Virtual Scribes and Physician Time Spent on Electronic Health Records.

Importance: Time on the electronic health record (EHR) is associated with burnout among physicians. Newer virtual scribe models, which enable support from either a real-time or asynchronous scribe, have the potential to reduce the burden of the EHR and EHR-related documentation. Objective: To characterize the association of use of virtual scribes with changes in physicians' EHR time and note and order composition and to identify the physician, scribe, and scribe response factors associated with changes in EHR time upon virtual scribe use. Design, Setting, and Participants: Retrospective, pre-post quality improvement study of 144 physicians across specialties who had used a scribe for at least 3 months from January 2020 to September 2022, were affiliated with Brigham and Women's Hospital and Massachusetts General Hospital, and cared for patients in the outpatient setting. Data were analyzed from November 2022 to January 2024. Exposure: Use of either a real-time or asynchronous virtual scribe. Main Outcomes: Total EHR time, time on notes, and pajama time (5:30 pm to 7:00 am on weekdays and nonscheduled weekends and holidays), all per appointment; proportion of the note written by the physician and team contribution to orders. Results: The main study sample included 144 unique physicians who had used a virtual scribe for at least 3 months in 152 unique scribe participation episodes (134 [88.2%] had used an asynchronous scribe service). Nearly two-thirds of the physicians (91 physicians [63.2%]) were female and more than half (86 physicians [59.7%]) were in primary care specialties. Use of a virtual scribe was associated with significant decreases in total EHR time per appointment (mean [SD] of 5.6 [16.4] minutes; P < .001) in the 3 months after vs the 3 months prior to scribe use. Scribe use was also associated with significant decreases in note time per appointment and pajama time per appointment (mean [SD] of 1.3 [3.3] minutes; P < .001 and 1.1 [4.0] minutes; P = .004). In a multivariable linear regression model, the following factors were associated with significant decreases in total EHR time per appointment with a scribe use at 3 months: practicing in a medical specialty (-7.8; 95% CI, -13.4 to -2.2 minutes), greater baseline EHR time per appointment (-0.3; 95% CI, -0.4 to -0.2 minutes per additional minute of baseline EHR time), and decrease in the percentage of the note contributed by the physician (-9.1; 95% CI, -17.3 to -0.8 minutes for every percentage point decrease). Conclusions and Relevance: In 2 academic medical centers, use of virtual scribes was associated with significant decreases in total EHR time, time spent on notes, and pajama time, all per appointment. Virtual scribes may be particularly effective among medical specialists and those physicians with greater baseline EHR time.

Medical record prompts improve the frequency and documentation of dizziness and driving conversations in the ENT balance clinic.

BACKGROUND: Driving capacity is affected by vestibular disorders and the medications used to treat them. Driving is not considered during medical consultations, with 92 per cent of patients attending a centre for dizziness not discussing it with the doctor. OBJECTIVE: To investigate if medical record prompts facilitate dizziness and driving conversations in ENT balance clinics. METHODS: A questionnaire was designed to reflect the current standards of practice and advice given regarding driving and dizziness during balance clinic consultations. RESULTS: Medical record prompts facilitated the improved frequency and recording of shared decision-making conversations about driving and dizziness in 98 per cent of consultations. CONCLUSION: This study highlights the benefits of medical record prompts for documented and accurate shared decision-making conversations surrounding dizziness, vertigo, vestibular conditions and driving. This potentially improves safety for all road users, and protects the patient and clinician in the event of road traffic accidents and medico-legal investigations.

Variable Impact of Medical Scribes on Physician Electronic Health Record Documentation Practices: A Quantitative Analysis Across a Large, Integrated Health-System.

