Safe Practices for Copy and Paste in the EHR. Systematic Review, Recommendations, and Novel Model for Health IT Collaboration

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

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

Real world challenges in maintaining data integrity in electronic health records in a cancer program

Electronic Health Record (EHR) systems increase clerical workload, promote copy-paste and error propagation. Documentation error rate in cancer diagnosis and treatment was examined in 776 patient records. Fifteen percent of the charts contained an error. Modern EHR systems, patient portals and engagement tools may facilitate the maintenance of accurate information.

Artificial intelligence: revolutionizing cardiology with large language models

Natural language processing techniques are having an increasing impact on clinical care from patient, clinician, administrator, and research perspective. Among others are automated generation of clinical notes and discharge letters, medical term coding for billing, medical chatbots both for patients and clinicians, data enrichment in the identification of disease symptoms or diagnosis, cohort selection for clinical trial, and auditing purposes. In the review, an overview of the history in natural language processing techniques developed with brief technical background is presented. Subsequently, the review will discuss implementation strategies of natural language processing tools, thereby specifically focusing on large language models, and conclude with future opportunities in the application of such techniques in the field of cardiology.

Designing a minimum data set of laboratory data for the electronic summary sheet of pediatric ward in Iran: A cross-sectional study

Background and Aim

Iranian hospitals are provided with hospital information systems (HISs) from different vendors, which make it hardly possible to summarize laboratory data in an consistent manner. Therefore, there is a need to design a minimum data set of laboratory data that will define standard criteria and reduce potential medical errors. The purpose of this study was to design a minimum data set (MDS) of laboratory data for an electronic summary sheet to be used in the pediatric ward of Iranian hospitals.

Methods

This study consists of three phases. In the first phase, out of 3997 medical records from the pediatric ward, 604 summary sheets were chosen as sample. The laboratory data of these sheets were examined and the recorded tests were categorized. In the second phase, based on the types of diagnosis we developed a list of tests. Then we asked the physicians of the ward to select which ones should be documented for each patient's diagnosis. In the third phase, the tests that were reported in 21%-80% of the records, and were verified by the same percentage of physicians, were evaluated by the experts' panel.

Results

In the first phase, 10,224 laboratory data were extracted. Of these, 144 data elements reported in more than 80% of the records, and more than 80% of experts approved them to be included in the MDS for patients' summary sheet. After data elements were investigated in the experts' panel, 292 items were chosen for the final list of the data set.

Conclusions

This MDS was designed such that, if implemented in hospital information systems, it could automatically enable registering data in the summary sheet when patient's diagnosis is registered.

Copy-Pasting in Patients' Electronic Medical Records (EMRs): Use Judiciously and With Caution

An electronic medical record (EMR) is an electronic, comprehensive, and up-to-date compilation of a patient's medical history and information stored in a secure digital format. It provides real-time access to patient data, enabling healthcare providers to make informed decisions quickly and accurately. EMR systems streamline a patient's healthcare journey and enable shared care across the medical practice. By providing a comprehensive view of a patient's medical history, EMRs can be invaluable tools for physicians and healthcare providers, allowing them to collaborate more effectively and provide better care. Additionally, EMRs can help reduce paperwork, improve accuracy, and increase efficiency, ultimately leading to improved patient outcomes. The true potential of EMR systems can be realized when they are used in conjunction with evidence-based medicine methodologies, quality improvement initiatives, and team-based care. This combination of technologies and practices can revolutionize healthcare delivery, improving patient outcomes, greater efficiency, and cost savings. "Copy-pasting" is an essential feature of EMR systems, with physicians relying on it for up to 35.7% of their workflow. By leveraging the copy-pasting feature of their EMR system, physicians can ensure that their data capture is accurate and timely, leading to better patient care. Copy-pasting can be a valuable tool for physicians, saving time and allowing them to focus on practical clinical issues. However, it is essential to note that while most clinicians copy-paste, 25% of them believe it can lead to a high frequency of medical errors, with the potential for a significant number of errors being attributed to this practice. Therefore, physicians must exercise caution when copy-pasting and take the necessary steps to ensure accuracy and reduce the risk of errors. Copy-pasting can cause severe adverse patient events by introducing new inaccuracies, rapidly spreading inaccurate or outdated information, leading to discordant notes, and creating long notes that mask essential clinical information. Despite these risks, copy-pasting has become widely used in EMRs. Additionally, copy-pasting can reduce the time spent on documentation, allowing healthcare providers to focus more on patient care. Inappropriate copy-pasting can have serious consequences, such as compromising data integrity, endangering patient safety, increasing costs, and even leading to fraudulent malpractice claims. In conclusion, copy-pasting can be helpful for healthcare professionals, but it must be used cautiously. Proper education and safeguards should be implemented to ensure accuracy and up-to-date patient data. Additionally, healthcare professionals should be aware of the legal implications of copy-pasting, as it may be considered a form of medical malpractice. With the proper precautions, copy-pasting can be a safe and efficient way to save time and reduce errors in patient records.

Do electronic health record systems "dumb down" clinicians?

A panel sponsored by the American College of Medical Informatics (ACMI) at the 2021 AMIA Symposium addressed the provocative question: "Are Electronic Health Records dumbing down clinicians?" After reviewing electronic health record (EHR) development and evolution, the panel discussed how EHR use can impair care delivery. Both suboptimal functionality during EHR use and longer-term effects outside of EHR use can reduce clinicians' efficiencies, reasoning abilities, and knowledge. Panel members explored potential solutions to problems discussed. Progress will require significant engagement from clinician-users, educators, health systems, commercial vendors, regulators, and policy makers. Future EHR systems must become more user-focused and scalable and enable providers to work smarter to deliver improved care.

