Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

Artificial intelligence-enhanced patient evaluation: bridging art and science

The advent of digital health and artificial intelligence (AI) has promised to revolutionize clinical care, but real-world patient evaluation has yet to witness transformative changes. As history taking and physical examination continue to rely on long-established practices, a growing pipeline of AI-enhanced digital tools may soon augment the traditional clinical encounter into a data-driven process. This article presents an evidence-backed vision of how promising AI applications may enhance traditional practices, streamlining tedious tasks while elevating diverse data sources, including AI-enabled stethoscopes, cameras, and wearable sensors, to platforms for personalized medicine and efficient care delivery. Through the lens of traditional patient evaluation, we illustrate how digital technologies may soon be interwoven into routine clinical workflows, introducing a novel paradigm of longitudinal monitoring. Finally, we provide a skeptic's view on the practical, ethical, and regulatory challenges that limit the uptake of such technologies.

Agreement between patient-reported and clinically documented symptoms of acute myeloid leukemia: Study protocol

AIM

To describe our methods to compare patient-reported symptoms of acute myeloid leukemia and the corresponding documentation by healthcare providers in the electronic health record.

BACKGROUND

Patients with acute myeloid leukemia experience many distressing symptoms, particularly related to chemotherapy. The timely recognition and provision of evidence-based interventions to manage these symptoms can improve outcomes. However, lack of standardized formatting for symptom documentation within electronic health records leads to challenges for clinicians when accessing and comprehending patients' symptom information, as it primarily exists in narrative forms in various parts of the electronic health record. This variability raises concerns about over- or under-reporting of symptoms. Consistency between patient-reported symptoms and clinician's symptom documentation is important for patient-centered symptom management, but little is known about the degree of agreement between patient reports and their documentation. This is a detailed description of the study's methodology, procedures and design to determine how patient-reported symptoms are similar or different from symptoms documented in electronic health records by clinicians.

DESIGN

Exploratory, descriptive study.

METHODS

Forty symptoms will be assessed as patient-reported outcomes using the modified version of the Memorial Symptom Assessment Scale. The research team will annotate symptoms from the electronic health record (clinical notes and flowsheets) corresponding to the 40 symptoms. The degree of agreement between patient reports and electronic health record documentation will be analyzed using positive and negative agreement, kappa statistics and McNemar's test.

CONCLUSION

We present innovative methods to comprehensively compare the symptoms reported by acute myeloid leukemia patients with all available electronic health record documentation, including clinical notes and flowsheets, providing insights into symptom reporting in clinical practice.

IMPACT

Findings from this study will provide foundational understanding and compelling evidence, suggesting the need for more thorough efforts to assess patients' symptoms. Methods presented in this paper are applicable to other symptom-intensive diseases.

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing

OBJECTIVE

Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients.

MATERIALS AND METHODS

We trained logistic regression models using note metadata and a Term Frequency Inverse Document Frequency (TF-IDF) text representation. We evaluated performance with precision, recall, F1, AUC, and a clinical qualitative assessment.

RESULTS

The metadata only model achieved an AUC 0.930 and the metadata and TF-IDF model an AUC 0.937. Qualitative assessment revealed a need for better text representation and to further customize predictions for the user.

DISCUSSION

Our model effectively surfaces the top 10 notes a clinician wants to review when seeing an oncology patient. Further studies can characterize different types of clinician users and better tailor the task for different care settings.

CONCLUSION

EHR audit logs can provide important relevance data for training ML models that assist with note-writing in the oncology setting.

A Qualitative Study of Physicians' Views on the Reuse of Electronic Health Record Data for Secondary Analysis

Electronic health records (EHRs) have become ubiquitous in clinical practice. Given the rich biomedical data captured for a large panel of patients, secondary analysis of these data for health research is also commonplace. Yet, there are many caveats to EHR data that the researchers must be aware of, such as the accuracy of and motive for documentation, and the reason for patients' visits to the clinic. The clinician-the author of the documentation-is thus central to the correct interpretation of EHR data for research purposes. In this study, I interviewed 11 physicians in various clinical specialties to bring attention to their view on the validity of research using EHR data. Qualitative, in-depth, one-on-one interviews were conducted with practicing physicians in inpatient and outpatient medicine. Content analysis using a data-driven, inductive approach to identify themes related to challenges and opportunities in the reuse of EHR data for secondary analysis generated seven themes. Themes that reflected challenges of EHRs for research included (1) audience, (2) accuracy of data, (3) availability of data, (4) documentation practices, and (5) representativeness. Themes that reflected opportunities of EHRs for research included (6) endorsement and (7) enablers. The greatest perceived barriers reflected the intended audience of the EHR, the interpretation and meaning of the data, and the quality of the data for research purposes. Physicians generally expressed more perceived challenges than opportunities in the reuse of EHR data for research purposes; however, they remained optimistic.

Efficient healthcare with large language models: optimizing clinical workflow and enhancing patient care

PURPOSE

This article explores the potential of large language models (LLMs) to automate administrative tasks in healthcare, alleviating the burden on clinicians caused by electronic medical records.

POTENTIAL

LLMs offer opportunities in clinical documentation, prior authorization, patient education, and access to care. They can personalize patient scheduling, improve documentation accuracy, streamline insurance prior authorization, increase patient engagement, and address barriers to healthcare access.

CAUTION

However, integrating LLMs requires careful attention to security and privacy concerns, protecting patient data, and complying with regulations like the Health Insurance Portability and Accountability Act (HIPAA). It is crucial to acknowledge that LLMs should supplement, not replace, the human connection and care provided by healthcare professionals.

CONCLUSION

By prudently utilizing LLMs alongside human expertise, healthcare organizations can improve patient care and outcomes. Implementation should be approached with caution and consideration to ensure the safe and effective use of LLMs in the clinical setting.

Utilization and efficacy of DotPhrases in the electronic medical record for improving physician documentation

Clinical documentation of patient visits has changed over the last 20 years, with the increasing use of electronic records causing a seismic shift in how notes are taken. Electronic note-taking aims at reducing the time taken to document a visit, and the introduction of dot phrases, or DotPhrases, in electronic medical records is a step toward reducing the time required to update patients' charts, which might allow doctors to spend more time with their patients. DotPhrases, abbreviated phrases used in the electronic medical record, help in the simplification of note-taking and the standardization of notes. They also allow for a more comprehensive note from physicians and ensure that no information is undocumented. On the contrary, however, excessive usage of DotPhrases can lead to an excessively long and cumbersome note. This can overwhelm physicians and lead to them missing crucial information that is buried somewhere in the notes. Although there is ample research studying the benefits of DotPhrases, adequate research must also be carried out to understand their shortcomings and disadvantages. This article aims to shed some light on use of DotPhrases and to outline their advantages and disadvantages affecting patient management and care.

Toward Alleviating Clinician Documentation Burden: A Scoping Review of Burden Reduction Efforts

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.

OBJECTIVES

 The objective of this review was to identify and comprehensively summarize the state of the science related to documentation burden reduction efforts.

METHODS

 Following Joanna Briggs Institute Manual for Evidence Synthesis and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, we conducted a comprehensive search of multiple databases, including PubMed, Medline, Embase, CINAHL Complete, Scopus, and Web of Science. Additionally, we searched gray literature and used Google Scholar to ensure a thorough review. Two reviewers independently screened titles and abstracts, followed by full-text review, with a third reviewer resolving any discrepancies. Data extraction was performed and a table of evidence was created.

RESULTS

 A total of 34 articles were included in the review, published between 2016 and 2022, with a majority focusing on the United States. The efforts described can be categorized into medical scribes, workflow improvements, educational interventions, user-driven approaches, technology-based solutions, combination approaches, and other strategies. The outcomes of these efforts often resulted in improvements in documentation time, workflow efficiency, provider satisfaction, and patient interactions.

CONCLUSION

 This scoping review provides a comprehensive summary of health system documentation burden reduction efforts. The positive outcomes reported in the literature emphasize the potential effectiveness of these efforts. However, more research is needed to identify universally applicable best practices, and considerations should be given to the transfer of burden among members of the health care team, quality of education, clinician involvement, and evaluation methods.

Exploring the Impact of In Basket Metrics on the Adoption of a New Electronic Health Record System Among Specialists in a Tertiary Hospital in Alberta: Descriptive Study

BACKGROUND

Health care organizations implement electronic health record (EHR) systems with the expectation of improved patient care and enhanced provider performance. However, while these technologies hold the potential to create improved care and system efficiencies, they can also lead to unintended negative consequences, such as patient safety issues, communication problems, and provider burnout.

