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There is a need to discriminate which COVID-19 inpatients are at higher risk for venous thromboembolism (VTE) to inform prophylaxis strategies. The IMPROVE-DD VTE risk assessment model (RAM) has previously demonstrated good discrimination in non-COVID populations. We aimed to externally validate the IMPROVE-DD VTE RAM in medical patients hospitalized with COVID-19. This retrospective cohort study evaluated the IMPROVE-DD VTE RAM in adult patients with COVID-19 admitted to one of thirteen Northwell Health hospitals in the New York metropolitan area between March 1, 2020 and April 27, 2020. VTE was defined as new-onset symptomatic deep venous thrombosis or pulmonary embolism. To assess the predictive value of the RAM, the receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Of 9407 patients who met study criteria, 274 patients developed VTE with a prevalence of 2.91%. The VTE rate was 0.41% for IMPROVE-DD score 0–1 (low risk), 1.21% for score 2–3 (moderate risk), and 5.30% for score ≥ 4 (high risk). Approximately 45.7% of patients were classified as high VTE risk, 33.3% moderate risk, and 21.0% low risk. Discrimination of low versus moderate-high VTE risk demonstrated sensitivity 0.971, specificity 0.215, PPV 0.036, and NPV 0.996. ROC AUC was 0.703. In this external validation study, the IMPROVE-DD VTE RAM demonstrated very good discrimination to identify hospitalized COVID-19 patients at low, moderate, and high VTE risk.

There is minimal information on coronavirus disease 2019 (COVID‐19) in immunocompromised individuals. We have studied 10 patients treated at 12 adult care hospitals. Ten kidney transplant recipients tested positive for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) by polymerase chain reaction, and 9 were admitted. The median age was 57 (interquartile range [IQR] 47‐67), 60% were male, 40% Caucasian, and 30% Black/African American. Median time from transplant to COVID‐19 testing was 2822 days (IQR 1272‐4592). The most common symptom was fever, followed by cough, myalgia, chills, and fatigue. The most common chest X‐ray and computed tomography abnormality was multifocal patchy opacities. Three patients had no abnormal findings. Leukopenia was seen in 20% of patients, and allograft function was stable in 50% of patients. Nine patients were on tacrolimus and a mycophenolic antimetabolite, and 70% were on prednisone. Hospitalized patients had their antimetabolite agent stopped. All hospitalized patients received hydroxychloroquine and azithromycin. Three patients died (30%), and 5 (50%) developed acute kidney injury. Kidney transplant recipients infected with COVID‐19 should be monitored closely in the setting of lowered immunosuppression. Most individuals required hospitalization and presenting symptoms were similar to those of nontransplant individuals.

In the absence of preventive therapies or effective treatment for most cases of coronavirus disease 2019 (COVID-19), governments worldwide have sought to minimize person-to-person severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through a variety of lock-down measures and social distancing policies. Extreme events like the COVID-19 pandemic present a tremendous opportunity to make quantitative connections between changes in anthropogenic forcing, social and economic activity, and the related Earth system response. In this paper, we examine the air quality impacts associated with the pandemic response measures in the Northeastern United States.

Background Our objective was to characterize young adult patients hospitalized with coronavirus disease 2019 (COVID-19) and identify predictors of survival at 30 days. Methods This retrospective cohort study took place at 12 acute care hospitals in the New York City area. Patients aged 18–39 hospitalized with confirmed COVID-19 between March 1 and April 27, 2020 were included in the study. Demographic, clinical, and outcome data were extracted from electronic health record reports. Results A total of 1013 patients were included in the study (median age, 33 years; interquartile range [IQR], 28–36; 52% female). At the study end point, 940 (92.8%) patients were discharged alive, 18 (1.8%) remained hospitalized, 5 (0.5%) were transferred to another acute care facility, and 50 (4.9%) died. The most common comorbidities in hospitalized young adult patients were obesity (51.2%), diabetes mellitus (14.8%), and hypertension (13%). Multivariable analysis revealed that obesity (adjusted hazard ratio [aHR], 2.71; 95% confidence interval [CI], 1.28–5.73; P = .002) and Charlson comorbidity index score (aHR, 1.20; 95% CI, 1.07–1.35; P = .002) were independent predictors of in-hospital 30-day mortality. Conclusions Obesity was identified as the strongest negative predictor of 30-day in-hospital survival in young adults with COVID-19.