It's time to change our documentation philosophy: writing better neurology notes without the burnout

Succinct clinical documentation is vital to effective twenty-first-century healthcare. Recent changes in outpatient and inpatient evaluation and management (E/M) guidelines have allowed neurology practices to make changes that reduce the documentation burden and enhance clinical note usability. Despite favorable changes in E/M guidelines, some neurology practices have not moved quickly to change their documentation philosophy. We argue in favor of changes in the design, structure, and implementation of clinical notes that make them shorter yet still information-rich. A move from physician-centric to team documentation can reduce work for physicians. Changing the documentation philosophy from "bigger is better" to "short but sweet" can reduce the documentation burden, streamline the writing and reading of clinical notes, and enhance their utility for medical decision-making, patient education, medical education, and clinical research. We believe that these changes can favorably affect physician well-being without adversely affecting reimbursement.

Summarizing Patients' Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models

Automatically summarizing patients' main problems from daily progress notes using natural language processing methods helps to battle against information and cognitive overload in hospital settings and potentially assists providers with computerized diagnostic decision support. Problem list summarization requires a model to understand, abstract, and generate clinical documentation. In this work, we propose a new NLP task that aims to generate a list of problems in a patient's daily care plan using input from the provider's progress notes during hospitalization. We investigate the performance of T5 and BART, two state-of-the-art seq2seq transformer architectures, in solving this problem. We provide a corpus built on top of progress notes from publicly available electronic health record progress notes in the Medical Information Mart for Intensive Care (MIMIC)-III. T5 and BART are trained on general domain text, and we experiment with a data augmentation method and a domain adaptation pre-training method to increase exposure to medical vocabulary and knowledge. Evaluation methods include ROUGE, BERTScore, cosine similarity on sentence embedding, and F-score on medical concepts. Results show that T5 with domain adaptive pre-training achieves significant performance gains compared to a rule-based system and general domain pre-trained language models, indicating a promising direction for tackling the problem summarization task.

Disappearing Help Text: Implementing a Note-Based Tool for In-Line Clinical Decision Support and Note Bloat Reduction

OBJECTIVE

The authors describe a novel solution to the challenges of lengthy notes and poor note readability by creating an unobtrusive clinical decision support tool named "disappearing help text."

METHODS

We designed this tool in Pediatric Hospital Medicine (PHM) note templates to provide in-line decision support on best documentation practices, note bloat reduction, billing compliance, and provider workflow enhancement.

RESULTS

After template changes that utilized disappearing help text, we reduced the percent of notes utilizing any laboratory SmartLink from 90.2 to 15.3% for admission notes (p <0.001), 92.6 to 17.8% for progress notes (p <0.001), and 14 to 7.2% for discharge summaries (p <0.001). In admission and progress notes, this correlated with a significant reduction in the median note length as a proxy of note bloat reduction, with a 18.7% character count reduction in progress notes (p <0.001) and a 6.4% reduction in admission notes (p <0.001). PHM coding queries decreased from an average of 42 per month to 36 per month, and there was no change in PHM attending billing compliance audit performance.

DISCUSSION

Note template changes that utilized disappearing help text significantly reduced the length of both progress and admission notes, a proxy for note bloat reduction, without negatively impacting coding query frequency or internal billing audit performance. One factor that likely contributed to this reduction in note length is the reduced usage of laboratory SmartLinks prompted by disappearing help text.

CONCLUSION

We present the use of in-line disappearing help text embedded into note templates as a clinical decision support tool to improve note readability, educate trainees on note documentation, and protect confidential teen information. Help text implementation correlated with a reduction in the automatic insertion of laboratories into notes and a decrease in note character count.

Prevalence and Sources of Duplicate Information in the Electronic Medical Record

IMPORTANCE

Duplicated text is a well-documented hazard in electronic medical records (EMRs), leading to wasted clinician time, medical error, and burnout. This study hypothesizes that text duplication is prevalent and increases with time and EMR size and that duplicate information is shared across authors.

OBJECTIVE

To examine the prevalence and scope of duplication behavior in clinical notes from a large academic health system and the factors associated with duplication.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, cross-sectional analysis of note length and content duplication rates used a set of 10 adjacent word tokens (ie, a 10-gram) sliding-window approach to identify spans of text duplicated exactly from earlier notes in a patient's record for all inpatient and outpatient notes written within the University of Pennsylvania Health System from January 1, 2015, through December 31, 2020. Text duplicated from a different author vs text duplicated from the same author was quantified. Furthermore, novel text and duplicated text per author for various note types and author types, as well as per patient record by number of notes in the record, were quantified. Information scatter, another documentation hazard, was defined as the inverse of novel text per note, and the association between information duplication and information scatter was graphed. Data analysis was performed from January to March 2022.

MAIN OUTCOMES AND MEASURES

Total, novel, and duplicate text by note type and note author were determined, as were the mean intra-author and inter-author duplication per note by type and author.

RESULTS

There were a total of 104 456 653 notes for 1 960 689 unique patients consisting of 32 991 489 889 words; 50.1% of the total text in the record (16 523 851 210 words) was duplicated from prior text written about the same patient. The duplication fraction increased year-over-year, from 33.0% for notes written in 2015 to 54.2% for notes written in 2020. Of the text duplicated, 54.1% came from text written by the same author, whereas 45.9% was duplicated from a different author. Records with more notes had more total duplicate text, approaching 60%. Note types with high information scatter tended to have low information overload, and vice versa, suggesting a trade-off between these 2 hazards under the current documentation paradigm.

