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Patient Safety Innovations

Algorithm-Based Decision Support System Guides Trauma Staff During Initial Treatment, Leading to Fewer Medical Errors

Innovation

This innovation was identified by the AHRQ PSNet Editorial Team from the AHRQ Health Care Innovations Exchange. That resource, established by AHRQ in 2008 and updated until 2016, highlighted many patient safety innovations. This particular innovation was identified by the Editorial Team as one of continued interest and importance to AHRQ PSNet users and therefore was selected to be updated and included in this new section of the AHRQ PSNet website. To prepare this updated summary, the Editorial Team worked closely with representatives associated with the innovation. Updates include expanded adoption (particularly international), additional results from expanded use, additional publications, and ensuring the correct contact information.

Summary

Trauma staff at The Alfred Hospital use a computerized decision support system to guide the care of patients during the critical first 60 minutes of resuscitation. Known as the Trauma Reception and Resuscitation System (TR&R®), this program generates prompts based on more than 40 algorithms and real-time clinical data, including patient vital signs and information entered by a trauma nurse. Displayed on a large overhead monitor, these prompts are used by clinicians to direct the care of trauma patients and to facilitate documentation and communication. The program reduced overall medical errors, along with the incidence of several specific types of mistakes, including aspiration pneumonia (caused by entrance of foreign materials into the bronchial tree) and errors during management of shock.

Innovation Patient Safety Focus

This innovation is designed to reduce medical errors during the critical first 60 minutes of resuscitation through the use of computerized decision support.

Evidence Rating

Strong: The evidence consists of a comparison of overall medical errors, patients receiving error-free treatment, incidence of aspiration pneumonia, and shock management errors in patients participating in the program to two similar control groups—one evaluated at baseline and a second randomized to receive usual care during a 2-year trial of the program.

Resources Used and Skills Needed
  • Staffing: Four hospital employees worked full-time over a 20-month period to develop and test the system, and many nursing and medical staff contributed expertise while continuing with their normal job responsibilities. System implementation led to the hiring of two critical care nursing project officers. Currently, approximately 80 physicians and 62 critical care nurses use the system as part of their regular job responsibilities.
  • Costs: The cost of developing the system totaled roughly $1.7 million (U.S.), while annual software maintenance contract averages about $30,000 (U.S.). The system interface, displays and software were revised and enhanced in 2018 (TR&R version2.0) for $0.7 million (US). Interested hospitals and/or health systems can license the software for $80,000 from The Alfred Hospital, the public trauma center where it was developed.
Use By Other Organizations

In addition to use at the Alfred Hospital (Australia), the system has been installed in trauma centres in Shenzhen and Huizhou (China), New Delhi (India) and Riyadh (Saudi Arabia). The program has not been marketed to US hospitals in the last few years, but the developers are interested in collaborations with US hospitals.

Date First Implemented
2006
Problem Addressed

Severely injured patients face a high risk of morbidity and mortality due to medical errors (e.g., delayed or omitted interventions or treatment) by time-pressed, highly stressed trauma staff in the emergency department (ED), especially during the critical first 30 minutes of treatment. Other industries have reduced errors in high-stress environments through decision support systems that guide critical decisions, yet few hospitals or trauma centers use this approach.

  • High risk of errors, preventable death: Multidisciplinary trauma teams face tremendous time pressures, have to perform multiple tasks simultaneously based on memory, and experience breakdowns in communication, especially during the initial minutes after patients arrive at the ED. Despite the existence of guidelines, protocols, and continuous performance improvement initiatives, medical errors still occur frequently in these situations (with these errors sometimes leading to death), even in established trauma centers with experienced trauma care professionals. For example, an expert panel found that a quarter of trauma deaths in Victoria, Australia could have been prevented if medical errors had not been made, with the ED phase of care being responsible for the greatest number of mistakes (an average of 7.5 per patient).
  • Unrealized potential of decision support: Systems that provide guidance in high-stress situations with a large number of variables have reduced human errors in other industries, including aviation and energy. For example, computerized prompts built into flight control systems provide immediate feedback that helps avoid errors. However, few hospitals or trauma centers use these types of decision support systems to guide trauma care.
Description of the Innovative Activity

Trauma staff at The Alfred Hospital use a computer decision support system to guide the care of patients during the critical first 60 minutes of resuscitation. Known as the Trauma Reception and Resuscitation System (TR&R®), this program generates prompts based on more than 40 algorithms and real-time clinical data, including patient vital signs and information entered by a trauma nurse. Displayed on a large overhead monitor, these prompts are used by clinicians to direct the care of trauma patients and to facilitate documentation and communication. Key program elements include the following:

