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Heart failure (HF) is one of the most common causes of hospitalization in the United States and carries a significant risk of morbidity and mortality. Use of evidence-based interventions may improve outcomes, but their use is encumbered in part by limitations in accurate prognostication. The REVeAL-HF (Risk EValuation And its Impact on ClinicAL Decision Making and Outcomes in Heart Failure) trial is the first to definitively evaluate the impact of knowledge about prognosis on clinical decision making and patient outcomes. The REVeAL-HF trial is a pragmatic, completely electronic, randomized controlled trial that has completed enrollment of 3,124 adults hospitalized for HF, defined as having an N-terminal pro–B-type natriuretic peptide level of >500 pg/ml and receiving intravenous diuretic agents within 24 h of admission. Patients randomized to the intervention had their risk of 1-year mortality generated with information in the electronic health record and presented to their providers, who had the option to give feedback on their impression of this risk assessment. The authors are examining the impact of this information on clinical decision-making (use of HF pharmacotherapies, referral to electrophysiology, palliative care referral, and referral for advanced therapies like heart transplantation or mechanical circulatory support) and patient outcomes (length of stay, post-discharge 30-day rehospitalizations, and 1-year mortality). The REVeAL-HF trial will definitively examine whether knowledge about prognosis in HF has an impact on clinical decision making and patient outcomes. It will also examine the relationship between calculated, perceived, and real risk of mortality in this patient population. (Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure [REVeAL-HF]; NCT03845660 ).

Background: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics. Methods: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined. Results: 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46–1.70] and 1.04 (95% CI, 0.96–1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53–0.90). Conclusions: Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types. Impact: This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3

Introduction Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown. Methods Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission. Results Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06–1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04–1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50–0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16–0.66) and former smokers (aOR, 0.47; 95% CI, 0.39–0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66–0.83) than never smokers (aOR, 0.87; 95% CI, 0.79–0.97). Conclusions Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers. Implications Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

ObjectiveTo evaluate the effect of colchicine and high-intensity rosuvastatin in addition to standard of care on the progression of COVID-19 disease in hospitalised patients.DesignA pragmatic, open-label, multicentre, randomised controlled trial conducted from October 2020 to September 2021. Follow-up was conducted at 30 and 60 days. The electronic medical record was used at all stages of the trial including screening, enrolment, randomisation, event ascertainment and follow-up.SettingFour centres in the Yale New Haven Health System.ParticipantsNon-critically ill hospitalised patients with COVID-19.InterventionsPatients were randomised 1:1 to either colchicine plus high-intensity rosuvastatin in addition to standard of care versus standard of care alone. Assigned treatment was continued for the duration of index hospitalisation or 30 days, whichever was shorter.Primary and secondary outcome measuresThe prespecified primary endpoint was progression to severe COVID-19 disease (new high-flow or non-invasive ventilation, mechanical ventilation, need for vasopressors, renal replacement therapy or extracorporeal membrane oxygenation, or death) or arterial/venous thromboembolic events (ischaemic stroke, myocardial infarction, deep venous thrombosis or pulmonary embolism) evaluated at 30 days.ResultsAmong the 250 patients randomised in this trial (125 to each arm), the median age was 61 years, 44% were women, 15% were Black and 26% were Hispanic/Latino. As part of the standard of care, patients received remdesivir (87%), dexamethasone (92%), tocilizumab (18%), baricitinib (2%), prophylactic/therapeutic anticoagulation (98%) and aspirin (91%). The trial was terminated early by the data and safety monitoring board for futility. No patients were lost to follow-up due to electronic medical record follow-up. There was no significant difference in the primary endpoint at 30 days between the active arm and standard of care arm (15.2% vs 8.8%, respectively, p=0.17).ConclusionsIn this small, open-label, randomised trial of non-critically ill hospitalised patients with COVID-19, the combination of colchicine and rosuvastatin in addition to standard of care did not appear to reduce the risk of progression of COVID-19 disease or thromboembolic events, although the trial was underpowered due to a lower-than-expected event rate. The trial leveraged the power of electronic medical records for efficiency and improved follow-up and demonstrates the utility of incorporating electronic medical records into future trials.Trial registrationNCT04472611.