BACKGROUND: Medical scribes have been utilized to reduce electronic health record (EHR) associated documentation burden. Although evidence suggests benefits to scribes, no large-scale studies have quantitatively evaluated scribe impact on physician documentation across clinical settings. This study aimed to evaluate the effect of scribes on physician EHR documentation behaviors and performance. METHODS: This retrospective cohort study used EHR audit log data from a large academic health system to evaluate clinical documentation for all ambulatory encounters between January 2014 and December 2019 to evaluate the effect of scribes on physician documentation behaviors. Scribe services were provided on a first-come, first-served basis on physician request. Based on a physician's scribe use, encounters were grouped into 3 categories: never using a scribe, prescribe (before scribe use), or using a scribe. Outcomes included chart closure time, the proportion of delinquent charts, and charts closed after-hours. RESULTS: Three hundred ninety-five physicians (23% scribe users) across 29 medical subspecialties, encompassing 1,132,487 encounters, were included in the analysis. At baseline, scribe users had higher chart closure time, delinquent charts, and after-hours documentation than physicians who never used scribes. Among scribe users, the difference in outcome measures postscribe compared with baseline varied, and using a scribe rarely resulted in outcome measures approaching a range similar to the performance levels of nonusing physicians. In addition, there was variability in outcome measures across medical specialties and within similar subspecialties. CONCLUSION: Although scribes may improve documentation efficiency among some physicians, not all will improve EHR-related documentation practices. Different strategies may help to optimize documentation behaviors of physician-scribe dyads and maximize outcomes of scribe implementation.

Evaluating feedback reports to support documentation of veterans' care preferences in home based primary care.

BACKGROUND: To evaluate the effectiveness of delivering feedback reports to increase completion of LST notes among VA Home Based Primary Care (HBPC) teams. The Life Sustaining Treatment Decisions Initiative (LSTDI) was implemented throughout the Veterans Health Administration (VHA) in the United States in 2017 to ensure that seriously ill Veterans have care goals and LST decisions elicited and documented. METHODS: We distributed monthly feedback reports summarizing LST template completion rates to 13 HBPC intervention sites between October 2018 and February 2020 as the sole implementation strategy. We used principal component analyses to match intervention to 26 comparison sites and used interrupted time series/segmented regression analyses to evaluate the differences in LST template completion rates between intervention and comparison sites. Data were extracted from national databases for VA HBPC in addition to interviews and surveys in a mixed methods process evaluation. RESULTS: LST template completion rose from 6.3 to 41.9% across both intervention and comparison HBPC teams between March 1, 2018, and February 26, 2020. There were no statistically significant differences for intervention sites that received feedback reports. CONCLUSIONS: Feedback reports did not increase documentation of LST preferences for Veterans at intervention compared with comparison sites. Observed increases in completion rates across intervention and comparison sites can likely be attributed to implementation strategies used nationally as part of the national roll-out of the LSTDI. Our results suggest that feedback reports alone were not an effective implementation strategy to augment national implementation strategies in HBPC teams.

Assessing the Usability and Feasibility of Digital Assistant Tools for Direct Support Professionals: Participatory Design and Pilot-Testing.