CONCLUSIONS AND RELEVANCE

Duplicate text casts doubt on the veracity of all information in the medical record, making it difficult to find and verify information in day-to-day clinical work. The findings of this cross-sectional study suggest that text duplication is a systemic hazard, requiring systemic interventions to fix, and simple solutions such as banning copy-paste may have unintended consequences, such as worsening information scatter. The note paradigm should be further examined as a major cause of duplication and scatter, and alternative paradigms should be evaluated.

Can Checklists Solve Our Ward Round Woes? A Systematic Review

BACKGROUND

Accurate and thorough surgical ward round documentation is crucial for maintaining quality clinical care. Accordingly, checklists have been proposed to improve ward round documentation. This systematic review aimed to evaluate the literature investigating the use of checklists to improve surgical ward round documentation.

METHODS

MEDLINE, EMBASE, and PsycINFO were searched on August 16, 2021. Study selection, data extraction, and risk of bias assessment were performed in duplicate. We included English studies that investigated the use of checklists during ward rounds in various surgical subspecialties compared to routine care, where the rates of documentation were reported as outcomes. We excluded studies that used checklists in outpatient, non-surgical, or pediatric settings. Due to heterogeneity of outcome measures, meta-analysis was precluded. This study was registered with PROSPERO (ID: CRD42021273735) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 (PRISMA 2020) reporting guidelines.

RESULTS

A total of 206 studies were identified, only 9 were suitable for inclusion. All included studies were single-center observational studies, spanning across seven surgical specialties. Rates of documentation on 4-23 parameters were reported. Documentation for all measured outcomes improved in 8/9 studies; however, statistical analyses were not included. There was a high risk of bias due to the nature of observational studies.

CONCLUSION

Ward round checklists can serve as a useful tool to improve inpatient care and safety. Currently, there is no high-level evidence showing the effectiveness of checklists on ward round documentation. The synthesis of results indicates that further high-quality research is imperative.

Workarounds in Electronic Health Record Systems and the Revised Sociotechnical Electronic Health Record Workaround Analysis Framework: Scoping Review

BACKGROUND

Electronic health record (EHR) system users devise workarounds to cope with mismatches between workflows designed in the EHR and preferred workflows in practice. Although workarounds appear beneficial at first sight, they frequently jeopardize patient safety, the quality of care, and the efficiency of care.

OBJECTIVE

This review aims to aid in identifying, analyzing, and resolving EHR workarounds; the Sociotechnical EHR Workaround Analysis (SEWA) framework was published in 2019. Although the framework was based on a large case study, the framework still required theoretical validation, refinement, and enrichment.

METHODS

A scoping literature review was performed on studies related to EHR workarounds published between 2010 and 2021 in the MEDLINE, Embase, CINAHL, Cochrane, or IEEE databases. A total of 737 studies were retrieved, of which 62 (8.4%) were included in the final analysis. Using an analytic framework, the included studies were investigated to uncover the rationales that EHR users have for workarounds, attributes characterizing workarounds, possible scopes, and types of perceived impacts of workarounds.

RESULTS

The SEWA framework was theoretically validated and extended based on the scoping review. Extensive support for the pre-existing rationales, attributes, possible scopes, and types of impact was found in the included studies. Moreover, 7 new rationales, 4 new attributes, and 3 new types of impact were incorporated. Similarly, the descriptions of multiple pre-existing rationales for workarounds were refined to describe each rationale more accurately.

CONCLUSIONS

SEWA is now grounded in the existing body of peer-reviewed empirical evidence on EHR workarounds and, as such, provides a theoretically validated and more complete synthesis of EHR workaround rationales, attributes, possible scopes, and types of impact. The revised SEWA framework can aid researchers and practitioners in a wider range of health care settings to identify, analyze, and resolve workarounds. This will improve user-centered EHR design and redesign, ultimately leading to improved patient safety, quality of care, and efficiency of care.

Comparing Scribed and Non-scribed Outpatient Progress Notes

Working with scribes can reduce provider documentation time, but few studies have examined how scribes affect clinical notes. In this retrospective cross-sectional study, we examine over 50,000 outpatient progress notes written with and without scribe assistance by 70 providers across 27 specialties in 2017-2018. We find scribed notes were consistently longer than those written without scribe assistance, with most additional text coming from note templates. Scribed notes were also more likely to contain certain templated lists, such as the patient's medications or past medical history. However, there was significant variation in how working with scribes affected a provider's mix of typed, templated, and copied note text, suggesting providers adapt their documentation workflows to varying degrees when working with scribes. These results suggest working with scribes may contribute to note bloat, but that providers' individual documentation workflows, including their note templates, may have a large impact on scribed note contents.

A Practical Approach for Monitoring the Use of Copy-Paste in Clinical Notes

The use of copy-paste in authoring clinical notes has been widely embraced by busy providers, but inappropriate copy-paste has been lambasted by critics for introducing risks related to patient safety and regulatory compliance. At an integrated academic health system with over 4,100 providers writing notes, we developed a pragmatic approach to assess the use of copy-paste. From January 1-December 31, 2020, approximately 2.3M inpatient notes and 6.6M ambulatory clinic notes were authored in our electronic health record. Of the inpatient notes, 42% used copy-paste, and 19% of overall note content was copied; in ambulatory notes, 18% used copy-paste and 12% of note content was copied. We describe an approach for including providers' copy-paste usage statistics into the ongoing professional practice evaluation process required for hospital accreditation, thereby offering individual training opportunities related to the lack of use of copy-paste or its potential overuse.

