Deprescription of aspirin for primary prevention is uncommon at discharge in hospitalised patients with gastrointestinal bleeding.

BACKGROUND: Guidelines recommend against aspirin for primary prevention of cardiovascular events in individuals with a history of gastrointestinal bleeding (GIB). It is unknown how often patients on primary prevention aspirin hospitalised with GIB have aspirin discontinued at discharge. AIMS: To determine the rate of aspirin deprescription and explore long-term outcomes in patients taking aspirin for primary prevention of cardiovascular events. METHODS: We evaluated all patients hospitalised at Yale-New Haven Hospital between January 2014 and October 2021 with GIB who were on aspirin for primary prevention. Our primary endpoint was the frequency of aspirin deprescription at discharge. Our secondary endpoints were post-discharge hospitalisations for major adverse cardiovascular events (MACE) or GIB. Time-to-event analysis was performed using Kaplan-Meier curves and the log-rank test. RESULTS: We identified 320 patients with GIB on aspirin for primary prevention: median age was 72 (interquartile range [IQR] 61-81) years and 297 (92.8%) were on aspirin 81 mg daily. Only 25 (9.0%) patients surviving their hospitalisation were deprescribed aspirin at discharge. Among 260 patients with follow-up (median 1103 days; IQR 367-1670), MACE developed post-discharge in 2/25 (8.0%) with aspirin deprescription versus 37/235 (15.7%) with aspirin continuation (log-rank p = 0.28). 0/25 patients with aspirin deprescription had subsequent hospitalisation for GIB versus 17/235 (7.2%) who continued aspirin (log-rank p = 0.13). CONCLUSIONS: Aspirin for primary cardiovascular prevention was rarely deprescribed at discharge in patients hospitalised with GIB. Processes designed to ensure appropriate deprescription of aspirin are crucial to improve adherence to guidelines, thereby improving the risk-benefit ratio in patients at high risk of subsequent GIB hospitalisations with minimal increased risk of MACE.

A Machine Learning Model to Successfully Predict Future Diagnosis of Chronic Myelogenous Leukemia With Retrospective Electronic Health Records Data.

BACKGROUND: Chronic myelogenous leukemia (CML) is a clonal stem cell disorder accounting for 15% of adult leukemias. We aimed to determine if machine learning models could predict CML using blood cell counts prior to diagnosis. METHODS: We identified patients with a diagnostic test for CML (BCR-ABL1) and at least 6 consecutive prior years of differential blood cell counts between 1999 and 2020 in the largest integrated health care system in the United States. Blood cell counts from different time periods prior to CML diagnostic testing were used to train, validate, and test machine learning models. RESULTS: The sample included 1,623 patients with BCR-ABL1 positivity rate 6.2%. The predictive ability of machine learning models improved when trained with blood cell counts closer to time of diagnosis: 2 to 5 years area under the curve (AUC), 0.59 to 0.67, 0.5 to 1 years AUC, 0.75 to 0.80, at diagnosis AUC, 0.87 to 0.92. CONCLUSIONS: Blood cell counts collected up to 5 years prior to diagnostic workup of CML successfully predicted the BCR-ABL1 test result. These findings suggest a machine learning model trained with blood cell counts could lead to diagnosis of CML earlier in the disease course compared to usual medical care.

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis.

OBJECTIVE: To derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time. MATERIALS AND METHODS: A cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time. RESULTS: Five out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month -0.01 hours; practicing cardiology -1.30 hours; medical subspecialties -0.89 hours (except gastroenterology, P = .002); neurology/psychiatry -2.60 hours; obstetrics/gynecology -1.88 hours; pediatrics -1.05 hours (P = .001); sports/physical medicine and rehabilitation -3.25 hours; and surgical specialties -3.65 hours. CONCLUSIONS: For every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.

Inpatient Telehealth Tools to Enhance Communication and Decrease Personal Protective Equipment Consumption during Disaster Situations: A Case Study during the COVID-19 Pandemic.

BACKGROUND: As the coronavirus disease 2019 pandemic exerts unprecedented stress on hospitals, health care systems have quickly deployed innovative technology solutions to decrease personal protective equipment (PPE) use and augment patient care capabilities. Telehealth technology use is established in the ambulatory setting, but not yet widely deployed at scale for inpatient care. OBJECTIVES: This article presents and describes our experience with evaluating and implementing inpatient telehealth technologies in a large health care system with the goals of reducing use of PPE while enhancing communication for health care workers and patients. METHODS: We discovered use cases for inpatient telehealth revealed as a result of an immense patient surge requiring large volumes of PPE. In response, we assessed various consumer products to address the use cases for our health system. RESULTS: We identified 13 use cases and eight device options. During device setup and implementation, challenges and solutions were identified in five areas: security/privacy, device availability and setup, device functionality, physical setup, and workflow and device usage. This enabled deployment of more than 1,800 devices for inpatient telehealth across seven hospitals with positive feedback from health care staff. CONCLUSION: Large-scale setup and distribution of consumer devices is feasible for inpatient telehealth use cases. Our experience highlights operational barriers and potential solutions for health systems looking to preserve PPE and enhance vital communication.

Estimating Aspirin Overuse for Primary Prevention of Atherosclerotic Cardiovascular Disease (from a Nationwide Healthcare System).