BACKGROUND: The United States is experiencing a direct support professional (DSP) crisis, with demand far exceeding supply. Although generating documentation is a critical responsibility, it is one of the most wearisome aspects of DSPs' jobs. Technology that enables DSPs to log informal time-stamped notes throughout their shift could help reduce the burden of end-of-shift documentation and increase job satisfaction, which in turn could improve the quality of life of the individuals with intellectual and developmental disabilities (IDDs) whom DSPs support. However, DSPs, with varied ages, levels of education, and comfort using technology, are not likely to adopt tools that detract from caregiving responsibilities or increase workload; therefore, technological tools for them must be relatively simple, extremely intuitive, and provide highly valued capabilities. OBJECTIVE: This paper describes the development and pilot-testing of a digital assistant tool (DAT) that enables DSPs to create informal notes throughout their shifts and use these notes to facilitate end-of-shift documentation. The purpose of the pilot study was to assess the usability and feasibility of the DAT. METHODS: The research team applied an established user-centered participatory design process to design, develop, and test the DAT prototypes between May 2020 and April 2023. Pilot-testing entailed having 14 DSPs who support adults with IDDs use the first full implementation of the DAT prototypes during 2 or 3 successive work shifts and fill out demographic and usability questionnaires. RESULTS: Participants used the DAT prototypes to create notes and help generate end-of-shift reports. The System Usability Scale score of 81.79 indicates that they found the prototypes easy to use. Survey responses imply that using the DAT made it easier for participants to produce required documentation and suggest that they would adopt the DAT if this tool were available for daily use. CONCLUSIONS: Simple technologies such as the DAT prototypes, which enable DSPs to use mobile devices to log time-stamped notes throughout their shift with minimal effort and use the notes to help write reports, have the potential to both reduce the burden associated with producing documentation and enhance the quality (level of detail and accuracy) of this documentation. This could help to increase job satisfaction and reduce turnover in DSPs, both of which would help improve the quality of life of the individuals with IDDs whom they support. The pilot test results indicate that DSPs found the DAT easy to use. Next steps include (1) producing more robust versions of the DAT with additional capabilities, such as storing data locally on mobile devices when Wi-Fi is not available; and (2) eliciting input from agency directors, families, and others who use data about adults with IDDs to help care for them to ensure that data produced by DSPs are relevant and useful.

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio. METHODS: We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i.e., SOcial DeterminAnts) to facilitate SDoH extraction from clinical narratives. We examined the performance and potential bias of SODA for different race and gender groups, tested the generalizability of SODA using two disease domains including cancer and opioid use, and explored strategies for improvement. We applied SODA to extract 19 categories of SDoH from the breast (n = 7,971), lung (n = 11,804), and colorectal cancer (n = 6,240) cohorts to assess patient-level extraction ratio and examine the differences among race and gender groups. RESULTS: We developed an SDoH corpus using 629 clinical notes of cancer patients with annotations of 13,193 SDoH concepts/attributes from 19 categories of SDoH, and another cross-disease validation corpus using 200 notes from opioid use patients with 4,342 SDoH concepts/attributes. We compared 7 transformer models and the GatorTron model achieved the best mean average strict/lenient F1 scores of 0.9122 and 0.9367 for SDoH concept extraction and 0.9584 and 0.9593 for linking attributes to SDoH concepts. There is a small performance gap (∼4%) between Males and Females, but a large performance gap (>16 %) among race groups. The performance dropped when we applied the cancer SDoH model to the opioid cohort; fine-tuning using a smaller opioid SDoH corpus improved the performance. The extraction ratio varied in the three cancer cohorts, in which 10 SDoH could be extracted from over 70 % of cancer patients, but 9 SDoH could be extracted from less than 70 % of cancer patients. Individuals from the White and Black groups have a higher extraction ratio than other minority race groups. CONCLUSIONS: Our SODA package achieved good performance in extracting 19 categories of SDoH from clinical narratives. The SODA package with pre-trained transformer models is available at https://github.com/uf-hobi-informatics-lab/SODA_Docker.

Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study.