OBJECTIVE

This study aims to document metrics related to the In Basket communication hub (time in In Basket per day, time in In Basket per appointment, In Basket messages received per day, and turnaround time) of the EHR system implemented by Alberta Health Services, the province-wide health delivery system called Connect Care (Epic Systems). The objective was to identify how a newly implemented EHR system was used, the timing of its use, and the duration of use specifically related to In Basket activities.

METHODS

A descriptive study was conducted. Due to the diversity of specialties, the providers were grouped into medical and surgical based on previous similar studies. The participants were further subgrouped based on their self-reported clinical full-time equivalent (FTE ) measure. This resulted in 3 subgroups for analysis: medical FTE <0.5, medical FTE >0.5, and surgical (all of whom reported FTE >0.5). The analysis was limited to outpatient clinical interactions and explicitly excluded inpatient activities.

RESULTS

A total of 72 participants from 19 different specialties enrolled in this study. The providers had, on average, 8.31 appointments per day during the reporting periods. The providers received, on average, 21.93 messages per day, and they spent 7.61 minutes on average in the time in In Basket per day metric and 1.84 minutes on average in the time in In Basket per appointment metric. The time for the providers to mark messages as done (turnaround time) was on average 11.45 days during the reporting period. Although the surgical group had, on average, approximately twice as many appointments per scheduled day, they spent considerably less connected time (based on almost all time metrics) than the medical group. However, the surgical group took much longer than the medical group to mark messages as done (turnaround time).

CONCLUSIONS

We observed a range of patterns with no consistent direction. There does not seem to be evidence of a "learning curve," which would have shown a consistent reduction in time spent on the system over time due to familiarity and experience. While this study does not show how the included metrics could be used as predictors of providers' satisfaction or feelings of burnout, the use trends could be used to start discussions about future Canadian studies needed in this area.

Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review

The cognitive load theory suggests that completing a task relies on the interplay between sensory input, working memory, and long-term memory. Cognitive overload occurs when the working memory's limited capacity is exceeded due to excessive information processing. In health care, clinicians face increasing cognitive load as the complexity of patient care has risen, leading to potential burnout. Electronic health records (EHRs) have become a common feature in modern health care, offering improved access to data and the ability to provide better patient care. They have been added to the electronic ecosystem alongside emails and other resources, such as guidelines and literature searches. Concerns have arisen in recent years that despite many benefits, the use of EHRs may lead to cognitive overload, which can impact the performance and well-being of clinicians. We aimed to review the impact of EHR use on cognitive load and how it correlates with physician burnout. Additionally, we wanted to identify potential strategies recommended in the literature that could be implemented to decrease the cognitive burden associated with the use of EHRs, with the goal of reducing clinician burnout. Using a comprehensive literature review on the topic, we have explored the link between EHR use, cognitive load, and burnout among health care professionals. We have also noted key factors that can help reduce EHR-related cognitive load, which may help reduce clinician burnout. The research findings suggest that inadequate efforts to present large amounts of clinical data to users in a manner that allows the user to control the cognitive burden in the EHR and the complexity of the user interfaces, thus adding more "work" to tasks, can lead to cognitive overload and burnout; this calls for strategies to mitigate these effects. Several factors, such as the presentation of information in the EHR, the specialty, the health care setting, and the time spent completing documentation and navigating systems, can contribute to this excess cognitive load and result in burnout. Potential strategies to mitigate this might include improving user interfaces, streamlining information, and reducing documentation burden requirements for clinicians. New technologies may facilitate these strategies. The review highlights the importance of addressing cognitive overload as one of the unintended consequences of EHR adoption and potential strategies for mitigation, identifying gaps in the current literature that require further exploration.

Impacts of an Acute Care Telenursing Program on Discharge, Patient Experience, and Nursing Experience: Retrospective Cohort Comparison Study

BACKGROUND

Despite widespread growth of televisits and telemedicine, it is unclear how telenursing could be applied to augment nurse labor and support nursing.

OBJECTIVE

This study evaluated a large-scale acute care telenurse (ACTN) program to support web-based admission and discharge processes for hospitalized patients.

METHODS

A retrospective, observational cohort comparison was performed in a large academic hospital system (approximately 2100 beds) in Houston, Texas, comparing patients in our pilot units for the ACTN program (telenursing cohort) between June 15, 2022, and December 31, 2022, with patients who did not participate (nontelenursing cohort) in the same units and timeframe. We used a case mix index analysis to confirm comparable patient cases between groups. The outcomes investigated were patient experience, measured using the Hospital Consumer Assessment of Health Care Providers and Systems (HCAHCPS) survey; nursing experience, measured by a web-based questionnaire with quantitative multiple-choice and qualitative open-ended questions; time of discharge during the day (from electronic health record data); and duration of discharge education processes.

RESULTS

Case mix index analysis found no significant case differences between cohorts (P=.75). For the first 4 units that rolled out in phase 1, all units experienced improvement in at least 4 and up to 7 HCAHCPS domains. Scores for "communication with doctors" and "would recommend hospital" were improved significantly (P=.03 and P=.04, respectively) in 1 unit in phase 1. The impact of telenursing in phases 2 and 3 was mixed. However, "communication with doctors" was significantly improved in 2 units (P=.049 and P=.002), and the overall rating of the hospital and the "would recommend hospital" scores were significantly improved in 1 unit (P=.02 and P=04, respectively). Of 289 nurses who were invited to participate in the survey, 106 completed the nursing experience survey (response rate 106/289, 36.7%). Of the 106 nurses, 101 (95.3%) indicated that the ACTN program was very helpful or somewhat helpful to them as bedside nurses. The only noticeable difference between the telenursing and nontelenursing cohorts for the time of day discharge was a shift in the volume of patients discharged before 2 PM compared to those discharged after 2 PM at a hospital-wide level. The ACTN admissions averaged 12 minutes and 6 seconds (SD 7 min and 29 s), and the discharges averaged 14 minutes and 51 seconds (SD 8 min and 10 s). The average duration for ACTN calls was 13 minutes and 17 seconds (SD 7 min and 52 s). Traditional cohort standard practice (nontelenursing cohort) of a bedside nurse engaging in discharge and admission processes was 45 minutes, consistent with our preimplementation time study.

CONCLUSIONS

This study shows that ACTN programs are feasible and associated with improved outcomes for patient and nursing experience and reducing time allocated to admission and discharge education.

Cumulated time to chart closure: a novel electronic health record-derived metric associated with clinician burnout

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. Established EHR use measures including daily total time in the EHR (EHR-Time8), time in the EHR outside scheduled hours, work outside of work (WOW8), and time spent on inbox (IB-Time8) were calculated. We examined the relationship between CTCC, EHR use metrics, and burnout using descriptive statistics and adjusted logistic regression models.

Results

We included data from 305 attendings, encompassing 242 432 ambulatory encounters (2021). Among them, 42% (128 physicians) experienced burnout. The median CTCC for all clinicians was 32.5 h. Unadjusted analyses revealed significant associations between CTCC, WOW8, IB-Time8, and burnout. In a final adjusted model, only CTCC remained statistically significant with an odds ratio estimate of 1.42 (95% CI, 1.00-2.01).

Discussion

These results suggest that CTCC is predictive of burnout and that purely measuring duration of interaction with the EHR itself is not sufficient to capture burnout.

Conclusion

Workload burden as manifested by average CTCC has the potential to be a practical, quantifiable measure that will allow for identification of clinicians at risk of burnout and to assess the success of interventions designed to address burnout.

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.

Large language models: a primer and gastroenterology applications

Over the past year, the emergence of state-of-the-art large language models (LLMs) in tools like ChatGPT has ushered in a rapid acceleration in artificial intelligence (AI) innovation. These powerful AI models can generate tailored and high-quality text responses to instructions and questions without the need for labor-intensive task-specific training data or complex software engineering. As the technology continues to mature, LLMs hold immense potential for transforming clinical workflows, enhancing patient outcomes, improving medical education, and optimizing medical research. In this review, we provide a practical discussion of LLMs, tailored to gastroenterologists. We highlight the technical foundations of LLMs, emphasizing their key strengths and limitations as well as how to interact with them safely and effectively. We discuss some potential LLM use cases for clinical gastroenterology practice, education, and research. Finally, we review critical barriers to implementation and ongoing work to address these issues. This review aims to equip gastroenterologists with a foundational understanding of LLMs to facilitate a more active clinician role in the development and implementation of this rapidly emerging technology.

