similarly, a group from Australia used simulation to determine that, although academically prepared, final-semester nursing students were unable to manage patient deterioration.32 Comprehensive Intervention
Finally, the most recent literature has combined all of the aforementioned research to develop a comprehensive intervention to improve escalation of care skills.33 Through a randomized controlled trial, this group was able to demonstrate that an intervention consisting of small-group interactive and didactic sessions in which trainees were taught a systematic method of patient assessment, initial management, and structured SBAR use improved escalation of care skills of junior surgeons in a simulated setting. AVENUE 3. SIMULATION TO RE-CREATE ADVERSE OUTCOMES: AN ADJUNCT TO RCA
The Joint Commission defines RCA as a process for identifying the causal factors underlying variation in performance, including those underlying catastrophic breakdowns in patient care resulting in severe harm—sentinel events.34 Typically, an RCA is performed in a retrospective manner by reviewing the health record and interviewing personnel directly involved in the event and classifying identified issues (for example, in terms of the Eindhoven Classification Model35). Such interviews often occur months after the event, creating recall or hindsight bias (that is, selected recall of the events based on the outcome). These biases often focus on the human decisions made, leaving out critical systems-related causes. As such, traditional RCA may have limited success in creating meaningful change36–39 that will help to trap and mitigate the latent conditions that often contribute to catastrophic adverse care events. Simulation may help overcome these limitations by using reconstructing events and placing individuals in a similar context and environment, allowing investigators to determine how and why individuals reacted to the event. Evaluation of the entire system and the interaction of the individual with the system may help identify systemsbased conditions that can be missed in the memory-based, retrospective review so commonly used in health care RCAs. In an attempt to address the limitations of retrospective RCAs, researchers at Tulane University School of Medicine have developed and assessed the feasibility of simulation of adverse outcomes (SAO) for adverse surgical events.40–42 In one study,40 this group examined 631 closed claims of a major medical malpractice insurance company and used simulation to create all aspects of three scenarios, including electronic health records, team composition, scripts, and other paperwork. The scenarios involved (1) an unrecognized duodenal perforation in which a patient was discharged to home by
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a covering surgeon; (2) a patient in a postoperative recovery unit who was tachycardic and anxious, with decreased hemoglobin and hematocrit, but with normal blood pressure; and (3) a case in which a surgeon took a patient to the OR to perform a cholecystectomy, only to discover the gall bladder had been removed during a prior surgery. In each of these scenarios, SAO was able to identify more system errors than the RCA process uncovered. In a similar study,42 the same group examined how systems changes suggested by SAO would decrease adverse events. In 88% of their simulations, systems changes were effectively used by participants, indicating that systems changes emerging from SAO can effectively correct deficiencies and help improve outcomes. AVENUE 4. SIMULATION TO EVALUATE NEGATIVE IMPACTS OF THE EHR
With the widespread implementation of the EHR across the United States, health care providers recognize the potential benefits of a centralized information management system. Electronic systems can add value to functionalities such as order entry, automated reporting, and documentation of routine clinical activity. However, inefficient structure and user interfaces of EHRs may detract from clinician work flow and patient interaction, and could even negatively affect patient care. For example, studies have shown that EHRs can have negative impacts on clinical care delivery,43 have frequent usability issues,44,45 and require extensive training that is unrealistic for clinicians who work in multiple care settings.46 For these reasons, in 2013 the American Medical Informatics Association convened a task force to examine evidence on the usability of EHRs and to make recommendations.47 One of the recommendations was to perform usability studies using simulation. In a similar manner to traditional simulation-based training, the EHR and its potential ramifications to patient care can be assessed in a realistic simulated environment that would protect the patient from unintended consequences of the technology or changes to its structure within a system. This approach has been adopted by the US Department of Defense (DoD), which was an early adopter of the EHR system. As is true in many civilian systems, in the DoD system, developments in and changes to the EHR are conceived by subject matter experts outside the clinical environment and tested in the sterility of the computer laboratory. After such piloting, the next phase of testing typically occurs at the bedside, where both providers and patients are the medium to fix problems. As a result, workarounds and other ad hoc solutions are enacted when difficulties are encountered, often leading to workplace frustration. Thus, the DoD was motivated to find solutions to ameliorate the inefficiencies elicited from this process. At Madigan Army Medical Center (Seattle), researchers have described the use of simulation to evaluate the impact
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of EHR changes on a standardized (ICU) admission nursing assessment, which must be completed within two hours of admission. Experienced ICU nurses were selected who had extensive informatics experience. An actual admission scenario was modified for the simulation-based exercise, and data were collected on screen navigation, patient-nurse contact time, computer-nurse contact time, and nurse-family contact time. A complete history and physical exam and admission order set were on the chart prior to initiation of the scenario. Three simulated phone calls were added to the scenario to add to the realism of the intensive care setting, in which multiple events can happen: a laboratory call with critical laboratory values, a resident call with telephone orders from the operating room, and a family inquiry as to the location of the patient. Results from these simulation-based exercises demonstrated that the nurses in the ICU were spending an inordinate amount of time interfacing with the EHR. In an unpublished data set, results indicated that, on average, each nurse spent approximately 116 minutes interfacing with the EHR. Given that the scenario was limited to 120 minutes, this amount of time represents more than 95% of the total interaction time. The disproportionate amount of computernurse vs. patient-nurse contact time clearly showed the potentially negative impact on nursing care time because of the cumbersome EHR interface in this setting and the requisite distraction from the critically ill patient and his or her physiologic status. Future work at Madigan will explore the specific tasks and areas within the EHR that are consuming the majority of this time. DISCUSSION