BACKGROUND: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics. The integration of ambient artificial intelligence (AI)-powered solutions offers a promising way to improve documentation while fitting seamlessly into existing workflows. OBJECTIVE: This study aims to assess the accuracy and quality of Subjective, Objective, Assessment, and Plan (SOAP) notes generated by ChatGPT-4, an AI model, using established transcripts of History and Physical Examination as the gold standard. We seek to identify potential errors and evaluate the model's performance across different categories. METHODS: We conducted simulated patient-provider encounters representing various ambulatory specialties and transcribed the audio files. Key reportable elements were identified, and ChatGPT-4 was used to generate SOAP notes based on these transcripts. Three versions of each note were created and compared to the gold standard via chart review; errors generated from the comparison were categorized as omissions, incorrect information, or additions. We compared the accuracy of data elements across versions, transcript length, and data categories. Additionally, we assessed note quality using the Physician Documentation Quality Instrument (PDQI) scoring system. RESULTS: Although ChatGPT-4 consistently generated SOAP-style notes, there were, on average, 23.6 errors per clinical case, with errors of omission (86%) being the most common, followed by addition errors (10.5%) and inclusion of incorrect facts (3.2%). There was significant variance between replicates of the same case, with only 52.9% of data elements reported correctly across all 3 replicates. The accuracy of data elements varied across cases, with the highest accuracy observed in the "Objective" section. Consequently, the measure of note quality, assessed by PDQI, demonstrated intra- and intercase variance. Finally, the accuracy of ChatGPT-4 was inversely correlated to both the transcript length (P=.05) and the number of scorable data elements (P=.05). CONCLUSIONS: Our study reveals substantial variability in errors, accuracy, and note quality generated by ChatGPT-4. Errors were not limited to specific sections, and the inconsistency in error types across replicates complicated predictability. Transcript length and data complexity were inversely correlated with note accuracy, raising concerns about the model's effectiveness in handling complex medical cases. The quality and reliability of clinical notes produced by ChatGPT-4 do not meet the standards required for clinical use. Although AI holds promise in health care, caution should be exercised before widespread adoption. Further research is needed to address accuracy, variability, and potential errors. ChatGPT-4, while valuable in various applications, should not be considered a safe alternative to human-generated clinical documentation at this time.

Using the Electronic Medical Record to Address Code Status Documentation: A Quality Improvement Project.

ABSTRACT: Code status (CS) is often overlooked while admitting patients to the hospital. This is important for patients with end-stage disease. This quality improvement project investigated whether a CS pop-up alert in the electronic medical record, combined with provider education, improved addressing CS. The project consisted of a baseline chart review, implementation of the alert and physician education, and a postintervention chart review. We reviewed 1828 charts at baseline and 1,775 at postintervention. From univariable analysis, there were improvements in addressing CS, being full code, cardiopulmonary resuscitation, intubation, use of vasopressors, and cardioversion technique categories (all p < .001). Documentation of do not resuscitate did not change. From logistic regression, after controlling for age, race, end-stage liver disease, stroke, cancer, hospital unit, and sepsis, patients in the postintervention period were two times more likely to have CS addressed (odds ratio [OR] = 2.04, p < .001). There was a significant improvement in CS documentation from our interventions.

The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden.

INTRODUCTION: Theoretically, the added value of electronic health records (EHRs) is extensive. Reusable data capture in EHRs could lead to major improvements in quality measurement, scientific research, and decision support. To achieve these goals, structured and standardized recording of healthcare data is a prerequisite. However, time spent on EHRs by physicians is already high. This study evaluated the effect of implementing an EHR embedded care pathway with structured data recording on the EHR burden of physicians. MATERIALS AND METHODS: Before and six months after implementation, consultations were recorded and analyzed with video-analytic software. Main outcome measures were time spent on specific tasks within the EHR, total consultation duration, and usability indicators such as required mouse clicks and keystrokes. Additionally, a validated questionnaire was completed twice to evaluate changes in physician perception of EHR system factors and documentation process factors. RESULTS: Total EHR time in initial oncology consultations was significantly reduced by 3.7 min, a 27 % decrease. In contrast, although a decrease of 13 % in consultation duration was observed, no significant effect on EHR time was found in follow-up consultations. Additionally, perceptions of physicians regarding the EHR and documentation improved significantly. DISCUSSION: Our results have shown that it is possible to achieve structured data capture while simultaneously reducing the EHR burden, which is a decisive factor in end-user acceptance of documentation systems. Proper alignment of structured documentation with workflows is critical for success. CONCLUSION: Implementing an EHR embedded care pathway with structured documentation led to decreased EHR burden.

Structured and unstructured social risk factor documentation in the electronic health record underestimates patients' self-reported risks.