  • Entry of clinical information into system: When emergency medical services personnel notify the trauma center of an incoming patient, the trauma nurse leader, known informally as the “nurse scribe,” enters preliminary information on the patient's status into the system. Once the patient arrives, the system uses physiologic monitors to track clinical data such as heart rate, blood pressure, peripheral oxygen saturation, the amount of carbon dioxide exhaled by the patient (if an endotracheal tube is in place), and body temperature. The nurse manually enters additional information (e.g., blood glucose level, level of consciousness, neurological assessment) as it becomes available.
  • Algorithm-based prompts for physicians: The system contains more than 40 algorithms covering five major subcategories of trauma resuscitation: airway management, ventilation and chest decompression, management of bleeding and shock, generic trauma, and specialty situations (neurotrauma, burns, spinal cord injury, and orthopedic trauma). Since interactions during trauma care tend to be complex, dozens of algorithms typically run simultaneously, meaning that many prompts may appear at once. The prompts appear in order of urgency in a drop-down menu format on a large overhead monitor on the wall of the trauma bay; the monitor also displays cumulative physiologic, diagnostic, and treatment data (Figure 1). The medical trauma team leader responds to these computer-generated diagnostic and intervention prompts, and the nurse scribe enters these. If the team ignores a prompt, a menu appears with selections for why it has been ignored, thus ensuring staff know they have decided against that pathway. The prompts serve as guides and do not replace the medical staff's expertise. Examples include the following:
    • Simple prompts: Prompts often remind trauma staff to perform a single task, such as to roll the patient to examine the back or measure the distance between the end of the endotracheal tube and gums.
    • Complex prompts: Some prompts are more complex. For example, prompts might remind staff working with a patient with abnormally low blood pressure to control external hemorrhage, check for related tachycardia, use intravenous blood transfusions to restore hemodynamics, and/or trigger activation of the air entry algorithm to ensure that tension pneumothorax, hemothorax, or pericardial tamponade are not contributing to low blood pressure.
  • Device integration: The system connects to the hospital's Cerner computer system, thus making it easier for trauma staff to communicate with each other and with staff elsewhere in the hospital, and to document what happens to the patient. The system has links to the following:
    • Vital signs monitors: A range of vital signs machines can be automatically, wirelessly read by the system, saving the trauma nurse leader from having to enter these values manually.
    • Video and screen capture: The system interfaces with a video camera to produce a recording of the entire session with an overlay of the vital signs display.
    • Barcode scanners: The system scans the patients’ identifier label on admission allowing direct input into the electronic medical record.
    • Electronic patient file: All information entered into the system is integrated via the TR&R® system into the patient’s electronic health record.  A secure, deidentified, disaggregated database is available to support medical research as well as machine learning.
  • Future program elements: Several new features of the TR&R® program are being evaluated by ongoing clinical trials:
    • Heads-up display integration: A variety of wearable devices have been trialed to allow doctors to have patient vital information without having to look away from the patients. The glasses will also have a camera and 4G+ connectivity, allowing trauma teams to remotely connect with off-site specialists.

Figure 1. Example of the TR&R v2.0 display

TR&R screen

 

Context of the Innovation

The Alfred Hospital is a tertiary academic medical center in Melbourne, Victoria, Australia with a Level I adult trauma center with five trauma/operating bays – each with imaging. Teams consisting of at least six clinicians (emergency medicine, anesthesiology, and surgeons) and nursing personnel care for each patient, with an emergency physician serving as team leader. The impetus for this program came from the aforementioned study finding that a quarter of trauma deaths in Victoria could have been prevented if medical errors had not occurred, with the ED phase of care being the most error prone. As a result, a multidisciplinary team began researching approaches for reducing medical errors during trauma treatment, which in turn led to development of the program.

Results

The program reduced overall medical errors, along with the incidence of specific problems such as aspiration pneumonia and errors in management of shock.

