Emergency Department Adverse Events Detected Using the Emergency Department Trigger Tool.

STUDY OBJECTIVE: The Emergency Department Trigger Tool (EDTT) is a novel approach to adverse event detection in the ED. We previously described the derivation, validation, and high-level performance of this tool. Here we further detail adverse events detected to demonstrate the utility of the EDTT and how it might be used for quality improvement. METHODS: This is a secondary analysis of data from a retrospective observational study. We ran the EDTT (a computerized query for triggers) on 13 months of ED visit data, reviewing 5,582 selected records using a typical 2-tiered trigger tool approach. The adverse events detected were categorized by place of occurrence (in the ED versus present on arrival), severity, omission/commission, and type using a taxonomy with categories, subcategories, and up to 3 cross-cutting modifiers. We present adverse event data in detail, focusing in turn on each of these descriptors (severity, event types, and cross-cutting themes) and highlight opportunities identified for targeted improvement. RESULTS: We identified 458 adverse events occurring in the ED for a 13-month period, 10% of which required urgent intervention. Nearly all (90%) were acts of commission. Events resulting in harm were most often related to medications administered and patient care. Common cross-cutting event types included adverse events related to bleeding, opioids, and the use of propofol. Most adverse events (80%) led to temporary harm. CONCLUSION: The EDTT identifies a broad spectrum of adverse event types, allowing a review by severity, frequency, and type to better understand existing levels of harm in the ED and identify targets for quality improvement. A multicenter study of the EDTT is currently underway, which will contribute additional power and assess generalizability.

The Emergency Department Trigger Tool: A Novel Approach to Screening for Quality and Safety Events.

STUDY OBJECTIVE: Trigger tools improve surveillance for harm by focusing reviews on records with "triggers" whose presence increases the likelihood of an adverse event. We refine and automate a previously developed emergency department (ED) trigger tool and present record selection strategies to further optimize yield. METHODS: We specified 97 triggers for extraction from our electronic medical record, identifying 76,894 ED visits with greater than or equal to 1 trigger. We reviewed 1,726 records with greater than or equal to 1 trigger, following a standard trigger tool review process. We validated query performance against manual review and evaluated individual triggers, retaining only those associated with adverse events in the ED. We explored 2 approaches to enhance record selection: on number of triggers present and using trigger weights derived with least absolute shrinkage and selection operator logistic regression. RESULTS: The automated query performed well compared with manual review (sensitivity >70% for 80 triggers; specificity >92% for all). Review yielded 374 adverse events (21.6 adverse events per 100 records). Thirty triggers were associated with risk of harm in the ED. An estimated 10.3% of records with greater than 1 of these triggers would include an adverse event in the ED. Selecting only records with greater than or equal to 4 or greater than or equal to 9 triggers improves yield to 17% and 34.8%, respectively, whereas use of least absolute shrinkage and selection operator trigger weighting enhances the yield to as high as 52%. CONCLUSION: The ED trigger tool is a promising approach to improve yield, scope, and efficiency of review for all-cause harm in emergency medicine. Beginning with a broad set of candidate triggers, we validated a computerized query that eliminates the need for manual screening for triggers and identified a refined set of triggers associated with adverse events in the ED. Review efficiency can be further enhanced with enhanced record selection.

The emergency department trigger tool: Multicenter trigger query validation.

