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Open Access Publications from the University of California

Scholarly Works (10 results)

  • Article
  • Peer Reviewed
Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, Volume 16, Issue 5 (2015)

Introduction: Application of a clinical decision rule for subarachnoid hemorrhage, in combination with cranial computed tomography (CT) performed within six hours of ictus (early cranial CT), may be able to reasonably exclude a diagnosis of aneurysmal subarachnoid hemorrhage (aSAH). This study’s objective was to examine the sensitivity of both early cranial CT and a previously validated clinical decision rule among emergency department (ED) patients with aSAH and a normal mental status.Methods: Patients were evaluated in the 21 EDs of an integrated health delivery system between January 2007 and June 2013. We identified by chart review a retrospective cohort of patients diagnosed with aSAH in the setting of a normal mental status and performance of early cranial CT. Variables comprising the SAH clinical decision rule (age >40, presence of neck pain or stiffness, headache onset with exertion, loss of consciousness at headache onset) were abstracted from the chart and assessed for inter-rater reliability. Results: One hundred fifty-five patients with aSAH met study inclusion criteria. The sensitivity of early cranial CT was 95.5% (95% CI [90.9-98.2]). The sensitivity of the SAH clinical decision rule was also 95.5% (95% CI [90.9-98.2]). Since all false negative cases for each diagnostic modality were mutually independent, the combined use of both early cranial CT and the clinical decision rule improved sensitivity to 100% (95% CI [97.6-100.0]). Conclusion: Neither early cranial CT nor the SAH clinical decision rule demonstrated ideal sensitivity for aSAH in this retrospective cohort. However, the combination of both strategies might optimize sensitivity for this life-threatening disease.

    Cover page: Sensitivity of a Clinical Decision Rule and Early Computed Tomography in Aneurysmal Subarachnoid HemorrhageCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, Volume 16, Issue 5 (2015)

    Introduction: We evaluated emergency physicians’ (EP) current perceptions, practice, and attitudes towards evaluating stroke as a cause of dizziness among emergency department patients.

    Methods: We administered a survey to all EPs in a large integrated healthcare delivery system. The survey included clinical vignettes, perceived utility of historical and exam elements, attitudes about the value of and requisite post-test probability of a clinical prediction rule for dizziness. We calculated descriptive statistics and post-test probabilities for such a clinical prediction rule.

    Results: The response rate was 68% (366/535). Respondents’ median practice tenure was eight years (37% female, 92% emergency medicine board certified). Symptom quality and typical vascular risk factors increased suspicion for stroke as a cause of dizziness. Most respondents reported obtaining head computed tomography (CT) (74%). Nearly all respondents used and felt confident using cranial nerve and limb strength testing. A substantial minority of EPs used the Epley maneuver (49%) and HINTS (head-thrust test, gaze-evoked nystagmus, and skew deviation) testing (30%); however, few EPs reported confidence in these tests’ bedside application (35% and 16%, respectively). Respondents favorably viewed applying a properly validated clinical prediction rule for assessment of immediate and 30-day stroke risk, but indicated it would have to reduce stroke risk to <0.5% to be clinically useful.

    Conclusion: EPs report relying on symptom quality, vascular risk factors, simple physical exam elements, and head CT to diagnose stroke as the cause of dizziness, but would find a validated clinical prediction rule for dizziness helpful. A clinical prediction rule would have to achieve a 0.5% post-test stroke probability for acceptability.

      Cover page: Emergency Physician Attitudes, Preferences, and Risk Tolerance for Stroke as a Potential Cause of Dizziness SymptomsCreative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2023)

      Objectives

      Efficient and accurate emergency department (ED) triage is critical to prioritize the sickest patients and manage department flow. We explored the use of electronic health record data and advanced predictive analytics to improve triage performance.

      Methods

      Using a data set of over 5 million ED encounters of patients 18 years and older across 21 EDs from 2016 to 2020, we derived triage models using deep learning to predict 2 outcomes: hospitalization (primary outcome) and fast-track eligibility (exploratory outcome), defined as ED discharge with <2 resource types used (eg, laboratory or imaging studies) and no critical events (eg, resuscitative medications use or intensive care unit [ICU] admission). We report area under the receiver operator characteristic curve (AUC) and 95% confidence intervals (CI) for models using (1) triage variables alone (demographics and vital signs), (2) triage nurse clinical assessment alone (unstructured notes), and (3) triage variables plus clinical assessment for each prediction target.