In this article we have reviewed four distinct areas—testing new facilities, escalation of care, adverse outcome investigation, and EHR usability—in which we have applied simulation to improve system needs. Even from this brief review, it is clear that health care professionals have begun to understand the inherent power of simulation as a research and performance improvement methodology. Our own work and that of others have shown that simulation is essential for proactive identification of latent safety threats and that it can also help improve worker attitudes, confidence, and readiness, as well as team processes. However, use of simulation in this manner requires extreme forethought and support from leadership. As new facility openings are on a very tight schedule (and are often behind schedule), the timing of simulation events may be a substantial obstacle, particularly when equipment and supplies are not fully accessible. In addition, scheduling and logistics issues may make it difficult to allow new staff to experience and provide input during planned simulation activities. We have also illustrated the importance of simulation to improve the processes related to escalation of care in the perioperative microsystem. Yet a large volume of research and training is still required in the field of escalation of
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care to ensure that patients are safely cared for by health care providers on surgical and medical hospital wards. Further interventional research and eventual translation of this work into the clinical environment are required to ensure that simulation-based research achieves improvement in the efficiency of health services and, ultimately, patient outcomes related to this potentially life-saving process of care. We have also demonstrated how SAO can identify unrecognized root causes that are more amenable to systemsbased improvements compared to traditional RCA. Current work in this field has shown that re-creating the context and environment in which errors have occurred can provide deeper levels of insight into clinician decision making and allow investigators to examine in a controlled setting why these events occurred. However, identifying a problem and determining the utility of an improvement are extremely difficult in a highly complex setting. Future work should continue to explore the situations in which simulation is most beneficial for this type of exploration. In addition, communication of these situations and development of training curricula should be performed to prevent their reoccurrence. Finally, our review highlighted some of the initial steps the Department of Defense has taken to better understand the effects of the EHR on nursing time and patient care activities. By conducting a simulation-based trial (at Madigan Army Medical Center) looking at changes to the EHR, the DoD recognized the exorbitant amount of time required to complete the requisite computer work. This finding resulted in the delay and redesign of an ICU EHR admission note system and has even inspired the development of informatics emulation laboratories to test future EHRs and EHR changes in a realistic simulation-based environment. Thus, our initial findings have supported further investment into simulation programs. Our experiences have shown an interesting paradox in proposing simulation for systems improvement processes: decision makers require data to invest in simulation programs, but those data rarely exist until we create simulation activities to examine processes. Aside from these areas, there are a number of other capacities in which simulation can be used to better understand and enhance the health care system. It could be applied to improve the patient experience in a number of ways. Whether the goal is to investigate wait times, continuity of care, gaps, or redundancy inspection, re-creating the longitudinal patient experience can provide a unique level of insight into the health care system. As institutions continue to move toward patientinfluenced reimbursement, this approach may provide a substantial return on investment for the hospital entity. Similarly, simulation can be used in both the onboarding and staffing processes to examine workload among clinicians and allied staff to promote a more even distribution of roles and responsibilities. Finally, while our review focused on EHR technology, simulation can play a valuable role in any situation
Simulation for Systems
that involves adoption of new devices, technology, or technique. It could not only provide a proactive snapshot of how the new technology would work in the new setting but also offer insight into clinician and staff proficiency with those new technologies. Further research that explores for whom and for what simulation is most beneficial in these settings is needed. Despite these and other broad applications, simulation has yet to be the standard approach for systems diagnostics and improvement. This is likely due to common constraints with any new methodology—time and resources. From a leadership standpoint, it may be difficult to predict monetary savings or the extent to which simulation for process improvement will be beneficial. In some situations, such as simulation for a new workspace opening, a monetary value can be determined. For example, Wetzel et al.5 were able to determine that each $700 investment in simulation resulted in one identified latent safety threat, and that each $3,390 investment resulted in one clinical improvement. The authors suggested that these values were likely underestimated, given the increased knowledge, skills, teamwork, and decision making that resulted from these simulations. Others have argued for a reconceptualization of what is meant by the term value, suggesting that true value of simulation is not just financial return on investment but should also be considered in terms of educational impact and patient care outcomes.48 Additional work that is able to demonstrate a direct link to all of these outcomes—educational, patient safety, and cost savings—is needed to enhance buy-in of this strategy. Persons seeking to use simulation may also consider strategic development and insertion of simulation into current processes. Systems-based simulation can be reasonably coupled with existing efforts, such as onboarding and orientation courses, to reduce the opportunity and financial costs of clinician and staff time. In addition, the inherent cost of not doing simulation and allowing for possible mistakes, errors, and adverse events should be considered. For example, the Risk Management Foundation of the Harvard Medical Institutions (CRICO/RMF) and Massachusetts General Hospital have embraced this concept to the extent that CRICO/RMF reduces liability insurance premiums for those engaging in simulation-based team training.49 CONCLUSION
This focused review of simulation-based interventions to test and improve components of the perioperative microsystem highlights the broad-based utility of simulation-based technologies in health care. To date, simulation in the perioperative environment has been predominantly focused on training individuals and teams in both technical and nontechnical (team-based) knowledge, skills, and abilities. Such work is very effective and has great utility in preparing practitioners to treat surgical patients more effectively. Yet simulation-based technologies can be leveraged to address effectively important systems-based aspects of the perioperative
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Table 1. Systems-Based Examples in Which Simulation-Based Activities Can Be Used for Evaluating and Improving Care in the Perioperative Setting System-Based Target
Purpose
Threats Identified
Clinical Workspace Escalation of Care Adverse Outcomes
Error-proofing facility/space before clinical use Enhancing team/practitioner communication and response Identifying additional issues; beta testing solutions
Electronic Health Record
Beta testing
LSTs LSTs; team dysfunction LSTs; team dysfunction; unintended consequences LSTs; unintended consequences
LST, latent safety threat.