Background: Social influencers of health namely race, ethnicity, and structural inequities are known to affect the incidence of out of hospital sudden death (OHSD). We sought to examine the association between social influencers of health and the incidence of OHSD in the diverse neighborhoods of New York City during the first wave of coronavirus disease 2019 (COVID-19) epidemic. Methods: New York City ZIP stratified data on OHSD were obtained from the Fire Department of New York during the first wave of COVID-19 epidemic (March 1 to April 10, 2019) and the same period in 2020. To assess associates of OHSD, ZIP code-specific sociodemographic characteristics for 8 491 238 New York City residents were obtained via the US Census Bureau’s 2018 American Community Survey and the New York Police Department’s crime statistics. Results: Between March 1 and April 10, 2020, the number of OHSD rose to 4334 from 1112 compared with the year prior. Of the univariate ZIP code level variables evaluated, proportions of Black race, Hispanic/Latino ethnicity, single parent household, unemployed inhabitants, people completing less than high school education, inhabitants with no health insurance, people financially struggling or living in poverty, percent of noncitizens, and population density were associated with increased rates of OHSD within ZIP codes. In multivariable analysis, ZIP codes with higher proportions of inhabitants with less than high school education ( P P =0.04) were independent predictors for increases in ZIP code rates of OHSD. Conclusions: Educational attainment and the proportion of Black race in New York City ZIP codes remained independent predictors of increased rates of ZIP code level OHSD during the COVID-19 outbreak even after controlling for 2019 rates. To facilitate health equity, future research should focus on characterizing the impacts of structural inequities while exploring strategies to mitigate their effects.

Key Points Question Is regionalization of the care of patients with ST-segment elevation myocardial infarction (STEMI) associated with widened or narrowed disparities in access, treatment, and outcomes for patients with STEMI between minority and nonminority communities? Findings In this cohort study, regionalization was associated with significantly smaller improvement for residents of minority communities compared with patients from nonminority communities when admission to PCI hospital and treatment received were measured from regionalization, ranging from only 15% to 71% of what patients in nonminority communities experienced. Moreover, White patients in nonminority communities experienced the largest improvement in care, whereas Black and Hispanic patients in minority communities had little or no improvement when exposed to regionalization. Meaning Patients in minority communities compared with those in nonminority communities derived smaller benefits when these were measured by access to PCI hospitals and receipt of PCI from regionalization., Importance Cardiac care regionalization, specifically for patients with ST-segment elevation myocardial infarction (STEMI), has been touted as a potential mechanism to reduce systematic disparities by protocolizing the treatment of these conditions. However, it is unknown whether such regionalization arrangements have widened or narrowed disparities in access, treatment, and outcomes for minority communities. Objective To determine the extent to which disparities in access, treatment, and outcomes have changed for patients with STEMI living in zip codes that are in the top tertile of the Black or Hispanic population compared with patients in nonminority zip codes in regionalized vs nonregionalized counties. Design, Setting, and Participants This cohort study used a quasi-experimental approach exploiting the different timing of regionalization across California. Nonpublic inpatient data for all patients with STEMI from January 1, 2006, to October 31, 2015, were analyzed using a difference-in-difference-in-differences estimation approach. Exposure Exposure to the intervention was defined as on and after the year a patient’s county was exposed to regionalization. Main Outcomes and Measures Access to percutaneous coronary intervention (PCI)–capable hospital, receipt of PCI on the same day and at any time during the hospitalization, and time-specific all-cause mortality. Results This study included 139 494 patients with STEMI; 61.9% of patients were non-Hispanic White, 5.6% Black, 17.8% Hispanic, and 9.0% Asian; 32.8% were women. Access to PCI-capable hospitals improved by 6.3 percentage points (95% CI, 5.5 to 7.1 percentage points; P, This cohort study examines the extent to which disparities in access, treatment, and outcomes have changed for patients with ST-segment elevation myocardial infarction (STEMI) who are living in zip codes that are largely composed of Black or Hispanic individuals compared with patients in nonminority communities in regionalized vs nonregionalized counties.

Background Clinicians often disregard potentially beneficial clinical decision support (CDS). Objective In this study, we sought to explore the psychological and behavioral barriers to the use of a CDS tool. Methods We conducted a qualitative study involving emergency medicine physicians and physician assistants. A semistructured interview guide was created based on the Capability, Opportunity, and Motivation-Behavior model. Interviews focused on the barriers to the use of a CDS tool built based on Wells’ criteria for pulmonary embolism to assist clinicians in establishing pretest probability of pulmonary embolism before imaging. Results Interviews were conducted with 12 clinicians. Six barriers were identified, including (1) Bayesian reasoning, (2) fear of missing a pulmonary embolism, (3) time pressure or cognitive load, (4) gestalt includes Wells’ criteria, (5) missed risk factors, and (6) social pressure. Conclusions Clinicians highlighted several important psychological and behavioral barriers to CDS use. Addressing these barriers will be paramount in developing CDS that can meet its potential to transform clinical care.

Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative consequences. An evidenced-based approach is best, whereby interventions that might have a significant deleterious effect on patients' health outcomes are first tested and rigorously evaluated before being systematically rolled out. In the case of clinical decision support, brief and thorough instructions should be provided for use. Physician performance when using these systems is best measured relatively, in the context of peers with similar training. Responsibility for errors must be shared with clinical team members and system designers.

ObjectiveOur primary objective was to use initial data available to clinicians to characterize and predict survival for hospitalized coronavirus disease 2019 (COVID-19) patients. While clinical characteristics and mortality risk factors of COVID-19 patients have been reported, a practical survival calculator based on data from a diverse group of U.S. patients has not yet been introduced. Such a tool would provide timely and valuable guidance in decision-making during this global pandemic.DesignWe extracted demographic, laboratory, clinical, and treatment data from electronic health records and used it to build and test the predictive accuracy of a survival probability calculator referred to as “the Northwell COVID-19 Survival (‘NOCOS’) calculator.”Setting13 acute care facilities at Northwell Health served as the setting for this study.Participants5,233 hospitalized COVID-19–positive patients served as the participants for this study.Main outcome measuresThe NOCOS calculator was constructed using multivariate regression with L1 regularization (LASSO) to predict survival during hospitalization. Model predictive performance was measured using Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC) of the calculators.ResultsPatient age, serum blood urea nitrogen, Emergency Severity Index, red cell distribution width, absolute neutrophil count, serum bicarbonate, and glucose were identified as the optimal predictors of survival by multivariate LASSO regression. The predictive performance of the NOCOS calculator had an AUC of 0.832, reaching 0.91 when updated for each patient daily, with stability assessed and maintained for 14 consecutive days. This outperformed other established models, including the Sequential Organ Failure Assessment (SOFA) score (0.732).ConclusionsWe present a practical estimate of survival probability that outperforms other general risk models. The seven early predictors of in-hospital survival can help clinicians identify patients with increased probabilities of survival and provide critical decision support as COVID-19 spreads across the U.S.Trial registrationN/A

Low provider adoption continues to be a significant barrier to realizing the potential of clinical decision support. "Think Aloud" and "Near Live" usability testing were conducted on two clinical decision support tools. Each was composed of an alert, a clinical prediction rule which estimated risk of either group A Streptococcus pharyngitis or pneumonia and an automatic order set based on risk. The objective of this study was to further understanding of the facilitators of usability and to evaluate the types of additional information gained from proceeding to "Near Live" testing after completing "Think Aloud".This was a qualitative observational study conducted at a large academic health care system with 12 primary care providers. During "Think Aloud" testing, participants were provided with written clinical scenarios and asked to verbalize their thought process while interacting with the tool. During "Near Live" testing participants interacted with a mock patient. Morae usability software was used to record full screen capture and audio during every session. Participant comments were placed into coding categories and analyzed for generalizable themes. Themes were compared across usability methods."Think Aloud" and "Near Live" usability testing generated similar themes under the coding categories visibility, workflow, content, understand-ability and navigation. However, they generated significantly different themes under the coding categories usability, practical usefulness and medical usefulness. During both types of testing participants found the tool easier to use when important text was distinct in its appearance, alerts were passive and appropriately timed, content was up to date, language was clear and simple, and each component of the tool included obvious indicators of next steps. Participant comments reflected higher expectations for usability and usefulness during "Near Live" testing. For example, visit aids, such as automatically generated order sets, were felt to be less useful during "Near-Live" testing because they would not be all inclusive for the visit.These complementary types of usability testing generated unique and generalizable insights. Feedback during "Think Aloud" testing primarily helped to improve the tools' ease of use. The additional feedback from "Near Live" testing, which mimics a real clinical encounter, was helpful for eliciting key barriers and facilitators to provider workflow and adoption.

Increased utilization of CT pulmonary angiography (CTPA) for the evaluation of pulmonary embolism has been associated with decreasing diagnostic yields and rising concerns about the harms of unnecessary testing. The objective of this study was to determine whether clinical decision support (CDS) use would be associated with increased imaging yields after controlling for selection bias.We performed a retrospective cohort study in the emergency departments of two tertiary care hospitals of all CTPAs performed between August 2015 and September 2018. Providers ordering a CTPA are routed to an optional CDS tool, which allows them to use Wells' Criteria for pulmonary embolism. After propensity score matching, CTPA yield was calculated for the CDS-use and CDS-dismissal groups and stratified by provider type.A total of 7,367 CTPAs were ordered during the study period. Of those, providers used the CDS tool in 2,568 (35%) cases and did not use the tool in 4,799 (65%) of cases. After propensity score matching, CTPA yield was 11.99% in the CDS-use group and 8.70% in the CDS-dismissal group (P.001). Attending physicians, residents, and physician assistant CDS users demonstrated a 56.5% (P = .006), 38.7% (P = .01), and 16.7% (P = .03) increased yield compared with those who dismissed the tool, respectively.Diagnostic yield was 38% higher for CTPAs when the provider used the CDS tool, after controlling for selection bias. Yields were higher for every provider type. Further research is needed to discover successful strategies to increase provider use of these important tools.

