Structured tools are increasingly used to identify diagnostic errors and related harms using electronic health record data. In this study, researchers compared the performance of two validated tools (Safer Dx and the DEER taxonomy) to identify diagnostic errors among patients with preventable or non-preventable deaths. Findings indicate that diagnostic errors and diagnostic process failures contributing to death were higher in preventable deaths (56%) but were also present in non-preventable deaths (17%).

Trigger tools alert patient safety personnel to potential adverse events (AE) which can then be followed up with retrospective chart review. This review sought to understand the variability in adverse event detection in acute care and study characteristics that may explain the variation. Fifty-four studies were included with a wide range of AEs detected per 100 admissions. The authors suggest developing guidelines for studies reporting on AEs identified using trigger tools to decrease study heterogeneity.

Healthcare organizations use trigger tools to identify potential errors or adverse events in the electronic health record (EHR), measure the frequency of errors, and track safety improvements. Three hospitals in Germany conducted a feasibility study of implementing the Institute for Healthcare Improvement (IHI) Global Trigger Tool (GTT) in two general surgery units and one neurosurgery unit. Twenty-two feasibility criteria were developed (low-, moderate-, problematic-level of challenge) which may help guide successful implementation of the GTT.

Trigger tools are a novel method of detecting adverse events. This article describes the location, severity, omission/commission, and type of adverse events retrospectively detected using the computerized Emergency Department Trigger Tool (EDTT). Understanding the characteristics of prior adverse events can guide future quality and safety improvement efforts.

Smart pump software can improve medication safety but can also introduce patient safety hazards, such as alert fatigue. In this study, dose error reduction software (DERS) was implemented across two large UK National Health Service (NHS) institutes for one year. Findings indicate that compliance with DERS was 45%, but across one year of implementation, severe harm or death was avoided in up to 110 patients.

Early recognition of clinical deterioration in patients is often difficult to detect and often results in poor patient outcomes. This scoping review focused on the delivery and response to deterioration alerts and their impact on patient outcomes. Only four out of 18 studies included in the review reported statistically significant improvements in at least two patient outcomes, Authors suggest that workflow and integration of the early warning system model’s features into the decision-making process may be helpful.

Voluntary event reporting (VER) systems are required in most hospitals, but their effectiveness is limited if adverse events (AE) go unreported. In this study, researchers compared rates of AE submitted to the VER against those identified using the Global Assessment of Pediatric Patient Safety (GAPPS) trigger tool to identify disparities based on patient characteristics (i.e., weight, race, English proficiency). The GAPPS tool identified 37 AE in patients with limited English proficiency; none of these were reported to the VER system, suggesting a systematic underreporting of AE in this population.

Adverse events can be identified through multiple methods, including trigger tools and voluntary reporting systems. In this comparison study, the Global Trigger Tool identified 79 AE in 88 oncology patients, compared to 21 in the voluntary reporting system; only two AE were identified by both. Results indicate multiple sources should be used to detect AE.

Organizations may employ one or more methods for identifying and examining near misses and preventable adverse events, including structured record review, web-based incident reporting systems, and daily safety briefings. Using each of the three methods, this study identified the number and types of near misses and adverse events. Results indicate that each method identifies different numbers and types of adverse events, suggesting a multi-focal approach to adverse event data collection may more effectively inform organizations. 

Patient exposure to allergens healthcare settings, such as latex or certain medications, can lead to adverse outcomes. Based on data from an incident reporting system, researchers in this study developed a system for classifying allergy-related safety events. Classification categories include: (1) incomplete or inaccurate EHR documentation, (2) human factors, such as overridden allergy alerts, (3) alert limitation or malfunction, (4) data exchange and interoperability failures, and (5) issues with EHR system default options. This classification system can be used to support improvements at the individual, team, and systems levels. 

Diagnostic errors can be identified by measuring concordance of initial and final diagnosis, for instance admission and discharge diagnoses. In this study, researchers developed and tested an automated trigger system to determine concordance between pairs of diagnoses. In comparison to the reference standard (concordance determined by experts) the automated system performance was excellent.

Trigger tools and incident reporting systems are two commonly used methods for detecting adverse events.  This retrospective study compared the performance of an electronic trigger tool plus manual screening versus existing incident reporting systems for identifying probable diagnostic errors among children with unplanned admissions following a prior emergency department (ED) visit. Of the diagnostic errors identified by the trigger tool and substantiated by manual review, less than 10% were identified through existing incident reporting systems.

Computerized decision support alerts for drug-drug interactions are commonly overridden by clinicians. This study examined fifteen well-known drug-drug interactions and identified risk factors that could reduce risk in the majority of interactions (e.g., medication order timing, medication dose, and patient factors).

Trigger tools are one method of retrospectively detecting adverse events. In this study, researchers used data from 31 Spanish hospitals to validate a trigger tool in general and gastrointestinal surgery departments. Of 40 triggers, 12 were identified for optimizing predictive power of the trigger tool, including broad spectrum antibiotherapy, unscheduled postoperative radiology, and reintervention.

The near ubiquitous use of electronic health records has increased interest in using artificial intelligence (AI) to detect errors, including preventable adverse drug events (ADEs). This scoping review identified 78 studies of AI conducted since 1998, and identified promising areas where AI could be used to predict (e.g., therapeutic response) or detect (e.g., medication prescribing errors) patient harm. 

The Harvard Medical Practice Study (HMPS) and the Institute for Healthcare Improvement Global Trigger Tool (GTT) are two of the most widely used trigger tools to identify adverse events and prompt medical record review. Fifty studies using either trigger tool to prompt a medical record review (MRR) for potentially preventable adverse events were included in this literature review. MRR reveals more adverse events than other methods; however, research is still lacking or is of moderate quality. 

Many medications and medical devices can result in preventable harm in pediatric patients. This article describes one hospital’s efforts to implement explicit, structured processes and huddles to increase situational awareness regarding high-risk therapies among the care team and family members. After implementation, the percentage of electronic health record (EHR) alerts correctly describing high-risk therapies increased from 11% to 96%.