micro-system (Table 1). These simulation-based activities to “test” processes and systems are directly applicable to other areas of our complex health care industry, and efforts to incorporate this form of piloting new processes and technologies should be made. Presentations. This article includes information provided in Gardner A, et al. Use of simulation to improve the perioperative system, a panel at the 15th Annual International Meeting on Simulation in Healthcare, New Orleans, Jan 14, 2015. Conflicts of Interest. All authors report no conflicts of interest.
Aimee K. Gardner, PhD, formerly Assistant Professor, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, is Assistant Dean of Evaluation and Research, Allied Health, and Associate Professor of Allied Health and Surgery, School of Allied Health Sciences, Baylor College of Medicine, Houston. Maximilian Johnston, MRCS, is Honorary Clinical Research Fellow, Imperial Patient Safety Translational Research Centre, Department of Surgery and Cancer, Imperial College London. James R. Korndorffer Jr., MD, is Professor, Department of Surgery, Tulane University School of Medicine, New Orleans. Imad Haque, MD, is Lieutenant Colonel, Madigan Army Medical Center, Seattle. John T. Paige, MD, is Professor of Clinical Surgery, Department of Surgery, LSU Health New Orleans School of Medicine, New Orleans. Please address correspondence to Aimee K. Gardner, [email protected].
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25. Steinemann S, et al. Assessing teamwork in the trauma bay: introduction of a modified “NOTECHS” scale for trauma. Am J Surg. 2012;203:69–75. 26. Hull L, et al. Improving surgical ward care: development and psychometric properties of a global assessment toolkit. Ann Surg. 2014;259:904–909. 27. Pucher PH, et al. Ward simulation to improve surgical ward round performance: a randomized controlled trial of a simulation-based curriculum. Ann Surg. 2014;260:236– 243. 28. Compton J, et al. Implementing SBAR across a large multihospital health system. Jt Comm J Qual Patient Saf. 2012;38:261–268. 29. Cunningham NJ, et al. Telephone referrals by junior doctors: a randomised controlled trial assessing the impact of SBAR in a simulated setting. Postgrad Med J. 2012;88:619– 626. 30. Johnston MJ, et al. Improving escalation of care: development and validation of the QUality of Information Transfer (QUIT) tool. Ann Surg. 2016;263:477–486. 31. Ludikhuize J, de Jonge E, Goossens A. Measuring adherence among nurses one year after training in applying the Modified Early Warning Score and Situation-BackgroundAssessment-Recommendation instruments. Resuscitation. 2011;82:1428–1433. 32. Cooper S, et al. Managing the deteriorating patient in a simulated environment: nursing students’ knowledge, skill and situation awareness. J Clin Nurs. 2010;19:2309–2318. 33. Johnston MJ, et al. Improving escalation of care: a doubleblinded randomized controlled trial. Ann Surg. 2016;263: 421–426. 34. Joint Commission International. Root Cause Analysis in Health Care: Tools and Techniques, 4th ed. Oak Brook, IL: Joint Commission Resources, 2010. 35. van Vuuren W, Shea CE, van der Schaaf TW. The Development of an Incident Analysis Tool for the Medical Field. Eindhoven, Netherlands: Technische Universiteit Eindhoven, 1997. 36. Wu AW, Lipshutz AK, Pronovost PJ. Effectiveness and efficiency of root cause analysis in medicine. JAMA. 2008 Feb 13;299:685–687.
Simulation for Systems 37. Percarpio KB, Watts BV, Weeks WB. The effectiveness of root cause analysis: what does the literature tell us? Jt Comm J Qual Patient Saf. 2008;34:391–398. 38. Pham JC, et al. ReCASTing the RCA: an improved model for performing root cause analyses. Am J Med Qual. 2010;25:186–191. 39. The Joint Commission. Sentinel Event Policies and Procedures. Feb 17, 2017. Accessed Jun 4, 2017. http:// www.jointcommission.org/Sentinel_Event_Policy_and _Procedures/. 40. Slakey DP, et al. Using simulation to improve root cause analysis of adverse surgical outcomes. Int J Qual Health Care. 2014;26:144–150. 41. Simms ER, et al. Can simulation improve the traditional method of root cause analysis: a preliminary investigation. Surgery. 2012;152:489–497. 42. Garstka ME, et al. Effectiveness of systems changes suggested by simulation of adverse surgical outcomes. BMJ Simul Technol Enhanced Learn. 2015;1:83–86. 43. Metzger J, et al. Mixed results in the safety performance of computerized physician order entry. Health Aff (Millwood). 2010;29:655–663. 44. Ammenwerth E, et al. Factors affecting and affected by user acceptance of computer-based nursing documentation: results of a two-year study. J Am Med Inform Assoc. 2003;10:69–84. 45. Beuscart-Zéphir MC, et al. Integrating users’ activity modeling in the design and assessment of hospital electronic patient records: the example of anesthesia. Int J Med Inform. 2001;64:157–171. 46. Shneiderman B. Tragic errors: usability and electronic health records. Interactions. 2011;18(6):60–63. 47. Middleton B, et al. Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA. J Am Med Inform Assoc. 2013;20(e1):e2–8. 48. Gardner AK, et al. The value proposition of simulation. Surgery. 2016;160:546–551. 49. Arriaga AF, et al. Pilot testing of a model for insurer-driven, large-scale multicenter simulation training for operating room teams. Ann Surg. 2014;259:403–410.