BACKGROUND: Clinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs). OBJECTIVE: To assess the impact of previously effective CDS on antibiotic-prescribing rates for ARIs when adapted and implemented in diverse primary care settings. DESIGN: Cluster randomized clinical trial (RCT) implementing a CDS tool designed to guide evidence-based evaluation and treatment of streptococcal pharyngitis and pneumonia. SETTING: Two large academic health system primary care networks with a mix of providers. PARTICIPANTS: All primary care practices within each health system were invited. All providers within participating clinic were considered a participant. Practices were randomized selection to a control or intervention group. INTERVENTIONS: Intervention practice providers had access to an integrated clinical prediction rule (iCPR) system designed to determine the risk of bacterial infection from reason for visit of sore throat, cough, or upper respiratory infection and guide evidence-based evaluation and treatment. MAIN OUTCOME(S): Change in overall antibiotic prescription rates. MEASURE(S): Frequency, rates, and type of antibiotics prescribed in intervention and controls groups. RESULTS: 33 primary care practices participated with 541 providers and 100,573 patient visits. Intervention providers completed the tool in 6.9% of eligible visits. Antibiotics were prescribed in 35% and 36% of intervention and control visits, respectively, showing no statistically significant difference. There were also no differences in rates of orders for rapid streptococcal tests (RR, 0.94; P = 0.11) or chest X-rays (RR, 1.01; P = 0.999) between groups. CONCLUSIONS: The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This has implications for the generalizability of CDS tools as they are adapted to heterogeneous clinical contexts. TRIAL REGISTRATION: Clinicaltrials.gov (NCT02534987). Registered August 26, 2015 at https://clinicaltrials.gov ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-06096-3) contains supplementary material, which is available to authorized users.

Background The benefits of computed tomography pulmonary angiography (CTPA) for pulmonary embolism (PE) diagnosis must be weighed against its risks, radiation-induced malignancy, and contrast-induced nephropathy. Appropriate use of CTPA can be assessed by monitoring yield, the percentage of tests positive for PE. We identify factors that are associated low CTPA yield, which may predict overtesting. Methods This was a retrospective cohort study of six emergency departments between June 2014 and February 2017. The electronic health record was queried for CTPAs ordered for adult patients in the emergency department. We assessed the following patient factors: age, gender, body mass index, number of comorbidities, race, and ethnicity, provider factors: type (resident, fellow, attending, physician assistant) and environment factors: test time of day, season of visit, and crowdedness of the department. Results A total of 14,782 CTPAs were reviewed, of which 1366 were found to be positive for PE, resulting in an overall CTPA yield of 9.24%. Provider type was not associated with a difference in yield. Testing was less likely to be positive in younger patients, females, those with lower body mass indexes and those identifying as Asian or Hispanic. Testing was also less likely to be positive when ordered during the overnight shift and during the winter and spring seasons. Conclusion Our study identified several patient and environmental factors associated with low CTPA yield suggesting potential targets for overtesting. Targeting education and clinical decision support to assist providers in these circumstances may meaningfully improve yields.

OBJECTIVE We employed an agile, user-centered approach to the design of a clinical decision support tool in our prior integrated clinical prediction rule study, which achieved high adoption rates. To understand if applying this user-centered process to adapt clinical decision support tools is effective in improving the use of clinical prediction rules, we examined utilization rates of a clinical decision support tool adapted from the original integrated clinical prediction rule study tool to determine if applying this user-centered process to design yields enhanced utilization rates similar to the integrated clinical prediction rule study. MATERIALS & METHODS: We conducted pre-deployment usability testing and semi-structured group interviews at 6 months post-deployment with 75 providers at 14 intervention clinics across the two sites to collect user feedback. Qualitative data analysis is bifurcated into immediate and delayed stages; we reported on immediate-stage findings from real-time field notes used to generate a set of rapid, pragmatic recommendations for iterative refinement. Monthly utilization rates were calculated and examined over 12 months. RESULTS We hypothesized a well-validated, user-centered clinical decision support tool would lead to relatively high adoption rates. Then 6 months post-deployment, integrated clinical prediction rule study tool utilization rates were substantially lower than anticipated based on the original integrated clinical prediction rule study trial (68%) at 17% (Health System A) and 5% (Health System B). User feedback at 6 months resulted in recommendations for tool refinement, which were incorporated when possible into tool design; however, utilization rates at 12 months post-deployment remained low at 14% and 4% respectively. DISCUSSION Although valuable, findings demonstrate the limitations of a user-centered approach given the complexity of clinical decision support. CONCLUSION Strategies for addressing persistent external factors impacting clinical decision support adoption should be considered in addition to the user-centered design and implementation of clinical decision support.