Restricted use of copy and paste in electronic health records potentially improves healthcare quality

ABSTRACT

The copy-and-paste feature is commonly used for clinical documentation, and a policy is needed to reduce overdocumentation. We aimed to determine if the restricted use of copy and paste by doctors could improve inpatient healthcare quality.Clinical documentation in an inpatient dataset compiled from 2016 to 2018 was used. Copied-and-pasted text was detected in word templates using natural language programming with a threshold of 70%. The prevalence of copying and pasting after the policy introduction was accessed by segmented regression for trend analysis. The rate of readmission for the same disease within 14 days was assessed to evaluate inpatient healthcare quality, and the completion of discharge summary notes within 3 days was assessed to determine the timeliness of note completion. The relationships between these factors were used cross-correlation to detect lag effect. Poisson regression was performed to identify the relative effect of the copy and paste restriction policy on the 14-day readmission rate or the discharge note completion rate within 3 days.The prevalence of copying and pasting initially decreased, then increased, and then flatly decreased. The cross-correlation results showed a significant correlation between the prevalence of copied-and-pasted text and the 14-day readmission rate (P < .001) and a relative risk of 1.105 (P < .005), with a one-month lag. The discharge note completion rate initially decreased and not affected long term after restriction policy.Appropriate policies to restrict the use of copying and pasting can lead to improvements in inpatient healthcare quality. Prospective research with cost analysis is needed.

Assessing the quality of electronic medical records as a platform for resident education

BACKGROUND

Previous studies have assessed note quality and the use of electronic medical record (EMR) as a part of medical training. However, a generalized and user-friendly note quality assessment tool is required for quick clinical assessment. We held a medical record writing competition and developed a checklist for assessing the note quality of participants' medical records. Using the checklist, this study aims to explore note quality between residents of different specialties and offer pedagogical implications.

METHODS

The authors created an inpatient checklist that examined fundamental EMR requirements through six note types and twenty items. A total of 149 records created by residents from 32 departments/stations were randomly selected. Seven senior physicians rated the EMRs using a checklist. Medical records were grouped as general medicine, surgery, paediatric, obstetrics and gynaecology, and other departments. The overall and group performances were analysed using analysis of variance (ANOVA).

RESULTS

Overall performance was rated as fair to good. Regarding the six note types, discharge notes (0.81) gained the highest scores, followed by admission notes (0.79), problem list (0.73), overall performance (0.73), progress notes (0.71), and weekly summaries (0.66). Among the five groups, other departments (80.20) had the highest total score, followed by obstetrics and gynaecology (78.02), paediatrics (77.47), general medicine (75.58), and surgery (73.92).

CONCLUSIONS

This study suggested that duplication in medical notes and the documentation abilities of residents affect the quality of medical records in different departments. Further research is required to apply the insights obtained in this study to improve the quality of notes and, thereby, the effectiveness of resident training.

Frequent but fragmented: use of note templates to document outpatient visits at an academic health center

Recent changes to billing policy have reduced documentation requirements for outpatient notes, providing an opportunity to rethink documentation workflows. While many providers use templates to write notes-whether to insert short phrases or draft entire notes-we know surprisingly little about how these templates are used in practice. In this retrospective cross-sectional study, we observed the templates that primary providers and other members of the care team used to write the provider progress note for 2.5 million outpatient visits across 52 specialties at an academic health center between 2018 and 2020. Templates were used to document 89% of visits, with a median of 2 used per visit. Only 17% of the 100 230 unique templates were ever used by more than one person and most providers had their own full-note templates. These findings suggest template use is frequent but fragmented, complicating template revision and maintenance. Reframing template use as a form of computer programming suggests ways to maintain the benefits of personalization while leveraging standardization to reduce documentation burden.

Harnessing the Electronic Health Record and Computerized Provider Order Entry Data for Resource Management During the COVID-19 Pandemic: Development of a Decision Tree

Background

The COVID-19 pandemic has resulted in shortages of diagnostic tests, personal protective equipment, hospital beds, and other critical resources.

Objective

We sought to improve the management of scarce resources by leveraging electronic health record (EHR) functionality, computerized provider order entry, clinical decision support (CDS), and data analytics.

Methods

Due to the complex eligibility criteria for COVID-19 tests and the EHR implementation–related challenges of ordering these tests, care providers have faced obstacles in selecting the appropriate test modality. As test choice is dependent upon specific patient criteria, we built a decision tree within the EHR to automate the test selection process by using a branching series of questions that linked clinical criteria to the appropriate SARS-CoV-2 test and triggered an EHR flag for patients who met our institutional persons under investigation criteria.

Results

The percentage of tests that had to be canceled and reordered due to errors in selecting the correct testing modality was 3.8% (23/608) before CDS implementation and 1% (262/26,643) after CDS implementation (P<.001). Patients for whom multiple tests were ordered during a 24-hour period accounted for 0.8% (5/608) and 0.3% (76/26,643) of pre- and post-CDS implementation orders, respectively (P=.03). Nasopharyngeal molecular assay results were positive in 3.4% (826/24,170) of patients who were classified as asymptomatic and 10.9% (1421/13,074) of symptomatic patients (P<.001). Positive tests were more frequent among asymptomatic patients with a history of exposure to COVID-19 (36/283, 12.7%) than among asymptomatic patients without such a history (790/23,887, 3.3%; P<.001).