Using Simulation to Improve Systems-Based Practices Aimee K. Gardner, PhD; Maximilian Johnston, MRCS; James R. Korndorffer, Jr., MD; Imad Haque, MD; John T. Paige, MD
Background: Ensuring the safe, effective management of patients requires efficient processes of care within a smoothly operating system in which highly reliable teams of talented, skilled health care providers are able to use the vast array of high-technology resources and intensive care techniques available. Simulation can play a unique role in exploring and improving the complex perioperative system by proactively identifying latent safety threats and mitigating their damage to ensure that all those who work in this critical health care environment can provide optimal levels of patient care. Methods: A panel of five experts from a wide range of institutions was brought together to discuss the added value of simulation-based training for improving systems-based aspects of the perioperative service line. Panelists shared the way in which simulation was demonstrated at their institutions. The themes discussed by each panel member were delineated into four avenues through which simulation-based techniques have been used. Results: Simulation-based techniques are being used in (1) testing new clinical workspaces and facilities before they open to identify potential latent conditions; (2) practicing how to identify the deteriorating patient and escalate care in an effective manner; (3) performing prospective root cause analyses to address system weaknesses leading to sentinel events; and (4) evaluating the efficiency and effectiveness of the electronic health record in the perioperative setting. Conclusion: This focused review of simulation-based interventions to test and improve components of the perioperative microsystem, which includes literature that has emerged since the panel’s presentation, highlights the broad-based utility of simulation-based technologies in health care.
S
imulation involves re-creating medical tasks and environments to allow learners to develop and hone both technical and nontechnical skills. Work demonstrating the success of simulation-based curricula has not only led to requirements of its inclusion in residency training curricula,1 but simulation has also been chosen as the modality for national certification exams in surgery.2,3 Outside its role within training programs, though, simulation can be a critical tool to better understand and refine the larger health care system. Simulation is particularly conducive to helping address challenges in this way because it re-creates rare, yet high-risk events and conditions in which providers can practice their responses;4 it provides a safe learning environment in which learners can try and fail without consequences to patients; and—because of its experiential nature—it creates an immersive learning environment in which learners can suspend disbelief, allowing for better retention of knowledge, skills, and attitudes learned in the setting. Simulation likely has unique value in improving complex systems, such as perioperative pathways. The perioperative clinical microsystem is a highly dynamic, fast-paced work environment in which multiple professions and disciplines come together to care for patients with a wide array of acuity
1553-7250/$-see front matter © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jcjq.2017.05.006
levels, ranging from outpatient walk-ins to the critically ill in multisystem organ failure (Figure 1). Ensuring the safe, effective management of this wide range of patients requires efficient processes of care within a smoothly operating system in which highly reliable teams of talented, skilled health care providers are able to use the vast array of high-technology resources and intensive care techniques available. Unfortunately, the perioperative microsystem does not always function in this ideal manner, leading to breakdowns at the service line and system level that can produce catastrophic failures and patient harm. These breakdowns are particularly difficult to identify because the latent safety threats5—those errors in design, organization, training, or maintenance that may contribute to medical errors—that predispose them are often masked by the workings of the system itself, only exposed at the last minute before an adverse event.6 Simulation can be used in diverse ways to proactively identify these threats and mitigate their damage to ensure that all those who work in this critical health care environment can provide optimal levels of patient care. Unfortunately, though, comprehensive review of how simulation can be used in this way has occurred in a piecemeal fashion, with published studies serving as single-institution case reports that describe how simulation helped fill a specific gap. To provide a broader perspective on this topic, an international group of five experts joined together on a panel, moderated by one of the authors [J.T.P.], at an international simulation conference in 2015 to discuss their own experiences
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Interactions Within the Perioperative Microsystem
Figure 1: Interactions of clinical areas that contribute to the complex perioperative microsystem are shown. Each of these interactions reflects situations in which health care providers from numerous specialties must join together to care for patients with varying acuity levels. Intensive Care Units refer to postanesthesia care unit and surgical intensive care unit.