OBJECTIVES: We previously described derivation and validation of the emergency department trigger tool (EDTT) for adverse event (AE) detection. As the first step in our multicenter study of the tool, we validated our computerized screen for triggers against manual review, establishing our use of this automated process for selecting records to review for AEs. METHODS: This is a retrospective observational study of visits to three urban, academic EDs over 18 months by patients ≥ 18 years old. We reviewed 912 records: 852 with at least one of 34 triggers found by the query and 60 records with none. Two first-level reviewers per site each manually screened for triggers. After completion, computerized query results were revealed, and reviewers could revise their findings. Second-level reviewers arbitrated discrepancies. We compare automated versus manual screening by positive and negative predictive values (PPVs, NPVs), present population trigger frequencies, proportions of records triggered, and how often manual ratings were changed to conform with the query. RESULTS: Trigger frequencies ranged from common (>25%) to rare (1/1000) were comparable at U.S. sites and slightly lower at the Canadian site. Proportions of triggered records ranged from 31% to 49.4%. Overall query PPV was 95.4%; NPV was 99.2%. PPVs for individual trigger queries exceeded 90% for 28-31 triggers/site and NPVs were >90% for all but three triggers at one site. Inter-rater reliability was excellent, with disagreement on manual screening results less than 5% of the time. Overall, reviewers amended their findings 1.5% of the time when discordant with query findings, more often when the query was positive than when negative (47% vs. 23%). CONCLUSIONS: The EDTT trigger query performed very well compared to manual review. With some expected variability, trigger frequencies were similar across sites and proportions of triggered records ranged 31%-49%. This demonstrates the feasibility and generalizability of implementing the EDTT query, providing a solid foundation for testing the triggers' utility in detecting AEs.

Near-Miss Events Detected Using the Emergency Department Trigger Tool.

OBJECTIVES: Near misses include conditions with potential for harm, intercepted medical errors, and events requiring monitoring or intervention to prevent harm. Little is reported on near misses or their importance for quality and safety in the emergency department (ED). METHODS: This is a secondary evaluation of data from a retrospective study of the ED Trigger Tool (EDTT) at an urban, academic ED (data from October 1, 2014, to October 31, 2015; 92,859 eligible visits). All patients 18 years and older completing a visit were eligible. We ran the EDTT, a computerized query for triggers on 13 months of ED visit data, reviewing 5582 selected records using a 2-tiered approach. Events were categorized by occurrence (ED vs present on arrival [POA]), severity, omission/commission, and type, using a taxonomy with categories, subcategories, and cross-cutting modifiers. RESULTS: We identified 1458 ED near misses in 1269 of 5582 records (22.7%) and 80 near misses that were POA. Patient care events represented most ED near misses, including delays in diagnosis, treatment, and failure to monitor, primarily driven by ED boarding and crowding. Medication events were second most common (17%), including 80 medication administration errors. Of 80 POA events, 42% were related to overanticoagulation. We estimate that 19.3% of all ED visits include a near miss. CONCLUSIONS: Near-miss events are relatively common (22.7% of our sample, 19.3% in the population) and are associated with an increased risk for an adverse event. Most events were patient care related (77%) involving delays due to crowding and ED boarding followed by medication administration errors. The EDTT is a high-yield approach for detecting important near misses and latent system deficiencies that impact patient safety.

The SQuID protocol (subcutaneous insulin in diabetic ketoacidosis): Impacts on ED operational metrics.

BACKGROUND: Studies using fast-acting subcutaneous (SQ) insulin analogs in diabetic ketoacidosis (DKA) have demonstrated efficacy, safety, and cost-effectiveness, allowing treatment of mild-to-moderate (MTM)-severity DKA patients in non-intensive care unit (ICU) settings. However, emergency department (ED)-based studies are few, with limited exploration of impacts on operational metrics. METHODS: We implemented the SQuID (Subcutaneous Insulin in Diabetic Ketoacidosis) protocol for adults with MTM-severity DKA in an urban academic ED, collecting data from August 1, 2021, to February 28, 2022. We examined fidelity (frequency of required q2h glucose checks), safety (proportion of patients administered rescue dextrose for hypoglycemia), and ED length of stay (EDLOS) for the SQuID cohort compared to patients (non-ICU) treated with a traditional insulin infusion. We also examined ICU admission rate among MTM-severity DKA patients after introduction of SQuID to two historical control periods (pre-intervention and pre-COVID). We used Mann-Whitney U to test for differences in EDLOS distributions, bootstrapped (n = 1000) confidence intervals (CIs) for EDLOS median differences, and the two-sample z-test for differences in ICU admissions. RESULTS: We identified 177 MTM-severity DKA patients in the study period (78 SQuID, 99 traditional cohort) and 163 preintervention and 161 pre-COVID historical control patients. Fidelity to the SQuID pathway was good, with glucose checks exceeding the q2-h requirement. We found no difference in the proportion of rescue dextrose administration compared to the traditional pathway. We observed significant reductions in median EDLOS for the SQuID cohort compared to the traditional cohort during the study period (-3.0, 95% CI -8.5 to -1.4), the preintervention period (-1.4, 95% CI -3.1 to -0.1), and the pre-COVID control period (-3.6, 95% CI -7.5 to -1.8). CONCLUSIONS: In this single-center study at an academic ED, treatment of patients with MTM-severity DKA with a SQ insulin protocol was effective, demonstrated equivalent safety, and reduced ED length of stay.