Conclusions

The leveraging of EHRs and our CDS algorithm resulted in a decreased incidence of order entry errors and the appropriate flagging of persons under investigation. These interventions optimized reagent and personal protective equipment usage. Data regarding symptoms and COVID-19 exposure status that were collected by using the decision tree correlated with the likelihood of positive test results, suggesting that clinicians appropriately used the questions in the decision tree algorithm.

Writing Practices Associated With Electronic Progress Notes and the Preferences of Those Who Read Them: Descriptive Study

Background

Hospital progress notes can serve as an important communication tool. However, they are criticized for their length, preserved content, and for the time physicians spend writing them.

Objective

We aimed to describe hospital progress note content, writing and reading practices, and the preferences of those who create and read them prior to the implementation of a new electronic health record system.

Methods

Using a sample of hospital progress notes from 1000 randomly selected admissions, we measured note length, similarity of content in successive daily notes for the same patient, the time notes were signed and read, and who read them. We conducted focus group sessions with note writers, readers, and clinical leaders to understand their preferences.

Results

We analyzed 4938 inpatient progress notes from 418 authors. The average length was 886 words, and most were in the Assessment & Plan note section. A total of 29% of notes (n=1432) were signed after 4 PM. Notes signed later in the day were read less often. Notes were highly similar from one day to the next, and 26% (23/88) had clinical risk associated with the preserved content. Note content of the highest value varied according to the reader’s professional role.

Conclusions

Progress note length varied widely. Notes were often signed late in the day when they were read less often and were highly similar to the note from the previous day. Measuring note length, signing time, when and by whom notes are read, and the amount and safety of preserved content will be useful metrics for measuring how the new electronic health record system is used, and can aid improvements.

Classification of Electronic Health Record-Related Patient Safety Incidents: Development and Validation Study

Background

It is assumed that the implementation of health information technology introduces new vulnerabilities within a complex sociotechnical health care system, but no international consensus exists on a standardized format for enhancing the collection, analysis, and interpretation of technology-induced errors.

Objective

This study aims to develop a classification for patient safety incident reporting associated with the use of mature electronic health records (EHRs). It also aims to validate the classification by using a data set of incidents during a 6-month period immediately after the implementation of a new EHR system.

Methods

The starting point of the classification development was the Finnish Technology-Induced Error Risk Assessment Scale tool, based on research on commonly recognized error types. A multiprofessional research team used iterative tests on consensus building to develop a classification system. The final classification, with preliminary descriptions of classes, was validated by applying it to analyze EHR-related error incidents (n=428) during the implementation phase of a new EHR system and also to evaluate this classification’s characteristics and applicability for reporting incidents. Interrater agreement was applied.

Results

The number of EHR-related patient safety incidents during the implementation period (n=501) was five-fold when compared with the preimplementation period (n=82). The literature identified new error types that were added to the emerging classification. Error types were adapted iteratively after several test rounds to develop a classification for reporting patient safety incidents in the clinical use of a high-maturity EHR system. Of the 427 classified patient safety incidents, interface problems accounted for 96 (22.5%) incident reports, usability problems for 73 (17.1%), documentation problems for 60 (14.1%), and clinical workflow problems for 33 (7.7%). Altogether, 20.8% (89/427) of reports were related to medication section problems, and downtime problems were rare (n=8). During the classification work, 14.8% (74/501) of reports of the original sample were rejected because of insufficient information, even though the reports were deemed to be related to EHRs. The interrater agreement during the blinded review was 97.7%.

Conclusions

This study presents a new classification for EHR-related patient safety incidents applicable to mature EHRs. The number of EHR-related patient safety incidents during the implementation period may reflect patient safety challenges during the implementation of a new type of high-maturity EHR system. The results indicate that the types of errors previously identified in the literature change with the EHR development cycle.

The Effect of Electronic Health Record Burden on Pediatricians' Work-Life Balance and Career Satisfaction

OBJECTIVES

To examine pediatricians' perspectives on administrative tasks including electronic health record (EHR) documentation burden and their effect on work-life balance and life and career satisfaction.

METHODS

We analyzed 2018 survey data from the American Academy of Pediatrics (AAP) Pediatrician Life and Career Experience Study (PLACES), a longitudinal cohort study of early and midcareer pediatricians. Cohorts graduated from residency between 2002 and 2004 or 2009 and 2011. Participants were randomly selected from an AAP database (included all pediatricians who completed U.S. pediatric residency programs). Four in 10 pediatricians (1,796 out of 4,677) were enrolled in PLACES in 2012 and considered participants in 2018. Data were weighted to adjust for differences between study participants and the overall population of pediatricians. Chi-square and multivariable logistic regression examined the association of EHR burden on work-life balance (three measures) and satisfaction with work, career, and life (three measures). Responses to an open-ended question on experiences with administrative tasks were reviewed.

RESULTS

A total of 66% of pediatrician participants completed the 2018 surveys (1,192 of 1,796; analytic sample = 1,069). Three-fourths reported EHR documentation as a major or moderate burden. Half reported such burden for billing and insurance and 42.7% for quality and performance measurement. Most pediatricians reported satisfaction with their jobs (86.7%), careers (84.5%), and lives (66.2%). Many reported work-life balance challenges (52.5% reported stress balancing work and personal responsibilities). In multivariable analysis, higher reported EHR burden was associated with lower scores on career and life satisfaction measures and on all three measures of work-life balance. Open-ended responses (n = 467) revealed several themes. Two predominant themes especially supported the quantitative findings-poor EHR functionality and lack of support for administrative burdens.