      Results

      We found 12.7% of patients were hospitalized (n = 673,659) and 37.0% were fast-track eligible (n = 1,966,615). The AUC was lowest for models using triage variables alone: AUC 0.77 (95% CI 0.77-0.78) and 0.70 (95% CI 0.70-0.71) for hospitalization and fast-track eligibility, respectively, and highest for models incorporating clinical assessment with triage variables for both hospitalization and fast-track eligibility: AUC 0.87 (95% CI 0.87-0.87) for both prediction targets.

      Conclusion

      Our findings highlight the potential to use advanced predictive analytics to accurately predict key ED triage outcomes. Predictive accuracy was optimized when clinical assessments were added to models using simple structured variables alone.
        Creative Commons 'BY' version 4.0 license
        • Article
        • Peer Reviewed
        UC Davis Previously Published Works (2016)

        Objective

        Adoption of clinical decision support (CDS) tools by clinicians is often limited by workflow barriers. We sought to assess characteristics associated with clinician use of an electronic health record-embedded clinical decision support system (CDSS).

        Methods

        In a prospective study on emergency department (ED) activation of a CDSS tool across 14 hospitals between 9/1/14 to 4/30/15, the CDSS was deployed at 10 active sites with an on-site champion, education sessions, iterative feedback, and up to 3 gift cards/clinician as an incentive. The tool was also deployed at 4 passive sites that received only an introductory educational session. Activation of the CDSS - which calculated the Pulmonary Embolism Severity Index (PESI) score and provided guidance - and associated clinical data were collected prospectively. We used multivariable logistic regression with random effects at provider/facility levels to assess the association between activation of the CDSS tool and characteristics at: 1) patient level (PESI score), 2) provider level (demographics and clinical load at time of activation opportunity), and 3) facility level (active vs. passive site, facility ED volume, and ED acuity at time of activation opportunity).

        Results

        Out of 662 eligible patient encounters, the CDSS was activated in 55%: active sites: 68% (346/512); passive sites 13% (20/150). In bivariate analysis, active sites had an increase in activation rates based on the number of prior gift cards the physician had received (96% if 3 prior cards versus 60% if 0, p<0.0001). At passive sites, physicians < age 40 had higher rates of activation (p=0.03). In multivariable analysis, active site status, low ED volume at the time of diagnosis and PESI scores I or II (compared to III or higher) were associated with higher likelihood of CDSS activation.

        Conclusions

        Performing on-site tool promotion significantly increased odds of CDSS activation. Optimizing CDSS adoption requires active education.
          Cover page: Optimizing Clinical Decision Support in the Electronic Health Record
          • Article
          • Peer Reviewed
          UC Davis Previously Published Works (2018)
          We sought to develop and validate a clinical calculator that can be used to quantify risk for appendicitis on a continuous scale for patients with acute abdominal pain. The pediatric appendicitis risk calculator (pARC) was developed and validated through secondary analyses of 3 distinct cohorts. The derivation sample included visits to 9 pediatric emergency departments between March 2009 and April 2010. The validation sample included visits to a single pediatric emergency department from 2003 to 2004 and 2013 to 2015. Variables evaluated were as follows: age, sex, temperature, nausea and/or vomiting, pain duration, pain location, pain with walking, pain migration, guarding, white blood cell count, and absolute neutrophil count. We used stepwise regression to develop and select the best model. Test performance of the pARC was compared with the Pediatric Appendicitis Score (PAS). The derivation sample included 2423 children, 40% of whom had appendicitis. The validation sample included 1426 children, 35% of whom had appendicitis. The final pARC model included the following variables: sex, age, duration of pain, guarding, pain migration, maximal tenderness in the right-lower quadrant, and absolute neutrophil count. In the validation sample, the pARC exhibited near perfect calibration and a high degree of discrimination (area under the curve: 0.85; 95% confidence interval: 0.83 to 0.87) and outperformed the PAS (area under the curve: 0.77; 95% confidence interval: 0.75 to 0.80). By using the pARC, almost half of patients in the validation cohort could be accurately classified as at <15% risk or ≥85% risk for appendicitis, whereas only 23% would be identified as having a comparable PAS of <3 or >8. In our validation cohort of patients with acute abdominal pain, the pARC accurately quantified risk for appendicitis.
            Cover page: Development and Validation of a Novel Pediatric Appendicitis Risk Calculator (pARC)
            • Article
            • Peer Reviewed
            UC Davis Previously Published Works (2021)
            Background Resource utilization among emergency department (ED) patients with possible coronary chest pain is highly variable. Methods and Results Controlled cohort study amongst 21 EDs of an integrated healthcare system examining the implementation of a graded coronary risk stratification algorithm (RISTRA-ACS [risk stratification for acute coronary syndrome]). Thirteen EDs had access to RISTRA-ACS within the electronic health record (RISTRA sites) beginning in month 24 of a 48-month study period (January 2016 to December 2019); the remaining 8 EDs served as contemporaneous controls. Study participants had a chief complaint of chest pain and serum troponin measurement in the ED. The primary outcome was index visit resource utilization (observation unit or hospital admission, or 7-day objective cardiac testing). Secondary outcomes were 30-day objective cardiac testing, 60-day major adverse cardiac events (MACE), and 60-day MACE-CR (MACE excluding coronary revascularization). Difference-in-differences analyses controlled for secular trends with stratification by estimated risk and adjustment for risk factors, ED physician and facility. A total of 154 914 encounters were included. Relative to control sites, 30-day objective cardiac testing decreased at RISTRA sites among patients with low (≤2%) estimated 60-day MACE risk (-2.5%, 95% CI -3.7 to -1.2%, P<0.001) and increased among patients with non-low (>2%) estimated risk (+2.8%, 95% CI +0.6 to +4.9%, P=0.014), without significant overall change (-1.0%, 95% CI -2.1 to 0.1%, P=0.079). There were no statistically significant differences in index visit resource utilization, 60-day MACE or 60-day MACE-CR. Conclusions Implementation of RISTRA-ACS was associated with better allocation of 30-day objective cardiac testing and no change in index visit resource utilization or 60-day MACE. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.
              Cover page: Graded Coronary Risk Stratification for Emergency Department Patients With Chest Pain: A Controlled Cohort Study
              • Article
              • Peer Reviewed
              UC Davis Previously Published Works (2021)

