Search

Purpose: The purpose of this study is to decrease overutilization of laboratory testing by eliminating a feature of the electronic ordering system that allowed providers to order laboratory tests to occur daily without review.Methods: We collected rates of utilization of a group of commonly ordered laboratory tests (number of tests per patient per day) throughout the entire hospital from June 10, 2013 through June 10, 2015. Our intervention, which eliminated the ability to order daily recurring tests, was implemented on June 11, 2014. We compared pre- and postintervention rates in order to assess the impact and surveyed providers about their experience with the intervention.Results: We examined 1,296,742 laboratory tests performed on 92,799 unique patients over 434,059 patient days. Before the intervention, the target tests were ordered using this daily recurring mechanism 33% of the time. After the intervention we observed an 8.5% (P <.001) to 20.9% (P <.001) reduction in tests per patient per day. The reduction in rate for some of the target tests persisted during the study period, but not for the 2 most commonly ordered tests. We estimated an approximate reduction in hospital costs of $300,000 due to the intervention.Conclusion: A simple modification to the order entry system significantly and immediately altered provider practices throughout a large tertiary care academic center. This strategy is replicable by the many hospitals that use the same electronic health record system, and possibly, by users of other systems. Future areas of study include evaluating the additive effects of education and real-time decision support. [ABSTRACT FROM AUTHOR]

Background We examined effects of single-nucleotide variants (SNVs) of IL1RN , the gene encoding the anti-inflammatory interleukin 1 receptor antagonist (IL-1Ra), on the cytokine release syndrome (CRS) and mortality in patients with acute severe respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods IL1RN CTA haplotypes formed from 3 SNVs (rs419598, rs315952, rs9005) and the individual SNVs were assessed for association with laboratory markers of inflammation and mortality. We studied 2589 patients hospitalized with SARS-CoV-2 between March 2020 and March 2021. Results Mortality was 15.3% and lower in women than men (13.1% vs 17.3%, P =.0003). Carriers of the CTA-1/2 IL1RN haplotypes exhibited decreased inflammatory markers and increased plasma IL-1Ra. Evaluation of the individual SNVs of the IL1RN, carriers of the rs419598 C/C SNV exhibited significantly reduced inflammatory biomarker levels and numerically lower mortality compared to the C/T-T/T genotype (10.0% vs 17.8%, P =.052) in men, with the most pronounced association observed in male patients ≤74 years old, whose mortality was reduced by 80% (3.1% vs 14.0%, P =.030). Conclusions The IL1RN haplotype CTA and C/C variant of rs419598 are associated with attenuation of the CRS and decreased mortality in men with acute SARS-CoV-2 infection. The data suggest that the IL1RN pathway modulates the severity of coronavirus disease 2019 (COVID-19) via endogenous anti-inflammatory mechanisms. [ABSTRACT FROM AUTHOR]

Background: Socio-economic status, living environments, and race have been implicated in the development of different congenital abnormalities. As orofacial clefting is the most common anomaly affecting the face, an understanding of its prevalence in the United States and its relationship with different determinants of health is paramount. Therefore, the purpose of this study is to determine the modern prevalence of oral–facial clefting in the United States and its association with different social determinants of health. Methods: Utilizing Epic Cosmos, data from approximately 180 US institutions were queried. Patients born between November 2012 and November 2022 were included. Eight orofacial clefting (OC) cohorts were identified. The Social Vulnerability Index (SVI) was used to assess social determinants of health. Results: Of the 15,697,366 patients identified, 31,216 were diagnosed with OC, resulting in a prevalence of 19.9 (95% CI: 19.7–20.1) per 10,000 live births. OC prevalence was highest among Asian (27.5 CI: 26.2–28.8) and Native American (32.8 CI: 30.4–35.2) patients and lowest among Black patients (12.96 CI: 12.5–13.4). Male and Hispanic patients exhibited higher OC prevalence than female and non-Hispanic patients. No significant differences were found among metropolitan (20.23/10,000), micropolitan (20.18/10,000), and rural populations (20.02/10,000). SVI data demonstrated that OC prevalence was positively associated with the percentage of the population below the poverty line and negatively associated with the proportion of minority language speakers. Conclusions: This study examined the largest US cohort of OC patients to date to define contemporary US prevalence, reporting a marginally higher rate than previous estimates. Multiple social determinants of health were found to be associated with OC prevalence, underscoring the importance of holistic prenatal care. These data may inform clinicians about screening and counseling of expectant families based on socio-economic factors and direct future research as it identifies potential risk factors and provides prevalence data, both of which are useful in addressing common questions related to screening and counseling. [ABSTRACT FROM AUTHOR]