CONCLUSION

Most early to midcareer pediatricians experience administrative burdens with EHRs. These experiences are associated with worse work-life balance including more stress in balancing responsibilities and less career and life satisfaction.

Length and Redundancy of Outpatient Progress Notes Across a Decade at an Academic Medical Center

IMPORTANCE

There is widespread concern that clinical notes have grown longer and less informative over the past decade. Addressing these concerns requires a better understanding of the magnitude, scope, and potential causes of increased note length and redundancy.

OBJECTIVE

To measure changes between 2009 and 2018 in the length and redundancy of outpatient progress notes across multiple medical specialties and investigate how these measures associate with author experience and method of note entry.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study was conducted at Oregon Health & Science University, a large academic medical center. Participants included clinicians and staff who wrote outpatient progress notes between 2009 and 2018 for a random sample of 200 000 patients. Statistical analysis was performed from March to August 2020.

EXPOSURES

Use of a comprehensive electronic health record to document patient care.

MAIN OUTCOMES AND MEASURES

Note length, note redundancy (ie, the proportion of text identical to the patient's last note), and percentage of templated, copied, or directly typed note text.

RESULTS

A total of 2 704 800 notes written by 6228 primary authors across 46 specialties were included in this study. Median note length increased 60.1% (99% CI, 46.7%-75.2%) from a median of 401 words (interquartile range [IQR], 225-660 words) in 2009 to 642 words (IQR, 399-1007 words) in 2018. Median note redundancy increased 10.9 percentage points (99% CI, 7.5-14.3 percentage points) from 47.9% in 2009 to 58.8% in 2018. Notes written in 2018 had a mean value of just 29.4% (99% CI, 28.2%-30.7%) directly typed text with the remaining 70.6% of text being templated or copied. Mixed-effect linear models found that notes with higher proportions of templated or copied text were significantly longer and more redundant (eg, in the 2-year model, each 1% increase in the proportion of copied or templated note text was associated with 1.5% [95% CI, 1.5%-1.5%] and 1.6% [95% CI, 1.6%-1.6%] increases in note length, respectively). Residents and fellows also wrote significantly (26.3% [95% CI, 25.8%-26.7%]) longer notes than more senior authors, as did more recent hires (1.8% for each year later [95% CI, 1.3%-2.4%]).

CONCLUSIONS AND RELEVANCE

In this study, outpatient progress notes grew longer and more redundant over time, potentially limiting their use in patient care. Interventions aimed at reducing outpatient progress note length and redundancy may need to simultaneously address multiple factors such as note template design and training for both new and established clinicians.

What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization

Summarization of clinical narratives is a long-standing research problem. Here, we introduce the task of hospital-course summarization. Given the documentation authored throughout a patient's hospitalization, generate a paragraph that tells the story of the patient admission. We construct an English, text-to-text dataset of 109,000 hospitalizations (2M source notes) and their corresponding summary proxy: the clinician-authored "Brief Hospital Course" paragraph written as part of a discharge note. Exploratory analyses reveal that the BHC paragraphs are highly abstractive with some long extracted fragments; are concise yet comprehensive; differ in style and content organization from the source notes; exhibit minimal lexical cohesion; and represent silver-standard references. Our analysis identifies multiple implications for modeling this complex, multi-document summarization task.

Impact of Data Entry Interface Design on Cognitive Workload, Documentation Correctness, and Documentation Efficiency

Clinical documentation serves as the legal record of patient care and used to guide clinical decision making. Inadequately designed data entry user-interfaces may result in unintended consequences that negatively impact patient safety and outcomes because inaccurate information is used to guide clinical decision making. This study utilized an electronic simulated documentation interface (i.e., artificial electronic health record) combined with eye-tracking hardware to analyze documentation correctness, documentation efficiency, and cognitive workload of anesthesia providers (N = 20) generating documentation using different computer-assisted data entry types (drop-down box, radio button, check-box, and free text with autocomplete suggestions). Our study methodology incorporating eye-tracking with electronic health record user interfaces to assess documentation correctness, efficiency, and cognitive workload can be translated to other health care provider types.

Association of Electronic Health Record Vendors With Hospital Financial and Quality Performance: Retrospective Data Analysis

Background

Electronic health records (EHRs) are a central feature of care delivery in acute care hospitals; however, the financial and quality outcomes associated with system performance remain unclear.

Objective

In this study, we aimed to evaluate the association between the top 3 EHR vendors and measures of hospital financial and quality performance.

Methods

This study evaluated 2667 hospitals with Cerner, Epic, or Meditech as their primary EHR and considered their performance with regard to net income, Hospital Value–Based Purchasing Total Performance Score (TPS), and the unweighted subdomains of efficiency and cost reduction; clinical care; patient- and caregiver-centered experience; and patient safety. We hypothesized that there would be a difference among the 3 vendors for each measure.

Results

None of the EHR systems were associated with a statistically significant financial relationship in our study. Epic was positively associated with TPS outcomes (R²=23.6%; β=.0159, SE 0.0079; P=.04) and higher patient perceptions of quality (R²=29.3%; β=.0292, SE 0.0099; P=.003) but was negatively associated with patient safety quality scores (R²=24.3%; β=−.0221, SE 0.0102; P=.03). Cerner and Epic were positively associated with improved efficiency (R²=31.9%; Cerner: β=.0330, SE 0.0135, P=.01; Epic: β=.0465, SE 0.0133, P<.001). Finally, all 3 vendors were associated with positive performance in the clinical care domain (Epic: β=.0388, SE 0.0122, P=.002; Cerner: β=.0283, SE 0.0124, P=.02; Meditech: β=.0273, SE 0.0123, P=.03) but with low explanatory power (R²=4.2%).

