COVID-19 hospitalization risk after outpatient nirmatrelvir/ritonavir use, January to August 2022, North Carolina.

BACKGROUND: In the USA, nirmatrelvir/ritonavir is authorized for the treatment of mild-to-moderate COVID-19 in patients at least 12 years of age, at high risk for progression to severe COVID-19. OBJECTIVES: To estimate the impact of outpatient nirmatrelvir/ritonavir on COVID-19 hospitalization risk in a US healthcare system. METHODS: We conducted a cohort study using electronic health records among outpatients with a positive SARS-CoV-2 PCR test between January and August 2022. We evaluated the association of nirmatrelvir/ritonavir therapy with time to hospitalization by estimating adjusted HRs and assessed the impact of nirmatrelvir/ritonavir on predicted COVID-19 hospitalizations using machine-learning methods. RESULTS: Among 44 671 patients, 4948 (11%) received nirmatrelvir/ritonavir, and 201 (0.4%) were hospitalized within 28 days of COVID-19 diagnosis. Nirmatrelvir/ritonavir recipients were more likely to be older, white, vaccinated, have comorbidities and reside in areas with higher average socioeconomic status. The 28 day cumulative incidence of hospitalization was 0.06% (95% CI: 0.02%-0.17%) among nirmatrelvir/ritonavir recipients and 0.52% (95% CI: 0.46%-0.60%) among non-recipients. For nirmatrelvir/ritonavir versus no therapy, the age-adjusted HR was 0.08 (95% CI: 0.03-0.26); the fully adjusted HR was 0.16 (95% CI: 0.05-0.50). In the machine-learning model, the primary features reducing predicted hospitalization risk were nirmatrelvir/ritonavir, younger age, vaccination, female gender and residence in a higher socioeconomic status area. CONCLUSIONS: COVID-19 hospitalization risk was reduced by 84% among nirmatrelvir/ritonavir recipients in a large, diverse healthcare system during the Omicron wave. These results suggest that nirmatrelvir/ritonavir remained highly effective in a setting substantially different than the original clinical trials.

Identifying and Addressing Barriers to Implementing Core Electronic Health Record Use Metrics for Ambulatory Care: Virtual Consensus Conference Proceedings.

Precise, reliable, valid metrics that are cost-effective and require reasonable implementation time and effort are needed to drive electronic health record (EHR) improvements and decrease EHR burden. Differences exist between research and vendor definitions of metrics. PROCESS: We convened three stakeholder groups (health system informatics leaders, EHR vendor representatives, and researchers) in a virtual workshop series to achieve consensus on barriers, solutions, and next steps to implementing the core EHR use metrics in ambulatory care. CONCLUSION: Actionable solutions identified to address core categories of EHR metric implementation challenges include: (1) maintaining broad stakeholder engagement, (2) reaching agreement on standardized measure definitions across vendors, (3) integrating clinician perspectives, and (4) addressing cognitive and EHR burden. Building upon the momentum of this workshop's outputs offers promise for overcoming barriers to implementing EHR use metrics.

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.

Assessing Usability and Ambulatory Clinical Staff Satisfaction with Two Electronic Health Records.

BACKGROUND: A growing body of literature has linked usability limitations within electronic health records (EHRs) to adverse outcomes which may in turn affect EHR system transitions. NewYork-Presbyterian Hospital, Columbia University College of Physicians and Surgeons (CU), and Weill Cornell Medical College (WC) are a tripartite organization with large academic medical centers that initiated a phased transition of their EHRs to one system, EpicCare. OBJECTIVES: This article characterizes usability perceptions stratified by provider roles by surveying WC ambulatory clinical staff already utilizing EpicCare and CU ambulatory clinical staff utilizing iterations of Allscripts before the implementation of EpicCare campus-wide. METHODS: A customized 19-question electronic survey utilizing usability constructs based on the Health Information Technology Usability Evaluation Scale was anonymously administered prior to EHR transition. Responses were recorded with self-reported demographics. RESULTS: A total of 1,666 CU and 1,065 WC staff with ambulatory self-identified work setting were chosen. Select demographic statistics between campus staff were generally similar with small differences in patterns of clinical and EHR experience. Results demonstrated significant differences in EHR usability perceptions among ambulatory staff based on role and EHR system. WC staff utilizing EpicCare accounted for more favorable usability metrics than CU across all constructs. Ordering providers (OPs) denoted less usability than non-OPs. The Perceived Usefulness and User Control constructs accounted for the largest differences in usability perceptions. The Cognitive Support and Situational Awareness construct was similarly low for both campuses. Prior EHR experience demonstrated limited associations. CONCLUSION: Usability perceptions can be affected by role and EHR system. OPs consistently denoted less usability overall and were more affected by EHR system than non-OPs. While there was greater perceived usability for EpicCare to perform tasks related to care coordination, documentation, and error prevention, there were persistent shortcomings regarding tab navigation and cognitive burden reduction, which have implications on provider efficiency and wellness.