Introduction: Emergency department (ED) patient care often hinges on the result of a diagnostic test. Frequently there is a lag time between a test result becoming available for review and physician decisionmaking or disposition based on that result. We implemented a system that electronically alerts ED providers when test results are available for review via a smartphone- and smartwatch- push notification. We hypothesized this would reduce the time from result to clinical decision-making. Methods: We retrospectively assessed the impact of the implementation of a push notification system at three EDs on time-to-disposition or time-to-follow-up order in six clinical scenarios of interest: chest radiograph (CXR) to disposition, basic metabolic panel (BMP) to disposition, urinalysis (UA) to disposition, respiratory pathogen panel (RPP) to disposition, hemoglobin (Hb) to blood transfusion order, and abnormal D-dimer to computed tomography pulmonary angiography (CTPA) order. All ED patients during a one-year period of push-notification availability were included in the study. The primary outcome was median time in each scenario from result availability to either disposition order or defined followup order. The secondary outcome was the overall usage rate of the opt-in push notification system by providers. Results: During the study period there were 6115 push notifications from 4183 ED encounters (2.7% of all encounters). Of the six clinical scenarios examined in this study, five were associated with a decrease in median time from test result availability to patient disposition or follow-up order when push notifications were employed: CXR to disposition, 80 minutes (interquartile range [IQR] 32-162 minutes) vs 56 minutes (IQR 18-141 minutes), difference 24 minutes (p<0.01); BMP to disposition, 128 minutes (IQR 62-225 minutes) vs 116 minutes (IQR 33-226 minutes), difference 12 minutes (p<0.01); UA to disposition, 105 minutes (IQR 43-200 minutes) vs 55 minutes (IQR 16-144 minutes), difference 50 minutes (p<0.01); RPP to disposition, 80 minutes (IQR 28-181 minutes) vs 37 minutes (IQR 10-116 minutes), difference 43 minutes (p<0.01); and D-dimer to CTPA, 14 minutes (IQR 6-30 minutes) vs 6 minutes (IQR 2.5-17.5 minutes), difference 8 minutes (p<0.01). The sixth scenario, Hb to blood transfusion (difference 19 minutes, p=0.73), did not meet statistical significance. Conclusion: Implementation of a push notification system for test result availability in the ED was associated with a decrease in lag time between test result and physician decision-making in the examined clinical scenarios. Push notifications were used in only a minority of ED patient encounters. [ABSTRACT FROM AUTHOR]

Purpose Despite progress in the treatment of coronavirus disease 2019 (COVID-19), including the development of monoclonal antibodies (mAbs), more clinical data to support the use of mAbs in outpatients with COVID-19 is needed. This study is designed to determine the impact of bamlanivimab, bamlanivimab/etesevimab, or casirivimab/imdevimab on clinical outcomes within 30 days of COVID-19 diagnosis. Methods A retrospective cohort study was conducted at a single academic medical center with 3 campuses in Manhattan, Brooklyn, and Long Island, NY. Patients 12 years of age or older who tested positive for COVID-19 or were treated with a COVID-19–specific therapy, including COVID-19 mAb therapies, at the study site between November 24, 2020, and May 15, 2021, were included. The primary outcomes included rates of emergency department (ED) visit, inpatient admission, intensive care unit (ICU) admission, or death within 30 days from the date of COVID-19 diagnosis. Results A total of 1,344 mAb-treated patients were propensity matched to 1,344 patients with COVID-19 patients who were not treated with mAb therapy. Within 30 days of diagnosis, among the patients who received mAb therapy, 101 (7.5%) presented to the ED and 79 (5.9%) were admitted. Among the patients who did not receive mAb therapy, 165 (12.3%) presented to the ED and 156 (11.6%) were admitted (relative risk [RR], 0.61 [95% CI, 0.50-0.75] and 0.51 [95% CI, 0.40-0.64], respectively). Four mAb patients (0.3%) and 2.64 control patients (0.2%) were admitted to the ICU (RR, 01.51; 95% CI, 0.45-5.09). Six mAb-treated patients (0.4%) and 3.37 controls (0.3%) died and/or were admitted to hospice (RR, 1.61; 95% CI, 0.54-4.83). mAb therapy in ambulatory patients with COVID-19 decreases the risk of ED presentation and hospital admission within 30 days of diagnosis. [ABSTRACT FROM AUTHOR]

