Publications by authors named "Rebecca G Mishuris"

Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship.

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Background Opioid overdoses have contributed significantly to mortality in the United States. Despite long-standing recommendations from the Centers for Disease Control and Prevention to co-prescribe naloxone for patients receiving opioids who are at high risk of overdose, compliance with these guidelines has remained low. Objectives The objective of this study was to develop and evaluate a hospital-wide electronic health record (EHR)-based clinical decision support (CDS) tool designed to promote naloxone co-prescription for high-risk opioids.

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Objectives:  Efforts to reduce documentation burden (DocBurden) for all health professionals (HP) are aligned with national initiatives to improve clinician wellness and patient safety. Yet DocBurden has not been precisely defined, limiting national conversations and rigorous, reproducible, and meaningful measures. Increasing attention to DocBurden motivated this work to establish a standard definition of DocBurden, with the emergence of excessive DocBurden as a term.

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Background:  Studies have shown that documentation burden experienced by clinicians may lead to less direct patient care, increased errors, and job dissatisfaction. Implementing effective strategies within health care systems to mitigate documentation burden can result in improved clinician satisfaction and more time spent with patients. However, there is a gap in the literature regarding evidence-based interventions to reduce documentation burden.

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Importance: The COVID-19 pandemic was associated with substantial growth in patient portal messaging. Higher message volumes have largely persisted, reflecting a new normal. Prior work has documented lower message use by patients who belong to minoritized racial and ethnic groups, but research has not examined differences in care team response to messages.

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Objective: We sought to determine whether average cumulated time to chart closure (CTCC), a novel construct to measure clinician workload burden, and electronic health record (EHR) measures were associated with a validated measure of burnout.

Materials And Methods: Physicians at a large academic institution participated in a well-being survey that was linked to their EHR use data. CTCC was defined as the average time from the start of patient encounters to chart closure over a set of encounters.

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Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS:  We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care.

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Background: The 21st Century Cures Act provides improved access to one's medical record but presents new challenges to adolescent confidentiality in the domain of health care information technology. Adolescent patients, who have the right to confidential care in certain areas as dictated by state law, face the prospect of parents and guardians erroneously accessing their confidential health information.

Objectives: Our institution, the largest safety net hospital in our region, sought to quantify the proportion of adolescent patient portal accounts likely being accessed by guardians and to implement corrective measures for the patient portal sign-up process in our electronic health record (EHR) system.

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Telehealth services, specifically telemedicine audio-video and audio-only patient encounters, expanded dramatically during the COVID-19 pandemic through temporary waivers and flexibilities tied to the public health emergency. Early studies demonstrate significant potential to advance the quintuple aim (patient experience, health outcomes, cost, clinician well-being, and equity). Supported well, telemedicine can particularly improve patient satisfaction, health outcomes, and equity.

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Background: Hypertension is a prevalent cardiovascular disease with severe longer-term implications. Conventional management based on clinical guidelines does not facilitate personalized treatment that accounts for a richer set of patient characteristics.

Methods: Records from 1/1/2012 to 1/1/2020 at the Boston Medical Center were used, selecting patients with either a hypertension diagnosis or meeting diagnostic criteria (≥ 130 mmHg systolic or ≥ 90 mmHg diastolic, n = 42,752).

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Article Synopsis
  • COVID-19 symptoms differ greatly, and a study was conducted to assess the effectiveness of three clinical screening tools (NTS, ED ROS, and attending physician PA) in identifying COVID-19 cases confirmed by RT-PCR tests in patients admitted to Boston Medical Center.* -
  • Results showed that the attending physician's probability assessment (PA) was more sensitive and specific than the other methods, indicating it was better at predicting COVID-19 presence, but none were sufficient enough to serve as a standalone diagnostic tool.* -
  • The study concluded that while the attending PA was the most reliable screening method, all tools were not accurate enough to replace RT-PCR testing; thus, universal testing for COVID-19 before patient admissions is recommended.*
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Objective: To develop predictive models of coronavirus disease 2019 (COVID-19) outcomes, elucidate the influence of socioeconomic factors, and assess algorithmic racial fairness using a racially diverse patient population with high social needs.

Materials And Methods: Data included 7,102 patients with positive (RT-PCR) severe acute respiratory syndrome coronavirus 2 test at a safety-net system in Massachusetts. Linear and nonlinear classification methods were applied.

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Background: To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an "opt-out" electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle evaluations guided by the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) compilation.

Methods: We identified stakeholders affected by implementation and conducted a local needs assessment starting 6 months-pre-launch.

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Article Synopsis
  • As of July 2020, the U.S. reported about 2.8 million COVID-19 cases and 130,000 related deaths, disproportionately affecting racial and ethnic minorities as well as individuals experiencing homelessness.
  • Boston Medical Center treated 2,729 COVID-19 patients from March to May 2020, with a majority being managed as outpatients (56.5%), while 3.6% of patients died during this period.
  • The patient demographics revealed that 44.6% were non-Hispanic Black and 30.1% Hispanic, with higher hospitalization rates among Hispanic patients (46.5%) compared to Black (
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Background: To address the burden of tobacco use in underserved populations, our safety net hospital developed a tobacco treatment intervention consisting of an "opt-out" electronic health record-based best practice alert + order set, which triggers consultation to an inpatient tobacco treatment consult (TTC) service for all hospitalized smokers.

Research Question: We sought to understand if the intervention would increase patient-level outcomes (receipt of tobacco treatment during hospitalization and at discharge; 6-month smoking abstinence) and improve hospital-wide performance on tobacco treatment metrics.

Design And Methods: We conducted two retrospective quasi-experimental analyses to examine effectiveness of the TTC service.

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Background: Effective implementation of technologies into clinical workflow is hampered by lack of integration into daily activities. Normalisation process theory (NPT) can be used to describe the kinds of 'work' necessary to implement and embed complex new practices. We determined the suitability of NPT to assess the facilitators, barriers and 'work' of implementation of two clinical decision support (CDS) tools across diverse care settings.

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Background: Low back pain (LBP) is one of the most prevalent and potentially disabling conditions for which people seek health care. Patients, providers, and payers agree that greater effort is needed to prevent acute LBP from transitioning to chronic LBP.

Methods And Study Design: The TARGET (Targeted Interventions to Prevent Chronic Low Back Pain in High-Risk Patients) Trial is a primary care-based, multisite, cluster randomized, pragmatic trial comparing guideline-based care (GBC) to GBC + referral to Psychologically Informed Physical Therapy (PIPT) for patients presenting with acute LBP and identified as high risk for persistent disabling symptoms.

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Background: Social determinants affect health, yet there are few systematic clinical strategies in primary care that leverage electronic health record (EHR) automation to facilitate screening for social needs and resource referrals. An EHR-based social determinants of health (SDOH) screening and referral model, adapted from the WE CARE model for pediatrics, was implemented in urban adult primary care.

Objectives: This study aimed to: (1) understand the burden of SDOH among patients at Boston Medical Center; and (2) evaluate the feasibility of implementing a systematic clinical strategy to screen new primary care patients for SDOH, use EHR technology to add these needs to the patient's chart through autogenerated ICD-10 codes, and print patient language-congruent referrals to available resources upon patient request.

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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.

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