Community Socioeconomic and Urban-Rural Disparities in Prehospital Notification of Stroke by Emergency Medical Services in North Carolina.

OBJECTIVES: Notification by emergency medical services (EMS) to the destination hospital of an incoming suspected stroke patient is associated with timelier in-hospital evaluation and treatment. Current data on adherence to this evidence-based best practice are limited, however. We examined the frequency of EMS stroke prenotification in North Carolina by community socioeconomic status (SES) and rurality. METHODS: Using a statewide database of EMS patient care reports, we selected 9-1-1 responses in 2019 with an EMS provider impression of stroke or documented stroke care protocol use. Eligible patients were 18 years old and older with a completed prehospital stroke screen. Incident street addresses were geocoded to North Carolina census tracts and linked to American Community Survey socioeconomic data and urban-rural commuting area codes. High, medium, and low SES tracts were defined by SES index tertiles. Tracts were classified as urban, suburban, and rural. We used multivariable logistic regression to estimate independent associations between tract-level SES and rurality with EMS prenotification, adjusting for patient age, sex, and race/ethnicity; duration of symptoms; incident day of week and time of day; 9-1-1 dispatch complaint; EMS provider primary impression; and prehospital stroke screen interpretation. RESULTS: The cohort of 9527 eligible incidents was mostly at least 65 years old (65%), female (55%), and non-Hispanic White (71%). EMS prenotification occurred in 2783 (29%) patients. Prenotification in low SES tracts (27%) occurred less often than in medium (30%) and high (32%) SES tracts. Rural tracts had the lowest frequency (21%) compared with suburban (28%) and urban (31%) tracts. In adjusted analyses, EMS prenotification was less likely in low SES (vs high SES; odds ratio 0.76, 95% confidence interval 0.67-0.88) and rural (vs urban; odds ratio 0.64, 95% confidence interval 0.52-0.77) tracts. CONCLUSIONS: Across a large, diverse population, EMS prenotification occurred in only one-third of suspected stroke patients. Furthermore, low SES and rural tracts were independently associated with a lower likelihood of prehospital notification. These findings suggest the need for education and quality improvement initiatives to increase EMS stroke prenotification, particularly in underserved communities.

Observational study of organisational responses of 17 US hospitals over the first year of the COVID-19 pandemic.

OBJECTIVES: The COVID-19 pandemic has required significant modifications of hospital care. The objective of this study was to examine the operational approaches taken by US hospitals over time in response to the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS: This was a prospective observational study of 17 geographically diverse US hospitals from February 2020 to February 2021. OUTCOMES AND ANALYSIS: We identified 42 potential pandemic-related strategies and obtained week-to-week data about their use. We calculated descriptive statistics for use of each strategy and plotted percent uptake and weeks used. We assessed the relationship between strategy use and hospital type, geographic region and phase of the pandemic using generalised estimating equations (GEEs), adjusting for weekly county case counts. RESULTS: We found heterogeneity in strategy uptake over time, some of which was associated with geographic region and phase of pandemic. We identified a body of strategies that were both commonly used and sustained over time, for example, limiting staff in COVID-19 rooms and increasing telehealth capacity, as well as those that were rarely used and/or not sustained, for example, increasing hospital bed capacity. CONCLUSIONS: Hospital strategies during the COVID-19 pandemic varied in resource intensity, uptake and duration of use. Such information may be valuable to health systems during the ongoing pandemic and future ones.

Community socioeconomic and urban-rural differences in emergency medical services times for suspected stroke in North Carolina.