Conclusions

The results of this study provide evidence of a difference in clinical outcome performance among the top 3 EHR vendors and may serve as supportive evidence for health care leaders to target future capital investments to improve health care delivery.

Are specific elements of electronic health record use associated with clinician burnout more than others?

OBJECTIVE

The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data.

MATERIALS AND METHODS

We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics.

RESULTS

Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039).

DISCUSSION

High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, "patient calls" encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being.

CONCLUSIONS

Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.

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.

The anatomy of electronic patient record ethics: a framework to guide design, development, implementation, and use

BACKGROUND

This manuscript presents a framework to guide the identification and assessment of ethical opportunities and challenges associated with electronic patient records (EPR). The framework is intended to support designers, software engineers, health service managers, and end-users to realise a responsible, robust and reliable EPR-enabled healthcare system that delivers safe, quality assured, value conscious care.

METHODS

Development of the EPR applied ethics framework was preceded by a scoping review which mapped the literature related to the ethics of EPR technology. The underlying assumption behind the framework presented in this manuscript is that ethical values can inform all stages of the EPR-lifecycle from design, through development, implementation, and practical application.

RESULTS

The framework is divided into two parts: context and core functions. The first part 'context' entails clarifying: the purpose(s) within which the EPR exists or will exist; the interested parties and their relationships; and the regulatory, codes of professional conduct and organisational policy frame of reference. Understanding the context is required before addressing the second part of the framework which focuses on EPR 'core functions' of data collection, data access, and digitally-enabled healthcare.

CONCLUSIONS

The primary objective of the EPR Applied Ethics Framework is to help identify and create value and benefits rather than to merely prevent risks. It should therefore be used to steer an EPR project to success rather than be seen as a set of inhibitory rules. The framework is adaptable to a wide range of EPR categories and can cater for new and evolving EPR-enabled healthcare priorities. It is therefore an iterative tool that should be revisited as new EPR-related state-of-affairs, capabilities or activities emerge.

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.

Impact of Patient Load on the Quality of Electronic Medical Record Documentation

OBJECTIVE

American College of Graduate Medical Education (ACGME) recommends ongoing care of 10 patients per resident however its implication is unclear. We hypothesized EMR quality to vary based on patient load and call status.

METHODS

We conducted a double-blind, single-center, retrospective observational study between 2017 and 2019 to investigate the quality and accuracy of resident documentation using the Responsible Electronic Documentation (RED) Checklist, a validated scoring system.

RESULTS

A total of 234 independent charts were analyzed and 80 met scoring criteria. Average patients per residents was 4, 9.1, 7.2, and 5.5 on "call" day (D0), "post-call" day (D1), "mid-call" day (D2), and "pre-call" day (D3), respectively. Mean RED checklist scores were 68.1%, 57%, 68.6%, and 72.1% on the above call status. The difference in score between D3 and D1 was statistically significant (P = .00042). There was a negative correlation between score and number of patients per resident (r = -0.286, P = .010).

CONCLUSION

EMR documentation quality is directly impacted by patient load and resident call status with the lowest documentation quality on post-call day, correlating with patient load.

The complex case of EHRs: examining the factors impacting the EHR user experience

Physicians can spend more time completing administrative tasks in their electronic health record (EHR) than engaging in direct face time with patients. Increasing rates of burnout associated with EHR use necessitate improvements in how EHRs are developed and used. Although EHR design often bears the brunt of the blame for frustrations expressed by physicians, the EHR user experience is influenced by a variety of factors, including decisions made by entities other than the developers and end users, such as regulators, policymakers, and administrators. Identifying these key influences can help create a deeper understanding of the challenges in developing a better EHR user experience. There are multiple opportunities for regulators, policymakers, EHR developers, payers, health system leadership, and users each to make changes to collectively improve the use and efficacy of EHRs.

Effects of Electronic Health Record Implementation and Barriers to Adoption and Use: A Scoping Review and Qualitative Analysis of the Content

Despite the great advances in the field of electronic health records (EHRs) over the past 25 years, implementation and adoption challenges persist, and the benefits realized remain below expectations. This scoping review aimed to present current knowledge about the effects of EHR implementation and the barriers to EHR adoption and use. A literature search was conducted in PubMed, Web of Science, IEEE Xplore Digital Library and ACM Digital Library for studies published between January 2005 and May 2020. In total, 7641 studies were identified of which 142 met the criteria and attained the consensus of all researchers on inclusion. Most studies (n = 91) were published between 2017 and 2019 and 81 studies had the United States as the country of origin. Both positive and negative effects of EHR implementation were identified, relating to clinical work, data and information, patient care and economic impact. Resource constraints, poor/insufficient training and technical/educational support for users, as well as poor literacy and skills in technology were the identified barriers to adoption and use that occurred frequently. Although this review did not conduct a quality analysis of the included papers, the lack of uniformity in the use of EHR definitions and detailed contextual information concerning the study settings could be observed.

Study design and ethical considerations related to using direct observation to evaluate physician behavior: reflections after a recent study

In a recent study using direct observation of physicians, we demonstrated that physician-generated clinical documentation is vulnerable to error. In fact, we found that physicians consistently overrepresented their actions in certain areas of the medical record, such as the physical examination. Because of our experiences carrying out this study, we believe that certain investigations, particularly those evaluating physician behavior, should not rely on documentation alone. Investigators seeking to evaluate physician behavior should instead consider using observation to obtain objective information about occurrences in the patient-physician encounter. In this article, we describe our experiences using observation, and we offer investigators our perspectives related to study design and ethical questions to consider when performing similar work.

