A human factors subsystems approach to trauma care.

IMPORTANCE: A physician-centered approach to systems design is fundamental to ameliorating the causes of many errors, inefficiencies, and reliability problems. OBJECTIVE: To use human factors engineering to redesign the trauma process based on previously identified impediments to care related to coordination problems, communication failures, and equipment issues. DESIGN, SETTING, AND PARTICIPANTS: This study used an interrupted time series design to collect historically controlled data via prospective direct observation by trained observers. We studied patients from a level I trauma center from August 1 through October 31, 2011, and August 1 through October 31, 2012. INTERVENTIONS: A range of potential solutions based on previous observations, trauma team engagement, and iterative cycles identified the most promising subsystem interventions (headsets, equipment storage, medication packs, whiteboard, prebriefing, and teamwork training). Five of the 6 subsystem interventions were successfully deployed. Communication headsets were found to be unsuitable in simulation. MAIN OUTCOMES AND MEASURES: The primary outcome measure was flow disruptions, with treatment time and length of stay as secondary outcome measures. RESULTS: A total of 86 patients were observed before the intervention and 120 after the intervention. Flow disruptions increased if the patient had undergone computed tomography (CT) (F1200 = 20.0, P < .001) and had been to the operating room (F1200 = 63.1, P < .001), with an interaction among the intervention, trauma level, and CT (F1200 = 6.50, P = .01). For total treatment time, there was an effect of the intervention (F1200 = 21.7, P < .001), whether the patient had undergone CT (F1200 = 43.0, P < .001), and whether the patient had been to the operating room (F1200 = 85.8, P < .001), with an interaction among the intervention, trauma level, and CT (F1200 = 15.1, P < .001), reflecting a 20- to 30-minute reduction in time in the emergency department. Length of stay was reduced significantly for patients with major mortality risk (P = .01) from a median of 8 to 5 days. CONCLUSIONS AND RELEVANCE: Deployment of complex subsystem interventions based on detailed human factors engineering and a systems analysis of the provision of trauma care resulted in reduced flow disruptions, treatment time, and length of stay.

Flow disruptions during trauma care.

BACKGROUND: Flow disruptions (FDs) are deviations from the progression of care that compromise safety or efficiency. The frequency and specific causes of FDs remain poorly documented in trauma care. We undertook this study to identify and quantify the rate of FDs during various phases of trauma care. METHODS: Seven trained observers studied a Level I trauma center over 2 months. Observers recorded details on FDs using a validated Tablet-PC data collection tool during various phases of care-trauma bay, imaging, operating room (OR)-and recorded work-system variables including breakdowns in communication and coordination, environmental distractions, equipment issues, and patient factors. RESULTS: Researchers observed 86 trauma cases including 72 low-level and 14 high-level activations. Altogether, 1,759 FDs were recorded (20.4/case). High-level trauma comprised a significantly higher number (p = 0.0003) and rate of FDs (p = 0.0158) than low-level trauma. Across the three phases of trauma care, there was a significant effect on FD number (p < 0.0001) and FD rate (p = 0.0005), with the highest in the OR, followed by computed tomography. The highest rates of FD per case and per hour were related to breakdowns in coordination. CONCLUSIONS: This study is the largest direct observational study of the trauma process conducted to date. Complexities associated with the critical patient who arrives in the trauma bay lead to a high prevalence of disruptions related to breakdowns in coordination, communication, equipment issues, and environmental factors. Prospective observation allows individual hospitals to identify and analyze these systemic deficiencies. Appropriate interventions can then be evaluated to streamline the care provided to trauma patients.

Barriers to trauma patient care associated with CT scanning.

BACKGROUND: Trauma care is often delivered to unstable patients with incomplete medical histories, under time pressure, and with a need for multidisciplinary collaboration. Trauma patient flow through radiology is particularly prone to deviations from optimal care. A better understanding of this process could reduce errors and improve quality, flow, and patient outcomes. STUDY DESIGN: Disruptions to the flow of trauma care during trauma activations were observed over a 10-week period at a level I trauma center. Using a validated data collection tool, the type, nature, and impact of disruptions to the care process were recorded. Two physicians unaffiliated with the study conducted a post hoc, blinded review of the flow disruptions and assigned a clinical impact score to each. RESULTS: There were 581 flow disruptions observed during the radiologic care of 76 trauma patients. An average of 30.5 minutes (95% CI, 27-34; median, 29; interquartile range, 20-38) was spent in the CT scanner, with a mean of 14.5 flow disruptions per hour (95% CI, 11.8-17.2). Coordination problems (34%), communication failures (19%), interruptions (13%), patient-related factors (12%), and equipment issues (8%) were the most frequent disruption types. Flow disruptions with the highest clinical impact were generally related to patient movements while in the scanner, problems with ordering systems, equipment unavailability, and ineffective teamwork. CONCLUSIONS: Although flow disruptions cannot be eliminated completely, specific targeted interventions are available to address the issues identified.

Flow disruptions in trauma care handoffs.

BACKGROUND: Effective handoffs of care are critical for maintaining patient safety and avoiding communication problems. Using the flow disruption observation technique, we examined transitions of care along the trauma pathway. We hypothesized that more transitions would lead to more disruptions, and that different pathways would have different numbers of disruptions. METHODS: We trained observers to identify flow disruptions, and then followed 181 patients from arrival in the emergency department (ED) to the completion of care using a specially formatted PC tablet. We mapped each patient's journey and recorded and classified flow disruptions during transition periods into seven categories. RESULTS: Mapping the transitions of care shows that approximately four of five patients were assessed in the ED, transferred to imaging for further diagnostics, and then returned to the ED. There was a mean of 2.2 ± 0.09 transitions per patient, a mean of 0.66 ± 0.15 flow disruptions per patient, and 0.31 ± 0.07 flow disruptions per transition. Most of these (53%) were related to coordination problems. Although disruptions did not rise with more transitions, patients who went directly to the operating room or needed direct admission to intensive care unit were significantly more likely (P=0.0028) to experience flow disruptions than those who took other, less expedited pathways. CONCLUSIONS: Transitions in trauma care are vulnerable to systems problems and human errors. Coordination problems predominate as the cause. Sicker, time-pressured, and more at-risk patients are more likely to experience problems. Safety practices used in motor racing and other industries might be applied to address these problems.