Background Despite improvement in the standard of care (SOC) for hospitalized COVID-19 patients, rates of morbidity and mortality remain high. There continues to be a need for easily available and cost-effective treatments. Colchicine and rosuvastatin are both safe and well-studied medications with anti-inflammatory and other pleiotropic effects that may provide additional benefits to hospitalized COVID-19 patients. Methods and results The Colchicine/Statin for the Prevention of COVID-19 Complications (COLSTAT) trial is a pragmatic, open-label, multicenter, randomized trial comparing the combination of colchicine and rosuvastatin in addition to SOC to SOC alone in hospitalized COVID-19 patients. Four centers in the Yale New Haven Health network will enroll a total of 466 patients with 1:1 randomization. The trial will utilize the electronic health record (Epic® Systems, Verona, Wisconsin, USA) at all stages including screening, randomization, intervention, event ascertainment, and follow-up. The primary endpoint is the 30-day composite of progression to severe COVID-19 disease as defined by the World Health Organization ordinal scale of clinical improvement and arterial/venous thromboembolic events. The secondary powered endpoint is the 30-day composite of death, respiratory failure requiring intubation, and myocardial injury. Conclusions The COLSTAT trial will provide evidence on the efficacy of repurposing colchicine and rosuvastatin for the treatment of hospitalized COVID-19 patients. Moreover, it is designed to be a pragmatic trial that will demonstrate the power of using electronic health records to improve efficiency and enrollment in clinical trials in an adapting landscape. Clinical Trial Registration: NCT04472611 ( https://clinicaltrials.gov/ct2/show/NCT04472611 ).

Background Hospitals across the country are investing millions of dollars to adopt new Health Insurance Portability and Accountability Act (HIPAA)-compliant secure text messaging systems. However, in nearly all cases, these implementations are occurring without evaluation of their impact on patient care. Objective To evaluate perceived impact on patient care and workflow of new text messaging system implemented in obstetrics at Yale-New Haven Hospital and to inform guidelines for future implementations in emergent settings. Methods A new HIPAA-compliant texting system was implemented in obstetrics in 2016. Before implementation of the new system, residents and nurses were surveyed on perceived effect of communication system (pagers with text receiving, service mobile phones, personal cell phones) on clinical workflow and patient care using 5-point Likert scale and open-ended questions. Following roll-out (1 and 6 months), both teams were surveyed with same questions. Results were compared using Wilcoxon–Mann–Whitney test (0–1 months and then 0–6 months). Open-ended question results were qualitatively compared for recurrent unifying themes. Results In both nursing and resident domains, 1 month after implementation, the new communication system was perceived to significantly improve efficiency and patient care across all metrics. After 6 months, this effect decayed in nearly all categories (including efficiency, real-time communication, and knowledge of covering provider). The exception was nurse's knowledge of which resident to contact and resident's timely evaluation of patient, for which we observed sustained improvements. System shortcomings identified included interrupted connection (i.e., dropped calls), dysfunctional and inaccurate alert system, and unclear identification of the covering provider. Conclusion A new text-messaging–based communication system may improve efficiency and patient care in emergent settings, but system shortcomings can substantially erode potential benefits over time. We recommend implementers evaluate new systems for a set of specific functional requirements to increase probability of sustained improvement and decrease risk of poor patient outcomes.

