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Ann Thorac Surg 2001;72:300-305
© 2001 The Society of Thoracic Surgeons
Address reprint requests to Dr Carthey, Cardiothoracic Unit, Great Ormond Street Hospital For Children NHS Trust, Great Ormond St, London WC1N 3JH, England
e-mail: jcarthey_gosh{at}yahoo.com
Abstract
In this review, we discuss human factors research in cardiac surgery and other medical domains. We describe a systems approach to understanding human factors in cardiac surgery and summarize the lessons that have been learned about critical incident and near-miss reporting in other high technology industries that are pertinent to this field.
During the past decade, the medical field has become increasingly aware of the need to understand human factors in adverse events (eg, near misses, critical incidents, and deaths). Of particular importance is research that takes a systems approach [1] to identify the organizational, team, and human causes that lead to adverse events. Such research includes the analysis of adverse drug events [2, 3], intensive care units [4, 5], transfusion medicine [6], and the seminal work of Gaba and coworkers [7, 8] on human factors in anesthesia.
Of particular relevance to cardiac surgeons is research on human factors in the operating room, which includes attitudes of the operating room team [9], surgeons’ leadership styles [10], the impact of new technology on performance [11], surgical decision-making in laparoscopic procedures [12], and the development of team training simulators [8, 10].
In addition to research that falls under the umbrella term "human factors research" there are several studies in cardiac surgery that have analyzed human factors variables, such as institutional and individual differences in surgical performance [13, 14], failure to rescue patients from postoperative complications [15], processes and structures that lead to good quality of care [16, 17], and the learning curve of a cardiac surgeon [18]. More recently, our own study on human factors and cardiac surgery has used the neonatal arterial switch operation (ASO) as a model of high-technology operations [19]. This multicenter study, done in the United Kingdom, was based on the premise that adverse events in cardiac operations can be explained in the same way as organizational accidents in complex, high-technology systems. Reason’s [20, 21] (1990) model of organizational accident causation was used to develop a methodology with which to study performance in the neonatal ASO.
Reason’s theory distinguishes between active failures and latent conditions. Active failures are errors and violations that are committed by people at the service delivery end of the system (eg, pilots, control room operators, financial traders, a ship’s crew, and, in cardiac surgery, the operating room team). Active failures by these people have an immediate impact on safety [20, 21].
Latent conditions result from poor decisions made by the higher management in an organization, eg, by regulators, governments, designers, and manufacturers. Latent conditions lead to weaknesses in the organization’s defenses, thus increasing the likelihood that when active failures occur they will combine with existing preconditions, breach the system’s defenses, and result in an organizational accident.
Latent conditions and active failures lead to windows of opportunity in a system’s defenses. When these windows of opportunity are aligned across several levels of a system, an accident trajectory is created. Figure 1 shows the model of organizational accidents adapted to a health care system. The accident trajectory is represented by the penetration of the levels of defense by an arrow. The holes represent latent and active failures that have breached successive levels of defense. When the arrow penetrates all the levels of defense, an adverse event (a death or a near miss) occurs. Table 1 gives examples of latent and active failures that can occur at the different levels of a health care system.
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In our study, data were collected from a questionnaire (Surgical Team Assessment Record) and from on-site observations made by a human factors researcher who attended the ASOs in 16 centers during an 18-month data collection period. Throughout the case the researcher took notes on the types of minor and major events (errors and problems) as they occurred. Minor events were errors that alone were not expected to have serious consequences for the patient; these included instrument handing errors by the scrub nurse, positioning and tension errors by the surgical assistants, and communication problems in the theater team. Major events were more serious errors, such as accidental injury of a coronary artery and severe laceration of a pulmonary artery branch requiring patch repair. Clinical data on patient and procedural variables were also collected.
Data were collected on a total of 243 neonatal ASOs. The data were analyzed using a multivariable logistic regression model that integrated the human factors and patient and procedural data to determine the relative contribution of each to adverse events (near misses and deaths). The full results of the study have been reported by de Leval and coworkers [19]. The ASO study produced some important insights into errors and near misses in cardiac operations. The remaining discussion focuses on these findings and more generally on lessons learned about near miss and critical incident reporting in other relevant domains.