OBJECTIVE: Our objectives were to describe time intervals of EMS encounters for suspected stroke patients in North Carolina (NC) and evaluate differences in EMS time intervals by community socioeconomic status (SES) and rurality. METHODS: This cross-sectional study used statewide data on EMS encounters of suspected stroke in NC in 2019. Eligible patients were adults requiring EMS transport to a hospital following a 9-1-1 call for stroke-like symptoms. Incident street addresses were geocoded to census tracts and linked to American Community Survey SES data and to rural-urban commuting area (RUCA) codes. Community SES was defined as high, medium, or low based on tertiles of an SES index. Urban, suburban, and rural tracts were defined by RUCA codes 1, 2-6, and 7-10, respectively. Multivariable quantile regression was used to estimate how the median and 90th percentile of EMS time intervals varied by community SES and rurality, adjusting for each other; patient age, gender, and race/ethnicity; and incident characteristics. RESULTS: We identified 17,117 eligible EMS encounters of suspected stroke from 2028 census tracts. The population was 65% 65+ years old; 55% female; and 69% Non-Hispanic White. Median response, scene, and transport times were 8 (interquartile range, IQR 6-11) min, 16 (IQR 12-20) min, and 14 (IQR 9-22) minutes, respectively. In quantile regression adjusted for patient demographics, minimal differences were observed for median response and scene times by community SES and rurality. The largest median differences were observed for transport times in rural (6.7 min, 95% CI 5.8, 7.6) and suburban (4.7 min, 95% CI 4.2, 5.1) tracts compared to urban tracts. Adjusted rural-urban differences in 90th percentile transport times were substantially greater (16.0 min, 95% CI 14.5, 17.5). Low SES was modesty associated with shorter median (-3.3 min, 95% CI -3.8, -2.9) and 90th percentile (-3.0 min, 95% CI -4.0, -2.0) transport times compared to high SES tracts. CONCLUSIONS: While community-level factors were not strongly associated with EMS response and scene times for stroke, transport times were significantly longer rural tracts and modestly shorter in low SES tracts, accounting for patient demographics. Further research is needed on the role of community socioeconomic deprivation and rurality in contributing to delays in prehospital stroke care.

Accuracy of the electronic health record's problem list in describing multimorbidity in patients with heart failure in the emergency department.

Patients with heart failure (HF) often suffer from multimorbidity. Rapid assessment of multimorbidity is important for minimizing the risk of harmful drug-disease and drug-drug interactions. We assessed the accuracy of using the electronic health record (EHR) problem list to identify comorbid conditions among patients with chronic HF in the emergency department (ED). A retrospective chart review study was performed on a random sample of 200 patients age ≥65 years with a diagnosis of HF presenting to an academic ED in 2019. We assessed participant chronic conditions using: (1) structured chart review (gold standard) and (2) an EHR-based algorithm using the problem list. Chronic conditions were classified into 37 disease domains using the Agency for Healthcare Research Quality's Elixhauser Comorbidity Software. For each disease domain, we report the sensitivity, specificity, positive predictive value, and negative predictive of using an EHR-based algorithm. We calculated the intra-class correlation coefficient (ICC) to assess overall agreement on Elixhauser domain count between chart review and problem list. Patients with HF had a mean of 5.4 chronic conditions (SD 2.1) in the chart review and a mean of 4.1 chronic conditions (SD 2.1) in the EHR-based problem list. The five most prevalent domains were uncomplicated hypertension (90%), obesity (42%), chronic pulmonary disease (38%), deficiency anemias (33%), and diabetes with chronic complications (30.5%). The positive predictive value and negative predictive value of using the EHR-based problem list was greater than 90% for 24/37 and 32/37 disease domains, respectively. The EHR-based problem list correctly identified 3.7 domains per patient and misclassified 2.0 domains per patient. Overall, the ICC in comparing Elixhauser domain count was 0.77 (95% CI: 0.71-0.82). The EHR-based problem list captures multimorbidity with moderate-to-good accuracy in patient with HF in the ED.

User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial.

OBJECTIVE: To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder. DESIGN: Pragmatic cluster randomized controlled trial (EMBED). SETTING: 18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform. PARTICIPANTS: 599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder. INTERVENTION: A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral. MAIN OUTCOME MEASURES: Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework. RESULTS: 1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01). CONCLUSIONS: User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT03658642.