Background Child maltreatment is a leading cause of pediatric morbidity and mortality. We previously reported on development and implementation of a child abuse clinical decision support system (CA-CDSS) in the Cerner electronic health record (EHR). Our objective was to develop a CA-CDSS in two different EHRs. Methods Using the CA-CDSS in Cerner as a template, CA-CDSSs were developed for use in four hospitals in the Northwell Health system who use Allscripts and two hospitals in the University of Wisconsin health system who use Epic. Each system had a combination of triggers, alerts and child abuse-specific order sets. Usability evaluation was done prior to launch of the CA-CDSS. Results Over an 18-month period, a CA-CDSS was embedded into Epic and Allscripts at two hospital systems. The CA-CDSSs vary significantly from each other in terms of the type of triggers which were able to be used, the type of alert, the ability of the alert to link directly to child abuse-specific order sets and the order sets themselves. Conclusions Dissemination of CA-CDSS from one EHR into the EHR in other health care systems is possible but time-consuming and needs to be adapted to the strengths and limitations of the specific EHR. Site-specific usability evaluation, buy-in of multiple stakeholder groups and significant information technology support are needed. These barriers limit scalability and widespread dissemination of CA-CDSS.

Importance There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19). Objective To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system. Design, Setting, and Participants Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates. Exposures Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission. Main Outcomes and Measures Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected. Results A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/min, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1). Conclusions and Relevance This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.

Background: Potential of the electronic health records (EHR) and clinical decision support (CDS) systems to improve the practice of medicine has been tempered by poor design and the resulting burden they place on providers. CDS is rarely tested in the real clinical environment. As a result, many tools are hard to use, placing strain on providers and resulting in low adoption rates. The existing CDS usability literature relies primarily on expert opinion and provider feedback via survey. This is the first study to evaluate CDS usability and the provider-computer-patient interaction with complex CDS in the real clinical environment. Objective: This study aimed to further understand the barriers and facilitators of meaningful CDS usage within a real clinical context. Methods: This qualitative observational study was conducted with 3 primary care providers during 6 patient care sessions. In patients with the chief complaint of sore throat, a CDS tool built with the Centor Score was used to stratify the risk of group A Streptococcus pharyngitis. In patients with a chief complaint of cough or upper respiratory tract infection, a CDS tool built with the Heckerling Rule was used to stratify the risk of pneumonia. During usability testing, all human-computer interactions, including audio and continuous screen capture, were recorded using the Camtasia software. Participants’ comments and interactions with the tool during clinical sessions and participant comments during a postsession brief interview were placed into coding categories and analyzed for generalizable themes. Results: In the 6 encounters observed, primary care providers toggled between addressing either the computer or the patient during the visit. Minimal time was spent listening to the patient without engaging the EHR. Participants mostly used the CDS tool with the patient, asking questions to populate the calculator and discussing the results of the risk assessment; they reported the ability to do this as the major benefit of the tool. All providers were interrupted during their use of the CDS tool by the need to refer to other sections of the chart. In half of the visits, patients’ clinical symptoms challenged the applicability of the tool to calculate the risk of bacterial infection. Primary care providers rarely used the incorporated incentives for CDS usage, including progress notes and patient instructions. Conclusions: Live usability testing of these CDS tools generated insights about their role in the patient-provider interaction. CDS may contribute to the interaction by being simultaneously viewed by the provider and patient. CDS can improve usability and lessen the strain it places on providers by being short, flexible, and customizable to unique provider workflow. A useful component of CDS is being as widely applicable as possible and ensuring that its functions represent the fastest way to perform a particular task.

