Clinicians' reasoning as reflected in electronic clinical note-entry and reading/retrieval: a systematic review and qualitative synthesis

Documentation of shared decision-making in diagnostic testing for dementia in Dutch general practice: A retrospective study in electronic patient records

OBJECTIVE

To explore (1) documentation of shared decision-making (SDM) in diagnostic testing for dementia in electronic patient records (EPR) in general practice and (2) study whether documentation of SDM is related to specific patient characteristics.

METHODS

In this retrospective observational study, EPRs of 228 patients in three Dutch general practices were explored for the documentation of SDM elements using Elwyn's model (team talk, option talk, decision talk). Patient characteristics (gender, age, comorbidities, chronic polypharmacy, the number of consultations on memory complaints) and decision outcome (wait-and-see, GP diagnostics, referral) were also extracted.

RESULTS

In EPRs of most patients (62.6 %), at least one SDM element was documented. Most often this concerned team talk (61.6 %). Considerably less often option talk (4.3 %) and decision talk (12.8 %) were documented. SDM elements were more frequently documented in patients with lower comorbidity scores and patients with a relatively high number of consultations. Decision talk was more frequently documented in referred patients.

CONCLUSION

Patients' and significant others' needs, goals, and wishes on diagnostic testing for dementia are often documented in EPRs.

PRACTICE IMPLICATIONS

Limited documentation of option and decision talk stresses the need for future SDM interventions to facilitate timely dementia diagnosis.

Impact of clinical note format on diagnostic accuracy and efficiency

BACKGROUND

Clinician notes are structured in a variety of ways. This research pilot tested an innovative study design and explored the impact of note formats on diagnostic accuracy and documentation review time.

OBJECTIVE

To compare two formats for clinical documentation (narrative format vs. list of findings) on clinician diagnostic accuracy and documentation review time.

METHOD

Participants diagnosed written clinical cases, half in narrative format, and half in list format. Diagnostic accuracy (defined as including correct case diagnosis among top three diagnoses) and time spent processing the case scenario were measured for each format. Generalised linear mixed regression models and bias-corrected bootstrap percentile confidence intervals for mean paired differences were used to analyse the primary research questions.

RESULTS

Odds of correctly diagnosing list format notes were 26% greater than with narrative notes. However, there is insufficient evidence that this difference is significant (75% CI 0.8-1.99). On average the list format notes required 85.6 more seconds to process and arrive at a diagnosis compared to narrative notes (95% CI -162.3, -2.77). Of cases where participants included the correct diagnosis, on average the list format notes required 94.17 more seconds compared to narrative notes (75% CI -195.9, -8.83).

CONCLUSION

This study offers note format considerations for those interested in improving clinical documentation and suggests directions for future research. Balancing the priority of clinician preference with value of structured data may be necessary.

IMPLICATIONS

This study provides a method and suggestive results for further investigation in usability of electronic documentation formats.

Documentation dynamics: Note composition, burden, and physician efficiency

OBJECTIVE

To analyze how physician clinical note length and composition relate to electronic health record (EHR)-based measures of burden and efficiency that have been tied to burnout.

DATA SOURCES AND STUDY SETTING

Secondary EHR use metadata capturing physician-level measures from 203,728 US-based ambulatory physicians using the Epic Systems EHR between September 2020 and May 2021.

STUDY DESIGN

In this cross-sectional study, we analyzed physician clinical note length and note composition (e.g., content from manual or templated text). Our primary outcomes were three time-based measures of EHR burden (time writing EHR notes, time in the EHR after-hours, and EHR time on unscheduled days), and one measure of efficiency (percent of visits closed in the same day). We used multivariate regression to estimate the relationship between our outcomes and note length and composition.

DATA EXTRACTION

Physician-week measures of EHR usage were extracted from Epic's Signal platform used for measuring provider EHR efficiency. We calculated physician-level averages for our measures of interest and assigned physicians to overall note length deciles and note composition deciles from six sources, including templated text, manual text, and copy/paste text.

PRINCIPAL FINDINGS

Physicians in the top decile of note length demonstrated greater burden and lower efficiency than the median physician, spending 39% more time in the EHR after hours (p < 0.001) and closing 5.6 percentage points fewer visits on the same day (p < 0.001). Copy/paste demonstrated a similar dose/response relationship, with top-decile copy/paste users closing 6.8 percentage points fewer visits on the same day (p < 0.001) and spending more time in the EHR after hours and on days off (both p < 0.001). Templated text (e.g., Epic's SmartTools) demonstrated a non-linear relationship with burden and efficiency, with very low and very high levels of use associated with increased EHR burden and decreased efficiency.

CONCLUSIONS

"Efficiency tools" like copy/paste and templated text meant to reduce documentation burden and increase provider efficiency may have limited efficacy.