The American College of Cardiology and American Heart Association recently published guidelines narrowing the indications for low-dose aspirin use. The suitability of the electronic health record (EHR) to identify patients for low-dose aspirin deprescribing is unknown. To apply the 3 low-dose aspirin guidelines to EHR data, the guidelines were deconstructed into components from their narrative text and assigned computer-interpretable definitions based on electronic data interchange standards. These definitions were used to search EHR data to identify patients for aspirin deprescribing. To verify EHR records for low-dose aspirin, we then compared the records with a survey of patients' self-reported use of low-dose aspirin. Of the 3 aspirin guidelines, only 1 had a definition suitable for EHR implementation. The other 2 contained difficult-to-implement phrases (e.g., "higher ASCVD risk", "increased bleeding risk"). An EHR search with the single implementable guideline identified 86,555 people for possible aspirin deprescribing (2% of 5,598,604). Only 676 of 1,135 (60%) patients who self-reported taking low-dose aspirin had an active EHR record for low-dose aspirin at that time. Limitations exist when using EHR data to identify patients for possible low-dose aspirin deprescribing such as incomplete EHR capture of and the interpretation of non-specific terminology when translating guidelines into an electronic equivalent. In conclusion, data show many people unnecessarily take low-dose aspirin.

Opportunities for addressing gaps in primary care shared decision-making with technology: a mixed-methods needs assessment.

OBJECTIVES: To analyze current practices in shared decision-making (SDM) in primary care and perform a needs assessment for the role of information technology (IT) interventions. MATERIALS AND METHODS: A mixed-methods study was conducted in three phases: (1) ethnographic observation of clinical encounters, (2) patient interviews, and (3) physician interviews. SDM was measured using the validated OPTION scale. Semistructured interviews followed an interview guide (developed by our multidisciplinary team) informed by the Traditional Decision Conflict Scale and Shared Decision Making Questionnaire. Field notes were independently coded and analyzed by two reviewers in Dedoose. RESULTS: Twenty-four patient encounters were observed in 3 diverse practices with an average OPTION score of 57.2 (0-100 scale; 95% confidence interval [CI], 51.8-62.6). Twenty-two patient and 8 physician interviews were conducted until thematic saturation was achieved. Cohen's kappa, measuring coder agreement, was 0.42. Patient domains were: establishing trust, influence of others, flexibility, frustrations, values, and preferences. Physician domains included frustrations, technology (concerns, existing use, and desires), and decision making (current methods used, challenges, and patients' understanding). DISCUSSION: Given low SDM observed, multiple opportunities for technology to enhance SDM exist based on specific OPTION items that received lower scores, including: (1) checking the patient's preferred information format, (2) asking the patient's preferred level of involvement in decision making, and (3) providing an opportunity for deferring a decision. Based on data from interviews, patients and physicians value information exchange and are open to technologies that enhance communication of care options. CONCLUSION: Future primary care IT platforms should prioritize the 3 quantitative gaps identified to improve physician-patient communication and relationships. Additionally, SDM tools should seek to standardize common workflow steps across decisions and focus on barriers to increasing adoption of effective SDM tools into routine primary care.

False Positive Positron Emission Tomography / Computed Tomography Scans in Treated Head and Neck Cancers.

OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) imaging for head and neck cancers (HNC) is commonly utilized for post-treatment assessment. Though PET/CT in this setting has been reported to have high negative predictive values (> 90%), positive predictive values have been reported at approximately 50%, leading to high rates of false positivity (FP) and troubling management decisions for both patient and practitioner. The objective of this study was to identify patient, disease, treatment and imaging factors that might be associated with a higher likelihood of FP on initial post-treatment PET/CT imaging for patients treated for HNC. MATERIALS AND METHODS: A retrospective chart review was performed on 84 patients treated for HNC who received radiation therapy (RT) as part of their overall management from October 2005 to August 2013. Of the patients screened, 19 were found to have mucosally based squamous cell carcinoma (SCC) with positive initial post-treatment PET/CT studies (23%). Fisher's exact test was used to analyze the association between categorical variables and FP, including patient's gender, disease laterality, primary tumor site and stage, nodal and overall stage, high dose RT fraction size, number of RT fractions completed, total RT dose, biologically effective dose and timing of PET/CT acquisition. Wilcoxon rank-sum test was used to analyze the association between continuous variables and FP, including patient age, total elapsed days of RT, an amount of infused fluorodeoxyglucose 18F-FDG, pre-PET/CT serum glucose levels, and maximum standardized uptake value SUVmax. Statistically significant findings were those that were deemed p <0.05. RESULTS: Among patients with positive initial post-treatment PET/CT scans for treated HNC, there was a lower proportion of higher primary disease stage associated with FP versus true positivity (T-stage 3-4: 20 vs 78%, respectively, p=0.023). We also discovered that 50% of patients that underwent confirmation for FP findings suffered serious complications as a direct consequence of invasive exploratory procedures. CONCLUSIONS: Although PET/CT is known for its exceptional negative predictive value (> 90%) in the post-treatment setting for HNC, high rates of FP remains a clinical challenge. Our study suggests that tumor stage (T-stage) may impact FP rates in positive initial post-treatment PET/CT scans. We recommend careful multidisciplinary discussion regarding positive PET/CT studies in the post-treatment setting for HNC, particularly if invasive intervention is considered.

Prostate Cancer-Associated Disseminated Intravascular Coagulation with Excessive Fibrinolysis Treated with Degarelix.

Disseminated intravascular coagulation (DIC) with excessive fibrinolysis (XFL) is a rare and acute life-threatening variant of DIC in patients with prostate cancer. Patients present with coagulopathy, hypofibrinogenemia, and systemic bleeding. We describe a case of DIC XFL caused by prostate cancer (PC) successfully treated with a single injection of degarelix, a gonadotropin-releasing hormone (GnRH) receptor antagonist. This led to prompt control of the patient's coagulopathy within ten days of treatment. Our case highlights features of this rare and devastating hemorrhagic complication of PC along with a fast-acting and effective therapeutic drug option.