Background: Successful clinical decision support (CDS) tools can help use evidence-based medicine to effectively improve patient outcomes. However, the impact of these tools has been limited by low provider adoption due to overtriggering, leading to alert fatigue. We developed a tracking mechanism for monitoring trigger (percent of total visits for which the tool triggers) and adoption (percent of completed tools) rates of a complex CDS tool based on the Wells criteria for pulmonary embolism (PE). Objective: We aimed to monitor and evaluate the adoption and trigger rates of the tool and assess whether ongoing tool modifications would improve adoption rates. Methods: As part of a larger clinical trial, a CDS tool was developed using the Wells criteria to calculate pretest probability for PE at 2 tertiary centers’ emergency departments (EDs). The tool had multiple triggers: any order for D-dimer, computed tomography (CT) of the chest with intravenous contrast, CT pulmonary angiography (CTPA), ventilation-perfusion scan, or lower extremity Doppler ultrasound. A tracking dashboard was developed using Tableau to monitor real-time trigger and adoption rates. Based on initial low provider adoption rates of the tool, we conducted small focus groups with key ED providers to elicit barriers to tool use. We identified overtriggering of the tool for non-PE-related evaluations and inability to order CT testing for intermediate-risk patients. Thus, the tool was modified to allow CT testing for the intermediate-risk group and not to trigger for CT chest with intravenous contrast orders. A dialogue box, “Are you considering PE for this patient?” was added before the tool triggered to account for CTPAs ordered for aortic dissection evaluation. Results: In the ED of tertiary center 1, 95,295 patients visited during the academic year. The tool triggered for an average of 509 patients per month (average trigger rate 2036/30,234, 6.73%) before the modifications, reducing to 423 patients per month (average trigger rate 1629/31,361, 5.22%). In the ED of tertiary center 2, 88,956 patients visited during the academic year, with the tool triggering for about 473 patients per month (average trigger rate 1892/29,706, 6.37%) before the modifications and for about 400 per month (average trigger rate 1534/30,006, 5.12%) afterward. The modifications resulted in a significant 4.5- and 3-fold increase in provider adoption rates in tertiary centers 1 and 2, respectively. The modifications increased the average monthly adoption rate from 23.20/360 (6.5%) tools to 81.60/280.20 (29.3%) tools and 46.60/318.80 (14.7%) tools to 111.20/263.40 (42.6%) tools in centers 1 and 2, respectively. Conclusions: Close postimplementation monitoring of CDS tools may help improve provider adoption. Adaptive modifications based on user feedback may increase targeted CDS with lower trigger rates, reducing alert fatigue and increasing provider adoption. Iterative improvements and a postimplementation monitoring dashboard can significantly improve adoption rates.

The effect of dietary isoflavone intake on systolic blood pressure (SBP) has not been studied in a large community-based cohort inclusive of African Americans. The authors analyzed data from the year 20 examination of the Coronary Artery Risk Development in Young Adults (CARDIA) study, including medical history, physical examination, and dietary intake surveys for 3142 participants. Multivariable linear regression models controlled for age, sex, body mass index, smoking, physical activity, and intakes of alcohol and total energy. Effect modification by race was tested. Overall, patients with hypertension had a lower daily intake of total dietary isoflavones (2.2±5.2 mg/d vs 4.1±11.7 mg/d; P

BACKGROUNDThe healthcare burden of hospital-acquired Clostridium difficile infection (CDI) demands attention and calls for a solution. Identifying patients’ risk of developing a primary nosocomial CDI is a critical first step in reducing the development of new cases of CDI.OBJECTIVETo derive a clinical prediction rule that can predict a patient’s risk of acquiring a primary CDI.DESIGNRetrospective cohort study.SETTINGLarge tertiary healthcare center.PATIENTSTotal of 61,482 subjects aged at least 18 admitted over a 1-year period (2013).INTERVENTIONNone.METHODSPatient demographic characteristics, evidence of CDI, and other risk factors were retrospectively collected. To derive the CDI clinical prediction rule the patient population was divided into a derivation and validation cohort. A multivariable analysis was performed in the derivation cohort to identify risk factors individually associated with nosocomial CDI and was validated on the validation sample.RESULTSAmong 61,482 subjects, CDI occurred in 0.46%. CDI outcome was significantly associated with age, admission in the past 60 days, mechanical ventilation, dialysis, history of congestive heart failure, and use of antibiotic medications. The sensitivity and specificity of the score, in the validation set, were 82.0% and 75.7%, respectively. The area under the receiver operating characteristic curve was 0.85.CONCLUSIONThis study successfully derived a clinical prediction rule that will help identify patients at high risk for primary CDI. This tool will allow physicians to systematically recognize those at risk for CDI and will allow for early interventional strategies.Infect Control Hosp Epidemiol 2016;37:896–900