OBJECTIVES: National attention has focused on increasing clinicians' responsiveness to the social determinants of health, for example, food security. A key step toward designing responsive interventions includes ensuring that information about patients' social circumstances is captured in the electronic health record (EHR). While prior work has assessed levels of EHR "social risk" documentation, the extent to which documentation represents the true prevalence of social risk is unknown. While no gold standard exists to definitively characterize social risks in clinical populations, here we used the best available proxy: social risks reported by patient survey. MATERIALS AND METHODS: We compared survey results to respondents' EHR social risk documentation (clinical free-text notes and International Statistical Classification of Diseases and Related Health Problems [ICD-10] codes). RESULTS: Surveys indicated much higher rates of social risk (8.2%-40.9%) than found in structured (0%-2.0%) or unstructured (0%-0.2%) documentation. DISCUSSION: Ideally, new care standards that include incentives to screen for social risk will increase the use of documentation tools and clinical teams' awareness of and interventions related to social adversity, while balancing potential screening and documentation burden on clinicians and patients. CONCLUSION: EHR documentation of social risk factors currently underestimates their prevalence.

Improving anthropometric measurements in hospitalized children: A quality-improvement project.

BACKGROUND: The objective of this quality-improvement project was to increase documentation rates of anthropometrics (measured weight, length/height, and body mass index [BMI], which are critical to identify patients at malnutrition (undernutrition) risk) from <50% to 80% within 24 hours of hospital admission for pediatric patients. METHODS: Multidisciplinary champion teams on surgical, cardiac, and intensive care (ICU) pilot units were established to identify and iteratively test interventions addressing barriers to documentation from May 2016 to June 2018. Percentage of patients with documented anthropometrics <24 h of admission was assessed monthly by statistical process control methodology. Percentage of patients at malnutrition (undernutrition) risk by anthropometrics was compared by χ2 for 4 months before and after intervention. RESULTS: Anthropometric documentation rates significantly increased (P < 0.001 for all): BMI, from 11% to 89% (surgical), 33% to 57% (cardiac), and 16% to 51% (ICU); measured weight, from 24% to 88% (surgical), 69% to 83% (cardiac), and 51% to 67% (ICU); and length/height, from 12% to 89% (surgical), 38% to 57% (cardiac), and 26% to 63% (ICU). Improvement hospital-wide was observed (BMI, 42% to 70%, P < 0.001) with formal dissemination tactics. For pilot units, moderate/severe malnutrition (undernutrition) rates tripled (1.2% [24 of 2081] to 3.4% [81 of 2374], P < 0.001). CONCLUSION: Documentation of anthropometrics on admission substantially improved after establishing multidisciplinary champion teams. Goal rate (80%) was achieved within 26 months for all anthropometrics in the surgical unit and for weight in the cardiac unit. Improved documentation rates led to significant increase in identification of patients at malnutrition (undernutrition) risk.

Enhancing operative documentation of emergency laparotomy: a systematic review and development of a synoptic reporting template.

INTRODUCTION: Currently, operative reports are narrative and often handwritten, making interpretation difficult and potentially omitting key steps of the procedure. This study undertook a systematic review to determine the current availability of synoptic operative reporting and develop a synoptic operative record template for emergency laparotomy (EL). METHODS: A PROSPERO registered study from January 1st, 2012, to December 31st, 2022, was conducted using PubMed, Scopus, and Web of Science databases in February 2023. KEYWORDS: emergency laparotomy AND operation notes OR operative notes OR documentation OR report OR pro forma OR narrative OR synoptic OR digital OR audio-visual. Studies on paediatric or pregnant patients, systematic reviews, meta-analyses, case reports, editorial comments, and letters were excluded. A synoptic operative record was designed to include key standards in the documentation, as suggested by the Colleges of Surgeons. RESULTS: The literature search yielded 4687 articles, and no relevant published articles were found. A detailed synoptic template was developed, which included 111 fields related to patient demographics, operative findings, interventions, and documentation of key variables associated with patient outcomes. 11 were text boxes, two were related to digital audio-visual uploads, and three facilitated the digital scoring/grading of findings. CONCLUSION: This systematic review identified a limited number of publications reporting synoptic operative reporting, and none related to emergency laparotomy. This novel operative template provides a platform for clear documentation of the surgery performed during emergency laparotomy, potentially facilitating data analysis, resident training, and research, in turn leading to a better understanding of patient outcomes.