  • Fewer overall medical errors: The 435 patients whose treatment was guided by the system during a 2-year period had an average of 2.1 medical errors, below the 2.5 average in a “baseline” control group (i.e., a group of 300 similar patients evaluated at program implementation) and the 2.3 average in the randomized group of 436 similar patients receiving usual care during the 2-year trial. Overall, 22 percent of those who participated in the program received error-free care, well above the 16-percent error-free rate in the baseline control group (p=0.049).
  • Fewer cases of aspiration pneumonia: Only 2.5 percent of those trauma patients served by the system during the 2-year trial experienced aspiration pneumonia, less than half the 5.3 percent rate experienced by those in the randomized control group over this time period (p=0.046).
  • Fewer shock management errors: The average patient served by the system experienced 0.55 shock management errors during treatment, below the 0.58 average in the randomized control group during the trial and the 0.75 average in the baseline control group. The program had a particularly large impact on the use of pressure dressings to control hemorrhage (p=0.03), an intervention that was associated with a significant reduction (p<0.001) in the amount of blood products transfused during the trial.
Planning and Development Process

Key steps included the following:

  • Team formation: In April 2004, the hospital formed the Trauma Reception and Resuscitation Team to research ways to reduce medical errors during trauma treatment. The team included 33 emergency, anesthesiology, surgical, and critical care medical and nursing staff, along with staff from the hospital's information technology (IT) department. The team decided to develop and implement a computer system that provided prompts based on trauma algorithms and real-time patient information.
  • Research: The team spent 9 months analyzing current practice and the medical literature on trauma reception and resuscitation. The review encompassed emergency medical, radiological, anesthesiology, surgical, and nursing texts. Based on this research, the team identified key decision points in initial trauma resuscitation and compiled a list of hundreds of published algorithms that guide many resuscitation-related tasks and decisions.
  • Software development: In 2005, the hospital partnered with IT specialists from Swinburne University of Technology, who began developing the system's software. Working together, staff from the hospital and university adapted algorithms from the research to create more than 40 draft algorithms specifically for the computer system. The draft algorithms underwent several levels of testing that focused on interfaces, screen displays, and content. The team reached a consensus on the final algorithms written into the software.
  • Staff training: In advance of implementation, the hospital conducted a series of training sessions for all staff who would use the system. Training included online education packages, simulated trauma cases, and real cases in which trainees were paired with staff who had completed the training.
  • Preliminary, small-scale trial: From October through December 2005, the team tested the system in two of the trauma center's four bays. Based on this small-scale test, the team made minor improvements, after which they deemed the system ready for a larger-scale trial.
  • Comprehensive trial: From January 2006 through February 2008, the hospital conducted the aforementioned randomized study comparing key outcomes in trauma treatment in patients receiving system-guided care (in two bays) with similar metrics in a group receiving usual care (in the other two bays) and a baseline group of patients.
  • Full implementation: Following publication of the results, the Hospital Ethics and Research Committee determined that this represented a new ‘standard of care’ and mandated it’s use for all major trauma patients in all trauma bays (November 2008).
  • Ongoing improvement: Hospital staff regularly update the software based on newly published data and their own experiences in the trauma center. The algorithms receive regular scrutiny, discussion, and evaluation by trauma specialists. Version 2.0 incorporates dynamic ECG monitoring, imaging display, videoconferencing facilities, and remote access. The team is also evaluating expanded features of the system, including a Heads-Up Display and integration with Google Glass. The TR&R team has also begun building resuscitation systems beyond trauma (i.e., cardiac, stroke, sepsis, toxicology).
Resources Used and Skills Needed
  • Staffing: Four hospital employees worked full-time over a 20-month period to develop and test the system, and many nursing and medical staff contributed expertise while continuing with their normal job responsibilities. System implementation led to the hiring of two critical care nursing project officers. Currently, approximately 80 physicians and 62 critical care nurses use the system as part of their regular job responsibilities.
  • Costs: The cost of developing the system totaled roughly $1.7 million (U.S.), while annual software maintenance contract averages about $30,000 (U.S.). The system interface, displays and software were revised and enhanced in 2018 (TR&R version2.0) for $0.7 million (US). Interested hospitals and/or health systems can license the software for $80,000 from The Alfred Hospital, the public trauma center where it was developed.
Getting Started with This Innovation
  • Rely on available information: Existing research, information systems, policies, processes and checklists can provide the basis for this type of system. Set aside sufficient time to systematically review and assimilate this information.
  • Give clinicians flexibility: Staff will be more likely to embrace the system if its role is to guide–rather than dictate–treatment decisions.
  • Use simulation before application: Before rolling out the system, make sure all staff practice using it through simulated scenarios that closely approximate the hectic atmosphere of the ED.
  • Training: TR&R program training is provided via an on-line module.
Sustaining This Innovation
  • Regularly update algorithms and computer system: Newly available research may make existing algorithms and prompts outdated. Consequently, staff need to stay abreast of current research and update the system accordingly. Similarly, technological advances can help the system run more smoothly, so work with IT specialists to update relevant software and hardware as appropriate.  In 2018, following the successful use in 35,000 trauma resuscitations, the TR&R system interface, displays and software were revised and enhanced (TR&R version2.0) for $0.7 million (US).
  • Monitor impact to stimulate quality improvement: Staff collect, critically analyze, and regularly discuss data on the program's impact on medical errors and outcomes, and then use this information to improve the program over time.
References/Related Articles

The Trauma Reception and Resuscitation Project (TR&R®): Decision Support for a Clinical Environment (2017). Available at: https://trrproject.com/. Accessed December 21, 2020.