and the associated opportunities, challenges, and considerations of using simulation in this manner.7 In this article we provide an overview of the themes discussed by each panel member, which we have delineated into four avenues through which simulation-based techniques have been used to improve systems-based aspects of the perioperative service line, as follows: 1. Simulation for Workplace Readiness: Testing new clinical workspaces and facilities before they open to identify potential latent conditions [A.K.G.] 2. Simulation to Improve Escalation of Care: Practicing how to identify the deteriorating patient and escalate care in an effective manner [M.J.] 3. Simulation to Re-Create Adverse Outcomes: Performing prospective root cause analyses (RCAs) to address system weaknesses leading to sentinel events [J.R.K.] 4. Simulation to Evaluate Negative Impacts of the EHR: Evaluating the efficiency and effectiveness of the electronic health record (EHR) in the perioperative setting [I.H.]. Literature that has emerged since the panel’s presentation is cited in this article, as appropriate. AVENUE 1. SIMULATION FOR WORKSPACE READINESS “Error-Proofing” of New Clinical Workspace
Making the transition to a new clinical workspace can be an extremely challenging endeavor. In situ simulation (that is, simulation activities that occur within an actual clinical
Simulation for Systems
space), though, can be invaluable for this process. By realistically playing out patient care scenarios in the actual clinical environment before it opens, a unique opportunity emerges to systematically analyze human, technical, and system performance. Simulation-based training (SBT) can not only make health care workers more comfortable with their new setting but can help hospital staff preemptively identify weaknesses in technologies or processes that may otherwise lie dormant until facility opening. The use of SBT for error-proofing has been studied in a number of ways. The beginning of this application of simulation began with a group of emergency medicine physicians who sought to investigate if workers who actually participated in SBT within a new workspace would benefit more than individuals who participated in a standard facility orientation to the new space.8 The researchers had a small group of emergency department (ED) staff participate in a medical resuscitation scenario four days before opening, and they evaluated the following: (1) the SBT group’s preparedness reactions compared to those individuals who only participated in the standard orientation, and (2) latent safety threats identified by the SBT participants who completed the simulated scenario. From this exercise, they were able to identify 18 latent safety threats from this one SBT activity and were able to correct most of them within the next few days before the facility opened. The threats identified ranged from seemingly small issues such as not knowing the location of switches within the space and less-thanideal placement of monitors to more serious concerns such as a faulty communication system that was for all intents and purposes unusable. More recently, another group of researchers assessed the readiness of two new trauma bays within another workspace by placing ED and surgery staff in a situation in which they had to manage a critically ill patient with trauma (patient simulator) who presented with multisystem injuries and then regroup to distribute resources and personnel to manage another arriving patient (standardized patient actor) complaining of severe, crushing chest pain.9 From this work, the researchers were able to recognize quickly that the trauma bays were lacking crucial components that could have a significant effect on actual patient care if the bays were used to treat trauma victims. For example, the researchers noted that lights were striking team members in the head, resuscitation equipment was absent, monitors were missing, and paths to the operating room (OR) were unmarked and unclear. In addition to identifying these important latent safety threats, the researchers were able to demonstrate that in situ SBT enhanced perceptions of readiness, self-efficacy, communication, and workspace satisfaction among the staff. Of note, these SBT exercises took place after a standard staff orientation and a “scavenger hunt” of the new workspace, typical standard techniques to familiarize workers to a new workspace. Thus, these improvements demonstrate that in situ SBT for new workspaces contributes unique value to clinical workers above
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and beyond what typical orientation approaches may offer. More recently, Medwid et al.10 examined the readiness of a new ED by rotating multidisciplinary teams through 15 in-situ simulations involving patients presenting as a cardiac arrest, stroke, septic shock, trauma, pediatric respiratory distress, and a precipitous labor and delivery. These researchers, much like those in the other cited studies, were able to uncover numerous (35) latent safety threats before opening the new facility. They also used this methodology to introduce and examine the efficacy of new process changes, including a new registration system, a new alert system for bedside triage, and a new process for medication distribution. By assigning each simulated patient a health record number, the researchers were able to register each patient in the computer system to allow for tracking and testing of these systems changes. Whereas the aforementioned studies assessed the impact of in situ simulation in a relatively short time span, Kerner et al.11 implemented in situ simulations during the course of three weeks to orient experienced clinicians to a new ED. This simulation curriculum was purposefully broad, including simulation for mass emergency and disaster preparedness, cadaveric tissue for technical skills refresher/training, and simulation with standardized patients and hybrid scenarios, to stress-test the new workspace. From these activities, this group was able to identify a number of latent safety threats related to patient flow, physical design/layout, community access, and transfer of deceased patients. In addition, issues related to culture, including how the health care teams managed errors and an overall feeling of distrust in the true purpose of the simulations, emerged from these activities. The authors were thus able to explore and manage a number of hidden psychosocial issues within their team debriefings as well. Evaluation of Workspace Readiness
In addition to assessing newly constructed clinical settings, SBT can be instrumental in evaluating the readiness of clinical spaces that are rarely, if ever, used, such as decontamination suites. The integrity and readiness of these facilities are crucial during outbreaks, such as the 2014 Ebola virus epidemic. As noted by Gaba,12 SBT can be a critical resource in these situations. Hospitals can use simulation to stress-test various hospital protocols and the functionality of decontamination suites. A common approach to identify latent safety threats in this context is to dust standardized patients with an ultraviolet substance designed to simulate the Ebola virus and present them to the clinical staff in the ED.13 Staff then perform simulated procedures and are scanned with an ultraviolet light after doffing or degowning their equipment to investigate any breaks in technique. Thus, in situ SBT can be used not only to identify latent safety threats of the space itself but also to detect potential gaps in education and training of protocols.
