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Learning Objectives: Patient care in the burn intensive care unit (BICU) is complex and understanding clinician decision making is a challenging. We developed a card sort to learn how clinicians perceive patient condition and how they prioritize care. Results will support development of cognitive aids to improve communication and decision making. Methods: We developed the card sort through serial interviews with experts in burn critical care. The interviews discovered 10 categories of information that clinicians use to assess patient condition ( features ) and 9 categories of care elements ( treatment ) they use to manage patient care. This resulted in 97 total cards (67 features and 30 treatments). During the card sorts, clinicians were asked to identify a patient s severity of illness on a scale from could die today to could leave the ICU today. Clinicians then reviewed cards. They chose the cards they considered important to how they identified the patient s condition and what treatments should be given. The resulting arrangement of cards depicts a visual representation of the mental model they use to understand and care for patients. Results: The research team completed 133 card sorts were performed on clinicians from three backgrounds (nurse, physician, other) caring for 70 patients. Clinician experience ranged from 0 42 years. Card sorts took on average 32 minutes to complete. Of the cards that were chosen, clinicians identified identical feature cards 48 23% of the time, and treatment cards 55 25% of the time. While most clinicians identified severity of illness similarly, there were notable differences with perceptions related to 7 patients ( 3 point variance). Clear patterns of clinician perspective emerged that can be used to develop cognitive aids. Conclusions: Card sorting is a simple, effective method to help clinicians unpack their complex, intuitive understanding of patients and how they prioritize information and treatment., Published in Critical Care Medicine, v42 n12 supp, 2014.

Learning Objectives: In spring 2013 the burn unit initiated Sepsis Alert software. Continuous electronic medical record (EMR) screening used novel predictors of burn sepsis (Burn6 Criteria): heart rate (HR) 130 bpm, mean arterial pressure (MAP) 60 mmHg, base deficit (BD) -6 mEq/L, temperature (T) 36 C, use of vasoactive medications (VM), or glucose 150 mg/dl. We hypothesize sepsis alerts will be both accurate and meaningful to the provider to avoid alert fatigue prior to expanding the number of clinical staff receiving the alerts. Methods: Prospective observational study of alert performance was conducted. An automated email was sent to identified personnel. Simple rules included: /= 2 of the parameters are out of range; patient /= 48 hours post admission; /= 12 hours post-operative; and admitted to the intensive care unit. EMR was reviewed for clinical applicability for each alert. Descriptive and non-parametric statistics were used to describe variables when alert triggered vs not triggered. Results: From 8/2013 7/2013 149 alerts were generated on 47 patients (3.7 3.6; range1-16 alerts/patient) with 24 16% total burn surface area. Frequencies of variables in alerts, with value mean SD for triggered vs not triggered respectively, were: glucose 67%, 181 32 vs 117 20; MAP 67%, 56 4 vs 81 14; VM 48%, 1.4 0.6 vs 0 0; HR 27%, 139 14 vs 97 18; T 15%, 35.6 0.4 vs 38 0.9; and BD 4%, -8.2 3 vs 3.7 4 (all p values within groups 0.0001). Each alert contained 2.1 0.31 (range 2 4) variables. Patients were receiving antibiotics and antifungals concurrent with 50/71 and 21/70 alerts, respectively. Cultures were obtained after 7/65 alerts, and prior to 27/65 alerts. Lactate was /= 2 mEq in 15/55 instances. Conclusions: BD and T appear to be poorly correlated with burn sepsis alerts. Most patients were receiving antimicrobial therapy when alert was triggered; a small number of alerts preceded culture acquisition., Published in Critical Care Medicine, v42 n12 supp, 2014.