Heart failure is a major cause of morbidity and mortality worldwide. The use of risk scores has the potential to improve targeted use of interventions by clinicians that improve patient outcomes, but this hypothesis has not been tested in a randomized trial.To evaluate whether prognostic information in heart failure translates into improved decisions about initiation and intensity of treatment, more appropriate end-of-life care, and a subsequent reduction in rates of hospitalization or death.This was a pragmatic, multicenter, electronic health record-based, randomized clinical trial across the Yale New Haven Health System, comprising small community hospitals and large tertiary care centers. Patients hospitalized for heart failure who had N-terminal pro-brain natriuretic peptide (NT-proBNP) levels of greater than 500 pg/mL and received intravenous diuretics within 24 hours of admission were automatically randomly assigned to the alert (intervention) or usual-care groups.The alert group had their risk of 1-year mortality calculated using an algorithm that was derived and validated using similar historic patients in the electronic health record. This estimate, including a categorical risk assessment, was presented to clinicians while they were interacting with a patient's electronic health record.The primary outcome was a composite of 30-day hospital readmissions and all-cause mortality at 1 year.Between November 27, 2019, through March 7, 2021, 3124 patients were randomly assigned to the alert (1590 [50.9%]) or usual-care (1534 [49.1%]) group. The alert group had a median (IQR) age of 76.5 (65-86) years, and 796 were female patients (50.1%). Patients from the following race and ethnicity groups were included: 13 Asian (0.8%), 324 Black (20.4%), 136 Hispanic (8.6%), 1448 non-Hispanic (91.1%), 1126 White (70.8%), 6 other ethnicity (0.4%), and 127 other race (8.0%). The usual-care group had a median (IQR) age of 77 (65-86) years, and 788 were female patients (51.4%). Patients from the following race and ethnicity groups were included: 11 Asian (1.4%), 298 Black (19.4%), 162 Hispanic (10.6%), 1359 non-Hispanic (88.6%), 1077 White (70.2%), 13 other ethnicity (0.9%), and 137 other race (8.9%). Median (IQR) NT-proBNP levels were 3826 (1692-8241) pg/mL in the alert group and 3867 (1663-8917) pg/mL in the usual-care group. A total of 284 patients (17.9%) and 270 patients (17.6%) were admitted to the intensive care unit in the alert and usual-care groups, respectively. A total of 367 patients (23.1%) and 359 patients (23.4%) had a left ventricular ejection fraction of 40% or less in the alert and usual-care groups, respectively. The model achieved an area under the curve of 0.74 in the trial population. The primary outcome occurred in 619 patients (38.9%) in the alert group and 603 patients (39.3%) in the usual-care group (P = .89). There were no significant differences between study groups in the prescription of heart failure medications at discharge, the placement of an implantable cardioverter-defibrillator, or referral to palliative care.Provision of 1-year mortality estimates during heart failure hospitalization did not affect hospitalization or mortality, nor did it affect clinical decision-making.ClinicalTrials.gov Identifier NCT03845660.

BackgroundSequential Organ Failure Assessment (SOFA) score predicts probability of in-hospital mortality. Many crisis standards of care use SOFA score to allocate medical resources during the COVID-19 pandemic.Research QuestionAre SOFA scores disproportionately elevated among Non-Hispanic Black and Hispanic patients hospitalized with COVID-19, compared to Non-Hispanic White patients?Study Design and MethodsRetrospective cohort study conducted in Yale New Haven Health System, including 5 hospitals with total of 2681 beds. Study population drawn from consecutive patients aged ≥18 admitted with COVID-19 from March 29thto August 1st, 2020. Patients excluded from the analysis if not their first admission with COVID-19, if they did not have SOFA score recorded within 24 hours of admission, if race and ethnicity data were not Non-Hispanic Black, Non-Hispanic White, or Hispanic, or if they had other missing data. The primary outcomes was SOFA score, with peak score within 24 hours of admission dichotomized as ResultsOf 2982 patients admitted with COVID-19, 2320 met inclusion criteria and were analyzed, of whom 1058 (45.6%) were Non-Hispanic White, 645 (27.8%) were Hispanic, and 617 (26.6%) were Non-Hispanic Black. Median age was 65.0 and 1226 (52.8%) were female. In univariate logistic screen and in full multivariate model, Non-Hispanic Black patients but not Hispanic patients had greater odds of an elevated SOFA score ≥6 when compared to Non-Hispanic White patients (OR 1.49, 95%CI 1.11-1.99).InterpretationCrisis standards of care utilizing the SOFA score to allocate medical resources would be more likely to deny these resources to Non-Hispanic Black patients.

BackgroundThe Veterans Health Administration COVID-19 (VACO) Index predicts 30-day all-cause mortality in patients with COVID-19 using age, sex and pre-existing comorbidity diagnoses. The VACO Index was initially developed and validated in a nationwide cohort of US veterans—we now assess its accuracy in an academic medical centre and a nationwide US Medicare cohort.MethodsWith measures and weights previously derived and validated in US national Veterans Health Administration (VA) inpatients and outpatients (n=13 323), we evaluated the accuracy of the VACO Index for estimating 30-day all-cause mortality using area under the receiver operating characteristic curve (AUC) and calibration plots of predicted versus observed mortality in inpatients at a single US academic medical centre (n=1307) and in Medicare inpatients and outpatients aged 65+ (n=427 224).Results30-day mortality varied by data source: VA 8.5%, academic medical centre 17.5%, Medicare 16.0%. The VACO Index demonstrated similar discrimination in VA (AUC=0.82) and academic medical centre inpatient population (AUC=0.80), and when restricted to patients aged 65+ in VA (AUC=0.69) and Medicare inpatient and outpatient data (AUC=0.67). The Index modestly overestimated risk in VA and Medicare data and underestimated risk in Yale New Haven Hospital data.ConclusionsThe VACO Index estimates risk of short-term mortality across a wide variety of patients with COVID-19 using data available prior to or at the time of diagnosis. The VACO Index could help inform primary and booster vaccination prioritisation, and indicate who among outpatients testing positive for SARS-CoV-2 should receive greater clinical attention or scarce treatments.