Fitzgerald M, Cameron P, Mackenzie C, et al. Trauma resuscitation errors and computer-assisted decision support. Arch Surg. 2011 Feb;146(2):218-25.

Fitzgerald M, Jamieson J, Tee JW, Dewan Y. ‘Trauma systems development challenges the conventional medical hierarchy’. Indian Journal of Neurotrauma 2011, Vol. 8, No. 2, pp. 67-70.  DOI:10.1016/S0973-0508(11)80002

Enticott JC, Jeffcott S, Ibrahim JE, Wood EM, Cole-Sinclair M, Fitzgerald M, Cameron PA, Phillips LE. ‘A review on decision support for massive transfusion: understanding human factors to support the implementation of complex interventions in trauma’. Transfusion. 2012 Dec;52(12):2692-705. doi: 10.1111/j.1537-2995.2012.03648.x. Epub 2012 Apr 15.

Leonard Hoon, Felix Ter Chian Tan, Rajesh Vasa, Mark Christopher Fitzgerald. ‘ICT-Enabled Time-Critical Clinical Practices: Examining the Affordances of an Information Processing Solution.’ Australasian Journal of Information Systems 19 Nov 2015. DOI:10.3127/ajisv1910.1146.

Nabil Chowdury, Peter Finnegan, Mark Christopher Fitzgerald, Wing Kong Chiu, ‘The Need for Casualty Care Decision Support in Civilian and Defense Sectors.’  Procedia Engineering 188:301-308, December 2017, DOI: 10.1016/j.proeng.2017.04.488.

Adam Bystrzycki, Yesul Kim, Mark Fitzgerald, Lorena Romero, Steven Clare. ‘Heads-Up-Displays (HUDs) and their Impact on Cognitive Load during Task Performance: A Protocol for Systematic Review.’  Biomed J Sci & Tech Res, Feb 2018, DOI: 10.26717/BJSTR.2018.02.000775

Chris J Groombridge, Yesul Kim, Amit Maini, de Villiers Smit, Mark C Fitzgerald. ‘Stress and decision-making in resuscitation: A systematic review.’ Resuscitation, 2019 Nov; 144:115-122.

Kim Y, Groombridge C, Romero L, Clare S, Fitzgerald MC.  ‘Decision support capabilities of telemedicine in emergency prehospital care: a systematic review.’  JMIR Preprints. 29/03/2020:18959; DOI: 10.2196/preprints.18959

Footnotes
  1. Houshian S, Larsen MS, Holm C. Missed injuries in a level I trauma center. J Trauma. 2002 Apr;52(4):715-9. 
  2. McDermott FT, Cordner SM, Tremayne AB. A “before and after” assessment of the influence of the new Victorian trauma care system (1997-1998 vs 2001-2003) on the emergency and clinical management of road traffic fatalities in Victoria. Victoria, Australia: Report of the Consultative Committee on Road Traffic Fatalities. December 2003.
  3. Burke CS, Salas E, Wilson-Donnelly K, et al. How to turn a team of experts into an expert medical team: guidance from the aviation and military communities. Qual Saf Health Care. 2004;13 Suppl 1:i96-i104. 
Original Publication
Original Publication indicates the date the innovation profile was first posted to the AHRQ Health Care Innovations Exchange website.
11/09/11
Last Updated
Last Updated indicates the date the most recent changes to the innovation profile were posted to the PSNet website.
03/16/21
Date Verified by Innovator
Date Verified by Innovator indicates the most recent date the innovator provided feedback during the review process.
03/01/21
The inclusion of an innovation in PSNet does not constitute or imply an endorsement by the U.S. Department of Health and Human Services, the Agency for Healthcare Research and Quality, or of the submitter or developer of the innovation.
Contact the Innovator

Professor Mark Fitzgerald ASM, MBBS MD FACEM AFRACMA 
Director of Trauma Services, The Alfred 
www.alfredhealth.org.au 
Director, National Trauma Research Institute 
Professor, Department of Surgery, Central Clinical School, Monash University 
t +613 90765325  e M.Fitzgerald@alfred.org.au