Post-Acute and Long-Term Care Patients Account for a Disproportionately High Number of Adverse Events in the Emergency Department.

OBJECTIVES: High rates of adverse events (AEs) are reported for post-acute and long-term care settings (PA/LTC: skilled nursing facilities, inpatient rehabilitation centers, long-term acute care facilities, and home health). However, emergency department (ED)-based studies in this area are lacking. We describe all-cause harm among patients from PA/LTC settings seen in the ED. DESIGN: Retrospective observational study using the ED Trigger Tool, with dual independent nurse reviews of 5582 ED records with triggers (findings increasing the likelihood of an AE) and confirmatory physician review of putative AEs. SETTING AND PARTICIPANTS: We captured data for all adult patients at an urban, academic ED over a 13-month period (92,859 visits). PA/LTC patients were identified using a computerized ED Trigger Tool and manual review (κ = 0.85). MEASURES: We characterize the AEs identified by severity and type using the ED Taxonomy of Adverse Events, and whether the AE occurred in the ED or was present on arrival. We estimate population AE rates using inverse probability weighting. RESULTS: Compared with non-PA/LTC patients, PA/LTC patients (4.4% of population; 8.2% of our sample) tended to be older (median age 69 vs 50 years), with comparable sex ratios (54% female overall). PA/LTC patients accounted for 21% of all AEs (26% present on arrival; 13% in ED). Rates of AEs occurring in the ED were comparable after matching on age. Present on arrival AEs from a PA/LTC setting were most commonly related to patient care (39%), medication (34%), and infections (16%). CONCLUSIONS AND IMPLICATIONS: PA/LTC patients account for a small proportion of ED visits but experience a disproportionate number of AEs that are primarily present on arrival and patient-care related, and contribute to an admission rate double that for non-PA/LTC patients. Arguably, this cohort represents PA/LTC patients with the most severe AEs. Understanding these AEs may help identify high-yield targets for quality improvement.

Multicenter Test of an Emergency Department Trigger Tool for Detecting Adverse Events.