Background The epidemiology of nosocomial bloodstream infections (NBSIs) in patients with coronavirus disease 2019 (COVID-19) is poorly understood, due in part to substantial disease heterogeneity resulting from multiple potential pathogens. Methods We identified risk factors for NBSIs and examined the association between NBSIs and mortality in a retrospective cohort of patients hospitalized with COVID-19 in 2 New York City hospitals during the height of the pandemic. We adjusted for the potential effects of factors likely to confound that association, including age, race, illness severity upon admission, and underlying health status. Results Between January 1 and October 1, 2020, 1403 patients had a positive blood culture, and 79 and 101 met the stringent criteria for NBSI among non-COVID-19 and COVID-19 patients, respectively. NBSIs occurred almost exclusively among patients who were severely ill with COVID-19 at hospital admission. NBSIs were associated with elevated mortality, even after adjusting for baseline differences in COVID-19 illness (55% cases vs 45% controls; P  = .13). Mortality was concentrated in patients with early-onset pneumonia caused by S. aureus and gram-negative bacteria. Less virulent Candida (49%) and Enterococcus (12%) species were the predominant cause of NBSI in the latter stages of hospitalization, after antibiotic treatment and COVID-19 treatments that attenuate immune response. Most Enterococcus and Candida infections did not have an identifiable source and were not associated with common risk factors for infection by these organisms. Conclusions Pathogen species and mortality exhibited temporal differences. Early recognition of risk factors among COVID-19 patients could potentially decrease NBSI-associated mortality through early COVID-19 and antimicrobial treatment. [ABSTRACT FROM AUTHOR]

The article reflects the views of author which focus on the positive association observed in our study between the use of oral anticoagulants and the risk of Covid-19. Topics include use of antihypertensive therapy is not relevant to the outcome in patients with Covid-19; and duration of hypertension or duration of treatment with specific agents will be accurately reflected in the electronic health records.

Background Pneumonia (PNU) is the second most common nosocomial infection in the United States and is associated with substantial morbidity and mortality. While definitions from CDC were developed to increase the reliability of surveillance data, reduce the burden of surveillance in healthcare facilities, and enhance the utility of surveillance data for improving patient safety - the algorithm is still laborious. We propose an implementation of a refined algorithm script which combines two CDC definitions with the use of natural language processing (NLP), a tool which relies on pattern matching to determine whether a condition of interest is reported as present or absent in a report, to automate PNU surveillance. Methods Using SAS v9.4 to write a query, we used a combination of National Healthcare Safety Network's (NHSN) PNU and ventilator-associated event (VAE) definitions that use discrete fields found in electronic medical records (EMR) and trained an NLP tool to determine whether chest x-ray report was indicative of PNU (Fig1). To validate, we assessed sensitivity/specificity of NLP tool results compared with clinicians' interpretations. Results The NLP tool was highly accurate in classifying the presence of PNU in chest x-rays. After training the NLP tool, there were only 4% discrepancies between NLP tool and clinicians interpretations of 223 x-ray reports - sensitivity 92.2% (81.1–97.8), specificity 97.1% (93.4–99.1), PPV 90.4% (79.0–96.8), NPV 97.7% (94.1–99.4). Combining the automated use of discrete EMR fields with NLP tool significantly reduces the time spent manually reviewing EMRs. A manual review for PNU without automation requires approximately 10 minutes each day per admission. With a monthly average of 2,350 adult admissions at our hospital and 16,170 patient-days for admissions with at least 2 days, the algorithm saves approximately 2,695 review hours. Conclusion The use of discrete EMR fields with an NLP tool proves to be a timelier, cost-effective yet accurate alternative to manual PNU surveillance review. By allowing an automated algorithm to review PNU, timely reports can be sent to units about individual cases. Compared with traditional CDC surveillance definitions, an automated tool allows real-time critical review for infection and prevention activities. Disclosures All authors: No reported disclosures. [ABSTRACT FROM AUTHOR]