BACKGROUND: Recently, automated alerts have been used to identify patients with respiratory failure based on set criteria, which can be gleaned from the electronic medical record (EMR). Such an approach may also be useful for identifying patients with severe adult respiratory distress syndrome (ARDS) who may benefit from extracorporeal membrane oxygenation (ECMO). Inhaled nitric oxide (iNO) is a common rescue therapy for severe ARDS which can be easily tracked in the EMR, and some patients started on iNO may have indications for initiating ECMO. This case series summarizes our experience with using automated electronic alerts for ECMO team activation focused particularly on an alert triggered by the initiation of iNO. METHODS: After a brief trial evaluation, our Smart Alert system generated an automated page and e-mail alert to ECMO team members whenever a nonzero value for iNO appeared in the respiratory care section of our EMR. If iNO was initiated for severe respiratory failure, a detailed evaluation by the ECMO team determined if ECMO was indicated. For those patients managed with ECMO, we tabulated baseline characteristics, indication for ECMO, and outcomes. RESULTS: From September 2012 to July 2013, 45 iNO alerts were generated on 42 unique patients. Six patients (14%) met criteria for ECMO. Of these, four were identified exclusively by the iNO alert. At the time of the alert, the median PaO2-to-FIO2 ratiowas 64 mm Hg (range, 55-107 mm Hg), the median age-adjusted oxygenation index was 73 (range, 51-96), and the median Murray score was 3.4 (range, 3-3.75), indicating severe respiratory failure. Median time from iNO alert to ECMO initiation was 81 hours (range, -2 to 292 hours). Survival to hospital discharge was 83% in those managed with ECMO. CONCLUSION: Automated alerts may be useful for identifying patients with severe ARDS who may be ECMO candidates., Published in Journal of Trauma and Acute Care Surgery, v77 n3 s2 pS184-S189, 2014.

The rate of wound healing and its effect on mortality has not been well described. The objective of this article is to report wound healing trajectories in burn patients and analyze their effects on in-hospital mortality. The authors used software (WoundFlow) to depict burn wounds, surgical results, and healing progression at multiple time points throughout admission. Data for all patients admitted to the intensive care unit with /= 20% TBSA burned were collected retrospectively. The open wound size (OWS), which includes both unhealed burns and unhealed donor sites, was measured. We calculated the rate of wound closure (healing rate), which we defined as the change in OWS/time. We also determined the time delay (DAYS) from day of burn until day on which there was a reduction in OWS 10%. Data are medians [interquartile range]. There were 38 patients with complete data; 25 had documentation of successful healing (H), and 13 did not (NH). H differed from NH on age (38 years [32 57] vs 63 [51 74]), body mass index (27 [21 28] vs 32 [19 52]), 24-hour fluid resuscitation (12 L [10 16] vs 18 [15 20]), pressors during first 48 hours (72% vs 100%), use of renal replacement therapy (32% vs 92%), and mortality (4% vs 100%). Repeated measures analysis of covariance showed a significant difference between survivors and nonsurvivors on OWS as a function of time (P.001). Patients with a positive healing rate (+2%/day) after postburn day 20 had 100% survival whereas those with a negative healing rate ( 2%/day) had 100% mortality. For H patients, median DAYS was 41 (28 54); median DAYS/TBSA was 1.3 (1.0 1.9). Survivors had a 0.62% drop in OWS/day, or 4.3%/week. In this cohort of patients with /= 20% TBSA, there was a difference in mortality after postburn day 20, between patients with a positive healing rate (+2%/day, 100% survival) and those with a negative healing rate ( 2%/day, 100% mortality, P .05)., Published in the Journal of Burn Care & Research, v35 n6 p474-479, Nov-Dec 2014. Presented at the 44th Annual Meeting of the American Burn Association held in Seattle, WA on 24-27 Apr 2012. Prepared in collaboration with the Uniformed Services University for the Health Sciences, Bethesda, MD, the Naval Medical Research Unit-San Antonio, TX, and the University of Texas Health Science Center at San Antonio.

In its influential 2001 report, Crossing the Quality Chasm, the U.S. Institute of Medicine (IOM) proposed: IT [information technology] must play a central role in the redesign of the health care system if a substantial improvement in health care quality is to be achieved in the coming decade. The U.S. government then launched a campaign (as part of the American Recovery and Reinvestment Act of 2009), Health Information Technology for Economic and Clinical Health, to support implementation and meaningful use of electronic health records (EHRs). That campaign is now underway. Are we headed in the right direction? On April 27, 2012, several users participated in a Luncheon Symposium at the American Burn Association annual meeting in Seattle. The purpose of the symposium was to discuss the use of the EHR in burn centers. What ensued was a thorough discussion of the advantages and disadvantages of the current generation of EHRs, and of the desirable features of the next generation. We would like to summarize our impressions from that meeting., Published in Journal of Burn Care & Research, v35 n2 p134-135, 2014.