OBJECTIVES: Traditional approaches to safety and quality screening in the emergency department (ED) are porous and low yield for identifying adverse events (AEs). A better approach may be in the use of trigger tool methodology. We recently developed a novel ED trigger tool using a multidisciplinary, multicenter approach. We conducted a multicenter test of this tool and assess its performance. METHODS: In design and participants, we studied the ED trigger tool for a 13-month period at four EDs. All patients 18 years and older with Emergency Severity Index acuity levels of 1 to 3 seen by a provider were eligible. Reviewers completed standardized training modules. Each site reviewed 50 randomly selected visits per month. A first-level reviewer screened for presence of predefined triggers (findings that increase the probability of an AE). If no trigger is present, the review is deemed complete. When present, a trigger prompts an in-depth review for an AE. Any event identified is assigned a level of harm using the Medication Event Reporting and Prevention (MERP) Index, ranging from a near miss (A) to patient death (I). Events are noted as present on arrival or in the ED, an act of commission or omission, and are assigned one of four event categories. A second-level physician performs a confirmatory review of all AEs and independently reviews 10% of cases to estimate the false-negative rate. All AEs or potential AEs were reviewed in monthly group calls for consensus on findings. The primary outcome is the proportion of visits in which an AE is identified, overall and by site. Secondary outcomes include categories of events, distribution of harm ratings, and association of AEs with sociodemographic and clinical factors and triggers. We present sociodemographic data and details about AEs and results of logistic regression for associations of AEs with of triggers, sociodemographics, and clinical variables. RESULTS: We captured 2594 visits that are representative, within site, of their patient population. Overall, the sample is 64% white, 54% female, and with a mean age of 51. Variability is observed between sites for age, race, and insurance, but not sex. A total of 240 events were identified in 228 visits (8.8%) of which 53.3% were present on arrival, 19.7% were acts of omission, and 44.6% were medication-related, with some variability across sites. A MERP F score (contributing to need for admission, higher level of care, or prolonged hospitalization) was the most common severity level (35.4% of events). Overall, 185 (77.1%) of 240 events involved patient harm (MERP level ≥ E), affecting 175 visits (6.7%). Triggers were present in 951 visits (36.6%). Presence of any trigger was strongly associated with an AE (adjusted odds ratio = 4.6, 95% confidence interval = 3.2-6.6). Ten triggers were individually associated with AEs (adjusted odds ratio = 2.1-7.7). Variability was observed across sites in individual trigger associations, event rates, and categories, but not in severity ratings of events. The overall false-negative rate was 6.1%. CONCLUSIONS: The trigger tool approach was successful in identifying meaningful events. The ED trigger tool seems to be a promising approach for identifying all-cause harm in the ED.

Anti-CfaE nanobodies provide broad cross-protection against major pathogenic enterotoxigenic Escherichia coli strains, with implications for vaccine design.

Enterotoxigenic Escherichia coli (ETEC) is estimated to cause approximately 380,000 deaths annually during sporadic or epidemic outbreaks worldwide. Development of vaccines against ETEC is very challenging due to the vast heterogeneity of the ETEC strains. An effective vaccines would have to be multicomponent to provide coverage of over ten ETEC strains with genetic variabilities. There is currently no vaccine licensed to prevent ETEC. Nanobodies are successful new biologics in treating mucosal infectious disease as they recognize conserved epitopes on hypervariable pathogens. Cocktails consisting of multiple nanobodies could provide even broader epitope coverage at a lower cost compared to monoclonal antibodies. Identification of conserved epitopes by nanobodies can also assist reverse engineering of an effective vaccine against ETEC. By screening nanobodies from immunized llamas and a naïve yeast display library against adhesins of colonization factors, we identified single nanobodies that show cross-protective potency against eleven major pathogenic ETEC strains in vitro. Oral administration of nanobodies led to a significant reduction of bacterial colonization in animals. Moreover, nanobody-IgA fusion showed extended inhibitory activity in mouse colonization compared to commercial hyperimmune bovine colostrum product used for prevention of ETEC-induced diarrhea. Structural analysis revealed that nanobodies recognized a highly-conserved epitope within the putative receptor binding region of ETEC adhesins. Our findings support further rational design of a pan-ETEC vaccine to elicit robust immune responses targeting this conserved epitope.

The Emergency Department Trigger Tool: Validation and Testing to Optimize Yield.