Effectiveness of Doctor Clerks Supporting Physicians' Work in Japan: A Systematic Review

The burgeoning administrative workload on physicians in Japan's healthcare system has necessitated innovative approaches to optimize clinical care. Integrating doctor clerks, tasked with administrative and clerical duties, has emerged as a potential solution to alleviate this burden. This systematic review aims to evaluate the effectiveness of doctor clerks in improving physicians' working conditions and patient care quality. A comprehensive literature search was conducted using Ichushi Web and Google Scholar from January 2000 to September 2023. Data were extracted on publication year, study setting, department focus, work scope, and outcomes of doctor clerk implementation. The search identified 3570 studies, with 17 meeting the inclusion criteria. Most studies were performed in general hospitals with 76.5% (13/17). The studies regarding university hospitals were 17.6% (3/17). Only one study was performed in a community hospital with 5.9% (1/17). More than half of doctor clerks worked not explicitly allocated to one department and did their work not specific to one department with 52.9% (9/17). Three studies report that doctor clerks collaborate with orthopedic surgeons. Two studies report that doctor clerks collaborate with emergency medicine physicians. Each study reports that doctor clerks collaborate with respiratory or general medicine. The most frequent is document support, with 94.1% (16/17). The second most frequent working content is consultation support, with 47.1% (8/17). The third most frequently working content is ordering support, with 23.5% (4/17). Call response, secretary work, education support, research support, conference support, and other professional support are included, each with 5.9% (1/17). Regarding clinical outcomes, five studies assessed a reduction in physician paperwork time (29.4%). Four studies assessed the frequency of the contents of doctor clerks' work (23.5%). Four studies assessed the positive perception of physicians (23.5%). Four studies assessed the amount of the reduction in physicians' overtime work (23.5%). Three studies assess the amount of the reduction in hospital costs (17.6%). One study assessed part-time physicians' fatigue reduction (5.9%). Each study assessed the quality of patient care, such as doctor's clerk education for standardization, increase in the number of patients accepted, reduction in medical incidents, decrease in patient waiting time, and primary to tertiary prevention. Introducing doctor clerks in Japan's healthcare system shows promise in enhancing physicians' working conditions and potentially improving patient care. However, conclusive evidence on the impact on patient care quality necessitates further investigation, serving as a foundation for future policy and healthcare system optimization.

Barriers to and facilitators of successful implementation of a palliative approach to care in primary care practices: a mixed methods study

OBJECTIVE

Integrating a palliative approach to care into primary care is an emerging evidence-based practice. Despite the evidence, this type of care has not been widely adopted into primary care settings. The objective of this study was to examine the barriers to and facilitators of successful implementation of a palliative approach to care in primary care practices by applying an implementation science framework.

DESIGN

This convergent mixed methods study analysed semistructured interviews and expression of interest forms to evaluate the implementation of a protocol, linked to implementation strategies, for a palliative approach to care called Early Palliation through Integrated Care (EPIC) in three primary care practices. This study assessed barriers to and facilitators of implementation of EPIC and was guided by the Consolidated Framework for Implementation Research (CFIR). A framework analysis approach was used during the study to determine the applicability of CFIR constructs and domains.

SETTING

Primary care practices in Canada. Interviews were conducted between September 2020 and November 2021.

PARTICIPANTS

10 individuals were interviewed, who were involved in implementing EPIC. Three individuals from each practice were reinterviewed to clarify emerging themes.

RESULTS

Overall, there were implementation barriers at multiple levels that caused some practices to struggle. However, barriers were mitigated when practices had the following facilitators: (1) a high level of intra-practice collaboration, (2) established practices with organisational structures that enhanced communications, (3) effective leveraging of EPIC project supports to transition care, (4) perceptions that EPIC was an opportunity to make a long-term change in their approach to care as opposed to a limited term project and (5) strong practice champions.

CONCLUSIONS

Future implementation work should consider assessing facilitators identified in our results to better gauge primary care pre-implementation readiness. In addition, providing primary care practices with support to help offset the additional work of implementing innovations and networking opportunities where they can share strategies may improve implementation success.

A Computational Framework to Evaluate Emergency Department Clinician Task Switching in the Electronic Health Record Using Event Logs

Workflow fragmentation, defined as task switching, may be one proxy to quantify electronic health record (EHR) documentation burden in the emergency department (ED). Few measures have been operationalized to evaluate task switching at scale. Theoretically grounded in the time-based resource-sharing model (TBRSM) which conceives task switching as proportional to the cognitive load experienced, we describe the functional relationship between cognitive load and the time and effort constructs previously applied for measuring documentation burden. We present a computational framework, COMBINE, to evaluate multilevel task switching in the ED using EHR event logs. Based on this framework, we conducted a descriptive analysis on task switching among 63 full-time ED physicians from one ED site using EHR event logs extracted between April-June 2021 (n=2,068,605 events) which were matched to scheduled shifts (n=952). On average, we found a high volume of event-level (185.8±75.3/hr) and within-(6.6±1.7/chart) and between-patient chart (27.5±23.6/hr) switching per shift worked.

Taking Action Against Clinician Burnout Through Reducing the Documentation Burden With an Operating Room Supply Scanning Approach

Documenting surgical supply items in the operating room can be a burdensome task for circulating nurses because of manual input within the electronic medical record. This can lead to documentation fatigue and contribute to nursing burnout. The aim of this quality improvement project was to design and implement a supply item scanning process and evaluate the effect on intraoperative documentation completion time, room turnover time, picklist documentation accuracy, nurse satisfaction, and burnout. The sample included nine acute care hospitals throughout the United States, with 189 total circulating nurses and 31 718 procedures occurring during the study timeframe of 8 months. Results indicated that nurses were able to complete documentation on average 37.33 minutes sooner, and the operating room turnover time decreased by 1.88 minutes. Although nurses reported that their perceived picklist documentation accuracy did not improve, and the presence of new scanning technology did not influence their hospital employment decision, subjective feedback was mostly positive, with most responses citing the helpfulness of scanning for documentation. This study shows that an interdisciplinary team can effectively work to optimize documentation efficiency and performance improvement using a scanning intervention. Lessons learned through this process can translate into optimizations elsewhere in the electronic medical record.

Electronic Health Record Usage Patterns Across Surgical Subspecialties

OBJECTIVES

This study aimed to utilize metrics from physician action logs to analyze surgeon clinical, volume, electronic health record (EHR) efficiency, EHR proficiency, and workload outside scheduled time as impacted by physician characteristics such as years of experience, gender, subspecialty, academic title, and administrative title.

METHODS

We selected 30 metrics from Epic Signal, an analytic tool in Epic that extracts metrics related to clinician documentation. Metrics measuring appointments, messages, and scheduled hours per day were used as a correlate for volume. EHR efficiency, and proficiency were measured by scores built into Epic Signal. Metrics measuring time spent in the EHR outside working hours were used as a correlate for documentation burden. We analyzed these metrics among surgeons at our institution across 4 months and correlated them with physician characteristics.

RESULTS

Analysis of 133 surgeons showed that, when stratified by gender, female surgeons had significantly higher EHR metrics for time per day, time per appointment, and documentation burden, and significantly lower EHR metrics for efficiency when compared to male surgeons. When stratified by experience, surgeons with 0 to 5 years of experience had significantly lower EHR metrics for volume, time per day, efficiency, and proficiency when compared to surgeons with 6 to 10 and more than 10 years of experience. On multivariate analysis, having over 10 years of experience was an independent predictor of more appointments per day, greater proficiency, and spending less time per completed message. Female gender was an independent predictor of spending more time in notes per appointment and time spent in the EHR outside working hours.

CONCLUSION

The burden associated with volume, proficiency, efficiency, and workload outside scheduled time related to EHR use varies by gender and years of experience in our cohort of surgeons. Evaluation of physician action logs could help identify those at higher risk of burnout due to burdensome medical documentation.

Interventions to Reduce Electronic Health Record-Related Burnout: A Systematic Review

BACKGROUND

Electronic health records are a significant contributing factor in clinician burnout, which negatively impacts patient care.

OBJECTIVES

To identify and appraise published solutions that aim to reduce EHR-related burnout in clinicians.

METHODS

A literature search strategy was developed following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Six databases were searched for articles published between January 1950 and March 2023. The inclusion criteria were peer-reviewed, full-text, English language articles that described interventions targeting EHR-related burnout in any type of clinician, with reported outcomes related to burnout, wellness, EHR satisfaction, or documentation workload. Studies describing interventions without an explicit focus on reducing burnout or enhancing EHR-related satisfaction were excluded.

RESULTS

We identified 44 articles describing interventions to reduce EHR-related burnout. These interventions included the use of scribes, EHR training, and EHR modifications. These interventions were generally well received by the clinicians and patients, with subjective improvements in documentation time and EHR satisfaction, although objective data were limited.