Critical incident and near-miss reporting in medicine
"A near miss is any situation which has clearly significant and potentially serious (safety related) consequences." (Van der Schaaf and coworkers, 1991) [22].
Near-miss reporting systems are used widely in the nuclear [23], aviation [24, 25], chemical [22, 26], and railway industries [27]. Central to the concept of near misses is that some form of recovery took place; ie, an accident sequence was initiated and then either by chance or by the actions of an individual, team, or organization it was averted before negative consequences occurred [22]. Analysis of near misses can highlight weaknesses in the organization, enhance risk awareness, and show how system operators successfully managed a bad situation.
Incident reporting systems are being adapted for use in medical domains such as anesthesia [28, 29], transfusion medicine [6], and intensive care units [30]. A key component of incident reporting systems is that they are based on error taxonomies that allow the incident investigator to trace the causal path from active failures to latent conditions. In transfusion medicine, the Medical Event Reporting System for Transfusion Medicine is based on the Eindhoven Classification Model, an error taxonomy that originally was developed to investigate near misses in the chemical process industry [22]. This error taxonomy classifies the root causes of an adverse event into three main categories—technical (equipment and software), organizational (policies, procedures, and protocols), and human (errors and violations) [6].
The Confidential Incident Reporting System for anesthesia [28] is an anonymous incident reporting system that can be found on the internet (www.medana.unibas.ch/cirs/). It was designed to collect data on anesthetic-related incidents across medical specialities. The person reporting the incident fills in fields relating to the patient, anesthetic, and incident. Data also are gathered on the reporter’s perception of the personal, team, equipment, and system factors that contributed to the adverse event.
An important aspect of Confidential Incident Reporting System is that there is a strong focus on the recovery mechanisms that allowed the event to be managed successfully. Insights into the processes that underlie successful recovery of an incident have been neglected in the human factors literature, and this is an important area for future research.
Analysis of near misses in cardiac surgery
Critical incident and near-miss reporting that is based on human error taxonomies is in its infancy in the field of cardiac surgery. However, a few studies have described and analyzed near misses and recovery in cardiac operations, including the analysis of near misses in a series of ASOs by one cardiac surgeon [31]; the management of complications and failure to rescue patients who had coronary arterial bypass grafting (CABG) [15]; and case studies of near misses in patients who had cardiac operations [32, 33] and critical incident reporting studies in perfusion [34]. de Leval and coworkers [31] have shown that monitoring near misses can provide early indication of deterioration in surgical performance. A series of 104 ASOs, all done by the same cardiac surgeon (MdL), were used in the analysis. A near miss was defined as "the need to go back onto the heart lung bypass machine after the first attempt to wean the patient off bypass had failed (due to hemodynamic instability of the patient)" [31]. Retrospective analysis of the 104 neonatal ASOs, using cumulative sum (CUSUM) modeling, showed that if a near-miss monitoring system had been in place the surgeon would probably have been alerted to the deterioration in his performance before a cluster of deaths.
Silber and coworkers [15] analyzed recovery from perioperative and postoperative complications in a multicenter study of CABG patients. This study compared the in-hospital mortality rate, complication rates, and rates of death after complication, termed "failure to rescue," in 16,673 patients who had a CABG procedure in 57 hospitals. Complication rates and mortality rates are used to rank the performance of hospitals, and the aim of the study was to test the validity of using complication rates as indicators of quality of care. Complications included cardiac and respiratory arrest, return to surgery, bleeding, pneumonia, hypotension, deep vein thrombosis, and pneumothorax. The findings showed that there was no correlation between hospital rankings based on complication rates and those based on either in-hospital mortality or failure-to-rescue rates. In contrast, mortality and failure-to-rescue rates are correlated with hospital characteristics that are traditionally thought to be related to quality of care. The hospital with the highest mortality rate also had a high failure-to-rescue rate, suggesting that there were problems in the management of complications. Failure to rescue a patient might therefore be an appropriate measure of organizational performance. This hypothesis is supported by the personal experience of one of the authors (MdL) who, in a recent analysis of 120 ASOs, found that although the incidence of near misses remained the same as in the 1994 study, the mortality rate had returned to a low level (2.5%). This finding suggests that the operating team was better at recovering from near misses.