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AVENUE 2. SIMULATION TO IMPROVE ESCALATION OF CARE Defining Escalation of Care and Its Importance
The recognition and communication of patient deterioration to a senior colleague who responds promptly to implement definitive treatment is termed “escalation of care.”14 Escalation of care differs from the handoff (handover) process, as it is usually unplanned, unstructured, and pressured. This places a great deal of importance on “getting it right the first time.” When professionals are unable to save patients who develop complications, it is termed “failure to rescue.”15 Unfortunately, delays in escalation of care and failure to rescue are frequent and deadly. For example, in a global systematic review of escalation of care, between one fifth to one half of deteriorating patients were subjected to delays in care.16 Whereas hospital volume, equipment availability, and other organizational factors affect patient outcome in these scenarios,17–19 one of the most worrying contributors to both failed escalation of care and failure to rescue is the inexperience of junior clinicians and nursing staff in the diagnosis and management of critical illness.20 Other contributors include workload, outdated communication systems, hierarchical barriers, and a lack of protocol-driven care.21,22 Simulation has been offered as a methodology to resolve the systems-related causes of these occurrences. By re-creating the systems requirements that need to be in place for successful escalation of care, researchers are able to narrow in on all three phases of the escalation of care process—(1) recognition of patient deterioration, (2) communication, and (3) response. As shown in Figure 2, the efficacy of each of these processes can be further dissected and examined by researchers.
Key Factors and Contributors Needed for Successful Escalation of Care Communication 1. Skills
2. Technology Recognition
Response
1. Prioritization
1. Prioritization
2. Assessment
2. Management
Escalation of care
Figure 2: The key factors and contributors that are needed for successful escalation of care are shown. For timely and effective escalation of care, all factors must be present. These areas are prime for further research and education.
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Recognition of Patient Deterioration 23
Pucher et al. have successfully used simulation to assess trainee ability to recognize a deteriorating patient. This group had surgery residents participate in simulated ward rounds in which they encountered three patients: a postoperative elderly man demonstrating signs of sepsis, a young woman with right iliac fossa pain, and a middle-aged woman with epigastric pain and blood results suggestive of pancreatitis. From these simulation activities, these researchers were able to assess diagnostic ability, clinical management skills, teamwork, leadership, and communication, by adapting a previously developed clinical handoff checklist24 and nontechnical assessment tool.25 Another group of researchers developed a comprehensive, expert-derived toolkit to assess ward care ability, which includes a Clinical Skills Assessment for Ward Care, a Teamwork Skills Assessment for Ward Care, and a Physician-Patient Interaction Global Rating Scale.26 This group, which placed 185 residents through 38 simulated scenarios involving a rapidly deteriorating patient, was able to demonstrate excellent interrater reliability and convergent validity between the three tools. Finally, through a randomized controlled trial, researchers have been able to demonstrate the value of using simulation to evaluate the effectiveness of interventions to improve the process of escalation of care in the surgical ward setting, with evidence of some success in improving the interaction between the various health care providers involved in the escalation of care.27 Communication Process
The second facet of Figure 2, the communication process, has also received some attention from simulation researchers. Specifically, the creation and use of escalation protocols to help health care workers structure their communication, such as use of the SBAR (Situation, Background, Assessment, Recommendation) tool, has been suggested as one solution to improve escalation of care.28 This tool has been used to attempt to improve telephone referral skills of junior residents but has been an unsuccessful intervention for improving the quality of information transferred.29 This work led to the development of the QUality of Information Transfer (QUIT) tool, which was developed through literature review and semistructured interviews, and has demonstrated validity in both simulated and real-time clinical environments to assess information transfer of deteriorating surgical patients.30 Response Phase
The final component of the escalation of care, the response phase, has received less simulation attention. The majority of these studies have arisen from the critical care and nursing literature. A group in Amsterdam found that nurses who were previously trained on using the SBAR communication tool and the Modified Early Warning Score
Simulation for Systems
(MEWS) vital measurement tool were better able to identify a deteriorating simulated patient but failed to use the escalation protocol tools available to them.31 Similarly, a group from Australia used simulation to determine that, although academically prepared, final-semester nursing students were unable to manage patient deterioration.32 Comprehensive Intervention
Finally, the most recent literature has combined all of the aforementioned research to develop a comprehensive intervention to improve escalation of care skills.33 Through a randomized controlled trial, this group was able to demonstrate that an intervention consisting of small-group interactive and didactic sessions in which trainees were taught a systematic method of patient assessment, initial management, and structured SBAR use improved escalation of care skills of junior surgeons in a simulated setting. AVENUE 3. SIMULATION TO RE-CREATE ADVERSE OUTCOMES: AN ADJUNCT TO RCA
The Joint Commission defines RCA as a process for identifying the causal factors underlying variation in performance, including those underlying catastrophic breakdowns in patient care resulting in severe harm—sentinel events.34 Typically, an RCA is performed in a retrospective manner by reviewing the health record and interviewing personnel directly involved in the event and classifying identified issues (for example, in terms of the Eindhoven Classification Model35). Such interviews often occur months after the event, creating recall or hindsight bias (that is, selected recall of the events based on the outcome). These biases often focus on the human decisions made, leaving out critical systems-related causes. As such, traditional RCA may have limited success in creating meaningful change36–39 that will help to trap and mitigate the latent conditions that often contribute to catastrophic adverse care events. Simulation may help overcome these limitations by using reconstructing events and placing individuals in a similar context and environment, allowing investigators to determine how and why individuals reacted to the event. Evaluation of the entire system and the interaction of the individual with the system may help identify systemsbased conditions that can be missed in the memory-based, retrospective review so commonly used in health care RCAs. In an attempt to address the limitations of retrospective RCAs, researchers at Tulane University School of Medicine have developed and assessed the feasibility of simulation of adverse outcomes (SAO) for adverse surgical events.40–42 In one study,40 this group examined 631 closed claims of a major medical malpractice insurance company and used simulation to create all aspects of three scenarios, including electronic health records, team composition, scripts, and other paperwork. The scenarios involved (1) an unrecognized duodenal perforation in which a patient was discharged to home by
