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Abstract Number: 0270
ACCURACY OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN CARDIOVASCULAR DISEASES: A SYSTEMATIC REVIEW
SHM Converge 2025
Background: According to the Global Burden of Disease (GBD) study, 523 million (95% UI: 497 to 550 million) people worldwide had cardiovascular diseases (CVDs) in 2019, resulting in a significant increase in DALYs and years of life lost, mostly due to ischemic heart disease. There are various accurate and economical gold standard tests to identify [...]
Abstract Number: 0275
EVERYTHING, EVERYWHERE AND ALL AT ONCE: EXPLORING HOSPITALISTS’ EXPERIENCES USING ARTIFICAL INTELLIGENCE TOOLS FOR WORK
SHM Converge 2025
Background: Healthcare systems in the United States are navigating a complex landscape of financial strain, high clinician burnout, and workforce instability. The emergence of artificial intelligence (AI) tools in the clinical space offers the potential to improve clinical care and productivity but faces challenges like cost, clinician acceptance, and bias. Use of AI tools in [...]
Abstract Number: 0279
REDUCING PRESCRIBING GAPS AND IMPROVING ADHERENCE WITH GDMT USING A UNIQUE, PRESCRIPTION-ORIENTED DIGITAL TOOL THROUGH A STANDARD NURSE NAVIGATOR PROGRAM
SHM Converge 2025
Background: In the U.S., hospitalizations related to Congestive Heart Failure (CHF) are amongst the most frequent and costly, yet a unified approach toward improving outcomes remains elusive. In 2022, the AHA/ACC/HFSA released updated guidelines for the management of heart failure. Recommendations include prescribing four classes of medications for eligible patients, known as guideline-directed medical therapy [...]
Abstract Number: 0281
BARRIERS IMPACTED THE USE OF WEARABLE SMART HEALTH DEVICE AMONG MINORITY OLDER ADULTS
SHM Converge 2025
Background: Hospital-at-home care is a viable alternative to traditional inpatient care for older patients, allowing them to remain in the comfort of their own home while receiving hospital level care. The program employ a wide array of wearable smart health device (SHD) to track patient’s vital sign and other health metrics, enabling clinicians to intervene [...]
Abstract Number: 0283
PILOT STUDY OF ARTIFICIAL INTELLIGENCE (AI) SCRIBES ON HOSPITALISTS’ TIME ALLOCATION AND PATIENT-PROVIDER INTERACTIONS
SHM Converge 2025
Background: Documentation burden has been on the rise since the introduction of electronic health records (EHRs). Artificial Intelligence (AI) scribes use ambient documentation technology with the potential to mitigate documentation burden. Few studies have investigated the implications of AI scribes on hospital medicine providers’ workflow and patient interactions. Methods: We conducted a stepped-wedge trial at [...]
Abstract Number: 0298
AUTOMATING A PENDING LABS LIST INTO DISCHARGE SUMMARIES
SHM Converge 2025
Background: Transitioning from inpatient to outpatient care is high-risk, often associated with harm from incomplete or ineffective communication of clinical information [1]. In one report, 41% of patients had at least one pending study at the time of discharge, 43% of which were abnormal and 9.4% potentially actionable [2]. The discharge summary is a ubiquitous [...]
Abstract Number: 0367
ENHANCING MORTALITY RISK DOCUMENTATION WITH MICHART CLINICAL ASSISTANCE AND SUPPORT TOOL: A NOVEL ELECTRONIC MEDICAL RECORD SMART PHRASE SOLUTION
SHM Converge 2025
Background: Mortality risk assessment is crucial for predicting patient outcomes, assessing patient care delivery, and improving healthcare quality. Although high-quality medical documentation is critical for mortality risk assessment tools, provider documentation may be inconsistent, relies on coding teams for support, and may not directly reflect provider orders. Complete and precise documentation and coding can improve [...]
Abstract Number: 0377
INNOVATIVE SOLUTIONS TO LONGEVITY: IMPLEMENTING A HYBRID WORK MODEL IN HOSPITAL MEDICINE
SHM Converge 2025
Background: Hospital medicine has expanded significantly over the last two decades but faces a higher physician turnover rate compared to other specialties1 and a critical shortage of providers. A survey conducted in 2019 and again in 2022 showed a reduction in the number of hospitalists identified as being “very satisfied” with their career (from 55% [...]
Abstract Number: 0382
OPTIMIZING RISK ADJUSTMENT AND QUALITY THROUGH AUTO DOCUMENTATION
SHM Converge 2025
Background: Accurate clinical documentation is essential for capturing patient severity of illness (SOI) and risk of mortality (ROM). These metrics directly influence hospital quality reporting, including rankings like Vizient and metrics such as Observed-to-Expected Mortality (O:E) ratios. Traditional documentation methods rely heavily on manual input, which in busy clinical practices, results in underrepresented patient risk [...]
Abstract Number: 0418
EFFECT OF AN AI-POWERED CLINICAL DOCUMENTATION TOOL ON RISK ADJUSTMENT INDICES
SHM Converge 2025
Background: Risk adjustment indices are frequently used for hospital billing and reimbursements in the United States. Severity of illness (SOI) and risk of mortality (ROM) are two risk adjustment indices used in determining the APR-DRG, a classification system commonly used by insurers to determine hospital reimbursements. Recently, many health systems implemented AI-powered clinical documentation assistants [...]
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