Browsing by Author "Patterson, Brian W."

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    Comparing Strategies for Identifying Falls in Older Adult Emergency Department Visits Using EHR Data
    (Wiley, 2020) Patterson, Brian W.; Jacobsohn, Gwen Costa; Maru, Apoorva P.; Venkatesh, Arjun K.; Smith, Maureen A.; Shah, Manish N.; Mendonça, Eneida A.; Pediatrics, School of Medicine
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    Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department
    (Biomed Central, 2019-07-22) Patterson, Brian W.; Jacobsohn, Gwen C.; Shah, Manish N.; Song, Yiqiang; Maru, Apoorva; Venkatesh, Arjun K.; Zhong, Monica; Taylor, Katherine; Hamedani, Azita G.; Mendonça, Eneida A.; Pediatrics, IU School of Medicine
    BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, emergency department encounters in order to deliver appropriate care and referrals. Unfortunately, falls are difficult to identify without manual chart review, a time intensive process infeasible for many applications including surveillance and quality reporting. Here we describe a pragmatic NLP approach to automating fall identification. METHODS: In this single center retrospective review, 500 emergency department provider notes from older adult patients (age 65 and older) were randomly selected for analysis. A simple, rules-based NLP algorithm for fall identification was developed and evaluated on a development set of 1084 notes, then compared with identification by consensus of trained abstractors blinded to NLP results. RESULTS: The NLP pipeline demonstrated a recall (sensitivity) of 95.8%, specificity of 97.4%, precision of 92.0%, and F1 score of 0.939 for identifying fall events within emergency physician visit notes, as compared to gold standard manual abstraction by human coders. CONCLUSIONS: Our pragmatic NLP algorithm was able to identify falls in ED notes with excellent precision and recall, comparable to that of more labor-intensive manual abstraction. This finding offers promise not just for improving research methods, but as a potential for identifying patients for targeted interventions, quality measure development and epidemiologic surveillance.
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    Fallacy of Median Door-to-ECG Time: Hidden Opportunities for STEMI Screening Improvement
    (American Heart Association, 2022) Yiadom, Maame Yaa A.B.; Gong, Wu; Patterson, Brian W.; Baugh, Christopher W.; Mills, Angela M.; Gavin, Nicholas; Podolsky, Seth R.; Salazar, Gilberto; Mumma, Bryn E.; Tanski, Mary; Hadley, Kelsea; Azzo, Caitlin; Dorner, Stephen C.; Ulintz, Alexander; Liu, Dandan; Emergency Medicine, School of Medicine
    Background: ST‐segment elevation myocardial infarction (STEMI) guidelines recommend screening arriving emergency department (ED) patients for an early ECG in those with symptoms concerning for myocardial ischemia. Process measures target median door‐to‐ECG (D2E) time of 10 minutes. Methods and Results: This 3‐year descriptive retrospective cohort study, including 676 ED‐diagnosed patients with STEMI from 10 geographically diverse facilities across the United States, examines an alternative approach to quantifying performance: proportion of patients meeting the goal of D2E≤10 minutes. We also identified characteristics associated with D2E>10 minutes and estimated the proportion of patients with screening ECG occurring during intake, triage, and main ED care periods. We found overall median D2E was 7 minutes (IQR:4–16; range: 0–1407 minutes; range of ED medians: 5–11 minutes). Proportion of patients with D2E>10 minutes was 37.9% (ED range: 21.5%–57.1%). Patients with D2E>10 minutes, compared to those with D2E≤10 minutes, were more likely female (32.8% versus 22.6%, P=0.005), Black (23.4% versus 12.4%, P=0.005), non‐English speaking (24.6% versus 19.5%, P=0.032), diabetic (40.2% versus 30.2%, P=0.010), and less frequently reported chest pain (63.3% versus 87.4%, P<0.001). ECGs were performed during ED intake in 62.1% of visits, ED triage in 25.3%, and main ED care in 12.6%. Conclusions: Examining D2E>10 minutes can identify opportunities to improve care for more ED patients with STEMI. Our findings suggest sex, race, language, and diabetes are associated with STEMI diagnostic delays. Moving the acquisition of ECGs completed during triage to intake could achieve the D2E≤10 minutes goal for 87.4% of ED patients with STEMI. Sophisticated screening, accounting for differential risk and diversity in STEMI presentations, may further improve timely detection.