OBJECTIVE: Recognized as a premier approach for adverse event (AE) detection, trigger tools have been developed for multiple clinical settings outside the emergency department (ED). We recently derived and tested an ED trigger tool (EDTT) with enhanced features for high-yield detection of harm, consisting of 30 triggers associated with AEs. In this study, we validate the EDTT in an independent sample and compare record selection approaches to optimize yield for quality improvement. METHODS: This is a retrospective observational study using data from 13 months of visits to an urban, academic ED by patients aged ≥ 18 years (92,859 records). We conducted standard two-tiered trigger tool reviews on an independent validation sample of 3,724 records with at least one of the 30 triggers found associated with AEs in our previous derivation sample (N = 1,786). We also tested three new candidate triggers and reviewed 72 records with no triggers for comparison purposes. We compare derivation and validation samples on: 1) triggers showing persistent associations with AEs, 2) AE yield (AEs detected/records reviewed), and 3) representativeness of AE types detected. We use bivariate associations of triggers with AEs as the basis for trigger selection. We then use multivariable modeling in the combined derivation and validation samples to determine AE risk scores using trigger weights. This allows us to predict occurrence of AEs and derive population prevalence estimates. Finally, we compare yield for detection of AEs under three record selection strategies (random selection, trigger counts, weighted trigger counts). RESULTS: Twenty-four of the 30 triggers were confirmed to be associated with AEs on bivariate testing. Three previously marginal triggers and two of three new candidate triggers were also found to be associated with AEs. The presence of any of these 29 triggers was associated with an AE rate of 10% in our selected sample (compared to 1.1% for none, p < 0.001). The risk of an AE increased with number of triggers. Combining data from both phases, we identified 461 AEs in 429 unique visits in 5,582 records reviewed. Our multivariable model (which emphasized parsimony) retained 12 triggers with a ROC AUC of 82% in both samples. Selecting records for review based on number of triggers improves yield to 14% for 4+ triggers (top 10% of visits) and to 28% for 8+ (top 1%). A weighted trigger count has corresponding yields of 18 and 38%. The method for selecting records for review did not appear to affect event-type representativeness, with similar distributions of event types and severities detected. CONCLUSIONS: In this single-site study of the EDTT we observed high levels of validity in trigger selection, yield, and representativeness of AEs, with yields that are superior to estimates for traditional approaches to AE detection. Record selection using weighted triggers outperforms a trigger count threshold approach and far outperforms random sampling from records with at least one trigger. The EDTT is a promising efficient and high-yield approach for detecting all-cause harm to guide quality improvement efforts in the ED.

Adverse Events Present on Arrival to the Emergency Department: The ED as a Dual Safety Net.

BACKGROUND: The emergency department (ED) is the natural venue for the provision of acute unscheduled care. However, little is known about the nature and proportion of this care that goes to addressing adverse events (AEs)-physical injury to a patient due to health care that requires some intervention-that are present on arrival (POA) to the ED. Described here are AEs that are POA, and population prevalence estimates for these events. METHODS: This retrospective observational study tested the ED Trigger Tool, using data from an urban academic medical center. Patients aged ≥18 completing an ED visit were eligible (N = 92,859). A total of 5,582 visits with triggers (findings that increase the likelihood of an AE) were reviewed using the two-tier trigger approach. AEs were categorized by severity, type, and whether they were POA. POA AEs, and sociodemographic and trigger associations with AEs are described. RESULTS: Of 1,181 AEs identified, 718 (60.8%) were POA to the ED. Patients with POA AEs were more often white (51.1% vs. 39.7%, p < 0.001) and older (median age 62 vs. 50, p < 0.001). The majority of POA AEs were medication-related and patient care-related events. In the population at this center, POA AEs account for an estimated 7.6% of ED visits (95% confidence interval = 6.9%-8.2%). CONCLUSION: In this single-center study, the majority of AEs detected using the ED Trigger Tool were POA. These findings highlight the importance of the ED as a safety net for harm occurring across the health system.

IgA as a potential candidate for enteric monoclonal antibody therapeutics with improved gastrointestinal stability.

Mucosal surfaces of the gastrointestinal tract play an important role in immune homeostasis and defense and may be compromised by enteric disorders or infection. Therapeutic intervention using monoclonal antibody (mAb) offers the potential for treatment with minimal off-target effects as well as the possibility of limited systemic exposure when administered orally. Critically, to achieve efficacy at luminal surfaces, mAb must remain stable and functionally active in the gastrointestinal environment. To better understand the impact of isotype, class, and molecular structure on the intestinal stability of recombinant antibodies, we used an in vitro simulated intestinal fluid (SIF) assay to evaluate a panel of antibody candidates for enteric mAb-based therapeutics. Recombinant IgG1 was the least stable following SIF incubation, while the stability of IgA generally increased upon polymerization, with subtle differences between subclasses. Notably, patterns of variability within and between mAbs suggest that variable regions contribute to mAb stability and potentially mediate mAb susceptibility to proteases. Despite relatively rapid degradation in SIF, mAbs targeting Enterotoxigenic Escherichia coli (ETEC) displayed functional activity following SIF treatment, with SIgA1 showing improved function compared to SIgA2. The results of this study have implications for the design of enteric therapeutics and subsequent selection of lead candidates based upon in vitro intestinal stability assessments.