CONCLUSION

The findings of this review underscore the potential benefits of interventions to reduce EHR-related burnout as well as the need for further research with more robust study designs involving randomized trials, control groups, longer study durations, and validated, objective outcome measurements.

Development and Evaluation of a Digital Scribe: Conversation Summarization Pipeline for Emergency Department Counseling Sessions towards Reducing Documentation Burden

Objective

We present a proof-of-concept digital scribe system as an ED clinical conversation summarization pipeline and report its performance.

Materials and Methods

We use four pre-trained large language models to establish the digital scribe system: T5-small, T5-base, PEGASUS-PubMed, and BART-Large-CNN via zero-shot and fine-tuning approaches. Our dataset includes 100 referral conversations among ED clinicians and medical records. We report the ROUGE-1, ROUGE-2, and ROUGE-L to compare model performance. In addition, we annotated transcriptions to assess the quality of generated summaries.

Results

The fine-tuned BART-Large-CNN model demonstrates greater performance in summarization tasks with the highest ROUGE scores (F1ROUGE-1=0.49, F1ROUGE-2=0.23, F1ROUGE-L=0.35) scores. In contrast, PEGASUS-PubMed lags notably (F1ROUGE-1=0.28, F1ROUGE-2=0.11, F1ROUGE-L=0.22). BART-Large-CNN's performance decreases by more than 50% with the zero-shot approach. Annotations show that BART-Large-CNN performs 71.4% recall in identifying key information and a 67.7% accuracy rate.

Discussion

The BART-Large-CNN model demonstrates a high level of understanding of clinical dialogue structure, indicated by its performance with and without fine-tuning. Despite some instances of high recall, there is variability in the model's performance, particularly in achieving consistent correctness, suggesting room for refinement. The model's recall ability varies across different information categories.

Conclusion

The study provides evidence towards the potential of AI-assisted tools in reducing clinical documentation burden. Future work is suggested on expanding the research scope with larger language models, and comparative analysis to measure documentation efforts and time.

Correctly structured problem lists lead to better and faster clinical decision-making in electronic health records compared to non-curated problem lists: A single-blinded crossover randomized controlled trial

BACKGROUND

Correctly structured problem lists in electronic health records (EHRs) offer major benefits to patient care. Without structured lists, diagnosis information is often scatteredly documented in free text, which may contribute to errors and inefficient information retrieval. This study aims to assess whether EHRs with correctly structured problem lists result in better and faster clinical decision-making compared to non-curated problem lists.

METHODS

Two versions of two patient records (A and B) were created in an EHR training environment: one version included diagnosis information structured and coded on the problem list ("correctly structured problem list"), the other version had missing problem list diagnoses and diagnosis information partly documented in free text ("non-curated problem list"). In this single-blinded crossover randomized controlled trial, healthcare providers, who can prescribe medications, from two Dutch university medical center locations first evaluated a randomized version of patient A, then B. Participants were asked to motivate their answer to two medication prescription questions. One (test) question required information similarly presented in both record versions. The second (comparison) question required information documented on problem lists and/or in notes. The primary outcome measure was the correctness of the motivated answer to the comparison question. Secondary outcome measure was the time to answer and motivate both questions correctly.

RESULTS

As planned, 160 participants enrolled. Two were excluded for not meeting inclusion criteria. Correctly structured problem lists increased providers' ability to answer the comparison question correctly (56.3 % versus 33.5 %, McNemar odds ratio 2.80 (1.65-4.93) 95 %-CI). Median time to answer both questions correctly was significantly lower for EHRs with correctly structured problem lists (Wilcoxon-signed-rank test p = 0.00002, with incorrect answers coded equally at slowest time).

CONCLUSIONS

Correctly structured problem lists lead to better and faster clinical decision-making. Increased structured problem lists usage may be warranted for which implementation policies should be developed.

New Coding Guidelines Reduce Emergency Department Note Bloat But More Work Is Needed

STUDY OBJECTIVE

The length and redundancy of notes authored by clinicians has significantly increased, giving rise to the term "note bloat." We analyzed the impact of new coding guidelines and documentation best practices on the length of emergency department (ED) notes and the amount of time clinicians spent documenting.

METHODS

In a large, multisite health care delivery organization, we retrospectively evaluated the length of all ED provider notes and the amount of time clinicians spent documenting between February 2018 and June 2023. In January 2023, we implemented changes to the standardized note template to align with the new coding guidelines from the American Medical Association and the Centers for Medicare & Medicaid Services. The primary outcomes were the length of provider notes and the amount of time spent documenting.

RESULTS

Our study sample consisted of 1,679,762 ED provider notes. Six months after the intervention, the average note length decreased by 872 words (95% confidence interval 867 to 877 words), whereas the amount of time clinicians spent documenting did not change.

CONCLUSIONS

Embracing new guidelines and practices, we reduced the length of ED provider notes by 872 words. Despite this, the time clinicians spent documenting did not change significantly. We provide an early report of success in reducing note bloat in the ED to help guide future efforts to reduce overall documentation burden.

Venous Access: National Guideline and Registry Development (VANGUARD): Advancing Patient-Centered Venous Access Care Through the Development of a National Coordinated Registry Network

There are over 8 million central venous access devices inserted each year, many in patients with chronic conditions who rely on central access for life-preserving therapies. Central venous access device-related complications can be life-threatening and add tens of billions of dollars to health care costs, while their incidence is most likely grossly mis- or underreported by medical institutions. In this communication, we review the challenges that impair retention, exchange, and analysis of data necessary for a meaningful understanding of critical events and outcomes in this clinical domain. The difficulty is not only with data extraction and harmonization from electronic health records, national surveillance systems, or other health information repositories where data might be stored. The problem is that reliable and appropriate data are not recorded, or falsely recorded, at least in part because policy, payment, penalties, proprietary concerns, and workflow burdens discourage completeness and accuracy. We provide a roadmap for the development of health care information systems and infrastructure that address these challenges, framed within the context of research studies that build a framework of standardized terminology, decision support, data capture, and information exchange necessary for the task. This roadmap is embedded in a broader Coordinated Registry Network Learning Community, and facilitated by the Medical Device Epidemiology Network, a Public-Private Partnership sponsored by the US Food and Drug Administration, with the scope of advancing methods, national and international infrastructure, and partnerships needed for the evaluation of medical devices throughout their total life cycle.

Harnessing the Benefits of the Nutrition Care Process Quality Evaluation and Standardization Tool: A National Auditing Initiative to Improve Quality of Documentation

The Nutrition Care Process Quality Standardization and Evaluation Tool (NCP QUEST) is a validated audit instrument assessing the quality of NCP documentation by registered dietitian nutritionists. The present quality improvement project describes change in documentation quality as measured by NCP QUEST and word count of notes after a monthly national digital training provided to Veterans Affairs registered dietitian nutritionists. The training and adoption of NCP QUEST was voluntary. Facilities were recruited among those that had participated during the design and validation study of NCP QUEST. The NCP QUEST score was calculated and the word count was determined for 52 documentation notes (28 from NCP QUEST nonuser facilities and 24 from NCP QUEST user facilities) before and after training. The mean pretraining NCP QUEST score for notes from NCP QUEST nonuser facilities was 13.71 and 13.88 for NCP QUEST user facilities. The mean posttraining total NCP QUEST score for nonuser facilities was 14.00 and 17.65 for user facilities, with no improvement for the nonuser facilities (P = 0.69). A significant improvement was identified for the NCP QUEST user facilities (P ≤ 0.001). All facilities experienced a significant reduction in the word count of assessment notes (P = 0.04). Use of the electronic NCP Terminology website increased 123-fold and was sustained after the training. NCP QUEST users reported that the audit tool is useful. The NCP QUEST should be at the center of registered dietitian nutritionists' training and more strategic effort is needed to engage practitioners in the optimal application of the NCP.

Novel Electronic Health Records-Based Consultation Workflow Improves Time to Operating Room for Vascular Surgery Patients in an Acute Setting

BACKGROUND

Inefficient clinical workflows can have downstream effects of increased costs, poor resource utilization, and worse patient outcomes. The surgical consultation process can be complex with unclear communication, potentially delaying care for patients requiring time-sensitive intervention in an acute setting. A novel electronic health records (EHR)-based workflow was implemented to improve the consultation process. After implementation, we assessed the impact of this initiative in patients requiring vascular surgery consultation.

METHODS

An EHR-driven consultation workflow was implemented at a single institution, standardizing the process across all consulting services. This order-initiated workflow automated notification to clinicians of consult requests, communication of patient data, patient addition to consultants' lists, and tracking consult completion. Preimplementation (1/1/2020-1/31/2022) and postimplementation (2/1/2022-12/4/2022) vascular surgery consultation cohorts were compared to evaluate the impact of this initiative on timeliness of care.