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a covering surgeon; (2) a patient in a postoperative recovery unit who was tachycardic and anxious, with decreased hemoglobin and hematocrit, but with normal blood pressure; and (3) a case in which a surgeon took a patient to the OR to perform a cholecystectomy, only to discover the gall bladder had been removed during a prior surgery. In each of these scenarios, SAO was able to identify more system errors than the RCA process uncovered. In a similar study,42 the same group examined how systems changes suggested by SAO would decrease adverse events. In 88% of their simulations, systems changes were effectively used by participants, indicating that systems changes emerging from SAO can effectively correct deficiencies and help improve outcomes. AVENUE 4. SIMULATION TO EVALUATE NEGATIVE IMPACTS OF THE EHR
With the widespread implementation of the EHR across the United States, health care providers recognize the potential benefits of a centralized information management system. Electronic systems can add value to functionalities such as order entry, automated reporting, and documentation of routine clinical activity. However, inefficient structure and user interfaces of EHRs may detract from clinician work flow and patient interaction, and could even negatively affect patient care. For example, studies have shown that EHRs can have negative impacts on clinical care delivery,43 have frequent usability issues,44,45 and require extensive training that is unrealistic for clinicians who work in multiple care settings.46 For these reasons, in 2013 the American Medical Informatics Association convened a task force to examine evidence on the usability of EHRs and to make recommendations.47 One of the recommendations was to perform usability studies using simulation. In a similar manner to traditional simulation-based training, the EHR and its potential ramifications to patient care can be assessed in a realistic simulated environment that would protect the patient from unintended consequences of the technology or changes to its structure within a system. This approach has been adopted by the US Department of Defense (DoD), which was an early adopter of the EHR system. As is true in many civilian systems, in the DoD system, developments in and changes to the EHR are conceived by subject matter experts outside the clinical environment and tested in the sterility of the computer laboratory. After such piloting, the next phase of testing typically occurs at the bedside, where both providers and patients are the medium to fix problems. As a result, workarounds and other ad hoc solutions are enacted when difficulties are encountered, often leading to workplace frustration. Thus, the DoD was motivated to find solutions to ameliorate the inefficiencies elicited from this process. At Madigan Army Medical Center (Seattle), researchers have described the use of simulation to evaluate the impact
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of EHR changes on a standardized (ICU) admission nursing assessment, which must be completed within two hours of admission. Experienced ICU nurses were selected who had extensive informatics experience. An actual admission scenario was modified for the simulation-based exercise, and data were collected on screen navigation, patient-nurse contact time, computer-nurse contact time, and nurse-family contact time. A complete history and physical exam and admission order set were on the chart prior to initiation of the scenario. Three simulated phone calls were added to the scenario to add to the realism of the intensive care setting, in which multiple events can happen: a laboratory call with critical laboratory values, a resident call with telephone orders from the operating room, and a family inquiry as to the location of the patient. Results from these simulation-based exercises demonstrated that the nurses in the ICU were spending an inordinate amount of time interfacing with the EHR. In an unpublished data set, results indicated that, on average, each nurse spent approximately 116 minutes interfacing with the EHR. Given that the scenario was limited to 120 minutes, this amount of time represents more than 95% of the total interaction time. The disproportionate amount of computernurse vs. patient-nurse contact time clearly showed the potentially negative impact on nursing care time because of the cumbersome EHR interface in this setting and the requisite distraction from the critically ill patient and his or her physiologic status. Future work at Madigan will explore the specific tasks and areas within the EHR that are consuming the majority of this time. DISCUSSION
In this article we have reviewed four distinct areas—testing new facilities, escalation of care, adverse outcome investigation, and EHR usability—in which we have applied simulation to improve system needs. Even from this brief review, it is clear that health care professionals have begun to understand the inherent power of simulation as a research and performance improvement methodology. Our own work and that of others have shown that simulation is essential for proactive identification of latent safety threats and that it can also help improve worker attitudes, confidence, and readiness, as well as team processes. However, use of simulation in this manner requires extreme forethought and support from leadership. As new facility openings are on a very tight schedule (and are often behind schedule), the timing of simulation events may be a substantial obstacle, particularly when equipment and supplies are not fully accessible. In addition, scheduling and logistics issues may make it difficult to allow new staff to experience and provide input during planned simulation activities. We have also illustrated the importance of simulation to improve the processes related to escalation of care in the perioperative microsystem. Yet a large volume of research and training is still required in the field of escalation of