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.

Identifying Reuse and Redundancies in Respiratory Flowsheet Documentation: Implications for Clinician Documentation Burden.

Documentation burden is experienced by clinical end-users of the electronic health record. Flowsheet measure reuse and clinical concept redundancy are two contributors to documentation burden. In this paper, we described nursing flowsheet documentation hierarchy and frequency of use for one month from two hospitals in our health system. We examined respiratory care management documentation in greater detail. We found 59 instances of reuse of respiratory care flowsheet measure fields over two or more templates and groups, and 5 instances of clinical concept redundancy. Flowsheet measure fields for physical assessment observations and measurements were the most frequently documented and most reused, whereas respiratory intervention documentation was less frequently reused. Further research should investigate the relationship between flowsheet measure reuse and redundancy and EHR information overload and documentation burden.

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.

Role of left atrial hypertension in pulmonary hypertension associated with bronchopulmonary dysplasia.

Left atrial hypertension (LAH) may contribute to pulmonary hypertension (PH) in premature infants with bronchopulmonary dysplasia (BPD). Primary causes of LAH in infants with BPD include left ventricular diastolic dysfunction or hemodynamically significant left to right shunt. The incidence of LAH, which is definitively diagnosed by cardiac catheterization, and its contribution to PH is unknown in patients with BPD-PH. We report the prevalence of LAH in an institutional cohort with BPD-PH with careful examination of hemodynamic contributors and impact on patient outcomes. This single-center, retrospective cohort study examined children <2 years of age with BPD-PH who underwent cardiac catheterization at Lucile Packard Children's Hospital Stanford. Patients with unrepaired simple shunt congenital heart disease (CHD) and pulmonary vein stenosis (only 1 or 2 vessel disease) were included. Patients with complex CHD were excluded. From April 2010 to December 2021, 34 patients with BPD-PH underwent cardiac catheterization. We define LAH as pulmonary capillary wedge pressure (PCWP) or left atrial pressure (LAP) of at least 10 mmHg. In this cohort, median PCWP was 8 mmHg, with LAH present in 32% (n = 11) of the total cohort. A majority (88%, n = 30) of the cohort had severe BPD. Most patients had some form of underlying CHD and/or pulmonary vein stenosis: 62% (n = 21) with an atrial septal defect or patent foramen ovale, 62% (n = 21) with patent ductus arteriosus, 12% (n = 4) with ventricular septal defect, and 12% (n = 4) with pulmonary vein stenosis. Using an unadjusted logistic regression model, baseline requirement for positive pressure ventilation at time of cardiac catheterization was associated with increased risk for LAH (odds ratio 8.44, 95% CI 1.46-48.85, p = 0.02). Small for gestational age birthweight, sildenafil use, and CHD were not associated with increased risk for LAH. LAH was associated with increased risk for the composite outcome of tracheostomy and/or death, with a hazard ratio of 6.32 (95% CI 1.72, 22.96; p = 0.005). While the etiology of BPD-PH is multifactorial, LAH is associated with PH in some cases and may play a role in clinical management and patient outcomes.

25 × 5 Symposium to Reduce Documentation Burden: Report-out and Call for Action.