RESULTS

There were 554 inpatient vascular surgery consultations (255 preimplementation and 299 postimplementation); 45 and 76 consults required surgery before and after implementation, respectively. The novel workflow resulted in placement of a consult note 32 min faster than preimplementation (preimplementation: 462 min, postimplementation: 430 min, P = 0.001) for all vascular surgery consults. Furthermore, vascular surgery patients with ASA class III or IV status requiring an urgent or emergent operation were transported to the operating room 63.3% faster after implementation of the workflow (preimplementation: 284 min, postimplementation: 180 min, P = 0.02). There were no differences in procedure duration, postoperative disposition, or intraoperative complication rates.

CONCLUSIONS

We implemented a novel workflow utilizing the EHR to standardize and automate the consultation process in the acute inpatient setting. This institutional initiative significantly improved timeliness of care for vascular surgery patients, including decreased time to operation. Innovations such as this can be further disseminated across shared EHR platforms across institutions, representing a powerful tool to increase the value of care in vascular surgery and healthcare overall.

Leveraging Generative AI and Large Language Models: A Comprehensive Roadmap for Healthcare Integration

Generative artificial intelligence (AI) and large language models (LLMs), exemplified by ChatGPT, are promising for revolutionizing data and information management in healthcare and medicine. However, there is scant literature guiding their integration for non-AI professionals. This study conducts a scoping literature review to address the critical need for guidance on integrating generative AI and LLMs into healthcare and medical practices. It elucidates the distinct mechanisms underpinning these technologies, such as Reinforcement Learning from Human Feedback (RLFH), including few-shot learning and chain-of-thought reasoning, which differentiates them from traditional, rule-based AI systems. It requires an inclusive, collaborative co-design process that engages all pertinent stakeholders, including clinicians and consumers, to achieve these benefits. Although global research is examining both opportunities and challenges, including ethical and legal dimensions, LLMs offer promising advancements in healthcare by enhancing data management, information retrieval, and decision-making processes. Continued innovation in data acquisition, model fine-tuning, prompt strategy development, evaluation, and system implementation is imperative for realizing the full potential of these technologies. Organizations should proactively engage with these technologies to improve healthcare quality, safety, and efficiency, adhering to ethical and legal guidelines for responsible application.

Co-design of an intervention to reduce the burden of clinical documentation: A clinician-researcher collaboration

AIM

To co-design an intervention to reduce the burden of clinical documentation for nurses and midwives.

METHODS

A clinician-researcher collaboration used an action research approach to co-design an intervention to reduce clinical documentation. The study consisted of three phases: 1) Analysis of pre-intervention data, 2) Evaluation of existing documentation, 3) Intervention co-design and implementation.

RESULTS

A total of 116 documents were reviewed using a three-stage evaluation process, identifying 28 documents that could be discontinued and 33 documents to be modified for the intervention. This resulted in an average of 7 documents for women who had a vaginal birth (decreased from 13), 9 documents for women who had a caesarean (decreased from 18), and 7 documents for newborns (previously 7-10). The minimum number of documents for a mother and baby reduced from 20 pre-intervention to 14 post-intervention.

CONCLUSION

The collaboration successfully co-designed and implemented an intervention to address the burden of clinical documentation that can be replicated in other healthcare settings.

Expanding horizons and navigating challenges for enhanced clinical workflows: ChatGPT in urology

Purpose of review

ChatGPT has emerged as a potential tool for facilitating doctors' workflows. However, when it comes to applying these findings within a urological context, there have not been many studies. Thus, our objective was rooted in analyzing the pros and cons of ChatGPT use and how it can be exploited and used by urologists.

Recent findings

ChatGPT can facilitate clinical documentation and note-taking, patient communication and support, medical education, and research. In urology, it was proven that ChatGPT has the potential as a virtual healthcare aide for benign prostatic hyperplasia, an educational and prevention tool on prostate cancer, educational support for urological residents, and as an assistant in writing urological papers and academic work. However, several concerns about its exploitation are presented, such as lack of web crawling, risk of accidental plagiarism, and concerns about patients-data privacy.

Summary

The existing limitations mediate the need for further improvement of ChatGPT, such as ensuring the privacy of patient data and expanding the learning dataset to include medical databases, and developing guidance on its appropriate use. Urologists can also help by conducting studies to determine the effectiveness of ChatGPT in urology in clinical scenarios and nosologies other than those previously listed.

Alerts and Collections for Automating Patients' Sensemaking and Organizing of Their Electronic Health Record Data for Reflection, Planning, and Clinical Visits: Qualitative Research-Through-Design Study

BACKGROUND

Electronic health record (EHR) data from multiple providers often exhibit important but convoluted and complex patterns that patients find hard and time-consuming to identify and interpret. However, existing patient-facing applications lack the capability to incorporate automatic pattern detection robustly and toward supporting making sense of the patient's EHR data. In addition, there is no means to organize EHR data in an efficient way that suits the patient's needs and makes them more actionable in real-life settings. These shortcomings often result in a skewed and incomplete picture of the patient's health status, which may lead to suboptimal decision-making and actions that put the patient at risk.

OBJECTIVE

Our main goal was to investigate patients' attitudes, needs, and use scenarios with respect to automatic support for surfacing important patterns in their EHR data and providing means for organizing them that best suit patients' needs.

METHODS

We conducted an inquisitive research-through-design study with 14 participants. Presented in the context of a cutting-edge application with strong emphasis on independent EHR data sensemaking, called Discovery, we used high-level mock-ups for the new features that were supposed to support automatic identification of important data patterns and offer recommendations-Alerts-and means for organizing the medical records based on patients' needs, much like photos in albums-Collections. The combined audio recording transcripts and in-study notes were analyzed using the reflexive thematic analysis approach.

RESULTS

The Alerts and Collections can be used for raising awareness, reflection, planning, and especially evidence-based patient-provider communication. Moreover, patients desired carefully designed automatic pattern detection with safe and actionable recommendations, which produced a well-tailored and scoped landscape of alerts for both potential threats and positive progress. Furthermore, patients wanted to contribute their own data (eg, progress notes) and log feelings, daily observations, and measurements to enrich the meaning and enable easier sensemaking of the alerts and collections. On the basis of the findings, we renamed Alerts to Reports for a more neutral tone and offered design implications for contextualizing the reports more deeply for increased actionability; automatically generating the collections for more expedited and exhaustive organization of the EHR data; enabling patient-generated data input in various formats to support coarser organization, richer pattern detection, and learning from experience; and using the reports and collections for efficient, reliable, and common-ground patient-provider communication.

CONCLUSIONS

Patients need to have a flexible and rich way to organize and annotate their EHR data; be introduced to insights from these data-both positive and negative; and share these artifacts with their physicians in clinical visits or via messaging for establishing shared mental models for clear goals, agreed-upon priorities, and feasible actions.

A behavioral intervention to promote use of multimodal pain medication for hospitalized patients: A randomized controlled trial

BACKGROUND

The use of nonsteroidal anti-inflammatory drugs (NSAIDs) can reduce pain and has become a core strategy to decrease opioid use, but there is a lack of data to describe encouraging use when admitting patients using electronic health record systems.

OBJECTIVE

Assess an electronic health record system to increase ordering of NSAIDs for hospitalized adults.

DESIGNS, SETTINGS AND PARTICIPANTS

We performed a cluster randomized controlled trial of clinicians admitting adult patients to a health system over a 9-month period. Clinicians were randomized to use a standard admission order set.

INTERVENTION

Clinicians in the intervention arm were required to actively order or decline NSAIDs; the control arm was shown the same order but without a required response.

MAIN OUTCOME AND MEASURES

The primary outcome was NSAIDs ordered and administered by the first full hospital day. Secondary outcomes included pain scores and opioid prescribing.

RESULTS

A total of 20,085 hospitalizations were included. Among these hospitalizations, patients had a mean age of 58 years, and a Charlson comorbidity score of 2.97, while 50% and 56% were female and White, respectively. Overall, 52% were admitted by a clinician randomized to the intervention arm. NSAIDs were ordered in 2267 (22%) interventions and 2093 (22%) control admissions (p = .10). Similarly, there were no statistical differences in NSAID administration, pain scores, or opioid prescribing. Average pain scores (0-5 scale) were 3.36 in the control group and 3.39 in the intervention group (p = .46). There were no differences in clinical harms.

CONCLUSIONS AND RELEVANCE

Requiring an active decision to order an NSAID at admission had no demonstrable impact on NSAID ordering. Multicomponent interventions, perhaps with stronger decision support, may be necessary to encourage NSAID ordering.