Physicians' Perspectives on a Multi-Dimensional Model for the Roles of Electronic Health Records in Approaching a Proper Differential Diagnosis

Many healthcare organizations have adopted Electronic Health Records (EHRs) to improve the quality of care and help physicians make proper clinical decisions. The vital roles of EHRs can support the accuracy of diagnosis, suggest, and rationalize the provided care to patients. This study aims to understand the roles of EHRs in approaching proper differential diagnosis and optimizing patient safety. This study utilized a cross-sectional survey-based descriptive research design to assess physicians' perceptions of the roles of EHRs on diagnosis quality and safety. Physicians working in tertiary hospitals in Saudi Arabia were surveyed. Three hundred and fifty-one participants were included in the study, of which 61% were male. The main participants were family/general practice (22%), medicine, general (14%), and OB/GYN (12%). Overall, 66% of the participants ranked themselves as IT competent, most of the participants underwent IT self-guided learning, and 65% of the participants always used the system. The results generally reveal positive physicians' perceptions toward the roles of the EHR system on diagnosis quality and safety. There was a statistically significant relationship between user characteristics and the roles of the EHR by enhancing access to care, patient-physician encounter, clinical reasoning, diagnostic testing and consultation, follow-up, and diagnostic safety functionality. The study participants demonstrate positive perceptions of physicians toward the roles of the EHR system in approaching differential diagnosis. Yet, areas of improvement in the design and using EHRs are emphasized.

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.

Merit-based incentive payment system participation and after-hours documentation among US office-based physicians: Findings from the 2021 National Electronic Health Records Survey

BACKGROUND

After-hours documentation burden among US clinicians is often uncompensated work and has been associated with burnout, leading health systems to identify root causes and seek interventions to reduce this. A few studies have suggested quality programme participation (e.g., Merit-Based Incentive Payment System [MIPS]) was associated with a higher administrative burden. However, the association between MIPS participation and after-hours documentation has not been fully explored. Thus, this study aims to assess whether participation in the MIPS programme was independently associated with after-hours documentation burden.

METHODS

We used 2021 data from the National Electronic Health Records Survey. We used a multivariable ordinal logistic regression model to assess whether MIPS participation was associated with the amount of after-hours documentation burden when controlling for other factors. We controlled for physician age, specialty, sex, number of practice locations, number of physicians, practice ownership, whether team support (e.g., scribes) is used for documentation tasks, and whether the practice accepts Medicaid patients.

RESULTS

We included 1801 office-based US physician respondents with complete data for variables of interest. After controlling for other factors, MIPS participation was associated with greater odds of spending a greater number of hours on after-hours documentation (odds ratio = 1.44, 95% confidence interval 1.06-1.95).

CONCLUSIONS

MIPS participation may increase after-hours documentation burden among US office-based physicians, suggesting that physicians may require additional resources to more efficiently report data.

Novel Note Templates to Enhance Signal and Reduce Noise in Medical Documentation: a Prospective Improvement Study

BACKGROUND

The introduction of electronic workflows has allowed for the flow of raw un-contextualized clinical data into medical documentation. As a result, many electronic notes have become replete of "noise" and deplete of clinically significant "signals". There is an urgent need to develop and implement innovative approaches in electronic clinical documentation that improve note quality and reduce unnecessary bloating.

OBJECTIVE

To describe the development and impact of a novel set of templates designed to change the flow of information in medical documentation.

METHODS

This is a multi-hospital nonrandomized prospective improvement study conducted on the Inpatient General Internal Medicine Service across three hospital campuses at the New York University (NYU) Langone Health System. A group of physician leaders representing each campus met biweekly for six months. The output of these meetings included 1) a conceptualization of the note bloat problem as a dysfunction in information flow 2) a set of guiding principles for organizational documentation improvement 3) the design and build of novel electronic templates that reduced the flow of extraneous information into provider notes by providing link outs to best practice data visualizations and 4) a documentation improvement curriculum for inpatient medicine providers. Prior to go-live, pragmatic usability testing was performed with the new progress note template, and the overall user experience measured using the System Usability Scale (SUS). Primary outcomes measures after go-live include template utilization rate and note length in characters.

RESULTS

In usability testing amongst 22 medicine providers, the new progress note template averaged a usability score of 90.6/100 on the System Usability Scale. 77% of providers strongly agreed that the new template was easy to use. 68% strongly agreed that they would like to use the template frequently. In the three months after template implementation, General Internal Medicine providers wrote 65% of all inpatient notes with the new templates. During this period of time the organization saw a 46%, 47%, and 32% reduction in note length for general medicine progress notes, consults, and H&Ps, respectively, when compared to a baseline measurement period prior to interventions.

CONCLUSIONS

A bundled intervention that included deployment of novel templates for inpatient general medicine providers significantly reduced average note length on the clinical service. Templates designed to reduce the flow of extraneous information into provider notes performed well during usability testing, and these templates were rapidly adopted across all hospital campuses. Further research is needed to assess the impact of novel templates on note quality, provider efficiency and patient outcomes.

CLINICALTRIAL

Agreement between patient's description of abdominal symptoms of possible upper gastrointestinal cancer and general practitioner consultation notes: a qualitative analysis of video-recorded UK primary care consultation data

INTRODUCTION

Abdominal symptoms are common in primary care but infrequently might be due to an upper gastrointestinal (UGI) cancer. Patients' descriptions may differ from medical terminology used by general practitioners (GPs). This may affect how information about abdominal symptoms possibly due to an UGI cancer are documented, creating potential missed opportunities for timely investigation.

OBJECTIVES

To explore how abdominal symptoms are communicated during primary care consultations, and identify characteristics of patients' descriptions that underpin variation in the accuracy and completeness with which they are documented in medical records.