Effect of a National VHA Medical Scribe Pilot on Provider Productivity, Wait Times, and Patient Satisfaction in Cardiology and Orthopedics.

BACKGROUND: Section 507 of the VA MISSION Act of 2018 mandated a 2-year pilot study of medical scribes in the Veterans Health Administration (VHA), with 12 VA Medical Centers randomly selected to receive scribes in their emergency departments or high wait time specialty clinics (cardiology and orthopedics). The pilot began on June 30, 2020, and ended on July 1, 2022. OBJECTIVE: Our objective was to evaluate the impact of medical scribes on provider productivity, wait times, and patient satisfaction in cardiology and orthopedics, as mandated by the MISSION Act. DESIGN: Cluster randomized trial, with intent-to-treat analysis using difference-in-differences regression. PATIENTS: Veterans using 18 included VA Medical Centers (12 intervention and 6 comparison sites). INTERVENTION: Randomization into MISSION 507 medical scribe pilot. MAIN MEASURES: Provider productivity, wait times, and patient satisfaction per clinic-pay period. KEY RESULTS: Randomization into the scribe pilot was associated with increases of 25.2 relative value units (RVUs) per full-time equivalent (FTE) (p < 0.001) and 8.5 visits per FTE (p = 0.002) in cardiology and increases of 17.3 RVUs per FTE (p = 0.001) and 12.5 visits per FTE (p = 0.001) in orthopedics. We found that the scribe pilot was associated with a decrease of 8.5 days in request to appointment day wait times (p < 0.001) in orthopedics, driven by a 5.7-day decrease in appointment made to appointment day wait times (p < 0.001), and observed no change in wait times in cardiology. We also observed no declines in patient satisfaction with randomization into the scribe pilot. CONCLUSIONS: Given the potential improvements in productivity and wait times with no change in patient satisfaction, our results suggest that scribes may be a useful tool to improve access to VHA care. However, participation in the pilot by sites and providers was voluntary, which could have implications for scalability and what effects could be expected if scribes were introduced to the care process without buy-in. Cost was not considered in this analysis but is an important factor for future implementation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04154462.

Improving documentation of blood product administration using a standardized electronic health record-based system: a single-institution experience.

OBJECTIVES: To improve documentation of blood product administration by assessing the completion status of blood transfusions. In this way, we can ensure compliance with the Association for the Advancement of Blood & Biotherapies standards and facilitate investigation of potential blood transfusion reactions. METHODS: This before-and-after study includes the implementation of an electronic health record (EHR)-based, standardized protocol for documenting the completion of blood product administration. Twenty-four months of retrospective data (January-December 2021) and prospective data (January-December 2022) were collected. Meetings were held before the intervention. Ongoing daily, weekly, and monthly reports were prepared, and targeted education to deficient areas as well as spot in-person audits by the blood bank residents were conducted. RESULTS: During 2022, 8,342 blood products were transfused, of which 6,358 blood product administrations were documented. The overall percentage of completed transfusion order documentation improved from 35.54% (units/units) in 2021 to 76.22% (units/units) in 2022. CONCLUSIONS: Interdisciplinary collaborative efforts helped produce quality audits to improve the documentation of blood product transfusion through a standardized and customized EHR-based blood product administration module.

Observational analysis of documentation burden and data duplication in trauma patient pathways at a major trauma centre.