Inter-rater agreement for the annotation of neurologic signs and symptoms in electronic health records

The extraction of patient signs and symptoms recorded as free text in electronic health records is critical for precision medicine. Once extracted, signs and symptoms can be made computable by mapping to signs and symptoms in an ontology. Extracting signs and symptoms from free text is tedious and time-consuming. Prior studies have suggested that inter-rater agreement for clinical concept extraction is low. We have examined inter-rater agreement for annotating neurologic concepts in clinical notes from electronic health records. After training on the annotation process, the annotation tool, and the supporting neuro-ontology, three raters annotated 15 clinical notes in three rounds. Inter-rater agreement between the three annotators was high for text span and category label. A machine annotator based on a convolutional neural network had a high level of agreement with the human annotators but one that was lower than human inter-rater agreement. We conclude that high levels of agreement between human annotators are possible with appropriate training and annotation tools. Furthermore, more training examples combined with improvements in neural networks and natural language processing should make machine annotators capable of high throughput automated clinical concept extraction with high levels of agreement with human annotators.

Administrative burden in Swiss nursing homes and its association with care workers' outcomes-a multicenter cross-sectional study

BACKGROUND

Care workers in nursing homes often perform tasks that are rather related to organizational or management activities than 'direct patient care'. 'Indirect care activities', such as documentation or other administrative tasks are often considered by care workers as a burden, as they increase overall workload and keep them away from caring for residents. So far, there is little investigation into what kind of administrative tasks are being performed in nursing homes, by which type of care workers, and to which extent, nor how administrative burden is associated with care workers' outcomes.

PURPOSE

The objective of this study was to describe care workers' administrative burden in Swiss nursing homes and to explore the association with four care worker outcomes (i.e., job dissatisfaction, emotional exhaustion, intention to leave the current job and the profession).

METHODS

This multicenter cross-sectional study used survey data from the Swiss Nursing Homes Human Resources Project 2018. It included a convenience sample of 118 nursing homes and 2'207 care workers (i.e., registered nurses, licensed practical nurses) from Switzerland's German- and French-speaking regions. Care workers completed questionnaires assessing the administrative tasks and burden, staffing and resource adequacy, leadership ability, implicit rationing of nursing care and care worker characteristics and outcomes. For the analysis, we applied generalized linear mixed models, including individual-level nurse survey data and data on unit and facility characteristics.

RESULTS

Overall, 73.9% (n = 1'561) of care workers felt strongly or rather strongly burdened, with one third (36.6%, n = 787) reporting to spend 2 h or more during a "normal" day performing administrative tasks. Ratings for administrative burden ranged from 42.6% (n = 884; ordering supplies and managing stocks) to 75.3% (n = 1'621; filling out the resident's health record). One out of four care workers (25.5%, n = 561) intended to leave the profession, whereby care workers reporting higher administrative task burden (OR = 1.24; 95%CI: 1.02-1.50) were more likely to intend to leave the profession.

CONCLUSION

This study provides first insights on care workers' administrative burden in nursing homes. By limiting care workers' burdensome administrative tasks and/or shifting such tasks from higher to lower educated care workers or administrative personnel when appropriate, nursing home managers could reduce care workers' workload and improve their job satisfaction and retention in the profession.

Descriptive Analysis of Documentation Time for the National Developmental-Behavioral Pediatric Physician Workforce Using a Commercial Electronic Health Record System

OBJECTIVE

The national developmental-behavioral pediatric (DBP) workforce struggles to meet current service demands because of several factors. Lengthy and inefficient documentation processes are likely to contribute to service demand challenges, but DBP documentation patterns have not been sufficiently studied. Identifying clinical practice patterns may inform strategies to address documentation burden in DBP practice.

METHODS

Nearly 500 DBP physicians in the United States use a single commercial electronic health record (EHR) system (EpicCare Ambulatory, Epic Systems Corporation, Verona WI). We evaluated descriptive statistics using the US Epic DBP provider data set. We then compared DBP documentation metrics against those of pediatric primary care and selected pediatric subspecialty providers who provide similar types of care. One-way analyses of variance (ANOVAs) were conducted to determine whether outcomes differed among provider specialties.

RESULTS

We identified 4 groups for analysis from November 2019 through February 2020: DBP (n = 483), primary care (n = 76,423), pediatric psychiatry (n = 783), and child neurology (n = 8589). Post hoc pairwise comparisons revealed statistically significant differences between multiple outcome-specialty combinations. Time in notes per appointment and progress note length demonstrated the strongest evidence of an increased burden on DBP providers compared with other similar provider groups.

CONCLUSION

DBP providers spend a significant amount of time documenting progress notes both during and outside of normal clinic hours. This preliminary analysis highlights the utility of using EHR user activity data to quantitatively measure documentation burden.

Eliciting Insights From Chat Logs of the 25X5 Symposium to Reduce Documentation Burden: Novel Application of Topic Modeling

BACKGROUND

Addressing clinician documentation burden through "targeted solutions" is a growing priority for many organizations ranging from government and academia to industry. Between January and February 2021, the 25 by 5: Symposium to Reduce Documentation Burden on US Clinicians by 75% (25X5 Symposium) convened across 2 weekly 2-hour sessions among experts and stakeholders to generate actionable goals for reducing clinician documentation over the next 5 years. Throughout this web-based symposium, we passively collected attendees' contributions to a chat functionality-with their knowledge that the content would be deidentified and made publicly available. This presented a novel opportunity to synthesize and understand participants' perceptions and interests from chat messages. We performed a content analysis of 25X5 Symposium chat logs to identify themes about reducing clinician documentation burden.

OBJECTIVE

The objective of this study was to explore unstructured chat log content from the web-based 25X5 Symposium to elicit latent insights on clinician documentation burden among clinicians, health care leaders, and other stakeholders using topic modeling.

METHODS

Across the 6 sessions, we captured 1787 messages among 167 unique chat participants cumulatively; 14 were private messages not included in the analysis. We implemented a latent Dirichlet allocation (LDA) topic model on the aggregated dataset to identify clinician documentation burden topics mentioned in the chat logs. Coherence scores and manual examination informed optimal model selection. Next, 5 domain experts independently and qualitatively assigned descriptive labels to model-identified topics and classified them into higher-level categories, which were finalized through a panel consensus.

RESULTS

We uncovered ten topics using the LDA model: (1) determining data and documentation needs (422/1773, 23.8%); (2) collectively reassessing documentation requirements in electronic health records (EHRs) (252/1773, 14.2%); (3) focusing documentation on patient narrative (162/1773, 9.1%); (4) documentation that adds value (147/1773, 8.3%); (5) regulatory impact on clinician burden (142/1773, 8%); (6) improved EHR user interface and design (128/1773, 7.2%); (7) addressing poor usability (122/1773, 6.9%); (8) sharing 25X5 Symposium resources (122/1773, 6.9%); (9) capturing data related to clinician practice (113/1773, 6.4%); and (10) the role of quality measures and technology in burnout (110/1773, 6.2%). Among these 10 topics, 5 high-level categories emerged: consensus building (821/1773, 46.3%), burden sources (365/1773, 20.6%), EHR design (250/1773, 14.1%), patient-centered care (162/1773, 9.1%), and symposium comments (122/1773, 6.9%).

CONCLUSIONS

We conducted a topic modeling analysis on 25X5 Symposium multiparticipant chat logs to explore the feasibility of this novel application and elicit additional insights on clinician documentation burden among attendees. Based on the results of our LDA analysis, consensus building, burden sources, EHR design, and patient-centered care may be important themes to consider when addressing clinician documentation burden. Our findings demonstrate the value of topic modeling in discovering topics associated with clinician documentation burden using unstructured textual content. Topic modeling may be a suitable approach to examine latent themes presented in web-based symposium chat logs.

Factors Impacting Treatment of Out-of-Hospital Cardiac Arrest: A Qualitative Study of Emergency Responders

Background Of the more than 250 000 emergency medical services-treated out-of-hospital cardiac arrests that occur each year in the United States, only about 8% survive to hospital discharge with good neurologic function. Treatment for out-of-hospital cardiac arrest involves a system of care that includes complex interactions among multiple stakeholders. Understanding the factors inhibiting optimal care is fundamental to improving outcomes. Methods and Results We conducted group interviews with emergency responders including 911 telecommunicators, law enforcement officers, firefighters, and transporting emergency medical services personnel (ie, emergency medical technicians and paramedics) who responded to the same out-of-hospital cardiac arrest incident. We used the American Heart Association System of Care as the framework for our analysis to identify themes and their contributory factors from these interviews. We identified 5 themes under the structure domain, which included workload, equipment, prehospital communication structure, education and competency, and patient attitudes. In the process domain, 5 themes were identified focusing on preparedness, field response and access to patient, on-scene logistics, background information acquisition, and clinical interventions. We identified 3 system themes including emergency responder culture; community support, education, and engagement; and stakeholder relationships. Three continuous quality improvement themes were identified, which included feedback provision, change management, and documentation. Conclusions We identified structure, process, system, and continuous quality improvement themes that may be leveraged to improve outcomes for out-of-hospital cardiac arrest. Interventions or programs amenable to rapid implementation include improving prearrival communication between agencies, appointing patient care and logistical leadership on-scene, interstakeholder team training, and providing more standardized feedback to all responder groups.

