A machine learning technology for addressing medication-related risk in older, multimorbid patients.

Objectives: To evaluate the FeelBetter machine learning system's ability to accurately identify older patients with multimorbidity at Brigham and Women's Hospital at highest risk of medication-associated emergency department (ED) visits and hospitalizations, and to assess the system's ability to provide accurate medication recommendations for these patients.

Study Design: Retrospective cohort study.

Methods: The system uses medications, demographics, diagnoses, laboratory results, health care utilization patterns, and costs to stratify patients' risk of ED visits and hospitalizations.

Racial and ethnic associations with interstitial lung disease and healthcare utilization in patients with systemic sclerosis.

Objective: Racial and ethnic differences in presentation and outcomes have been reported in systemic sclerosis (SSc) and SSc-interstitial lung disease (ILD). However, prior studies have limited diversity. We aim to evaluate if there are racial/ethnic differences associated with ILD, time intervals between SSc and ILD and with emergency department (ED) visit or hospitalization rates.

A Calculated Risk: Evaluation of QTc Drug-Drug Interaction (DDI) Clinical Decision Support (CDS) Alerts and Performance of the Tisdale Risk Score Calculator.

Introduction: A risk factor for a potentially fatal ventricular arrhythmia Torsade de Pointes is a prolongation in the heart rate-corrected QT interval (QTc) ≥ 500 milliseconds (ms) or an increase of ≥ 60 ms from a patient's baseline value, which can cause sudden cardiac death. The Tisdale risk score calculator uses clinical variables to predict which hospitalized patients are at the highest risk for QTc prolongation.

Objective: To determine the rate of overridden QTc drug-drug interaction (DDI)-related clinical decision support (CDS) alerts per patient admission and the prevalence by Tisdale risk score category of these overridden alerts.

Frequency and preventability of adverse drug events in the outpatient setting.

Background: Limited data exist regarding adverse drug events (ADEs) in the outpatient setting. The objective of this study was to determine the incidence, severity, and preventability of ADEs in the outpatient setting and identify potential prevention strategies.

Methods: We conducted an analysis of ADEs identified in a retrospective electronic health records review of outpatient encounters in 2018 at 13 outpatient sites in Massachusetts that included 13 416 outpatient encounters in 3323 patients.

Straight to the point: evaluation of a Point of Care Information (POCI) resource in answering disease-related questions.

Objective: To evaluate the ability of DynaMedex, an evidence-based drug and disease Point of Care Information (POCI) resource, in answering clinical queries using keyword searches.

Methods: Real-world disease-related questions compiled from clinicians at an academic medical center, DynaMedex search query data, and medical board review resources were categorized into five clinical categories (complications & prognosis, diagnosis & clinical presentation, epidemiology, prevention & screening/monitoring, and treatment) and six specialties (cardiology, endocrinology, hematology-oncology, infectious disease, internal medicine, and neurology). A total of 265 disease-related questions were evaluated by pharmacist reviewers based on if an answer was found (yes, no), whether the answer was relevant (yes, no), difficulty in finding the answer (easy, not easy), cited best evidence available (yes, no), clinical practice guidelines included (yes, no), and level of detail provided (detailed, limited details).

Racial and ethnic associations with interstitial lung disease and healthcare utilization in patients with systemic sclerosis.

Rationale: Racial and ethnic differences in presentation and outcomes have been reported in systemic sclerosis (SSc) and SSc-interstitial lung disease (ILD). However, diverse cohorts and additional modeling can improve understanding of risk features and outcomes, which is important for reducing associated disparities.

Objectives: To determine if there are racial/ethnic differences associated with SSc-ILD risk and age; time intervals between SSc and ILD, and with emergency department (ED) visit or hospitalization rates.

How Safe are Outpatient Electronic Health Records? An Evaluation of Medication-Related Decision Support using the Ambulatory Electronic Health Record Evaluation Tool.

Background: The purpose of the Ambulatory Electronic Health Record (EHR) Evaluation Tool is to provide outpatient clinics with an assessment that they can use to measure the ability of the EHR system to detect and prevent common prescriber errors. The tool consists of a medication safety test and a medication reconciliation module.

Objectives: The goal of this study was to perform a broad evaluation of outpatient medication-related decision support using the Ambulatory EHR Evaluation Tool.

Correction: Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

[This corrects the article DOI: 10.2196/43960.].

Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson.

Background: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue.

Objective: This study aimed to collect clinicians' feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex.

Development and validation of algorithms to build an electronic health record based cohort of patients with systemic sclerosis.

Objectives: To evaluate methods of identifying patients with systemic sclerosis (SSc) using International Classification of Diseases, Tenth Revision (ICD-10) codes (M34*), electronic health record (EHR) databases and organ involvement keywords, that result in a validated cohort comprised of true cases with high disease burden.

Methods: We retrospectively studied patients in a healthcare system likely to have SSc. Using structured EHR data from January 2016 to June 2021, we identified 955 adult patients with M34* documented 2 or more times during the study period.

Dynamic reaction picklist for improving allergy reaction documentation: A usability study.

Objective: To assess novel dynamic reaction picklists for improving allergy reaction documentation compared to a static reaction picklist.

Materials And Methods: We developed three web-based user interfaces (UIs) mimicking the Mass General Brigham's EHR allergy module: the first and second UIs (i.e.

Reconciling Allergy Information in the Electronic Health Record After a Drug Challenge Using Natural Language Processing.

Background: Drug challenge tests serve to evaluate whether a patient is allergic to a medication. However, the allergy list in the electronic health record (EHR) is not consistently updated to reflect the results of the challenge, affecting clinicians' prescription decisions and contributing to inaccurate allergy labels, inappropriate drug-allergy alerts, and potentially ineffective, more toxic, and/or costly care. In this study, we used natural language processing (NLP) to automatically detect discrepancies between the EHR allergy list and drug challenge test results and to inform the clinical recommendations provided in a real-time allergy reconciliation module.