Description and Yield of Current Quality and Safety Review in Selected US Academic Emergency Departments.

OBJECTIVES: Quality and safety review for performance improvement is important for systems of care and is required for US academic emergency departments (EDs). Assessment of the impact of patient safety initiatives in the context of increasing burdens of quality measurement compels standardized, meaningful, high-yield approaches for performance review. Limited data describe how quality and safety reviews are currently conducted and how well they perform in detecting patient harm and areas for improvement. We hypothesized that decades-old approaches used in many academic EDs are inefficient and low yield for identifying patient harm. METHODS: We conducted a prospective observational study to evaluate the efficiency and yield of current quality review processes at five academic EDs for a 12-month period. Sites provided descriptions of their current practice and collected summary data on the number and severity of events identified in their reviews and the referral sources that led to their capture. Categories of common referral sources were established at the beginning of the study. Sites used the Institute for Healthcare Improvement's definition in defining an adverse event and a modified National Coordinating Council for Medication Error Reporting and Prevention (MERP) Index for grading severity of events. RESULTS: Participating sites had similar processes for quality review, including a two-level review process, monthly reviews and conferences, similar screening criteria, and a grading system for evaluating cases. In 60 months of data collection, we reviewed a total of 4735 cases and identified 381 events. This included 287 near-misses, errors/events (MERP A-I) and 94 adverse events (AEs) (MERP E-I). The overall AE rate (event rate with harm) was 1.99 (95% confidence interval = 1.62%-2.43%), ranging from 1.24% to 3.47% across sites. The overall rate of quality concerns (events without harm) was 6.06% (5.42%-6.78%), ranging from 2.96% to 10.95% across sites. Seventy-two-hour returns were the most frequent referral source used, accounting for 47% of the cases reviewed but with a yield of only 0.81% in identifying harm. Other referral sources similarly had very low yields. External referrals were the highest yield referral source, with 14.34% (10.64%-19.03%) identifying AEs. As a percentage of the 94 AEs identified, external referrals also accounted for 41.49% of cases. CONCLUSIONS: With an overall adverse event rate of 1.99%, commonly used referral sources seem to be low yield and inefficient for detecting patient harm. Approximately 6% of the cases identified by these criteria yielded a near miss or quality concern. New approaches to quality and safety review in the ED are needed to optimize their yield and efficiency for identifying harm and areas for improvement.

Development of an Emergency Department Trigger Tool Using a Systematic Search and Modified Delphi Process.

OBJECTIVE: This study aimed to develop an emergency department (ED) trigger tool to improve the identification of adverse events in the ED and that can be used to direct patient safety and quality improvement. This work describes the first step toward the development of an ED all-cause harm measurement tool by experts in the field. METHODS: We identified a multidisciplinary group of emergency medicine safety experts from whom we solicited candidate triggers. We then conducted a modified Delphi process consisting of 4 stages as follows: (1) a systematic literature search and review, including an independent oversampling of review for inclusion, (2) solicitation of empiric triggers from participants, (3) a Web-based survey ranking triggers on specific performance constructs, and (4) a final in-person meeting to arrive at consensus triggers for testing. Results of each step were shared with participants between each stage. RESULTS: Among an initial 804 unique articles found using our search criteria, we identified 94 that were suitable for further review. Interrater reliability was high (κ = 0.80). Review of these articles yielded 56 candidate triggers. These were supplemented by 58 participant-submitted triggers yielding a total of 114 candidate triggers that were shared with team members electronically along with their definitions. Team members then voted on each measure via a Web-based survey, ranking triggers on their face validity, utility for quality improvement, and fidelity (sensitivity/specificity). Participants were also provided the ability to flag any trigger about which they had questions or they felt merited further discussion at the in-person meeting. Triggers were ranked by combining the first 2 categories (face validity and utility), and information on fidelity was reviewed for decision making at the in-person meeting. Seven redundant triggers were eliminated. At an in-person meeting including representatives from all facilities, we presented the 50 top-ranked triggers as well as those that were flagged on the survey by 2 or more participants. We reviewed each trigger individually, identifying 41 triggers about which there was a clear agreement for inclusion. Of the seven additional triggers that required subsequent voting via e-mail, 5 were adopted, arriving at a total of 46 consensus-derived triggers. CONCLUSIONS: Our modified Delphi process resulted in the identification of 46 final triggers for the detection of adverse events among ED patients. These triggers should be pilot field tested to quantify their individual and collective performance in detecting all-cause harm to ED patients.

