The Impact of Team-Based Ordering Workflows on Ambulatory Physician EHR Time, Order Volume, and Visit Volume.

Objective: To analyze national rates of team-based ordering and evaluate changes in key outcomes following adoption.

Study Setting And Design: We conducted an observational pre-post intervention-comparison study of 249,463 ambulatory physicians across 401 organizations using the Epic EHR. Our intervention was the adoption of team-based ordering, measured as the proportion of orders involving team support.

Adoption of Health Information Technologies by Area Socioeconomic Deprivation Among US Hospitals.

Importance: Access to and quality of care vary substantially by area socioeconomic status. Expanding hospital health information technology (HIT) adoption may help reduce these disparities, given hospitals' central role in serving underserved populations.

Objective: To examine variations in US hospital adoption of telehealth and health information exchange (HIE) functionalities by hospital service area (HSA) socioeconomic deprivation.

Electronic health record market consolidation and implications for cybersecurity.

Over the past decade, the electronic health record (EHR) market has become increasingly consolidated, with the majority of care delivery organizations now using 1 of 2 vendors -Epic and Oracle Health. This consolidation creates a "single-point-of-failure" tail risk for cybersecurity: 1 successful attack could expose millions of patients' private data and could potentially impact documentation, billing, and clinical care across thousands of sites. Moreover, dependence on other technology vendors, such as shared cloud hosts, broadens the potential attack surface beyond vendors' core firewalls.

Emerging Domains for Measuring Health Care Delivery With Electronic Health Record Metadata.

This article aims to introduce emerging measurement domains made feasible through the electronic health record (EHR) use metadata, to inform the changing landscape of health care delivery. We reviewed emerging domains in which EHR metadata may be used to measure health care delivery, outlining a framework for evaluating measures based on desirability, feasibility, and viability. We argue that EHR use metadata may be leveraged to develop and operationalize novel measures in the domains of team structure and dynamics, workflows, and cognitive environment to provide a clearer understanding of modern health care delivery.

National trends in oncology specialists' EHR inbox work, 2019-2022.

Background: Electronic health record (EHR) burden is an important driver of the ongoing physician burnout crisis. In particular, EHR-based messaging (also known as "inbox")-including messages from patients-is associated with burnout and decreased well-being. Little is known about EHR messaging burden for oncologists.

Imputation of missing aggregate EHR audit log data across individual and multiple organizations.

Objective: To compare naive versus machine learning imputation strategies' efficacy for imputing missing data in EHR-vendor generated data, explore subgrouping criteria, and evaluate performance and feasibility for in-house implementation.

Materials And Methods: Missing data imputation experiments involving various types and sizes of organizations were conducted using physician-only aggregate EHR audit log data. Organizations were categorized by teaching status.

Current Use And Evaluation Of Artificial Intelligence And Predictive Models In US Hospitals.

Effective evaluation and governance of predictive models used in health care, particularly those driven by artificial intelligence (AI) and machine learning, are needed to ensure that models are fair, appropriate, valid, effective, and safe, or FAVES. We analyzed data from the 2023 American Hospital Association Annual Survey Information Technology Supplement to identify how AI and predictive models are used and evaluated for accuracy and bias in hospitals. Hospitals use AI and predictive models to predict health trajectories or risks for inpatients, identify high-risk outpatients to inform follow-up care, monitor health, recommend treatments, simplify or automate billing procedures, and facilitate scheduling.

Inbox message prioritization and management approaches in primary care.

Objectives: Patient messaging to clinicians has dramatically increased since the pandemic, leading to informatics efforts to categorize incoming messages. We examined how message prioritization (as distinct from categorization) occurs in primary care, and how primary care clinicians managed their inbox workflows.

Materials And Methods: Semi-structured interviews and inbox work observations with 11 primary care clinicians at MedStar Health.

Trending in the right direction: critical access hospitals increased adoption of advanced electronic health record functions from 2018 to 2023.

Objectives: We analyzed trends in adoption of advanced patient engagement and clinical data analytics functionalities among critical access hospitals (CAHs) and non-CAHs to assess how historical gaps have changed.

Materials And Methods: We used 2014, 2018, and 2023 data from the American Hospital Association Annual Survey IT Supplement to measure differences in adoption rates (ie, the "adoption gap") of patient engagement and clinical data analytics functionalities across CAHs and non-CAHs. We measured changes over time in CAH and non-CAH adoption of 6 "core" clinical data analytics functionalities, 5 "core" patient engagement functionalities, 5 new patient engagement functionalities, and 3 bulk data export use cases.