OBJECTIVES: Trauma patients require extensive documentation across paper and electronic modalities. The objectives of this study were (1) to assess the documentation burden for trauma patients by contrasting entries against predetermined key information elements, dubbed 'data entry points' (DEPs) of a thorough trauma clerking, and by evaluating completeness of entries; and (2) to assess documentation for repetition using a Likert scale and through identification of copied data elements. METHODS: A 1-month retrospective observational pilot study analysing documentation within the first 24 hours of a patient's presentation to a major trauma centre. Documentation was analysed across three platforms: paper notes, electronic health record (EHR) and patient organisation system (POS) entries. Entries were assessed against predetermined DEPs, for completeness, for directly copied elements and for uniqueness (using a Likert scale). RESULTS: 30 patients were identified. The mean completeness of a clerking on paper, EHR and POS was 79%, 70% and 62%, respectively. Mean completeness decreased temporally down to 41% by the second ward round. The mean proportion of documented DEPs on paper, EHR and POS entries was 47%, 49% and 35%, respectively. 77% of POS entries contained copied elements, with a low level of uniqueness of 1.3/5. DISCUSSION: Our results show evidence of high documentation burden with unnecessary repetition of data entry in the management of trauma patients. CONCLUSION: This pilot study of trauma patient documentation demonstrates multiple inefficiencies and a marked administrative burden, further compounded by the need to document across multiple platforms, which may lead to eventual patient safety concerns.

Medical Scribes: Symptom or Cause of Impeded Evolution of a Transformative Artificial Intelligence in the Electronic Health Record?

Studies have quantified various specific benefits related to the use of medical scribes, finding physician workflow and productivity improvements, with some demonstrating marginal value or detrimental impact. However, this evidence base misses a critical underlying issue with the expanding number of physicians using medical scribes routinely. There are an estimated 28,000-33,000 peer reviewed biomedical journals worldwide, currently publishing an estimated 1.8-2 million scientific articles every year. Over a typical physician's career from the 11-13 years of undergraduate through medical school and specialty/residency training as well as 34-36 practice/care delivery years beyond (to age 65), this yields 84-94+ million peer reviewed journal articles that are published in the global medical literature and to be potentially consumed/ considered over a roughly 47-year career. Clinical trial results in various stages of peer review, with 409,000 clinical trials registered in 2022, augment this massive volume of new clinical and bioscience information that clinicians might utilize to advance their care delivery by over 19 million bioscientific reports over a lifetime of training and care delivery. Inclusive of clinical trial reports and peer reviewed journal articles, a physician might derive clinical care value from an expanding career-long evidence base of 103-113+ million scientific communications. Even if only 0.1 percent of the global output of biomedical science has clinical relevance to a highly specialized physician, the narrowed career-long total remains a staggering 103,000 journal publications and clinical trial reports. For physicians with a more general and diverse clinical focus such as family medicine, emergency medicine physicians, and hospitalists, if 1 percent of newly published evidence-based literature is pertinent, the total career-long estimate is over 1 million journal articles and clinical trials to be reviewed and clinically integrated. As a result, a challenging issue created by the increasing role of medical scribes is not just evaluating their value (or lack thereof) for practicing physicians in their workflows and productivity. Rather it concerns the impact that medical scribes may be having by decoupling physicians from the iterative technological and cognitive progression of the electronic health record (EHR) and its evolving artificial intelligence (AI), which can facilitate the integration of the year-over-year proliferation of clinically pertinent new scientific evidence into a physician's practice of medicine. This commentary addresses the challenge to the evolution of the AI of the EHR posed by physicians' increasing use of and reliance upon medical scribes, and highlights how medical scribes may also, inadvertently, isolate and insulate physicians from their essential role in continuous refinement and advancement of EHR AI. Consideration is given to the broader challenge of inadequate focus and resources needed across sectors to drive the evolution of AI in the EHR, and associated health informatics research, as a US national priority.