              Background

              Coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has extracted devastating tolls. Despite its pervasiveness, robust information on disease characteristics in the emergency department (ED) and how that information predicts clinical course remain limited.

              Methods

              We conducted a retrospective cohort study of the first ED visit from SARS-CoV-2-positive patients in our health system, from February 21, 2020 to April 5, 2020. We reviewed each patient's ED visit(s) and included the first visit with symptoms consistent with COVID-19. We collected demographic, clinical, and treatment variables from electronic health records and structured manual chart review. We used multivariable logistic regression to examine the association between patient characteristics and 2 primary outcomes: a critical outcome and hospitalization from index visit. Our critical outcome was defined as death or advanced respiratory support (high flow nasal cannula or greater) within 21 days.

              Results

              Of the first 1030 encounters, 801 met our inclusion criteria: 15% were over age 75 years, 47% were female, and 24% were non-Hispanic white. We found 161 (20%) had a critical outcome and 393 (49%) were hospitalized. Independent predictors of a critical outcome included a history of hypertension, abnormal chest x-ray, elevated neutrophil to lymphocyte ratio, elevated blood urea nitrogen (BUN), measured fever, and abnormal respiratory vital signs (respiratory rate, oxygen saturation). Independent predictors of hospitalization included abnormal pulmonary auscultation, elevated BUN, measured fever, and abnormal respiratory vital signs.

              Conclusions

              In this large, diverse study of ED patients with COVID-19, we have identified numerous clinical characteristics that have independent associations with critical illness and hospitalization.
                Cover page: Clinical characteristics of COVID‐19 patients evaluated in the emergency department: A retrospective cohort study of 801 cases
                • Article
                • Peer Reviewed
                UC Davis Previously Published Works (2021)
                Background Coronary risk stratification is recommended for emergency department patients with chest pain. Many protocols are designed as "rule-out" binary classification strategies, while others use graded-risk stratification. The comparative performance of competing approaches at varying levels of risk tolerance has not been widely reported. Methods and Results This is a prospective cohort study of adult patients with chest pain presenting between January 2018 and December 2019 to 13 medical center emergency departments within an integrated healthcare delivery system. Using an electronic clinical decision support interface, we externally validated and assessed the net benefit (at varying risk thresholds) of several coronary risk scores (History, ECG, Age, Risk Factors, and Troponin [HEART] score, HEART pathway, Emergency Department Assessment of Chest Pain Score Accelerated Diagnostic Protocol), troponin-only strategies (fourth-generation assay), unstructured physician gestalt, and a novel risk algorithm (RISTRA-ACS). The primary outcome was 60-day major adverse cardiac event defined as myocardial infarction, cardiac arrest, cardiogenic shock, coronary revascularization, or all-cause mortality. There were 13 192 patient encounters included with a 60-day major adverse cardiac event incidence of 3.7%. RISTRA-ACS and HEART pathway had the lowest negative likelihood ratios (0.06, 95% CI, 0.03-0.10 and 0.07, 95% CI, 0.04-0.11, respectively) and the greatest net benefit across a range of low-risk thresholds. RISTRA-ACS demonstrated the highest discrimination for 60-day major adverse cardiac event (area under the receiver operating characteristic curve 0.92, 95% CI, 0.91-0.94, P<0.0001). Conclusions RISTRA-ACS and HEART pathway were the optimal rule-out approaches, while RISTRA-ACS was the best-performing graded-risk approach. RISTRA-ACS offers promise as a versatile single approach to emergency department coronary risk stratification. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.
                  Cover page: Prospective Validation and Comparative Analysis of Coronary Risk Stratification Strategies Among Emergency Department Patients With Chest Pain
                  • Article
                  • Peer Reviewed
                  UC Davis Previously Published Works (2020)

