Objective: Acute pharyngitis is one of the most common causes of ambulatory clinic visits; however, group A Streptococcus accounts for less than a third. National guidelines recommend against streptococcal testing in patients with viral features. This study aims to assess the rate of inappropriate streptococcal rapid antigen detection tests (RADT)s in children evaluated in urgent care clinics (UCC)s and emergency department (ED)s at a children's hospital. Methods:We retrospectively reviewed charts of 10% of children 3 years or older with RADTs ordered between April and September 2018 at EDs and UCCs. The test was determined to be inappropriate if the patient had no sore throat and/or had 2 or more viral symptoms: rhinorrhea/congestion, cough, diarrhea, hoarseness, conjunctivitis, or viral exanthem.Results: Over the study period, 7678 RADTs were performed, of which 7024 (91.2%) were in children 3 years or older. We evaluated 708 charts and found 44% of RADTs were inappropriate. The predicted probability of inappropriate RADT was highest among patients with a triaged reason for visit for respiratory complaints (70.5%), viral upper respiratory tract infection (69.7%), and rash (61.3%). Of the inappropriate RADTs, 20.1% were positive, whereas 32.2% of the appropriate RADTs were positive. Conclusion:Quality improvement initiatives are needed to decrease the rate of inappropriate RADTs in pediatric UCC and ED settings.
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Background Acute pharyngitis is one of the most common causes of pediatric health care visits, accounting for approximately 12 million ambulatory care visits each year. Rapid antigen detection tests (RADTs) for Group A Streptococcus (GAS) are one of the most commonly ordered tests in the ambulatory settings. Approximately 40–60% of RADTs are estimated to be inappropriate. Determination of inappropriate RADT frequently requires time-intensive chart reviews. The purpose of this study was to determine if natural language processing (NLP) can provide an accurate and automated alternative for assessing RADT inappropriateness. Methods Patients ≥ 3 years of age who received an RADT while evaluated in our EDs/UCCs between April 2018 and September 2018 were identified. A manual chart review was completed on a 10% random sample to determine the presence of sore throat or viral symptoms (i.e., conjunctivitis, rhinorrhea, cough, diarrhea, hoarse voice, and viral exanthema). Inappropriate RADT was defined as either absence of sore throat or reporting 2 or more viral symptoms. An NLP algorithm was developed independently to assign the presence/absence of symptoms and RADT inappropriateness. The NLP sensitivity/specificity was calculated using the manual chart review sample as the gold standard. Results Manual chart review was completed on 720 patients, of which 320 (44.4%) were considered to have an inappropriate RADT. When compared to the manual review, the NLP approach showed high sensitivity (se) and specificity (sp) when assigning inappropriateness (88.4% and 90.0%, respectively). Optimal sensitivity/specificity was also observed for select symptoms, including sore throat (se: 92.9%, sp: 92.5%), cough (se: 94.5%, sp: 96.5%), and rhinorrhea (se: 86.1%, sp: 95.3%). The prevalence of clinical symptoms was similar when running NLP on subsequent, independent validation sets. After validating the NLP algorithm, a long term monthly trend report was developed. Figure Inappropriate GAS RADTs Determined by NLP, June 2018-May 2020 Conclusion An NLP algorithm can accurately identify inappropriate RADT when compared to a gold standard. Manual chart review requires dozens of hours to complete. In contrast, NLP requires only a couple of minutes and offers the potential to calculate valid metrics that are easily scaled-up to help monitor comprehensive, long-term trends. Disclosures Brian R. Lee, MPH, PhD, Merck (Grant/Research Support)
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