BackgroundThe COVID-19 pandemic has had a devastating impact in the United States, particularly for Black populations, and has heavily burdened the healthcare system. Hospitals have created protocols to allocate limited resources, but there is concern that these protocols will exacerbate disparities. The sequential organ failure assessment (SOFA) score is a tool often used in triage protocols. In these protocols, patients with higher SOFA scores are denied resources based on the assumption that they have worse clinical outcomes. The purpose of this study was to assess whether using SOFA score as a triage tool among COVID-positive patients would exacerbate racial disparities in clinical outcomes.MethodsWe analyzed data from a retrospective cohort of hospitalized COVID-positive patients in the Yale-New Haven Health System. We examined associations between race/ethnicity and peak overall/24-hour SOFA score, in-hospital mortality, and ICU admission. Other predictors of interest were age, sex, primary language, and insurance status. We used one-way ANOVA and chi-square tests to assess differences in SOFA score across racial/ethnic groups and linear and logistic regression to assess differences in clinical outcomes by sociodemographic characteristics.ResultsOur final sample included 2,554 patients. Black patients had higher SOFA scores compared to patients of other races. However, Black patients did not have significantly greater in-hospital mortality or ICU admission compared to patients of other races.ConclusionWhile Black patients in this sample of hospitalized COVID-positive patients had higher SOFA scores compared to patients of other races, this did not translate to higher in-hospital mortality or ICU admission. Results demonstrate that if SOFA score had been used to allocate care, Black COVID patients would have been denied care despite having similar clinical outcomes to white patients. Therefore, using SOFA score to allocate resources has the potential to exacerbate racial inequities by disproportionately denying care to Black patients and should not be used to determine access to care. Healthcare systems must develop and use COVID-19 triage protocols that prioritize equity.

Heart failure (HF) is one of the most common causes of hospitalization in the United States and carries a significant risk of morbidity and mortality. Use of evidence-based interventions may improve outcomes, but their use is encumbered in part by limitations in accurate prognostication. The REVeAL-HF (Risk EValuation And its Impact on ClinicAL Decision Making and Outcomes in Heart Failure) trial is the first to definitively evaluate the impact of knowledge about prognosis on clinical decision making and patient outcomes. The REVeAL-HF trial is a pragmatic, completely electronic, randomized controlled trial that has completed enrollment of 3,124 adults hospitalized for HF, defined as having an N-terminal pro-B-type natriuretic peptide level of500 pg/ml and receiving intravenous diuretic agents within 24 h of admission. Patients randomized to the intervention had their risk of 1-year mortality generated with information in the electronic health record and presented to their providers, who had the option to give feedback on their impression of this risk assessment. The authors are examining the impact of this information on clinical decision-making (use of HF pharmacotherapies, referral to electrophysiology, palliative care referral, and referral for advanced therapies like heart transplantation or mechanical circulatory support) and patient outcomes (length of stay, post-discharge 30-day rehospitalizations, and 1-year mortality). The REVeAL-HF trial will definitively examine whether knowledge about prognosis in HF has an impact on clinical decision making and patient outcomes. It will also examine the relationship between calculated, perceived, and real risk of mortality in this patient population. (Risk EValuation And Its Impact on ClinicAL Decision Making and Outcomes in Heart Failure [REVeAL-HF]; NCT03845660).