Other research has found a decrease in the rate of surgical complications with increased surgical experience; Novick and coworkers [18] found decreased rates of perioperative myocardial infarction (7.0% to 2.2%, p = 0.005), intraaortic balloon pump use (7.0% to 3.0%, p = 0.05), and reoperation for bleeding (8.4% to 2.2%) in series of 1,347 patients operated on by the same surgeon over a 10-year period. Hence, surgical experience might improve the surgeon’s ability to recover from near misses and reduce the incidence of certain types of complications.
Lessons from other high-technology industries
In other high-technology industries, several practical lessons about near-miss and incident reporting have been learned which have implications for this field. The first problem is that of definition. Defining near misses in cardiac surgery is complicated by the need to distinguish between near misses and serious perioperative and postoperative complications. The definition of a near miss by de Leval and coworkers [31] may be used as an example. The need to go back onto bypass after the first weaning period because of the patient’s hemodynamic instability can be viewed as a near miss or as an intraoperative complication, depending on the stance of the researcher. In their retrospective analysis of CABG patients, Silber and coworkers [15] classified many events as complications, which in our own prospective analysis of ASOs were classified as near misses; for example, cardiac arrest in the intensive care unit and return to the operating room for reinvestigation. Developing consensus definitions for the field of cardiac surgery is an important issue for future research.
Methods should be developed that assess the relative contribution of the patient and procedural and human factors to outcomes. Too often human factors research fails to take account of patient and procedural variables, and too often medical research fails to consider human factors. The work of Silber and coworkers [15] has shown that serious complications can result from patient variables, whereas our research on the ASO has also identified some of the human errors and systems problems that cause adverse events [19].
Near-miss and critical incident reporting systems must have realistic aims and objectives. Clinicians often start collecting incident and human error data with misconceptions about what can be achieved. For example, a statement one sees frequently in the adverse drug event literature is the desire to achieve a zero-incident rate [2]. This goal is impossible in any system operated by humans. Rather, efforts should be focused on increasing the error tolerance of the system and gaining a better understanding of error and near-miss recovery mechanisms.
Incident reporting systems should also aim to have a high reporting rate and to have systems in place to feed back information to staff. Underreporting of incidents is a serious problem, and there is evidence that it relates to the existence of a blame culture in medicine; for example, junior doctors do not report incidents because they fear they will be blamed by senior staff [35]. Previous research has shown that the organizational culture in which the incident reporting system is developed is essential to its success [26]. No-blame or blame-free cultures [25, 26] are ones in which people are encouraged to report incidents and near misses on the premise that they will not be held accountable for the human errors involved. The experience of the nuclear and rail [23, 27] industries in the United Kingdom has shown that no-blame incident reporting cultures do not work in practice. Sooner or later an incident occurs for which a senior manager disciplines a member of staff, thus undermining the whole ethos of the system. It is recommended that incident reporting systems are introduced within the framework of a just culture, where the aims of the system are to learn lessons about human and organizational problems and about error recovery rather than as a mechanism to apportion blame.
Confidentiality and anonymity of incident reporting are also important because they encourage a better reporting rate. However, anonymity has to be balanced with the objective of getting the best description of the incident or near miss as possible. The Australian Incident Monitoring Study [29] has a novel solution to this problem. Incident reporting forms have a tear-off top sheet for name and role of the person reporting the incident. This gives the analyst the chance to clarify points of interest before tearing off this sheet and ensuring anonymity of the data.
Many incident reporting systems are based solely on retrospective reports and can therefore be subject to recall bias. Cross-validation of incident information using multiple data collection methods, such as interviews, questionnaires, and patient information, is essential to check the facts of the case and to identify all the latent failures that were involved.
Ideally, a panel of medical experts from different specialties should be involved in categorizing the active and latent errors [3]. Data should be collected on the number of times that the expert panel disagrees on the classification of a root cause (ie, the latent system, design, technical, and cultural factors that were important precursors of the incident). This is a good quality assurance measure and provides an early indication of lack of concordance in the data analysis process. Also, interrater reliability measures of concordance between experts who are classifying root causes should be done. Finally, both quantitative and qualitative analyses of near-miss data provide important insights into causation and recovery. The importance of qualitative analyses is illustrated in the following case studies.