METHODS AND ANALYSIS

Primary care consultation video recordings, transcripts and medical records from an existing dataset were screened for adults reporting abdominal symptoms. We conducted a qualitative content analysis to capture alignments (medical record entries matching patient verbal and non-verbal descriptions) and misalignments (symptom information omitted or differing from patient descriptions). Categories were informed by the Calgary-Cambridge guide's 'gathering information' domains and patterns in descriptions explored.

RESULTS

Our sample included 28 consultations (28 patients with 18 GPs): 10 categories of different clinical features of abdominal symptoms were discussed. The information GPs documented about these features commonly did not match what patients described, with misalignments more common than alignments (67 vs 43 instances, respectively). Misalignments often featured patients using vague descriptors, figurative speech, lengthy explanations and broad hand gestures. Alignments were characterised by patients using well-defined terms, succinct descriptions and precise gestures for symptoms with an exact location. Abdominal sensations reported as 'pain' were almost always documented compared with expressions of 'discomfort'.

CONCLUSIONS

Abdominal symptoms that are well defined or communicated as 'pain' may be more salient to GPs than those expressed vaguely or as 'discomfort'. Variable documentation of abdominal symptoms in medical records may have implications for the development of clinical decision support systems and decisions to investigate possible UGI cancer.

Development and Validation of a Machine Learning Model for Automated Assessment of Resident Clinical Reasoning Documentation

BACKGROUND

Residents receive infrequent feedback on their clinical reasoning (CR) documentation. While machine learning (ML) and natural language processing (NLP) have been used to assess CR documentation in standardized cases, no studies have described similar use in the clinical environment.

OBJECTIVE

The authors developed and validated using Kane's framework a ML model for automated assessment of CR documentation quality in residents' admission notes.

DESIGN, PARTICIPANTS, MAIN MEASURES

Internal medicine residents' and subspecialty fellows' admission notes at one medical center from July 2014 to March 2020 were extracted from the electronic health record. Using a validated CR documentation rubric, the authors rated 414 notes for the ML development dataset. Notes were truncated to isolate the relevant portion; an NLP software (cTAKES) extracted disease/disorder named entities and human review generated CR terms. The final model had three input variables and classified notes as demonstrating low- or high-quality CR documentation. The ML model was applied to a retrospective dataset (9591 notes) for human validation and data analysis. Reliability between human and ML ratings was assessed on 205 of these notes with Cohen's kappa. CR documentation quality by post-graduate year (PGY) was evaluated by the Mantel-Haenszel test of trend.

KEY RESULTS

The top-performing logistic regression model had an area under the receiver operating characteristic curve of 0.88, a positive predictive value of 0.68, and an accuracy of 0.79. Cohen's kappa was 0.67. Of the 9591 notes, 31.1% demonstrated high-quality CR documentation; quality increased from 27.0% (PGY1) to 31.0% (PGY2) to 39.0% (PGY3) (p < .001 for trend). Validity evidence was collected in each domain of Kane's framework (scoring, generalization, extrapolation, and implications).

CONCLUSIONS

The authors developed and validated a high-performing ML model that classifies CR documentation quality in resident admission notes in the clinical environment-a novel application of ML and NLP with many potential use cases.

Clinician documentation of patient centered care in the electronic health record

Background

In this study we sought to explore the possibility of using patient centered care (PCC) documentation as a measure of the delivery of PCC in a health system.

Methods

We first selected 6 VA medical centers based on their scores for a measure of support for self-management subscale from a national patient satisfaction survey (the Survey for Healthcare Experience-Patients). We accessed clinical notes related to either smoking cessation or weight management consults. We then annotated this dataset of notes for documentation of PCC concepts including: patient goals, provider support for goal progress, social context, shared decision making, mention of caregivers, and use of the patient's voice. We examined the association of documentation of PCC with patients’ perception of support for self-management with regression analyses.

Results

Two health centers had < 50 notes related to either tobacco cessation or weight management consults and were removed from further analysis. The resulting dataset includes 477 notes related to 311 patients total from 4 medical centers. For a majority of patients (201 out of 311; 64.8%) at least one PCC concept was present in their clinical notes. The most common PCC concepts documented were patient goals (patients n = 126; 63% clinical notes n = 302; 63%), patient voice (patients n = 165, 82%; clinical notes n = 323, 68%), social context (patients n = 105, 52%; clinical notes n = 181, 38%), and provider support for goal progress (patients n = 124, 62%; clinical notes n = 191, 40%). Documentation of goals for weight loss notes was greater at health centers with higher satisfaction scores compared to low. No such relationship was found for notes related to tobacco cessation.

Conclusion

Providers document PCC concepts in their clinical notes. In this pilot study we explored the feasibility of using this data as a means to measure the degree to which care in a health center is patient centered. Practice Implications: clinical EHR notes are a rich source of information about PCC that could potentially be used to assess PCC over time and across systems with scalable technologies such as natural language processing.

