Community Validation of an Approach to Detect Delayed Diagnosis of Appendicitis in Big Databases
Abstract
BACKGROUND: Detection of delayed diagnosis using administrative databases may illuminate the healthcare settings at highest risk. A method for detection of delays in claims has been validated in children's hospitals. We sought to further validate the method in community emergency departments (EDs).
METHODS: We studied patients <21 years old diagnosed with appendicitis from 2008 to 2019 in 8 eastern Massachusetts EDs. Eligible patients had 2 ED encounters within 7 days, the second with an appendicitis diagnosis. Delayed diagnosis was evaluated in medical records by trained reviewers. A previously validated trigger tool was applied to participants' electronic medical record data. The tool used data elements included in administrative data, including initial encounter diagnoses, time between encounters, presence of medical complexity, and ultimate length of stay. The tool assigned a probability of delayed diagnosis for each patient. Test characteristics at 4 confidence thresholds were determined, and the area under the receiver operating curve was calculated.
RESULTS: We analyzed 68 children with 2 encounters leading to a diagnosis of appendicitis (i.e., possible delay). When assigning a delayed diagnosis prediction to patients at 4 thresholds of confidence (>0%, >50%, >75%, and >90% confident), the positive predictive values were respectively 74%, 89%, 92%, and 89%; the negative predictive values were respectively 100%, 57%, 50%, and 33%. The area under the receiver operating…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 68 participants or records.
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