Background: Use of computed tomography pulmonary angiography (CTPA) in the assessment of pulmonary embolism (PE) has markedly increased over the past two decades. While this technology has improved the accuracy of radiological testing for PE, CTPA also carries the risk of substantial iatrogenic harm. Each CTPA carries a 14% risk of contrast-induced nephropathy and a lifetime malignancy risk that can be as high as 2.76%. The appropriate use of CTPA can be estimated by monitoring the CTPA yield, the percentage of tests positive for PE. This is the first study to propose and validate a computerized method for measuring the CTPA yield in the emergency department (ED). Objective: The objective of our study was to assess the validity of a novel computerized method of calculating the CTPA yield in the ED. Methods: The electronic health record databases at two tertiary care academic hospitals were queried for CTPA orders completed in the ED over 1-month periods. These visits were linked with an inpatient admission with a discharge diagnosis of PE based on the International Classification of Diseases codes. The computerized the CTPA yield was calculated as the number of CTPA orders with an associated inpatient discharge diagnosis of PE divided by the total number of orders for completed CTPA. This computerized method was then validated by 2 independent reviewers performing a manual chart review, which included reading the free-text radiology reports for each CTPA. Results: A total of 349 CTPA orders were completed during the 1-month periods at the two institutions. Of them, acute PE was diagnosed on CTPA in 28 studies, with a CTPA yield of 7.7%. The computerized method correctly identified 27 of 28 scans positive for PE. The one discordant scan was tied to a patient who was discharged directly from the ED and, as a result, never received an inpatient discharge diagnosis. Conclusions: This is the first successful validation study of a computerized method for calculating the CTPA yield in the ED. This method for data extraction allows for an accurate determination of the CTPA yield and is more efficient than manual chart review. With this ability, health care systems can monitor the appropriate use of CTPA and the effect of interventions to reduce overuse and decrease preventable iatrogenic harm.

Background and Purpose Posttraumatic stress disorder (PTSD) is common in survivors of acute life-threatening illness, but little is known about the burden of PTSD in survivors of stroke and transient ischemic attack (TIA). This study estimated the prevalence of stroke or TIA-induced posttraumatic stress disorder (PTSD) using systematic review and meta-analysis. Methods Potentially relevant peer-reviewed journal articles were identified by searching the Ovid MEDLINE, PsycINFO, PILOTS Database, The Cochrane Library and Scopus from inception to January 2013; all searches were conducted on January 31, 2013. Observational cohort studies that assessed PTSD with specific reference to a stroke or TIA that occurred at least 1 month prior to the PTSD assessment were included. PTSD rates and characteristics of the study and sample were abstracted from all included studies. The coding of all articles included demographics, sample size, study country, and method and timing of PTSD assessment. Results Nine studies (N = 1,138) met our inclusion criteria. PTSD rates varied significantly across studies by timing of PTSD assessment (i.e., within 1 year of stroke/TIA versus greater than 1 year post-stroke/TIA; 55% of heterogeneity explained; Q 1 = 10.30; P = .001). Using a random effects model, the estimated rate of PTSD following stroke or TIA was 23% (95% CI, 16%–33%) within 1 year of the stroke or TIA and 11% (95% CI, 8%–14%) after 1 year. Conclusions Although PTSD is commonly thought to be triggered by external events such as combat or sexual assault, these results suggest that 1 in 4 stroke or TIA survivors develop significant PTSD symptoms due to the stroke or TIA. Screening for PTSD in a large population-based prospective cohort study with cardiovascular outcome assessments is needed to yield definitive prevalence, and determine whether stroke or TIA-induced PTSD is a risk factor for subsequent cardiovascular events or mortality.

The purpose of this review is to summarize the available information regarding salt sensitivity particularly as it relates to non-Hispanic blacks and Hispanics and to clarify possible etiologies, especially those that might shed light on potential treatment options. In non-Hispanic blacks, there is evidence that endothelial dysfunction, reduced potassium intake, decreased urinary kallikrein excretion, upregulation of sodium channel activity, dysfunction in atrial natriuretic peptide (ANP) production, and APOL1 gene nephropathy risk variants may cause or contribute to salt sensitivity. Supported treatment avenues include diets high in potassium and soybean protein, the components of which stimulate nitric oxide production. Racial heterogeneity complicates the study of salt sensitivity in Hispanic populations. Caribbean Hispanics, who have a higher proportion of African ancestry, may respond to commonly prescribed anti-hypertensive agents in a way that is characteristic of non-Hispanic black hypertensives. The low-renin hypertensive phenotype commonly seen in non-Hispanic blacks has been linked to salt sensitivity and may indicate an increased risk for salt sensitivity in a portion of the Hispanic population. In conclusion, increased morbidity and mortality associated with salt sensitivity mandates further studies evaluating the efficacy of tailored dietary and pharmacologic treatment in non-Hispanic blacks and determining the prevalence of low renin hypertension and salt sensitivity within the various subgroups of Hispanic Americans.

