New Tool Identifies Harms Among Children Due to Hospital Care

A newly developed “trigger tool” shows promise in flagging adverse events in children, according to a new study published in the May edition of Pediatrics. The Global Assessment of Pediatric Patient Safety (GAPPS) trigger tool, which can use electronic data to identify adverse events in pediatric patients, was developed and tested with AHRQ support. Trigger tools are commonly used to identify adverse events after they occur. A trigger tool scans a health record system and flags entries that indicate that an adverse event may have occurred. However, most existing trigger tools are not designed for pediatric patients. Read the abstract for more information about how this tool was developed and tested and its potential impact on pediatric patient safety.

Performance of the Global Assessment of Pediatric Patient Safety (GAPPS) Tool

Christopher P. Landrigan, David Stockwell, Sara L. Toomey, Samuel Loren, Michaela Tracy, Jisun Jang, Jessica A. Quinn, Sepideh Ashrafzadeh, Michelle Wang, Paul J. Sharek, Gareth Parry, Mark A. Schuster

Abstract

BACKGROUND AND OBJECTIVE: Efforts to advance patient safety have been hampered by the lack of high quality measures of adverse events (AEs). This study's objective was to develop and test the Global Assessment of Pediatric Patient Safety (GAPPS) trigger tool, which measures hospital-wide rates of AEs and preventable AEs.

METHODS: Through a literature review and expert panel process, we developed a draft trigger tool. Tool performance was tested in 16 academic and community hospitals across the United States. At each site, a primary reviewer (nurse) reviewed ∼240 randomly selected medical records; 10% of records underwent an additional primary review. Suspected AEs were subsequently evaluated by 2 secondary reviewers (physicians). Ten percent of records were also reviewed by external expert reviewers. Each trigger's incidence and positivity rates were assessed to refine GAPPS.

RESULTS: In total, 3814 medical records were reviewed. Primary reviewers agreed 92% of the time on presence or absence of a suspected AE (κ = 0.69). Secondary reviewers verifying AE presence or absence agreed 92% of the time (κ = 0.81). Using expert reviews as a standard for comparison, hospital-based primary reviewers had a sensitivity and specificity of 40% and 91%, respectively. As primary reviewers gained experience, their agreement with expert reviewers improved significantly. After removing low-yield triggers, 27 and 30 (of 54) triggers met inclusion criteria to form final manual and automated trigger lists, respectively.

CONCLUSIONS: GAPPS reliably identifies AEs and can be used to guide and monitor quality improvement efforts. Ongoing refinement may facilitate future interhospital comparisons.