Development of a Clinical Reasoning Documentation Assessment Tool for Resident and Fellow Admission Notes: a Shared Mental Model for Feedback

BACKGROUND

Residents and fellows receive little feedback on their clinical reasoning documentation. Barriers include lack of a shared mental model and variability in the reliability and validity of existing assessment tools. Of the existing tools, the IDEA assessment tool includes a robust assessment of clinical reasoning documentation focusing on four elements (interpretive summary, differential diagnosis, explanation of reasoning for lead and alternative diagnoses) but lacks descriptive anchors threatening its reliability.

OBJECTIVE

Our goal was to develop a valid and reliable assessment tool for clinical reasoning documentation building off the IDEA assessment tool.

DESIGN, PARTICIPANTS, AND MAIN MEASURES

The Revised-IDEA assessment tool was developed by four clinician educators through iterative review of admission notes written by medicine residents and fellows and subsequently piloted with additional faculty to ensure response process validity. A random sample of 252 notes from July 2014 to June 2017 written by 30 trainees across several chief complaints was rated. Three raters rated 20% of the notes to demonstrate internal structure validity. A quality cut-off score was determined using Hofstee standard setting.

KEY RESULTS

The Revised-IDEA assessment tool includes the same four domains as the IDEA assessment tool with more detailed descriptive prompts, new Likert scale anchors, and a score range of 0-10. Intraclass correlation was high for the notes rated by three raters, 0.84 (95% CI 0.74-0.90). Scores ≥6 were determined to demonstrate high-quality clinical reasoning documentation. Only 53% of notes (134/252) were high-quality.

CONCLUSIONS

The Revised-IDEA assessment tool is reliable and easy to use for feedback on clinical reasoning documentation in resident and fellow admission notes with descriptive anchors that facilitate a shared mental model for feedback.

Diagnosis Documentation of Critically Ill Children at Admission to a PICU

OBJECTIVES

Multidisciplinary PICU teams must effectively share information while caring for critically ill children. Clinical documentation helps clinicians develop a shared understanding of the patient's diagnosis, which informs decision-making. However, diagnosis-related documentation in the PICU is understudied, thus limiting insights into how pediatric intensivists convey their diagnostic reasoning. Our objective was to describe how pediatric critical care clinicians document patients' diagnoses at PICU admission.

DESIGN

Retrospective mixed methods study describing diagnosis documentation in electronic health records.

SETTING

Academic tertiary referral PICU.

PATIENTS

Children 0-17 years old admitted nonelectively to a single PICU over 1 year.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One hundred PICU admission notes for 96 unique patients were reviewed. In 87% of notes, both attending physicians and residents or advanced practice providers documented a primary diagnosis; in 13%, primary diagnoses were documented by residents or advanced practice providers alone. Most diagnoses (72%) were written as narrative free text, 11% were documented as problem lists/billing codes, and 17% used both formats. At least one rationale was documented to justify the primary diagnosis in 91% of notes. Diagnostic uncertainty was present in 52% of notes, most commonly suggested by clinicians' use of words indicating uncertainty (65%) and documentation of differential diagnoses (60%). Clinicians' integration and interpretation of information varied in terms of: 1) organization of diagnosis narratives, 2) use of contextual details to clarify the diagnosis, and 3) expression of diagnostic uncertainty.

CONCLUSIONS

In this descriptive study, most PICU admission notes documented a rationale for the primary diagnosis and expressed diagnostic uncertainty. Clinicians varied widely in how they organized diagnostic information, used contextual details to clarify the diagnosis, and expressed uncertainty. Future work is needed to determine how diagnosis narratives affect clinical decision-making, patient care, and outcomes.

Characterizing styles of clinical note production and relationship to clinical work hours among first-year residents

OBJECTIVE

To characterize variation in clinical documentation production patterns, how this variation relates to individual resident behavior preferences, and how these choices relate to work hours.

MATERIALS AND METHODS

We used unsupervised machine learning with clinical note metadata for 1265 progress notes written for 279 patient encounters by 50 first-year residents on the Hospital Medicine service in 2018 to uncover distinct note-level and user-level production patterns. We examined average and 95% confidence intervals of median user daily work hours measured from audit log data for each user-level production pattern.

RESULTS

Our analysis revealed 10 distinct note-level and 5 distinct user-level production patterns (user styles). Note production patterns varied in when writing occurred and in how dispersed writing was through the day. User styles varied in which note production pattern(s) dominated. We observed suggestive trends in work hours for different user styles: residents who preferred producing notes in dispersed sessions had higher median daily hours worked while residents who preferred producing notes in the morning or in a single uninterrupted session had lower median daily hours worked.

DISCUSSION

These relationships suggest that note writing behaviors should be further investigated to understand what practices could be targeted to reduce documentation burden and derivative outcomes such as resident work hour violations.

CONCLUSION

Clinical note documentation is a time-consuming activity for physicians; we identify substantial variation in how first-year residents choose to do this work and suggestive trends between user preferences and work hours.

The Healthcare Journey of Women With Advanced Gynecological Cancer From Diagnosis Through Terminal Illness: Qualitative Analysis of Progress Note Data

OBJECTIVE

To examine women's journeys with gynecologic cancer from before diagnosis through death and identify elements of their healthcare experience that warrant improvement.

METHODS

This exploratory study used longitudinal progress notes data from a multispecialty practice in Northern California. The sample included women with stage IV gynecological cancer diagnosed after 2011 and who died before 2018. Available progress notes from prior to diagnosis to death were qualitatively analyzed.