Electronic Health Record Documentation Burden Crowds Out Health Information Exchange Use By Primary Care Physicians.

Although electronic health record (EHR) documentation burden is known to be associated with reduced clinician well-being and burnout, it may have even worse unintended consequences if documentation work also crowds out other high-value EHR tasks. We examined this possibility by assessing the relationship between documentation burden and a high-value but optional EHR task: the use of health information exchange (HIE) to view patient records from outside organizations. Our study took advantage of an exogenous shock to documentation time: appointment no-shows.

Physician EHR Time and Visit Volume Following Adoption of Team-Based Documentation Support.

Importance: Physicians spend the plurality of active electronic health record (EHR) time on documentation. Excessive documentation limits time spent with patients and is associated with burnout. Organizations need effective strategies to reduce physician documentation burden; however, evidence on team-based documentation (eg, medical scribes) has been limited to small, single-institution studies lacking rigorous estimates of how documentation support changes EHR time and visit volume.

Accounting for taste: preferences mediate the relationship between documentation time and ambulatory physician burnout.

Objectives: Physician burnout in the US has reached crisis levels, with one source identified as extensive after-hours documentation work in the electronic health record (EHR). Evidence has illustrated that physician preferences for after-hours work vary, such that after-hours work may not be universally burdensome. Our objectives were to analyze variation in preferences for after-hours documentation and assess if preferences mediate the relationship between after-hours documentation time and burnout.

Consistency is key: documentation distribution and efficiency in primary care.

Objectives: We analyzed the degree to which daily documentation patterns in primary care varied and whether specific patterns, consistency over time, and deviations from clinicians' usual patterns were associated with note-writing efficiency.

Materials And Methods: We used electronic health record (EHR) active use data from the Oracle Cerner Advance platform capturing hourly active documentation time for 498 physicians and advance practice clinicians (eg, nurse practitioners) for 65 152 clinic days. We used k-means clustering to identify distinct daily patterns of active documentation time and analyzed the relationship between these patterns and active documentation time per note.

Physicians in ACOs report greater documentation burden.

Objectives: First, to analyze the relationship between value-based payment (VBP) program participation and documentation burden among office-based physicians. Second, to analyze the relationship between specific VBP programs (eg, accountable care organizations [ACOs]) and documentation burden.

Study Design: Retrospective analyses of US office-based physicians in 2019 and 2021.

Interoperability in the Wild: Comparison of Real-World Electronic C-CDA Documents from Two Sources.

Although health information exchange (HIE) networks exist in multiple nations, providers still require access multiple sources to obtain medical records. We sought to measure and compare differences in data presence and concordance across regional HIE and EHR vendor-based networks. Using 1,054 randomly selected patients from a large health system in the US, we generated consolidated clinical document architecture (C-CDA) documents from each network.

Guidance for reporting analyses of metadata on electronic health record use.

Introduction: Research on how people interact with electronic health records (EHRs) increasingly involves the analysis of metadata on EHR use. These metadata can be recorded unobtrusively and capture EHR use at a scale unattainable through direct observation or self-reports. However, there is substantial variation in how metadata on EHR use are recorded, analyzed and described, limiting understanding, replication, and synthesis across studies.

The health effects of nursing home specialization in post-acute care.

Nursing homes serve both long-term care and post-acute care (PAC) patients, two groups with distinct financing mechanisms and requirements for care. We examine empirically the effect of nursing home specialization in PAC using 2011-2018 data for Medicare patients admitted to nursing homes following a hospital stay. To address patient selection into specialized nursing homes, we use an instrumental variables approach that exploits variation over time in the distance from the patient's residential ZIP code to the closest nursing home with different levels of PAC specialization.

Examining primary care provider experiences with using a clinical decision support tool for pain management.

Objective: To evaluate primary care provider (PCP) experiences using a clinical decision support (CDS) tool over 16 months following a user-centered design process and implementation.

Materials And Methods: We conducted a qualitative evaluation of the Chronic Pain OneSheet (OneSheet), a chronic pain CDS tool. OneSheet provides pain- and opioid-related risks, benefits, and treatment information for patients with chronic pain to PCPs.