BACKGROUND: The widespread adoption of electronic health records and a simultaneous increase in regulatory demands have led to an acceleration of documentation requirements among clinicians. The corresponding burden from documentation requirements is a central contributor to clinician burnout and can lead to an increased risk of suboptimal patient care. OBJECTIVE: To address the problem of documentation burden, the 25 by 5: Symposium to Reduce Documentation Burden on United States Clinicians by 75% by 2025 (Symposium) was organized to provide a forum for experts to discuss the current state of documentation burden and to identify specific actions aimed at dramatically reducing documentation burden for clinicians. METHODS: The Symposium consisted of six weekly sessions with 33 presentations. The first four sessions included panel presentations discussing the challenges related to documentation burden. The final two sessions consisted of breakout groups aimed at engaging attendees in establishing interventions for reducing clinical documentation burden. Steering Committee members analyzed notes from each breakout group to develop a list of action items. RESULTS: The Steering Committee synthesized and prioritized 82 action items into Calls to Action among three stakeholder groups: Providers and Health Systems, Vendors, and Policy and Advocacy Groups. Action items were then categorized into as short-, medium-, or long-term goals. Themes that emerged from the breakout groups' notes include the following: accountability, evidence is critical, education and training, innovation of technology, and other miscellaneous goals (e.g., vendors will improve shared knowledge databases). CONCLUSION: The Symposium successfully generated a list of interventions for short-, medium-, and long-term timeframes as a launching point to address documentation burden in explicit action-oriented ways. Addressing interventions to reduce undue documentation burden placed on clinicians will necessitate collaboration among all stakeholders.

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.

Clinician and Health Care Leaders' Experiences with-and Perceptions of-COVID-19 Documentation Reduction Policies and Practices.

BACKGROUND: Substantial strategies to reduce clinical documentation were implemented by health care systems throughout the coronavirus disease-2019 (COVID-19) pandemic at national and local levels. This natural experiment provides an opportunity to study the impact of documentation reduction strategies on documentation burden among clinicians and other health professionals in the United States. OBJECTIVES: The aim of this study was to assess clinicians' and other health care leaders' experiences with and perceptions of COVID-19 documentation reduction strategies and identify which implemented strategies should be prioritized and remain permanent post-pandemic. METHODS: We conducted a national survey of clinicians and health care leaders to understand COVID-19 documentation reduction strategies implemented during the pandemic using snowball sampling through professional networks, listservs, and social media. We developed and validated a 19-item survey leveraging existing post-COVID-19 policy and practice recommendations proposed by Sinsky and Linzer. Participants rated reduction strategies for impact on documentation burden on a scale of 0 to 100. Free-text responses were thematically analyzed. RESULTS: Of the 351 surveys initiated, 193 (55%) were complete. Most participants were informaticians and/or clinicians and worked for a health system or in academia. A majority experienced telehealth expansion (81.9%) during the pandemic, which participants also rated as highly impactful (60.1-61.5) and preferred that it remain (90.5%). Implemented at lower proportions, documenting only pertinent positives to reduce note bloat (66.1 ± 28.3), changing compliance rules and performance metrics to eliminate those without evidence of net benefit (65.7 ± 26.3), and electronic health record (EHR) optimization sprints (64.3 ± 26.9) received the highest impact scores compared with other strategies presented; support for these strategies widely ranged (49.7-63.7%). CONCLUSION: The results of this survey suggest there are many perceived sources of and solutions for documentation burden. Within strategies, we found considerable support for telehealth, documenting pertinent positives, and changing compliance rules. We also found substantial variation in the experience of documentation burden among participants.

Characterizing Multitasking and Workflow Fragmentation in Electronic Health Records among Emergency Department Clinicians: Using Time-Motion Data to Understand Documentation Burden.

BACKGROUND: The impact of electronic health records (EHRs) in the emergency department (ED) remains mixed. Dynamic and unpredictable, the ED is highly vulnerable to workflow interruptions. OBJECTIVES: The aim of the study is to understand multitasking and task fragmentation in the clinical workflow among ED clinicians using clinical information systems (CIS) through time-motion study (TMS) data, and inform their applications to more robust and generalizable measures of CIS-related documentation burden. METHODS: Using TMS data collected among 15 clinicians in the ED, we investigated the role of documentation burden, multitasking (i.e., performing physical and communication tasks concurrently), and workflow fragmentation in the ED. We focused on CIS-related tasks, including EHRs. RESULTS: We captured 5,061 tasks and 877 communications in 741 locations within the ED. Of the 58.7 total hours observed, 44.7% were spent on CIS-related tasks; nearly all CIS-related tasks focused on data-viewing and data-entering. Over one-fifth of CIS-related task time was spent on multitasking. The mean average duration among multitasked CIS-related tasks was shorter than non-multitasked CIS-related tasks (20.7 s vs. 30.1 s). Clinicians experienced 1.4 ± 0.9 task switches/min, which increased by one-third when multitasking. Although multitasking was associated with a significant increase in the average duration among data-entering tasks, there was no significant effect on data-viewing tasks. When engaged in CIS-related task switches, clinicians were more likely to return to the same CIS-related task at higher proportions while multitasking versus not multitasking. CONCLUSION: Multitasking and workflow fragmentation may play a significant role in EHR documentation among ED clinicians, particularly among data-entering tasks. Understanding where and when multitasking and workflow fragmentation occurs is a crucial step to assessing potentially burdensome clinician tasks and mitigating risks to patient safety. These findings may guide future research on developing more scalable and generalizable measures of CIS-related documentation burden that do not necessitate direct observation techniques (e.g., EHR log files).