RESULTS

We identified 32 women, (median age 61 years) with mostly uterine (n=17) and ovarian (n=9) cancers and median survival of 9.2 months (min:2.9 and max:47.5). Sixteen (50%) received outpatient palliative care and 18 (56%) received hospice care. The analysis found wide variation in documentation about communication about diagnosis, prognosis, goals of care, stopping treatment, and starting hospice care. Challenges included escalating/severe symptoms, repeated urgent care/emergency department/hospital encounters, and lack of or late access to palliative and hospice care. Notes also illustrated how patient background and goals influenced care trajectory and communication. Documentation styles varied substantially, with palliative care notes more consistently documenting conversations about goals of care and psychosocial needs.

CONCLUSION

This analysis of longitudinal illness experience of women with advanced gynecological cancer suggests that clinicians may want to (1) prioritize earlier discussion about goals of care; (2) provide supplemental support to patients with higher needs, possibly through palliative care or navigation; and (3) write notes to enhance patient understanding now that patients may access all notes.

Building the evidence-base to reduce electronic health record-related clinician burden

Clinicians face competing pressures of being clinically productive while using imperfect electronic health record (EHR) systems and maximizing face-to-face time with patients. EHR use is increasingly associated with clinician burnout and underscores the need for interventions to improve clinicians' experiences. With an aim of addressing this need, we share evidence-based informatics approaches, pragmatic next steps, and future research directions to improve 3 of the highest contributors to EHR burden: (1) documentation, (2) chart review, and (3) inbox tasks. These approaches leverage speech recognition technologies, natural language processing, artificial intelligence, and redesign of EHR workflow and user interfaces. We also offer a perspective on how EHR vendors, healthcare system leaders, and policymakers all play an integral role while sharing responsibility in helping make evidence-based sociotechnical solutions available and easy to use.

Feeling and thinking: can theories of human motivation explain how EHR design impacts clinician burnout?

The psychology of motivation can help us understand the impact of electronic health records (EHRs) on clinician burnout both directly and indirectly. Informatics approaches to EHR usability tend to focus on the extrinsic motivation associated with successful completion of clearly defined tasks in clinical workflows. Intrinsic motivation, which includes the need for autonomy, sense-making, creativity, connectedness, and mastery is not well supported by current designs and workflows. This piece examines existing research on the importance of 3 psychological drives in relation to healthcare technology: goal-based decision-making, sense-making, and agency/autonomy. Because these motives are ubiquitous, foundational to human functioning, automatic, and unconscious, they may be overlooked in technological interventions. The results are increased cognitive load, emotional distress, and unfulfilling workplace environments. Ultimately, we hope to stimulate new research on EHR design focused on expanding functionality to support intrinsic motivation, which, in turn, would decrease burnout and improve care.

Documentation of ethically relevant information in out-of-hospital resuscitation is rare: a Danish nationwide observational study of 16,495 out-of-hospital cardiac arrests

Background

Decision-making in out-of-hospital cardiac arrest should ideally include clinical and ethical factors. Little is known about the extent of ethical considerations and their influence on prehospital resuscitation. We aimed to determine the transparency in medical records regarding decision-making in prehospital resuscitation with a specific focus on ethically relevant information and consideration in resuscitation providers’ documentation.

Methods

This was a Danish nationwide retrospective observational study of out-of-hospital cardiac arrests from 2016 through 2018. After an initial screening using broadly defined inclusion criteria, two experienced philosophers performed a qualitative content analysis of the included medical records according to a preliminary codebook. We identified ethically relevant content in free-text fields and categorised the information according to Beauchamp and Childress’ four basic bioethical principles: autonomy, non-maleficence, beneficence, and justice.

Results

Of 16,495 medical records, we identified 759 (4.6%) with potentially relevant information; 710 records (4.3%) contained ethically relevant information, whereas 49 did not. In general, the documentation was vague and unclear. We identified four kinds of ethically relevant information: patients’ wishes and perspectives on life; relatives’ wishes and perspectives on patients’ life; healthcare professionals’ opinions and perspectives on resuscitation; and do-not-resuscitate orders. We identified some “best practice” examples that included all perspectives of decision-making.

Conclusions

There is sparse and unclear evidence on ethically relevant information in the medical records documenting resuscitation after out-of-hospital cardiac arrests. However, the “best practice” examples show that providing sufficient documentation of decision-making is, in fact, feasible. To ensure transparency surrounding prehospital decisions in cardiac arrests, we believe that it is necessary to ensure more systematic documentation of decision-making in prehospital resuscitation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12910-021-00654-y.

Investigation of usability problems of electronic medical record systems in the emergency department

BACKGROUND

Despite the benefits of using electronic medical record (EMR) systems, existing studies show that many healthcare providers are uncertain regarding their usability. The usability issues of these systems decrease their efficiency, discourage clinicians, and cause dissatisfaction among patients, which may result in safety risks and harm.

OBJECTIVE

The aim of this study was to collect and analyze EMR system usability problems from actual users. Practical user interface guidelines were presented based on the medical practices of these users.

METHODS

Employing an online questionnaire with a seven-point Likert scale, usability issues of EMR systems were collected from 200 emergency department healthcare providers (103 physicians (medical doctors) and 97 nurses) from South Korea.

