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

Disparities in Patient Safety Voluntary Event Reporting: A Scoping Review

Voluntary event reporting (VER) systems underestimate the incidence of safety events and often capture only serious events. A limited amount of data is collected through these systems, and they may be inadequate to characterize disparities in reported safety events. We conducted a scoping review of the literature to summarize the state of the evidence as it relates to differences in safety events and safety event reporting by age, gender, and race. Using a broad-based query, a systematic search for published, peer-reviewed literature that discusses patient safety event reporting and differences by age, gender, race, and socioeconomic status was conducted. Based on modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 283 studies underwent title and abstract review, yielding 56 studies for full text review. After full text review, 23 studies were carefully reviewed individually, grouped thematically, and summarized to highlight the most pertinent findings. The studies reviewed yielded important insights, particularly with regard to race, gender, and the ways events are identified. Patients from minoritized groups may be less likely to have events reported and more likely to suffer serious events. Some studies found differences in rates of reporting safety events for female vs. male providers. The rate of VER is consistently lower than the rate of events identified through identified using automated detection. The current literature describing VER data shows disparities by race, language, age, and gender for patients and providers. Further research and systematic change are needed to specifically study these disparities to guide health care institutions on ways to mitigate bias and deliver more equitable care.

How safe are paediatric emergency departments? A national prospective cohort study

BACKGROUND

Despite the high number of children treated in emergency departments, patient safety risks in this setting are not well quantified. Our objective was to estimate the risk and type of adverse events, as well as their preventability and severity, for children treated in a paediatric emergency department.

METHODS

Our prospective, multicentre cohort study enrolled children presenting for care during one of 168 8-hour study shifts across nine paediatric emergency departments. Our primary outcome was an adverse event within 21 days of enrolment which was related to care provided at the enrolment visit. We identified 'flagged outcomes' (such as hospital visits, worsening symptoms) through structured telephone interviews with patients and families over the 21 days following enrolment. We screened admitted patients' health records with a validated trigger tool. For patients with flags or triggers, three reviewers independently determined whether an adverse event occurred.

RESULTS

We enrolled 6376 children; 6015 (94%) had follow-up data. Enrolled children had a median age of 4.3 years (IQR 1.6-9.8 years). One hundred and seventy-nine children (3.0%, 95% CI 2.6% to 3.5%) had at least one adverse event. There were 187 adverse events in total; 143 (76.5%, 95% CI 68.9% to 82.7%) were deemed preventable. Management (n=98, 52.4%) and diagnostic issues (n=36, 19.3%) were the most common types of adverse events. Seventy-nine (42.2%) events resulted in a return emergency department visit; 24 (12.8%) resulted in hospital admission; and 3 (1.6%) resulted in transfer to a critical care unit.

CONCLUSION

In this large-scale study, 1 in 33 children treated in a paediatric emergency department experienced an adverse event related to the care they received there. The majority of events were preventable; most were related to management and diagnostic issues. Specific patient populations were at higher risk of adverse events. We identify opportunities for improvement in care.

Retrospective identification of medication related adverse events in the emergency medical services through the analysis of a patient safety register

Adverse drug events encompass a wide range of potential unintended and harmful events, from adverse drug reactions to medication errors, many of which in retrospect, are considered preventable. However, the primary challenge towards reducing their burden lies in consistently identifying and monitoring these occurrences, a challenge faced across the spectrum of healthcare, including the emergency medical services. The aim of this study was to identify and describe medication related adverse events (AEs) in the out-of-hospital setting. The medication components of a dedicated patient safety register were analysed and described for the period Jan 2017–Sept 2020. Univariate descriptive analysis was used to summarize and report on basic case and patient demographics, intervention related AEs, medication related AEs, and AE severity. Multivariable logistic regression was used to assess the odds of AE severity, by AE type. A total of 3475 patient records were assessed where 161 individual medication AEs were found in 150 (4.32%), 12 of which were categorised as harmful. Failure to provide a required medication was found to be the most common error (1.67%), followed by the administration of medications outside of prescribed practice guidelines (1.18%). There was evidence to suggest a 63% increase in crude odds of any AE severity [OR 1.63 (95% CI 1.03–2.6), p = 0.035] with the medication only AEs when compared to the intervention only AEs. Prehospital medication related adverse events remain a significant threat to patient safety in this setting and warrant greater widespread attention and future identification of strategies aimed at their reduction.

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.

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.

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.