BackgroundThe Veterans Health Administration COVID-19 (VACO) Index incorporates age, sex, and pre-existing comorbidity diagnoses readily available in the electronic health record (EHR) to predict 30-day all-cause mortality in both inpatients and outpatients infected with SARS-CoV-2. We examined the performance of the Index using data from Yale New Haven Hospital (YNHH) and national Medicare data overall, over time, and within important patient subgroups.Methods and findingsWith measures and weights previously derived and validated in a national Veterans Healthcare Administration (VA) sample, we evaluated the accuracy of the VACO Index for estimating inpatient (YNHH) and both inpatient and outpatient mortality (Medicare) using area under the receiver operating characteristic curve (AUC) and comparisons of predicted versus observed mortality by decile (calibration plots). The VACO Index demonstrated similar discrimination and calibration in both settings, over time, and among important patient subgroups including women, Blacks, Hispanics, Asians, and Native Americans. In sensitivity analyses, we allowed component variables to be re-weighted in the validation datasets and found that weights were largely consistent with those determined in VA data. Supplementing the VACO Index with body mass index and race/ethnicity had no effect on discrimination.ConclusionAmong COVID-19 positive individuals, the VACO Index accurately estimates risk of short-term mortality among a wide variety of patients. While it modestly over-estimates risk in recent intervals, the Index consistently identifies those at greatest relative risk. The VACO Index could identify individuals who should continue practicing social distancing, help determine who should be prioritized for vaccination, and among outpatients who test positive for SARS-CoV-2, indicate who should receive greater clinical attention or monoclonal antibodies.

BackgroundSequential Organ Failure Assessment (SOFA) score predicts probability of in-hospital mortality. Many crisis standards of care suggest the use of SOFA scores to allocate medical resources during the COVID-19 pandemic.Research questionAre SOFA scores elevated among Non-Hispanic Black and Hispanic patients hospitalized with COVID-19, compared to Non-Hispanic White patients?Study design and methodsRetrospective cohort study conducted in Yale New Haven Health System, including 5 hospitals with total of 2681 beds. Study population drawn from consecutive patients aged ≥18 admitted with COVID-19 from March 29thto August 1st, 2020. Patients excluded from the analysis if not their first admission with COVID-19, if they did not have SOFA score recorded within 24 hours of admission, if race and ethnicity data were not Non-Hispanic Black, Non-Hispanic White, or Hispanic, or if they had other missing data. The primary outcome was SOFA score, with peak score within 24 hours of admission dichotomized as ResultsOf 2982 patients admitted with COVID-19, 2320 met inclusion criteria and were analyzed, of whom 1058 (45.6%) were Non-Hispanic White, 645 (27.8%) were Hispanic, and 617 (26.6%) were Non-Hispanic Black. Median age was 65.0 and 1226 (52.8%) were female. In univariate logistic screen and in full multivariate model, Non-Hispanic Black patients but not Hispanic patients had greater odds of an elevated SOFA score ≥6 when compared to Non-Hispanic White patients (OR 1.49, 95%CI 1.11–1.99).InterpretationGiven current unequal patterns in social determinants of health, US crisis standards of care utilizing the SOFA score to allocate medical resources would be more likely to deny these resources to Non-Hispanic Black patients.

BackgroundPatients with comorbid conditions have a higher risk of mortality with SARS-CoV-2 (COVID-19) infection, but the impact on heart failure patients living near a disease hotspot is unknown. Therefore, we sought to characterize the prevalence and outcomes of COVID-19 in a live registry of heart failure patients across an integrated health care system in Connecticut.MethodsIn this retrospective analysis, the Yale Heart Failure Registry (NCT04237701) that includes 26,703 patients with heart failure across a 6-hospital integrated health care system in Connecticut was queried on April 16th, 2020 for all patients tested for COVID-19. Sociodemographic and geospatial data as well as, clinical management, respiratory failure, and patient mortality were obtained via the real-time registry. Data on COVID-19 specific care was extracted by retrospective chart review.ResultsCOVID-19 testing was performed on 900 symptomatic patients, comprising 3.4% of the Yale Heart Failure Registry (N=26,703). Overall, 206 (23%) were COVID-19+. As compared to COVID-19-, these patients were more likely to be older, black, have hypertension, coronary artery disease, and were less likely to be on renin angiotensin blockers (P- patients tended to be more diffusely spread across the state whereas COVID-19+ were largely clustered around urban centers. 20% of COVID-19+ patients died, and age was associated with increased risk of death [OR 1.92 95% CI (1.33–2.78); P+ patients who were ≥85 years of age rates of hospitalization were 87%, rates of death 36%, and continuing hospitalization 62% at time of manuscript preparation.ConclusionsIn this real-world snapshot of COVID-19 infection among a large cohort of heart failure patients, we found that a small proportion had undergone testing. Patients found to be COVID-19+ tended to be black with multiple comorbidities and clustered around lower socioeconomic status communities. Elderly COVID-19+ patients were very likely to be admitted to the hospital and experience high rates of mortality.