Identifying and Reconciling Patients' Allergy Information Within the Electronic Health Record.

Allergy information is often documented in diverse sections of the electronic health record (EHR). Systematically reconciling allergy information across the EHR is critical to improve the accuracy and completeness of patients' allergy lists and ensure patient safety. In this retrospective cohort study, we examined the prevalence of incompleteness, inaccuracy, and redundancy of allergy information for patients with a clinical encounter at any Mass General Brigham facility between January 1, 2018 and December 31, 2018.

Heterogeneity of Drug Allergies and Reaction Lists in Two U.S. Health Care Systems' Electronic Health Records.

Background: Health care institutions have their own "picklist" for clinicians to document adverse drug reactions (ADRs) into the electronic health record (EHR) allergy list. Whether the lack of a nationally standardized picklist impacts clinician data entries is unknown.

Objectives: The objective of this study was to assess the impact of defined reaction picklists on clinical documentation and, therefore, downstream analytics and clinical research using these data at two institutions.

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review.

Adverse drug events (ADEs) represent one of the most prevalent types of health-care-related harm, and there is substantial room for improvement in the way that they are currently predicted and detected. We conducted a scoping review to identify key use cases in which artificial intelligence (AI) could be leveraged to reduce the frequency of ADEs. We focused on modern machine learning techniques and natural language processing.

The Development and Piloting of the Ambulatory Electronic Health Record Evaluation Tool: Lessons Learned.

Background: Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed.

Objective: To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot.

Methods: The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group.

Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events.

Introduction: Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy.

Objective: We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing.

Comparison of Medication Alerts from Two Commercial Applications in the USA.

Introduction: Medication organizations across the USA have adopted electronic health records, and one of the most anticipated benefits of these was improved medication safety, but alert fatigue has been a major issue.

Objective: We compared the appropriateness of medication-related clinical decision support alerts triggered by two commercial applications: EPIC and Seegnal's platform.

Methods: This was a retrospective comparison of two commercial applications.

Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts.

Objective: To assess the appropriateness of medication-related clinical decision support (CDS) alerts associated with renal insufficiency and the potential/actual harm from overriding the alerts.

Materials And Methods: Override rate frequency was recorded for all inpatients who had a renal CDS alert trigger between 05/2017 and 04/2018. Two random samples of 300 for each of 2 types of medication-related CDS alerts associated with renal insufficiency-"dose change" and "avoid medication"-were evaluated by 2 independent reviewers using predetermined criteria for appropriateness of alert trigger, appropriateness of override, and patient harm.

The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support.

Objective: The study sought to evaluate the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018, along with their performance against fatal orders and nuisance orders.

Materials And Methods: We evaluated 1599 hospitals that took the test in both 2017 and 2018 by using their overall percentage scores on the test, along with the percentage of fatal orders appropriately alerted on, and the percentage of nuisance orders incorrectly alerted on.

Results: Hospitals showed overall improvement; the mean score in 2017 was 58.

A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record.

Objective: Incomplete and static reaction picklists in the allergy module led to free-text and missing entries that inhibit the clinical decision support intended to prevent adverse drug reactions. We developed a novel, data-driven, "dynamic" reaction picklist to improve allergy documentation in the electronic health record (EHR).

Materials And Methods: We split 3 decades of allergy entries in the EHR of a large Massachusetts healthcare system into development and validation datasets.

High-priority drug-drug interaction clinical decision support overrides in a newly implemented commercial computerized provider order-entry system: Override appropriateness and adverse drug events.

Objective: The study sought to determine frequency and appropriateness of overrides of high-priority drug-drug interaction (DDI) alerts and whether adverse drug events (ADEs) were associated with overrides in a newly implemented electronic health record.

Materials And Methods: We conducted a retrospective study of overridden high-priority DDI alerts occurring from April 1, 2016, to March 31, 2017, from inpatient and outpatient settings at an academic health center. We studied highest-severity DDIs that were previously designated as "hard stops" and additional high-priority DDIs identified from clinical experience and literature review.

Lab monitoring and acute care utilization during initiation of renin angiotensin aldosterone inhibitors or diuretics in chronic kidney disease.

Renin angiotensin aldosterone system inhibitors (RAASi) and diuretics are among the most frequently prescribed anti-hypertensives. Individuals with chronic kidney disease (CKD) are particularly at risk for electrolyte disturbances and kidney injury but the appropriate use of lab monitoring following RAASi or diuretic initiation is uncertain in CKD.We describe the frequency and time interval of lab monitoring during initiation of RAASi and diuretics in CKD and assess whether close lab monitoring associates with one-year risk of emergency department (ED) visit or hospitalization.

Patient-centered Pharmacist Care in the Hemodialysis Unit: a quasi-experimental interrupted time series study.

Background: Nonadherence to medications by patients requiring hemodialysis (HD) leads to unfavorable clinical outcomes. Limited data exist to demonstrate the effect of incorporating patient-centered interventions using concepts of medication therapy management and motivational interview by pharmacists on pharmacoadherence in patients requiring HD. Therefore, we assessed the impact of patient-centered pharmacist care on pharmacoadherence and its outcomes in patients requiring HD.

The Burden of Opioid-Related Adverse Drug Events on Hospitalized Previously Opioid-Free Surgical Patients.

Objective: Opioid analgesics are a mainstay for acute pain management, but postoperative opioid administration has risks. We examined the prevalence, risk factors, and consequences of opioid-related adverse drug events (ORADEs) in a previously opioid-free surgical population.

Methods: A retrospective, observational, cohort study using administrative, billing, clinical, and medication administration data from two hospitals.