RESULTS

The most common usability problem among the physicians and nurses was generating in-patient selection. This pertained to the difficulty in finding the required information on-screen because of poor visibility and a lack of distinctiveness.

CONCLUSIONS

The major problems of EMR systems and their causes were identified. It is recommended that intensive visual enhancement of EMR system interfaces should be implemented to support user tasks. By providing a better understanding of the current usability problems among medical practitioners, the results of this study can be useful for developing EMR systems with increased effectiveness and efficiency.

Physicians' perceptions about narrative note sections format and content: A multi-specialty survey

OBJECTIVE

To assess physicians' perceptions about narrative note sections format and content commonly reported in visit notes to inform future research and EHR development.

METHODS

We conducted two online surveys with a multi-specialty panel of outpatient physicians from a large health system to collect their perceptions of the usefulness of three narrative formats and the relevance of content reported in the note sections history of present illness (HPI) and assessment and plan (AP). Survey questions were responded with a 7-point Likert scale and include two open-ended questions for comments on challenges and suggestions related to electronic clinical documentation.

RESULTS

Eighty-eight physicians completed the surveys. The most preferred format for HPI was story (i.e., coherent paragraph), followed by list without categories (i.e., non-categorized sentences) and list with categories (i.e., categorized sentences). The most preferred format for AP was list with categories, followed by story and list without categories. The most relevant type of content in HPI was temporal information and finding/condition. The most relevant type of content reported in AP was intervention and reasons and justifications. Challenges frequently mentioned include suboptimal note creation interfaces and bloated notes, and the most common suggestions for improvements are related to note entry facilitators and organizational improvements.

CONCLUSION

Physicians' input is extremely valuable to inform improvements to EHRs. More effective clinical documentation systems should include less intrusive, more intuitive and automated user interfaces for note creation, smarter autopoluation functionality and linkage between note content and data from other parts of the record.

Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance

INTRODUCTION

Drug safety research asks causal questions but relies on observational data. Confounding bias threatens the reliability of studies using such data. The successful control of confounding requires knowledge of variables called confounders affecting both the exposure and outcome of interest. However, causal knowledge of dynamic biological systems is complex and challenging. Fortunately, computable knowledge mined from the literature may hold clues about confounders. In this paper, we tested the hypothesis that incorporating literature-derived confounders can improve causal inference from observational data.

METHODS

We introduce two methods (semantic vector-based and string-based confounder search) that query literature-derived information for confounder candidates to control, using SemMedDB, a database of computable knowledge mined from the biomedical literature. These methods search SemMedDB for confounders by applying semantic constraint search for indications treated by the drug (exposure) and that are also known to cause the adverse event (outcome). We then include the literature-derived confounder candidates in statistical and causal models derived from free-text clinical notes. For evaluation, we use a reference dataset widely used in drug safety containing labeled pairwise relationships between drugs and adverse events and attempt to rediscover these relationships from a corpus of 2.2 M NLP-processed free-text clinical notes. We employ standard adjustment and causal inference procedures to predict and estimate causal effects by informing the models with varying numbers of literature-derived confounders and instantiating the exposure, outcome, and confounder variables in the models with dichotomous EHR-derived data. Finally, we compare the results from applying these procedures with naive measures of association (χ2 and reporting odds ratio) and with each other.

RESULTS AND CONCLUSIONS

We found semantic vector-based search to be superior to string-based search at reducing confounding bias. However, the effect of including more rather than fewer literature-derived confounders was inconclusive. We recommend using targeted learning estimation methods that can address treatment-confounder feedback, where confounders also behave as intermediate variables, and engaging subject-matter experts to adjudicate the handling of problematic covariates.

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.

Formal representation of patients' care context data: the path to improving the electronic health record

Objective

To develop a collection of concept-relationship-concept tuples to formally represent patients’ care context data to inform electronic health record (EHR) development.

Materials and Methods

We reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources.

Results

We annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts.

Conclusions

We produced a robust set of 82 tuples useful to represent patients’ care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.

Teasing out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine

The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI (and those who control it) has created challenges to conventional assessments of patient and physician autonomy. The unclear legal relationship between AI and its users cannot be settled presently, an progress in AI and its implementation in patient care will necessitate an iterative discourse to preserve humanitarian concerns in future models of care. This paper proposes that physicians should neither uncritically accept nor unreasonably resist developments in AI but must actively engage and contribute to the discourse, since AI will affect their roles and the nature of their work. One's moral imaginative capacity must be engaged in the questions of beneficence, autonomy, and justice of AI and whether its integration in healthcare has the potential to augment or interfere with the ends of medical practice.