Objective To illustrate the need for wider implementation of the CancelRx message by quantifying and characterizing the inappropriate usage of new electronic prescription (NewRx) messages for communicating discontinuation instructions to pharmacies. Materials and Methods A retrospective analysis on a nationally representative random sample of 1 400 000 NewRx messages transmitted over 7 days to identify e-prescriptions containing medication discontinuation instructions in NewRx text fields. A vocabulary of search terms signifying cancellation instructions was formulated and then iteratively refined. True-positives were subsequently identified programmatically and through manual reviews. Two independent reviewers identified incidences in which these instructions were associated with high-alert or look-alike-sound-like (LASA) medications. Results We identified 9735 (0.7% of the total) NewRx messages containing prescription cancellation instructions with 78.5% observed in the Notes field; 35.3% of identified NewRxs were associated with high-alert or LASA medications. The most prevalent cancellation instruction types were medication strength or dosage changes (39.3%) and alternative therapy replacement orders (39.0%). Discussion While the incidence of prescribers using the NewRx to transmit cancellation instructions was low, their transmission in NewRx fields not intended to accommodate such information can produce significant potential patient safety concerns, such as duplicate or inaccurate therapies. These findings reveal the need for wider industry adoption of the CancelRx message by electronic health record (EHR) and pharmacy systems, along with clearer guidance and improved end-user training, particularly as states increasingly mandate electronic prescribing of controlled substances. Conclusion Encouraging the use of CancelRx and reducing the misuse of NewRx fields would reduce workflow disruptions and unnecessary risks to patient safety.

133 Background: In 2016 ASCO updated its guideline for early integration of palliative care (PC) into standard oncologic care for all “inpatients and outpatients with advanced cancer.” PC has been shown to improve quality of life, align care at the end of life with patient preferences, and reduce health-care utilization. In preparation for the expansion of our palliative care service into ambulatory disease-based practices at Smilow Cancer Hospital at Yale-New Haven, we sought to create a decision support tool (DST) in the EPIC Electronic Health Record (EHR) that would identify patients for PC referral. Methods: This DST identifies patients with a GI or thoracic malignancy who have had an ICD-10 diagnosis of metastatic or stage IV disease, have not had a palliative care visit in the last 6 months, and are not enrolled in hospice. If the patient meets criteria, the DST will remind providers that “this patient meets ASCO and IOM criteria for concurrent palliative care with oncologic care ” and offers a one-click option to place the referral. To understand the volume of patients this DST would refer, we ran it silently in the EHR background from 7/15/16 through 9/1/16. We tracked how many patients were seen in the clinics, how many were eligible, and how many were referred to PC. Results: See table. Conclusions: Our silent BPA indicated that only 5% of patients eligible for a palliative care consult received it at baseline; this matches national data, which suggests that most patients who would benefit from PC do not receive it. This DST has the potential to dramatically improve PC referral rates and increase adherence with ASCO and IOM guidelines. We plan to move the DST into the live clinical EHR in 2017 after the integrated PC clinics are open. We anticipate that once our BPA is activated, we will see a dramatic increase in the number of eligible patients referred to palliative care. [Table: see text]

The Guideline Elements Model (GEM) was developed in 2000 to organize the information contained in clinical practice guidelines using XML and to represent guideline content in a form that can be understood by human readers and processed by computers. In this work, we systematically reviewed the literature to better understand how GEM was being used, potential barriers to its use, and suggestions for improvement. Fifty external and twelve internally produced publications were identified and analyzed. GEM was used most commonly for modeling and ontology creation. Other investigators applied GEM for knowledge extraction and data mining, for clinical decision support for guideline generation. The GEM Cutter software—used to markup guidelines for translation into XML— has been downloaded 563 times since 2000. Although many investigators found GEM to be valuable, others critiqued its failure to clarify guideline semantics, difficulties in markup, and the fact that GEM files are not usually executable.