Background: There is concern about the potential of an increased risk related to medications that act on the renin-angiotensin-aldosterone system in patients exposed to coronavirus disease 2019 (Covid-19), because the viral receptor is angiotensin-converting enzyme 2 (ACE2).Methods: We assessed the relation between previous treatment with ACE inhibitors, angiotensin-receptor blockers, beta-blockers, calcium-channel blockers, or thiazide diuretics and the likelihood of a positive or negative result on Covid-19 testing as well as the likelihood of severe illness (defined as intensive care, mechanical ventilation, or death) among patients who tested positive. Using Bayesian methods, we compared outcomes in patients who had been treated with these medications and in untreated patients, overall and in those with hypertension, after propensity-score matching for receipt of each medication class. A difference of at least 10 percentage points was prespecified as a substantial difference.Results: Among 12,594 patients who were tested for Covid-19, a total of 5894 (46.8%) were positive; 1002 of these patients (17.0%) had severe illness. A history of hypertension was present in 4357 patients (34.6%), among whom 2573 (59.1%) had a positive test; 634 of these patients (24.6%) had severe illness. There was no association between any single medication class and an increased likelihood of a positive test. None of the medications examined was associated with a substantial increase in the risk of severe illness among patients who tested positive.Conclusions: We found no substantial increase in the likelihood of a positive test for Covid-19 or in the risk of severe Covid-19 among patients who tested positive in association with five common classes of antihypertensive medications. [ABSTRACT FROM AUTHOR]

Introduction: Major guidelines recommend moderate to high-intensity statins and antiplatelet agents in patients with atherosclerotic cardiovascular disease (ASCVD). Guideline-directed medical therapy (GDMT), however, remains suboptimal in population-based cohorts and randomized controlled trials. Methods: We conducted a quality initiative for ASCVD patients being discharged from a large tertiary care hospital. Best practice alerts (BPA) in the electronic health record (EHR) were triggered in patients with any history of ASCVD (≥ 18 years-old and without a precluding allergy) to alert the provider to prescribe GDMT on discharge. Rates of GDMT were compared for the 5 months pre- and post-BPA implementation using chi-squared tests. Multivariable regression was used to identify predictors of GDMT after adjusting for age, sex, admission type, admitting service, and month of admission. Results: In 5,985 pre- and 5,568 post-BPA patients who met our inclusion criteria, the average age was 69.1 (± 12.8) years and 58.5% were male. On admission, 66.2% and 74.3% were on a statin or antiplatelet, respectively. Comparing pre- and post-BPA implementation, there was a modest improvement in discharge GDMT rates (4.0% and 2.9% increase in statin and antiplatelet use, respectively), particularly with high-intensity statins and statin use among inpatient and surgical patients [ Figure ]. Similar trends were seen with antiplatelet use. After multivariable regression, age, male sex, admission to a cardiology service and post-BPA implementation were associated with discharge on GDMT. We observed that 8-9% of providers changed prescribing behavior based on the BPA. Conclusions: This simple EHR-based initiative was associated with more ASCVD patients being discharged on GDMT. Leveraging clinical decision support tools at hospital discharge provides an opportunity to influence provider behavior and improve care for ASCVD patients, warranting further investigation. [ABSTRACT FROM AUTHOR]

This study examines the incidence of and risk factors for venous and arterial thrombosis in patients hospitalized with COVID-19 in 4 New York City hospitals. [ABSTRACT FROM AUTHOR]

Background: Testing for venous thromboembolism (VTE) is associated with cost and risk to patients (e.g. radiation). To assess the appropriateness of imaging utilization at the provider level, it is important to know that provider's diagnostic yield (percentage of tests positive for the diagnostic entity of interest). However, determining diagnostic yield typically requires either time-consuming, manual review of radiology reports or the use of complex and/or proprietary natural language processing software.Objectives: The objectives of this study were twofold: 1) to develop and implement a simple, user-configurable, and open-source natural language processing tool to classify radiology reports with high accuracy and 2) to use the results of the tool to design a provider-specific VTE imaging dashboard, consisting of both utilization rate and diagnostic yield.Methods: Two physicians reviewed a training set of 400 lower extremity ultrasound (UTZ) and computed tomography pulmonary angiogram (CTPA) reports to understand the language used in VTE-positive and VTE-negative reports. The insights from this review informed the arguments to the five modifiable parameters of the NLP tool. A validation set of 2,000 studies was then independently classified by the reviewers and by the tool; the classifications were compared and the performance of the tool was calculated.Results: The tool was highly accurate in classifying the presence and absence of VTE for both the UTZ (sensitivity 95.7%; 95% CI 91.5-99.8, specificity 100%; 95% CI 100-100) and CTPA reports (sensitivity 97.1%; 95% CI 94.3-99.9, specificity 98.6%; 95% CI 97.8-99.4). The diagnostic yield was then calculated at the individual provider level and the imaging dashboard was created.Conclusions: We have created a novel NLP tool designed for users without a background in computer programming, which has been used to classify venous thromboembolism reports with a high degree of accuracy. The tool is open-source and available for download at http://iturrate.com/simpleNLP. Results obtained using this tool can be applied to enhance quality by presenting information about utilization and yield to providers via an imaging dashboard. [ABSTRACT FROM AUTHOR]