Association between ICU interruptions and physicians trainees' electronic health records efficiency

The intensive care unit (ICU) is a stressful and complex environment in due to its dynamic nature and severity of admitted patients. EHR interface design can be cumbersome and lead to prolonged times to complete tasks. This paper investigated the relationship between a prominent EHR interface design and interruptions with physician's efficiency during patient chart review at ICU Pre-Rounds. We conducted a live observation of ICU physicians in a 30-bed MICU at a tertiary, southeastern medical center. Directly after the observation sessions, the physicians completed a modified System Usability Scale (SUS) survey. A total of 52 EHR patient chart reviews were observed at the MICU Pre-rounds. There was statistically significant positive correlation between time spent to review patient EHR with both number of scrolling(p-value<0.0001) across EHR interface; and with number of visited EHR  screens (p-value=0.0444). There was positive correlation between number of interruptions with time spent to review patient EHR during ICU prerounds. EHR design and the occurrence of interruptions lead to reduced physician-EHR efficiency levels. We report that the number of scrolling and visited screens executed by physicians to gather the required information was associated with increased screen time and consequently decreased physician efficiency.

Putting the "why" in "EHR": capturing and coding clinical cognition

Complaints about electronic health records, including information overload, note bloat, and alert fatigue, are frequent topics of discussion. Despite substantial effort by researchers and industry, complaints continue noting serious adverse effects on patient safety and clinician quality of life. I believe solutions are possible if we can add information to the record that explains the “why” of a patient’s care, such as relationships between symptoms, physical findings, diagnostic results, differential diagnoses, therapeutic plans, and goals. While this information may be present in clinical notes, I propose that we modify electronic health records to support explicit representation of this information using formal structure and controlled vocabularies. Such information could foster development of more situation-aware tools for data retrieval and synthesis. Informatics research is needed to understand what should be represented, how to capture it, and how to benefit those providing the information so that their workload is reduced.

Capturing Clinician Reasoning in Electronic Health Records: An Exploratory Study of Under-Treated Essential Hypertension

Monitoring response to antihypertensive medications is a frequent reason for outpatient visits. Blood pressure (BP) is often documented as elevated, but no change in medication occurs (Medication Non-adjustment or MNA). We studied the frequency of MNA, reasons for non-adjustment, how reasons (including reasons for patient nonadherence) were documented, and whether they could be represented in a clinical care context ontology. We examined 129 visit notes with MNA occurring in 80 cases (59%). We coded MNA as Conscious Maintenance (patient adherent but clinician continues therapy for stated reason), Nonadherence (clinician attributes BP elevation to patient nonadherence), and Finding Not Addressed (clinician does not indicate reasoning for MNA). We characterized Conscious Maintenance with 11 subcodes and Nonadherence with 6 subcodes. Our ontology successfully represented relationships between concepts and reasoning, supporting the feasibility of formal representation of clinical care contexts for patient care, decision support and research.

The anatomy of clinical documentation: an assessment and classification of narrative note sections format and content

Introduction. We systematically analyzed the most commonly used narrative note formats and content found in primary and specialty care visit notes to inform future research and electronic health record (EHR) development. Methods. We extracted data from the history of present illness (HPI) and impression and plan (IP) sections of 80 primary and specialty care visit notes. Two authors iteratively classified the format of the sections and compared the size of each section and the overall note size between primary and specialty care notes. We then annotated the content of these sections to develop a taxonomy of types of data communicated in the narrative note sections. Results. Both HPI and IP were significantly longer in primary care when compared to specialty care notes (HPI: n = 187 words, SD[130] vs. n = 119 words, SD [53]; p = 0.004 / IP: n = 270 words, SD [145] vs. n = 170 words, SD [101]; p < 0.001). Although we did not find a significant difference in the overall note size between the two groups, the proportion of HPI and IP content in relation to the total note size was significantly higher in primary care notes (40%, SD [13] vs. 28%, SD [11]; p < 0.001). We identified five combinations of format of HPI + IP sections respectively: (A) story + list with categories; (B) story + story; (C) list without categories + list with categories; (D) list with categories + list with categories; and (E) list with categories + story. HPI and IP content was significantly smaller in combination C compared to combination A (-172 words, [95% Conf. -326, -17.89]; p = 0.02). We identified seven taxa representing 45 different types of data: finding/condition documented (n = 14), intervention documented (n = 9), general descriptions and definitions (n = 7), temporal information (n = 6), reasons and justifications (n = 4), participants and settings (n = 4), and clinical documentation (n = 1). Conclusion. We identified commonly used narrative note section formats and developed a taxonomy of narrative note content to help researchers to tailor their efforts and design more efficient clinical documentation systems.

Accelerating the De-Personalization of Medicine: The Ethical Toxicities of COVID-19

The COVID-19 pandemic has, of necessity, demanded the rapid incorporation of virtual technologies which, suddenly, have superseded the physical medical encounter. These imperatives have been implemented in advance of evaluation, with unclear risks to patient care and the nature of medical practice that might be justifiable in the context of a pandemic but cannot be extrapolated as a new standard of care. Models of care fit for purpose in a pandemic should not be generalized to reconfigure medical care as virtual by default, and personal by exception at the conclusion of the emergency.

Twilighted Homegrown Systems: The Experience of Six Traditional Electronic Health Record Developers in the Post-Meaningful Use Era

Objectives  This study aimed to understand if and how homegrown electronic health record (EHR) systems are used in the post–Meaningful Use (MU) era according to the experience of six traditional EHR developers.

Methods  We invited informatics leaders from a convenience sample of six health care organizations that have recently replaced their long used homegrown systems with commercial EHRs. Participants were asked to complete a written questionnaire with open-ended questions designed to explore if and how their homegrown system(s) is being used and maintained after adoption of a commercial EHR. We used snowball sampling to identify other potential respondents and institutions.