Woman-centred care and integrated electronic medical records within Australian maternity settings: Point prevalence audit and observational study

OBJECTIVE

Transition to paperless records brings new challenges to midwifery practice across the continuum of woman-centred care. There is limited and conflicting evidence on the relative benefits of electronic medical records in maternity settings. This article aims to inform the use of integrative electronic medical records within the maternity services' environment with attention to the midwife-woman relationship.

DESIGN

This descriptive two-part study includes 1) an audit of electronic records in the early period following implementation (2-time points); and 2) an observational study to observe midwives' practice relating to electronic record use.

SETTING

Two regional tertiary public hospitals PARTICIPANTS: Midwives providing care for childbearing women across antenatal, intrapartum and postnatal areas.

FINDINGS

400 integrated electronic medical records were audited for completeness. Most fields had high levels of complete data in the correct location. However, between time 1 (T1) and time 2 (T2), persistent missing data (foetal heart rate documented 30 minutely T1 36%; T2 42%), and incomplete or incorrectly located data (pathology results T1:63%; T2 54%; perineal repair T1 60%; T2 46%) were identified. Observationally, midwives were actively engaged with the integrative electronic medical record between 23% to 68% (median 46%; IQR 16) of the time.

CONCLUSION

Midwives spent a significant amount of time completing documentation during clinical episodes of care. Largely, this documentation was found to be accurate, yet exceptions to data completeness, precision and location remained, indicating some concerns with software usability.

IMPLICATIONS FOR PRACTICE

Time-intensive monitoring and documentation may hinder woman-centred midwifery care.

Using Time Series Clustering to Segment and Infer Emergency Department Nursing Shifts from Electronic Health Record Log Files

Few computational approaches exist for abstracting electronic health record (EHR) log files into clinically meaningful phenomena like clinician shifts. Because shifts are a fundamental unit of work recognized in clinical settings, shifts may serve as a primary unit of analysis in the study of documentation burden. We conducted a proof- of-concept study to investigate the feasibility of a novel approach using time series clustering to segment and infer clinician shifts from EHR log files. From 33,535,585 events captured between April-June 2021, we computationally identified 43,911 potential shifts among 2,285 (74.2%) emergency department nurses. On average, computationally-identified shifts were 10.6±3.1 hours long. Based on data distributions, we classified these shifts based on type: day, evening, night; and length: 12-hour, 8-hour, other. We validated our method through manual chart review of computationally-identified 12-hour shifts achieving 92.0% accuracy. Preliminary results suggest unsupervised clustering methods may be a reasonable approach for rapidly identifying clinician shifts.

Understanding the perceived role of electronic health records and workflow fragmentation on clinician documentation burden in emergency departments

OBJECTIVE

Understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED).

METHODS

From February to June 2022, we conducted semistructured interviews among a national sample of US prescribing providers and registered nurses who actively practice in the adult ED setting and use Epic Systems' EHR. We recruited participants through professional listservs, social media, and email invitations sent to healthcare professionals. We analyzed interview transcripts using inductive thematic analysis and interviewed participants until we achieved thematic saturation. We finalized themes through a consensus-building process.

RESULTS

We conducted interviews with 12 prescribing providers and 12 registered nurses. Six themes were identified related to EHR factors perceived to contribute to documentation burden including lack of advanced EHR capabilities, absence of EHR optimization for clinicians, poor user interface design, hindered communication, increased manual work, and added workflow blockages, and five themes associated with cognitive load. Two themes emerged in the relationship between workflow fragmentation and EHR documentation burden: underlying sources and adverse consequences.

DISCUSSION

Obtaining further stakeholder input and consensus is essential to determine whether these perceived burdensome EHR factors could be extended to broader contexts and addressed through optimizing existing EHR systems alone or through a broad overhaul of the EHR's architecture and primary purpose.

CONCLUSION

While most clinicians perceived that the EHR added value to patient care and care quality, our findings underscore the importance of designing EHRs that are in harmony with ED clinical workflows to alleviate the clinician documentation burden.

Meaningless Use: Assessing Compliance With a Clinically Meaningless Emergency Department Documentation Requirement

Introduction A New York State initiative requests that Emergency Department (ED) providers document in the electronic health record (EHR) each admitted patient's employment status and, if applicable, their mode of commute. This initiative diverts them from their primary duties and increases the likelihood they will either disregard the request or input incorrect information to complete the data fields as fast as possible. This study intends to understand how well providers adhere to this regulation, which, while important for society as a whole, has little clinical relevance, especially in the ED, where the focus is to identify and treat emergent conditions. We hypothesized that clinician-collected employment data would contain many more "N/A" responses than registration-collected employment data (the "gold standard").  Methods We took a randomly selected convenience sample of 100 patients admitted from the ED and compared each patient's provider-entered response to the employment data field to the registration-recorded response. The EHR operates such that the "Employment" field must be completed in order to complete the admission electronically. Data fields collected were: last name, first name, date of birth, medical record number, date and time of arrival, date and time of admission, attending physician, resident physician (if there was one), mid-level provider (if there was one), provider-entered employment status, registration-entered employment status, admitting service (eg, Medicine, Surgery, OB/Gyn), and disposition level (eg, ICU). We assessed the percent of employment data that was concordant between the provider's entry and the registration clerk's entry. We also assessed for the potential confounding variable of how busy the ED was at time of admission, as providers may not take ask about employment or enter such data during particularly busy times. Finally, we interviewed providers to elicit reasons they did not enter accurate data. Statistical significance was set a priori at p <0.05. Results One hundred six patients were screened; six were excluded because one of the authors (MR) was their attending physician. For 92 of the remaining 100 patients, providers recorded employment as "N/A," and for eight patients they recorded "retired." For seven of these eight patients, provider entry matched registration entry (87.5% concordance). To adjust for whether how busy the ED was may have impacted the accuracy of data entry, admissions were categorized according to what time of day the patient was admitted. There was no statistically significant correlation between how busy the ED was and accuracy of data entry. The majority of providers stated they responded "NA" because the employment information was unrelated to the ED visit.  Conclusion In New York, for each patient admitted from the ED, the ED provider is requested to enter the patient's job information and, if they commute to work, the method they use. However, this takes providers' attention away from what they should be doing most: diagnosing and treating patients. This study highlights the unintended consequence of requesting data fields that are not clinically relevant and, from the patient and provider perspective, are not good investments of time and energy and distract from the clinical visit. Persons interpreting such clinically irrelevant data should do so with caution, as the results are unlikely to reflect the truth of what the questions intend to determine.

Implementing Digital Scribes to Reduce Electronic Health Record Documentation Burden Among Cancer Care Clinicians: A Mixed-Methods Pilot Study

PURPOSE

To address shortcomings of human scribes (eg, turnover), clinicians are considering digital scribes (DSs). To our knowledge, to date, no study has assessed DS implementation or clinician user experience in cancer centers. We assessed the DS's feasibility, acceptability, appropriateness, usability and its preliminary association on clinician well-being in a cancer center. We also identified implementation facilitators and barriers to DS use.

METHODS

Using a mixed-methods longitudinal pilot study design, we implemented a DS at a cancer center. Data collection included surveys at baseline and 1 month after DS use and a semistructured interview with clinicians. The survey assessed demographics, Mini Z (workplace stress and burnout), sleep quality, and implementation outcomes (feasibility, acceptability, appropriateness, and usability). The interview assessed how the DS was used and its impacts on workflows and recommendations for future implementations of the DS. We used paired t tests to assess differences in Mini Z and sleep quality measures over time.

RESULTS

Across nine survey responses and eight interviews, we found that although feasibility scores were slightly lower than our cutoff point (15.2 v 16.0), clinicians rated the DS as marginally acceptable (16.0) and appropriate (16.3). Usability was considered marginally usable (68.6 v 68.0). Although the DS did not significantly improve burnout (3.6 v 3.9, P = .081), it improved perceptions of having sufficient documentation time (2.1 v 3.6, P = .005). Clinicians identified suggestions for future implementations, including training needs and usability improvements.