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

BACKGROUND: . OBJECTIVE: Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout. While clear classifications and validated measures of burnout exist, documentation burden remains ill-defined and inconsistently measured. We aim to conduct a scoping review focused on identifying approaches to documentation burden measurement and their characteristics. MATERIALS AND METHODS: Based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews (ScR) guidelines, we conducted a scoping review assessing MEDLINE, Embase, Web of Science, and CINAHL from inception to April 2020 for studies investigating documentation burden among physicians and nurses in ambulatory or inpatient settings. Two reviewers evaluated each potentially relevant study for inclusion/exclusion criteria. RESULTS: Of the 3482 articles retrieved, 35 studies met inclusion criteria. We identified 15 measurement characteristics, including 7 effort constructs: EHR usage and workload, clinical documentation/review, EHR work after hours and remotely, administrative tasks, cognitively cumbersome work, fragmentation of workflow, and patient interaction. We uncovered 4 time constructs: average time, proportion of time, timeliness of completion, activity rate, and 11 units of analysis. Only 45.0% of studies assessed the impact of EHRs on clinicians and/or patients and 40.0% mentioned clinician burnout. DISCUSSION: Standard and validated measures of documentation burden are lacking. While time and effort were the core concepts measured, there appears to be no consensus on the best approach nor degree of rigor to study documentation burden. CONCLUSION: Further research is needed to reliably operationalize the concept of documentation burden, explore best practices for measurement, and standardize its use.

Clinician involvement in research on machine learning-based predictive clinical decision support for the hospital setting: A scoping review.

OBJECTIVE: The study sought to describe the prevalence and nature of clinical expert involvement in the development, evaluation, and implementation of clinical decision support systems (CDSSs) that utilize machine learning to analyze electronic health record data to assist nurses and physicians in prognostic and treatment decision making (ie, predictive CDSSs) in the hospital. MATERIALS AND METHODS: A systematic search of PubMed, CINAHL, and IEEE Xplore and hand-searching of relevant conference proceedings were conducted to identify eligible articles. Empirical studies of predictive CDSSs using electronic health record data for nurses or physicians in the hospital setting published in the last 5 years in peer-reviewed journals or conference proceedings were eligible for synthesis. Data from eligible studies regarding clinician involvement, stage in system design, predictive CDSS intention, and target clinician were charted and summarized. RESULTS: Eighty studies met eligibility criteria. Clinical expert involvement was most prevalent at the beginning and late stages of system design. Most articles (95%) described developing and evaluating machine learning models, 28% of which described involving clinical experts, with nearly half functioning to verify the clinical correctness or relevance of the model (47%). DISCUSSION: Involvement of clinical experts in predictive CDSS design should be explicitly reported in publications and evaluated for the potential to overcome predictive CDSS adoption challenges. CONCLUSIONS: If present, clinical expert involvement is most prevalent when predictive CDSS specifications are made or when system implementations are evaluated. However, clinical experts are less prevalent in developmental stages to verify clinical correctness, select model features, preprocess data, or serve as a gold standard.

Development and validation of early warning score system: A systematic literature review.