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care to ensure that patients are safely cared for by health care providers on surgical and medical hospital wards. Further interventional research and eventual translation of this work into the clinical environment are required to ensure that simulation-based research achieves improvement in the efficiency of health services and, ultimately, patient outcomes related to this potentially life-saving process of care. We have also demonstrated how SAO can identify unrecognized root causes that are more amenable to systemsbased improvements compared to traditional RCA. Current work in this field has shown that re-creating the context and environment in which errors have occurred can provide deeper levels of insight into clinician decision making and allow investigators to examine in a controlled setting why these events occurred. However, identifying a problem and determining the utility of an improvement are extremely difficult in a highly complex setting. Future work should continue to explore the situations in which simulation is most beneficial for this type of exploration. In addition, communication of these situations and development of training curricula should be performed to prevent their reoccurrence. Finally, our review highlighted some of the initial steps the Department of Defense has taken to better understand the effects of the EHR on nursing time and patient care activities. By conducting a simulation-based trial (at Madigan Army Medical Center) looking at changes to the EHR, the DoD recognized the exorbitant amount of time required to complete the requisite computer work. This finding resulted in the delay and redesign of an ICU EHR admission note system and has even inspired the development of informatics emulation laboratories to test future EHRs and EHR changes in a realistic simulation-based environment. Thus, our initial findings have supported further investment into simulation programs. Our experiences have shown an interesting paradox in proposing simulation for systems improvement processes: decision makers require data to invest in simulation programs, but those data rarely exist until we create simulation activities to examine processes. Aside from these areas, there are a number of other capacities in which simulation can be used to better understand and enhance the health care system. It could be applied to improve the patient experience in a number of ways. Whether the goal is to investigate wait times, continuity of care, gaps, or redundancy inspection, re-creating the longitudinal patient experience can provide a unique level of insight into the health care system. As institutions continue to move toward patientinfluenced reimbursement, this approach may provide a substantial return on investment for the hospital entity. Similarly, simulation can be used in both the onboarding and staffing processes to examine workload among clinicians and allied staff to promote a more even distribution of roles and responsibilities. Finally, while our review focused on EHR technology, simulation can play a valuable role in any situation
Simulation for Systems
that involves adoption of new devices, technology, or technique. It could not only provide a proactive snapshot of how the new technology would work in the new setting but also offer insight into clinician and staff proficiency with those new technologies. Further research that explores for whom and for what simulation is most beneficial in these settings is needed. Despite these and other broad applications, simulation has yet to be the standard approach for systems diagnostics and improvement. This is likely due to common constraints with any new methodology—time and resources. From a leadership standpoint, it may be difficult to predict monetary savings or the extent to which simulation for process improvement will be beneficial. In some situations, such as simulation for a new workspace opening, a monetary value can be determined. For example, Wetzel et al.5 were able to determine that each $700 investment in simulation resulted in one identified latent safety threat, and that each $3,390 investment resulted in one clinical improvement. The authors suggested that these values were likely underestimated, given the increased knowledge, skills, teamwork, and decision making that resulted from these simulations. Others have argued for a reconceptualization of what is meant by the term value, suggesting that true value of simulation is not just financial return on investment but should also be considered in terms of educational impact and patient care outcomes.48 Additional work that is able to demonstrate a direct link to all of these outcomes—educational, patient safety, and cost savings—is needed to enhance buy-in of this strategy. Persons seeking to use simulation may also consider strategic development and insertion of simulation into current processes. Systems-based simulation can be reasonably coupled with existing efforts, such as onboarding and orientation courses, to reduce the opportunity and financial costs of clinician and staff time. In addition, the inherent cost of not doing simulation and allowing for possible mistakes, errors, and adverse events should be considered. For example, the Risk Management Foundation of the Harvard Medical Institutions (CRICO/RMF) and Massachusetts General Hospital have embraced this concept to the extent that CRICO/RMF reduces liability insurance premiums for those engaging in simulation-based team training.49 CONCLUSION
This focused review of simulation-based interventions to test and improve components of the perioperative microsystem highlights the broad-based utility of simulation-based technologies in health care. To date, simulation in the perioperative environment has been predominantly focused on training individuals and teams in both technical and nontechnical (team-based) knowledge, skills, and abilities. Such work is very effective and has great utility in preparing practitioners to treat surgical patients more effectively. Yet simulation-based technologies can be leveraged to address effectively important systems-based aspects of the perioperative
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Table 1. Systems-Based Examples in Which Simulation-Based Activities Can Be Used for Evaluating and Improving Care in the Perioperative Setting System-Based Target
Purpose
Threats Identified
Clinical Workspace Escalation of Care Adverse Outcomes
Error-proofing facility/space before clinical use Enhancing team/practitioner communication and response Identifying additional issues; beta testing solutions
Electronic Health Record
Beta testing
LSTs LSTs; team dysfunction LSTs; team dysfunction; unintended consequences LSTs; unintended consequences
LST, latent safety threat.
micro-system (Table 1). These simulation-based activities to “test” processes and systems are directly applicable to other areas of our complex health care industry, and efforts to incorporate this form of piloting new processes and technologies should be made. Presentations. This article includes information provided in Gardner A, et al. Use of simulation to improve the perioperative system, a panel at the 15th Annual International Meeting on Simulation in Healthcare, New Orleans, Jan 14, 2015. Conflicts of Interest. All authors report no conflicts of interest.
Aimee K. Gardner, PhD, formerly Assistant Professor, Department of Surgery, University of Texas Southwestern Medical Center, Dallas, is Assistant Dean of Evaluation and Research, Allied Health, and Associate Professor of Allied Health and Surgery, School of Allied Health Sciences, Baylor College of Medicine, Houston. Maximilian Johnston, MRCS, is Honorary Clinical Research Fellow, Imperial Patient Safety Translational Research Centre, Department of Surgery and Cancer, Imperial College London. James R. Korndorffer Jr., MD, is Professor, Department of Surgery, Tulane University School of Medicine, New Orleans. Imad Haque, MD, is Lieutenant Colonel, Madigan Army Medical Center, Seattle. John T. Paige, MD, is Professor of Clinical Surgery, Department of Surgery, LSU Health New Orleans School of Medicine, New Orleans. Please address correspondence to Aimee K. Gardner, [email protected].
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