Critical incidents in cardiac surgery: some illustrative examples
Recovering from a major error: prevention of a near miss
While surgeon A was doing a CABG procedure, after removing the cross-clamp the heart dilated and there was poor ventricular function. On visual inspection the heart was laboring and poorly perfused. The surgeon expressed doubts about the quality of his anastomosis and was concerned that the patient’s ischemic mitral regurgitation was worse than that noted in preoperative investigations. A transesophogeal echocardiogram was done, which confirmed that there was severe mitral regurgitation in the obtuse marginal area. On receiving this information, the surgeon decided not to attempt to wean the patient from the heart-lung bypass machine. He chose instead to recool the patient and after investigating the surgical repair he regrafted the obtuse marginal coronary arteries. The patient was rewarmed for a second time and successfully weaned off bypass on the first attempt.
In this case the surgeon compensated for (ie, recovered from) the major surgical error of suboptimal grafting of the coronaries. Error recovery was cued by the symptoms of the heart and echocardiographic information, to which the surgeon responded appropriately. Had the surgeon tried to wean the patient off the heart-lung bypass machine the result would have been a near miss, where the first attempt at weaning the patient off the heart lung bypass machine would have been unsuccessful because of the hemodynamic instability of the patient, necessitating the reinstitution of bypass.
Minor errors set the incident sequence in motion
Surgeon B was preparing a patient for bypass. During the prebypass surgical tasks he was interrupted by the theater manager, who came into the operating room to discuss reorganizing the cases for the following day. Surgeon B was annoyed at the loss of surgical flow caused by this interruption but nevertheless answered the questions the theater manager asked him. After this event the surgeon continued to prepare the patient to be put onto the heart-lung bypass machine. The theater manager entered the operating room a second time to request further information from surgeon B. The second interruption occurred when the surgeon and the anesthesiologist usually communicated with each other to confirm that the heparin had been given before putting the patient onto the heart-lung bypass machine. Surgeon B was distracted by the question that the theater manager had asked him and annoyed that he had been forced to lose his surgical flow for a second time. He forgot to initiate the usual heparin checking protocol that he and the anesthesiologist always used at this stage of the procedure. This protocol involved surgeon B asking the anesthesiologist to administer the heparin; the drug would then by given by the anesthesiologist, and when it had been given he would inform surgeon B that he had completed this stage of the task. Surgeon B would then request confirmation that the heparin had been given before proceeding any further. Once he had received a second confirmation from the anesthesiologist he would prepare for the patient to be put on the heart-lung bypass machine. In this case surgeon B did not ask for the heparin to be given, so the anesthesiologist, who could not see the surgical area because there were resident physicians observing the case, waited for the heparin request. Surgeon B began to insert the arterial cannula into the aorta. He then instructed the perfusionist to prepare to go onto the heart-lung bypass machine in a few minutes. At this point the anesthesiologist was alerted to the missing step in the procedure, intervened, and reminded the surgeon that he had not yet given the heparin. The anesthesiologist had been waiting for surgeon B to ask for the heparin to be given, as was the normal practice in this team. The heparin protocol was then initiated normally and the case proceeded smoothly thereafter.
This case study shows how a series of minor events (internal and external distractors that interrupted the surgical flow of the procedure) set an incident sequence in motion. In this case the tight coupling between the anesthesiologist and the surgeon cued the former to recover the situation before the occurrence of an adverse event. It is important to note that several system defenses remained in place; for example, surgeon B still had to insert the venous cannula and begin to circulate blood through the bypass catheters.
Comment
There is an important role for human factors research in cardiac surgery. More research is needed to refine methods for the prospective analysis of surgical performance in the operating room and the retrospective analysis of near misses and critical incidents. By gaining a better understanding of the types of minor and major events, near misses, or critical incidents that occur during surgical procedures, we can teach a new generation of surgeons the necessary recovery strategies. Future research should attempt to identify the minor and major events that occur in cardiac procedures other than the ASO and to gain a better understanding of the processes underlying compensation of errors and recovery from near misses. The error taxonomies that have been used to develop near-miss and critical incident reporting systems in other medical domains should be applied to cardiac surgery, taking into consideration the lessons learned about their implementation in other industries.
References
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