CONCLUSION

Our preliminary findings suggest that DS implementation is marginally acceptable, appropriate, and usable among cancer care clinicians. Individualized training and on-site support may improve implementation.

A co-designed health information system implementation into residential aged care: A mixed-method evaluation

INTRODUCTION

Internationally, the adoption of technology into residential aged care settings has been slow and fraught with multiple challenges for residents, staff and service providers. The aim of this study was to evaluate the acceptability, efficiency, and quality of health information system implementation into aged care.

METHODS

Three-stage, mixed-methods participatory action research, concurrent with the natural experiment of a co-designed health information system implementation into a 169-bed aged care home in Australia. Data were collected pre-, during, and post implementation between 2019 and 2021. Qualitative data included focus groups, interviews, and observations. Quantitative data included work observations, pedometers, record audits, incident reports and staff and resident surveys. There were 162 participants composed of 65 aged care residents, 90 staff, and 7 managers/consultants.

RESULTS

Improved work efficiency included reduced staff time searching for information (6%); reduced nurse time on documentation (20.4% to 6.4%), and 25% less steps. Documentation improvement included resident assessments (68% to 96%); resident-focused goals (56% to 88%) and evaluations (31% to 88%). The staff reported being better equipped to manage the 'delicacies of dignity'.

CONCLUSION

Implementation of a health information system into a residential aged care facility was associated with improved resident-focused care and staff efficiency.

CLINICAL RELEVANCE

Technology can support nurses and care staff to spend more time with residents in residential aged care homes, improve the quality of resident care, and assist meeting regulatory reporting requirements. Flexible and tailored co-design strategies can enhance both effectiveness and success of technology implementation into residential aged care.

Early Performance of the Patients Over Paperwork Initiative among Family Medicine Physicians

OBJECTIVES

In 2019, the Centers for Medicare & Medicaid Services began implementing the Patients Over Paperwork (POP) initiative in response to clinicians reporting burdensome documentation regulations. To date, no study has evaluated how these policy changes have influenced documentation burden.

METHODS

Our data came from the electronic health records of an academic health system. Using quantile regression models, we assessed the association between the implementation of POP and clinical documentation word count using data from family medicine physicians in an academic health system from January 2017 to May 2021 inclusive. Studied quantiles included the 10th, 25th, 50th, 75th, and 90th quantiles. We controlled for patient-level (race/ethnicity, primary language, age, comorbidity burden), visit-level (primary payer, level of clinical decision making involved, whether a visit was done through telemedicine, whether a visit was for a new patient), and physician-level (sex) characteristics.

RESULTS

We found that the POP initiative was associated with lower word counts across all of the quantiles. In addition, we found lower word counts among notes for private payers and telemedicine visits. Conversely, higher word counts were observed in notes that were written by female physicians, notes for new patient visits, and notes involving patients with greater comorbidity burden.

CONCLUSIONS

Our initial evaluation suggests that documentation burden, as measured by word count, has declined over time, particularly following implementation of the POP in 2019. Additional research is needed to see whether the same occurs when examining other medical specialties, clinician types, and longer evaluation periods.

Scoping review: Positive and negative impact of technology on clinicians

BACKGROUND

Unnecessary electronic health record (EHRs) documentation burden and usability issues have negatively impacted clinician well-being (e.g., burnout and moral distress).

PURPOSE

This scoping review was conducted by members from three expert panels of the American Academy of Nurses to generate consensus on the evidence of both positive and negative impact of EHRs on clinicians.

METHODS

The scoping review was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews guidelines.

RESULTS

The scoping review captured 1,886 publications screened against title and abstract 1,431 excluded, examined 448 in a full-text review, excluded 347 with 101 studies informing the final review.

DISCUSSION

Findings suggest few studies that have explored the positive impact of EHRs and more studies that have explored the clinician's satisfaction and work burden. Significant gaps were identified in associating distress to use of EHRs and minimal studies on EHRs' impact on nurses.

CONCLUSION

Examined the evidence of HIT's positive and negative impacts on clinician's practice, clinicians work environment, and if psychological impact differed among clinicians.

An evaluation of copy and paste events in electronic notes of patients with hospital acquired conditions

BACKGROUND

The increased use of the copy and paste function (CPF) in Electronic Health Records (EHRs) has raised concerns about possible clinician miscommunication and adverse patient outcomes.

OBJECTIVE

This study investigated the prevalence and extent of CPF in the EHRs of patients diagnosed with Hospital-acquired Conditions (HACs). We also examined the association between the use of CPF and patient characteristics.

MATERIALS AND METHODS

The prevalence and extent of CPF were investigated using electronic clinical notes of 50 patients hospitalized with HACs between 2017 and 2021 at a large academic medical center. Study patients were adults aged 21 and older with a length of stay greater than three days. ANOVA analysis was used to examine the differences in CPF use between patients with different characteristics.

RESULTS

A total of 7,844 clinical notes across seven note types are compared in the study. The mean patient age was 63.7, with an average length of stay of 15.6 days. 54% of Discharge Summaries, 53% of Consults, and 47% of history and physical (H&P) notes had duplications with the same type of notes. In the Discharge Summary, ED notes, and Plan of Care, duplications accounted for 40% or higher of the full text. H&P and Consults, H&P and Discharge Summary, and Discharge Summary and Consults were more likely to have duplications than between other types of notes. Duplications accounted for 15.5% of the information provided in H&P and Consults. The prevalence of CPF was higher in the Discharge Summary of patients who were younger, female, and had longer hospital stays.

CONCLUSION

Both prevalence and extent of duplication were high in the Discharge Summary, Consults, and H&P notes of patients with HACs. Future studies are needed to examine the intention and appropriateness of CPF use and its impact on patient outcomes.

Electronic Health Record Maturity Matters! Texas Nurses Speak Out in Their Second Statewide Study

With the passage of the Health Information Technology for Economic and Clinical Health Act in 2009, Texas nurses were faced with the rapid uptake of technology driven by this legislation. Texas Nurses Association and Texas Organization for Nursing Leadership formed a partnership to collectively track the impact on practicing nurses. The Health IT Committee was commissioned to evaluate the changing health information technology environment and associated solutions. As such, a study in 2015, entitled "Statewide Study Assessing the Experiences of Nurses with their Electronic Health Records," was conducted. The follow-up study in 2020 was conducted to compare 2015 and 2020 findings to identify improvements made on nurses' satisfaction with EHRs and identify improvement opportunities. The study design was an exploratory descriptive comparative analysis with a cross-sectional survey from a random sample of Texas nurses for the two study periods of 2015 (n = 1177) and 2020 (n = 1117). The Clinical Information Systems Implementation Evaluation Scale and a demographic survey including the Meaningful Use Maturity-Sensitive Index were the measurement instruments. Results and key covariates are discussed along with recommendations for achieving more mature EHRs and more mature organizational culture and leadership.

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., UI-1D, UI-2D) implemented two dynamic reaction picklists with different ranking algorithms and the third UI (UI-3S) implemented a static reaction picklist like the one used in the current EHR. We recruited 18 clinicians to perform allergy entry for 10 test cases each via UI-1D and UI-3S, and another 18 clinicians via UI-2D and UI-3S. Primary measures were the number of free-text entries and time to complete the allergy entry. Clinicians were also interviewed using 30 questions before and after the data entry.

RESULTS AND DISCUSSIONS

Among 36 clinicians, less than half were satisfied with the current EHR reaction picklists, due to their incomprehensiveness, inefficiency, and lack of intuitiveness. The clinicians used significantly fewer free-text entries when using UI-1D or UI-2D compared to UI-3S (p < 0.05). The clinicians used on average 51 s (15 %) less time via UI-1D and 50 s (16 %) less time via UI-2D in completing the allergy entries versus UI-3S, and there was not a statistically significant difference in documentation time for either group between the dynamic and static UIs. Overall, 15-17 (83-94 %) clinicians rated UI-1D and 13-15 (72-83 %) clinicians rated UI-2D as efficient, easy to use, and useful, while less than half rated the same for UI-3S. Most clinicians reported that the dynamic reaction picklists always or often suggested appropriate reactions (n = 30, 83 %) and would decrease the free-text entries (n = 26, 72 %); nearly all preferred the dynamic picklist over the static picklist (n = 32, 89 %).

CONCLUSION

We found that dynamic reaction picklists significantly reduced the number of free-text entries and could reduce the time for allergy documentation by 15%. Clinicians preferred the dynamic reaction picklist over the static picklist.