Diabetic Ketoacidosis Management in the Emergency Department: Implementation of a Protocol to Reduce Variability and Improve Safety.

Emergency departments (EDs) are the primary venue for diagnosis and initiation of treatment of diabetic ketoacidosis (DKA). Typically managed in an intensive care unit (ICU), in many medical centers, limited ICU bed availability necessitates DKA-extended ED management until sufficient improvement for admission to a non-ICU bed. Although DKA treatment is well established, coordinating safe and effective extended care in a busy ED is complex. Recurrent problems in this high-risk transition of care led us to improvement efforts. We studied the impact of a standardizing ED DKA management in two phases: rollout of a DKA pathway in our computerized order entry system followed by audit and feedback. We evaluated adherence, clinical process, operational, and safety measures following these interventions. Adherence to the pathway was initially slow, improving significantly after audit and feedback. We observed mixed improvements in clinical processes, no changes in operational metrics (as expected), and reductions in variability for several measures. There were no deteriorations and improvements in measures of safety, and a reduction in the number of adverse event reports in the postimplementation periods.

Critical Review, Development, and Testing of a Taxonomy for Adverse Events and Near Misses in the Emergency Department.

OBJECTIVES: An adverse event (AE) is a physical harm experienced by a patient due to health care, requiring intervention. Describing and categorizing AEs is important for quality and safety assessment and identifying areas for improvement. Safety science suggests that improvement efforts should focus on preventing and mitigating harm rather than on error, which is commonplace but infrequently leads to AEs. Most taxonomies fail to describe harm experienced by patients (e.g., hypoxia, hemorrhage, anaphylaxis), focusing instead on errors, and use categorizations that are too broad to be useful (e.g., "communication error"). We set out to create a patient-centered, emergency department (ED)-specific framework for describing AEs and near misses to advance quality and safety in the acute care setting. METHODS: We performed a critical review of existing taxonomies of harm, evaluating their applicability to the ED. We identified and adopted a classification framework and developed a taxonomy using an iterative process categorizing approximately 600 previously identified AEs and near misses. We reviewed this taxonomy with collaborators at four medical centers, receiving feedback and providing clarification. We then disseminated a set of representative scenarios for these safety experts to categorize independently using the taxonomy. We calculated interrater reliability and performance compared to our criterion standard. RESULTS: Our search identified candidate taxonomies for detailed review. We selected the Adventist Health Systems AE taxonomy and modified this for use in the ED, adopting a framework of categories, subcategories, and up to three modifiers to further describe events. On testing, overall reviewer agreement with the criterion standard was 92% at the category level and 88% at the subcategory level. Three of the four raters concurred in 55 of 59 scenarios (93%) and all four concurred in 46 of 59 scenarios (78%). At the subcategory level, there was complete agreement in 40 of 59 (68%) scenarios and majority agreement in 55 of 59 instances (93%). Performance of individual raters ranged from very good (88%, 52/59) to near perfect (98%, 58/59) at the main category level. CONCLUSIONS: We developed a taxonomy of AEs and near misses for the ED, modified from an existing framework. Testing of the tool with minimal training yielded high performance and good inter-rater reliability. This taxonomy can be adapted and modified by EDs seeking to enhance their quality and safety reviews and characterize harm occurring in their EDs for quality improvement purposes.