Most studies examining potential associations between psychological factors and cardiovascular outcomes have focused on either depression or anxiety. The effect of perceived stress on incident coronary heart disease (CHD) has yet to be reviewed systematically. We conducted a systematic review and meta-analysis of the association between perceived stress and incident CHD. Ovid MEDLINE and PsycINFO were searched as data sources. Prospective observational cohort studies were selected that measured self-reported perceived stress and assessed incident CHD at minimum of 6 months later. We extracted study characteristics and estimates of the risk of incident CHD associated with high perceived stress vs. low perceived stress. We identified 23 potentially relevant articles, of which 6 met our criteria (N = 118,696). Included studies measured perceived stress with both validated measures and non-validated simple self-report surveys. Incident CHD was defined as new diagnosis of, hospitalization for, or mortality secondary to CHD. Meta-analysis yielded an aggregate risk ratio of 1.27 (95% confidence interval 1.12 – 1.45) for the magnitude of the relation between high perceived stress and incident CHD. In conclusion this meta-analysis suggests that high perceived stress is associated with a moderately increased risk of incident CHD.

Depression is a recognized risk marker for mortality among acute coronary syndrome (ACS) patients. We hypothesized that ventricular arrhythmia detected by inpatient telemetry monitoring is more frequent among ACS patients with elevated depressive symptoms compared to those without depressive symptoms.We analysed data from patients enrolled in a prospective observational study of depression in ACS. Telemetry recordings during the index admission (average recording 21.3±3.0 hours) were analysed for frequent premature ventricular complexes (PVCs), defined as ≥10 per hour. The self-report Beck Depression Inventory (BDI) was used to assess depressive symptoms. Among 200 ACS patients, frequent PVCs were observed in 29% of patients with moderate depressive symptoms (BDI ≥10), 27% of those with mild symptoms (BDI 5-9), and only 11% of those with no/minimal symptoms (p=0.02). Log-transformed PVCs per hour were associated with depressive symptom category (p=0.008). In a multivariable logistic regression model that included age, gender, left ventricular ejection fraction, cardiovascular risk score, heart rate, and QT interval, mild symptoms (OR 3.02, 95% 0.97-9.43, p=0.058) and moderate-severe symptoms (OR 3.94, 95% CI 1.27-12.22, p=0.018) were associated with frequent PVCs.In this sample of ACS patients, depressive symptoms were independently associated with frequent PVCs during inpatient telemetry monitoring.

Background Acute coronary syndromes (ACS; myocardial infarction or unstable angina) can induce posttraumatic stress disorder (PTSD), and ACS-induced PTSD may increase patients’ risk for subsequent cardiac events and mortality. Objective: To determine the prevalence of PTSD induced by ACS and to quantify the association between ACS-induced PTSD and adverse clinical outcomes using systematic review and meta-analysis. Data Sources: Articles were identified by searching Ovid MEDLINE, PsycINFO, and Scopus, and through manual search of reference lists. Methodology/Principal Findings Observational cohort studies that assessed PTSD with specific reference to an ACS event at least 1 month prior. We extracted estimates of the prevalence of ACS-induced PTSD and associations with clinical outcomes, as well as study characteristics. We identified 56 potentially relevant articles, 24 of which met our criteria (N = 2383). Meta-analysis yielded an aggregated prevalence estimate of 12% (95% confidence interval [CI], 9%–16%) for clinically significant symptoms of ACS-induced PTSD in a random effects model. Individual study prevalence estimates varied widely (0%–32%), with significant heterogeneity in estimates explained by the use of a screening instrument (prevalence estimate was 16% [95% CI, 13%–20%] in 16 studies) vs a clinical diagnostic interview (prevalence estimate was 4% [95% CI, 3%–5%] in 8 studies). The aggregated point estimate for the magnitude of the relationship between ACS-induced PTSD and clinical outcomes (ie, mortality and/or ACS recurrence) across the 3 studies that met our criteria (N = 609) suggested a doubling of risk (risk ratio, 2.00; 95% CI, 1.69–2.37) in ACS patients with clinically significant PTSD symptoms relative to patients without PTSD symptoms. Conclusions/Significance This meta-analysis suggests that clinically significant PTSD symptoms induced by ACS are moderately prevalent and are associated with increased risk for recurrent cardiac events and mortality. Further tests of the association of ACS-induced PTSD and clinical outcomes are needed.

Objectives To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Conclusions Healthcare providers describe clear preferences for certain clinical prediction rules, based on medical specialty.

Isoflavones are highly prevalent in soybeans and lead to activation of endothelial nitric oxide (NO) synthases, increased NO bioavailability and possibly lowered blood pressure (BP). However, the relation of isoflavone intake with blood pressure has not been studied in a biracial population cohort