Results  Participants from all six organizations included in our initial sample completed the questionnaire and provided referrals to four other organizations; from these, two did not respond to our invitations and two had not yet replaced their system and were excluded. Two organizations (Columbia University and University of Alabama at Birmingham) still use their homegrown system for direct patient care and as a downtime system. Four organizations (Intermountain Healthcare, Partners Healthcare, Regenstrief Institute, and Vanderbilt University) kept their systems primarily to access historical data. All organizations reported the need to continue to develop or maintain local applications despite having adopted a commercial EHR. The most common applications developed include display and visualization tools and clinical decision support systems.

Conclusion  Homegrown EHR systems continue to be used for different purposes according to the experience of six traditional homegrown EHR developers. The annual cost to maintain these systems varies from $21,000 to over 1 million. The collective experience of these organizations indicates that commercial EHRs have not been able to provide all functionality needed for patient care and local applications are often developed for multiple purposes, which presents opportunities for future research and EHR development.

Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis

OBJECTIVE

The study sought to describe the literature describing clinical reasoning ontology (CRO)-based clinical decision support systems (CDSSs) and identify and classify the medical knowledge and reasoning concepts and their properties within these ontologies to guide future research.

METHODS

MEDLINE, Scopus, and Google Scholar were searched through January 30, 2019, for studies describing CRO-based CDSSs. Articles that explored the development or application of CROs or terminology were selected. Eligible articles were assessed for quality features of both CDSSs and CROs to determine the current practices. We then compiled concepts and properties used within the articles.

RESULTS

We included 38 CRO-based CDSSs for the analysis. Diversity of the purpose and scope of their ontologies was seen, with a variety of knowledge sources were used for ontology development. We found 126 unique medical knowledge concepts, 38 unique reasoning concepts, and 240 unique properties (137 relationships and 103 attributes). Although there is a great diversity among the terms used across CROs, there is a significant overlap based on their descriptions. Only 5 studies described high quality assessment.

CONCLUSION

We identified current practices used in CRO development and provided lists of medical knowledge concepts, reasoning concepts, and properties (relationships and attributes) used by CRO-based CDSSs. CRO developers reason that the inclusion of concepts used by clinicians' during medical decision making has the potential to improve CDSS performance. However, at present, few CROs have been used for CDSSs, and high-quality studies describing CROs are sparse. Further research is required in developing high-quality CDSSs based on CROs.

Copy-and-Paste in Medical Student Notes: Extent, Temporal Trends, and Relationship to Scholastic Performance

BACKGROUND

Medical students may observe and subsequently perpetuate redundancy in clinical documentation, but the degree of redundancy in student notes and whether there is an association with scholastic performance are unknown.

OBJECTIVES

This study sought to quantify redundancy, defined generally as the proportion of similar text between two strings, in medical student notes and evaluate the relationship between note redundancy and objective indicators of student performance.

METHODS

Notes generated by medical students rotating through their medicine clerkship during a single academic year at our institution were analyzed. A student-patient interaction (SPI) was defined as a history and physical and at least two contiguous progress notes authored by the same student during a single patient's hospitalization. For some students, SPI pairs were available from early and late in the clerkship. Redundancy between analogous sections of consecutive notes was calculated on a 0 to 100% scale and was derived from edit distance, the number of changes needed to transform one text string into another. Indicators of student performance included United States Medical Licensing Exam (USMLE) scores.

RESULTS

Ninety-four single SPIs and 58 SPI pairs were analyzed. Redundancy in the assessment/plan section was high (40%) and increased within individual SPIs (to 60%; p < 0.001) and between SPI pairs over the course of the clerkship (by 30-40%; p < 0.001). Students in the lowest tertile of USMLE step II clinical knowledge scores had higher redundancy in the assessment/plan section than their classmates (67 ± 24% vs. 38 ± 22%; p = 0.002).

CONCLUSION

During the medicine clerkship, the assessment/plan section of medical student notes became more redundant over a patient's hospital course and as students gained clinical experience. These trends may be indicative of deficiencies in clinical knowledge or reasoning, as evidenced by performance on some standardized evaluations.

Unintended Consequences of Nationwide Electronic Health Record Adoption: Challenges and Opportunities in the Post-Meaningful Use Era

The US health system has recently achieved widespread adoption of electronic health record (EHR) systems, primarily driven by financial incentives provided by the Meaningful Use (MU) program. Although successful in promoting EHR adoption and use, the program, and other contributing factors, also produced important unintended consequences (UCs) with far-reaching implications for the US health system. Based on our own experiences from large health information technology (HIT) adoption projects and a collection of key studies in HIT evaluation, we discuss the most prominent UCs of MU: failed expectations, EHR market saturation, innovation vacuum, physician burnout, and data obfuscation. We identify challenges resulting from these UCs and provide recommendations for future research to empower the broader medical and informatics communities to realize the full potential of a now digitized health system. We believe that fixing these unanticipated effects will demand efforts from diverse players such as health care providers, administrators, HIT vendors, policy makers, informatics researchers, funding agencies, and outside developers; promotion of new business models; collaboration between academic medical centers and informatics research departments; and improved methods for evaluations of HIT.