OBJECTIVES: This review aims to: 1) evaluate the quality of model reporting, 2) provide an overview of methodology for developing and validating Early Warning Score Systems (EWSs) for adult patients in acute care settings, and 3) highlight the strengths and limitations of the methodologies, as well as identify future directions for EWS derivation and validation studies. METHODOLOGY: A systematic search was conducted in PubMed, Cochrane Library, and CINAHL. Only peer reviewed articles and clinical guidelines regarding developing and validating EWSs for adult patients in acute care settings were included. 615 articles were extracted and reviewed by five of the authors. Selected studies were evaluated based on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist. The studies were analyzed according to their study design, predictor selection, outcome measurement, methodology of modeling, and validation strategy. RESULTS: A total of 29 articles were included in the final analysis. Twenty-six articles reported on the development and validation of a new EWS, while three reported on validation and model modification. Only eight studies met more than 75% of the items in the TRIPOD checklist. Three major techniques were utilized among the studies to inform their predictive algorithms: 1) clinical-consensus models (n = 6), 2) regression models (n = 15), and 3) tree models (n = 5). The number of predictors included in the EWSs varied from 3 to 72 with a median of seven. Twenty-eight models included vital signs, while 11 included lab data. Pulse oximetry, mental status, and other variables extracted from electronic health records (EHRs) were among other frequently used predictors. In-hospital mortality, unplanned transfer to the intensive care unit (ICU), and cardiac arrest were commonly used clinical outcomes. Twenty-eight studies conducted a form of model validation either within the study or against other widely-used EWSs. Only three studies validated their model using an external database separate from the derived database. CONCLUSION: This literature review demonstrates that the characteristics of the cohort, predictors, and outcome selection, as well as the metrics for model validation, vary greatly across EWS studies. There is no consensus on the optimal strategy for developing such algorithms since data-driven models with acceptable predictive accuracy are often site-specific. A standardized checklist for clinical prediction model reporting exists, but few studies have included reporting aligned with it in their publications. Data-driven models are subjected to biases in the use of EHR data, thus it is particularly important to provide detailed study protocols and acknowledge, leverage, or reduce potential biases of the data used for EWS development to improve transparency and generalizability.

Time-motion examination of electronic health record utilization and clinician workflows indicate frequent task switching and documentation burden.

Clinical documentation burden has been broadly acknowledged, yet few interprofessional measures of burden exist. Using interprofessional time-motion study (TMS) data, we evaluated clinical workflows with a focus on electronic health record (EHR) utilization and fragmentation among 47 clinicians: 34 advanced practice providers (APPs) and 13 registered nurses (RNs) from: an acute care unit (n=15 observations [obs]), intensive care unit (nobs=14), ambulatory clinic (nobs=3), and emergency department (nobs=15). We examined workflow fragmentation, task-switch type, and task involvement. In our study, clinicians on average exhibited 1.4±0.6 switches per minute in their workflow. Eighty-four (19.6%) of the 429 task-switch types presented in the data accounted for 80.1% of all switches. Among those, data viewing- and data entry-related tasks were involved in 48.2% of all switches, indicating documentation burden may play a critical role in workflow disruptions. Therefore, interruption rate evaluated through task switches may serve as a proxy for measuring burden.

What Is Karyotype Coding and Why Is Genomic Topology Important for Cancer and Evolution?

While the importance of chromosomal/nuclear variations vs. gene mutations in diseases is becoming more appreciated, less is known about its genomic basis. Traditionally, chromosomes are considered the carriers of genes, and genes define bio-inheritance. In recent years, the gene-centric concept has been challenged by the surprising data of various sequencing projects. The genome system theory has been introduced to offer an alternative framework. One of the key concepts of the genome system theory is karyotype or chromosomal coding: chromosome sets function as gene organizers, and the genomic topologies provide a context for regulating gene expression and function. In other words, the interaction of individual genes, defined by genomic topology, is part of the full informational system. The genes define the "parts inheritance," while the karyotype and genomic topology (the physical relationship of genes within a three-dimensional nucleus) plus the gene content defines "system inheritance." In this mini-review, the concept of karyotype or chromosomal coding will be briefly discussed, including: 1) the rationale for searching for new genomic inheritance, 2) chromosomal or karyotype coding (hypothesis, model, and its predictions), and 3) the significance and evidence of chromosomal coding (maintaining and changing the system inheritance-defined bio-systems). This mini-review aims to provide a new conceptual framework for appreciating the genome organization-based information package and its ultimate importance for future genomic and evolutionary studies.