                  Objectives

                  Pediatric appendicitis remains a challenging diagnosis in the emergency department (ED). Available risk prediction algorithms may contribute to excessive ED imaging studies. Incorporation of physician gestalt assessment could help refine predictive tools and improve diagnostic imaging decisions.

                  Methods

                  This study was a subanalysis of a parent study that prospectively enrolled patients ages 5 to 20.9 years with a chief complaint of abdominal pain presenting to 11 community EDs within an integrated delivery system between October 1, 2016, and September 30, 2018. Prior to diagnostic imaging, attending emergency physicians enrolled patients with ≤5 days of right-sided or diffuse abdominal pain using a Web-based application embedded in the electronic health record. Predicted risk (gestalt) of acute appendicitis was prospectively entered using a sliding scale from 1% to 100%. As a planned secondary analysis, we assessed the performance of gestalt via c-statistics of receiver operating characteristic (ROC) curves; tested associations between gestalt performance and patient, physician, and facility characteristics; and examined clinical characteristics affecting gestalt estimates.

                  Results

                  Of 3,426 patients, 334 (9.8%) had confirmed appendicitis. Physician gestalt had excellent ROC curve characteristics (c-statistic = 0.83, 95% confidence interval = 0.81 to 0.85), performing particularly well in the low-risk strata (appendicitis rate = 1.1% in gestalt 1%-10% range, negative predictive value of 98.9% for appendicitis diagnosis). Physicians with ≥5 years since medical school graduation demonstrated improved gestalt performance over those with less experience (p = 0.007). All clinical characteristics tested, except pain <24 hours, were significantly associated with physician gestalt value (p < 0.05).

                  Conclusion

                  Physician gestalt for acute appendicitis diagnosis performed well, especially in low-risk patients and when employed by experienced physicians.
                    Cover page: Diagnostic Performance of Emergency Physician Gestalt for Predicting Acute Appendicitis in Patients Age 5 to 20 Years
                    • Article
                    • Peer Reviewed
                    UC Davis Previously Published Works (2023)

                    Background

                    Management of adults with atrial fibrillation (AF) or atrial flutter in the emergency department (ED) includes rate reduction, cardioversion, and stroke prevention. Different approaches to these components of care may lead to variation in frequency of hospitalization and stroke prevention actions, with significant implications for patient experience, cost of care, and risk of complications. Standardization using evidence-based recommendations could reduce variation in management, preventable hospitalizations, and stroke risk.

                    Methods

                    We describe the rationale for our ED-based AF treatment recommendations. We also describe the development of an electronic clinical decision support system (CDSS) to deliver these recommendations to emergency physicians at the point of care. We implemented the CDSS at three pilot sites to assess feasibility and solicit user feedback. We will evaluate the impact of the CDSS on hospitalization and stroke prevention actions using a stepped-wedge cluster randomized pragmatic clinical trial across 13 community EDs in Northern California.

                    Discussion

                    We hypothesize that the CDSS intervention will reduce hospitalization of adults with isolated AF or atrial flutter presenting to the ED and increase anticoagulation prescription in eligible patients at the time of ED discharge and within 30 days. If our hypotheses are confirmed, the treatment protocol and CDSS could be recommended to other EDs to improve management of adults with AF or atrial flutter.

                    Trial registration

                    ClinicalTrials.gov NCT05009225 .  Registered on 17 August 2021.
                      Cover page: Clinical decision support to Optimize Care of patients with Atrial Fibrillation or flutter in the Emergency department: protocol of a stepped-wedge cluster randomized pragmatic trial (O’CAFÉ trial)
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