A Randomized Trial of Voice-Generated Inpatient Progress Notes: Effects on Professional Fee Billing

BACKGROUND

Prior evaluations of automated speech recognition (ASR) to create hospital progress notes have not analyzed its effect on professional revenue billing codes. As ASR becomes a more common method of entering clinical notes, clinicians, hospital administrators, and payers should understand whether this technology alters charges associated with inpatient physician services.

OBJECTIVES

This study aimed to measure the difference in professional fee charges between using voice and keyboard to create inpatient progress notes.

METHODS

In a randomized trial of a novel voice with ASR system, called voice-generated enhanced electronic note system (VGEENS), to generate physician notes, we compared 1,613 notes created using intervention (VGEENS) or control (keyboard with template) created by 31 physicians. We measured three outcomes, as follows: (1) professional fee billing levels assigned by blinded coders, (2) number of elements within each note domain, and (3) frequency of organ system evaluations documented in review of systems (ROS) and physical exam.

RESULTS

Participants using VGEENS generated a greater portion of high-level (99233) notes than control users (31.8 vs. 24.3%, p < 0.01). After adjustment for clustering by author, the finding persisted; intervention notes were 1.43 times more likely (95% confidence interval [CI]: 1.14-1.79) to receive a high-level code. Notes created using voice contained an average of 1.34 more history of present illness components (95% CI: 0.14-2.54) and 1.62 more review of systems components (95% CI: 0.48-2.76). The number of physical exam components was unchanged.

CONCLUSION

Using this voice with ASR system as tested slightly increases documentation of patient symptom details without reliance on copy and paste and may raise physician charges. Increased provider reimbursement may encourage hospital and provider group to offer use of voice and ASR to create hospital progress notes as an alternative to usual methods.

Clinical Documentation as End-User Programming

As healthcare providers have transitioned from paper to electronic health records they have gained access to increasingly sophisticated documentation aids such as custom note templates. However, little is known about how providers use these aids. To address this gap, we examine how 48 ophthalmologists and their staff create and use content-importing phrases - a customizable and composable form of note template - to document office visits across two years. In this case study, we find 1) content-importing phrases were used to document the vast majority of visits (95%), 2) most content imported by these phrases was structured data imported by data-links rather than boilerplate text, and 3) providers primarily used phrases they had created while staff largely used phrases created by other people. We conclude by discussing how framing clinical documentation as end-user programming can inform the design of electronic health records and other documentation systems mixing data and narrative text.

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

Objective

To describe the literature exploring the use of electronic health record (EHR) systems to support creation and use of clinical documentation to guide future research.

Materials and Methods

We searched databases including MEDLINE, Scopus, and CINAHL from inception to April 20, 2018, for studies applying qualitative or mixed-methods examining EHR use to support creation and use of clinical documentation. A qualitative synthesis of included studies was undertaken.

Results

Twenty-three studies met the inclusion criteria and were reviewed in detail. We briefly reviewed 9 studies that did not meet the inclusion criteria but provided recommendations for EHR design. We identified 4 key themes: purposes of electronic clinical notes, clinicians' reasoning for note-entry and reading/retrieval, clinicians' strategies for note-entry, and clinicians' strategies for note-retrieval/reading. Five studies investigated note purposes and found that although patient care is the primary note purpose, non-clinical purposes have become more common. Clinicians' reasoning studies (n = 3) explored clinicians' judgement about what to document and represented clinicians' thought process in cognitive pathways. Note-entry studies (n = 6) revealed that what clinicians document is affected by EHR interfaces. Lastly, note-retrieval studies (n = 12) found that "assessment and plan" is the most read note section and what clinicians read is affected by external stimuli, care/information goals, and what they know about the patient.

Conclusion

Despite the widespread adoption of EHRs, their use to support note-entry and reading/retrieval is still understudied. Further research is needed to investigate approaches to capture and represent clinicians' reasoning and improve note-entry and retrieval/reading.

Using Voogle to Search Within Patient Records in the VA Corporate Data Warehouse

The VA has developed a tool to search its Corporate Data Warehouse, which provides easy access to patient data for better clinical decision making.

Adoption of Electronic Health Records and Perceptions of Financial and Clinical Outcomes Among Ophthalmologists in the United States

Importance

Assessing the rate of electronic health record (EHR) adoption and ophthalmologists' perceptions on financial and clinical productivity is important in understanding how to direct future design and health care policy.

Objective

To assess adoption rate and perceptions of financial and clinical outcomes of EHRs among ophthalmologists in the United States.

Design, Setting, and Participants

Population-based, cross-sectional study. A random sample of 2000 ophthalmologists was generated on the basis of mailing address zip codes from the 2015 American Academy of Ophthalmology US active membership database, which included more than 18 000 ophthalmologists. A survey was sent by email to assess adoption rate of EHRs, perceptions of financial and clinical productivity, and engagement with Medicare and Medicaid programs that incentivize the use of EHRs. The survey was conducted between 2015 and 2016.

Main Outcomes and Measures

Adoption rate of EHRs and perceptions of financial and clinical productivity.

Results

The adoption rate of EHRs among surveyed ophthalmologists (348 respondents) was 72.1%. The responding ophthalmologists perceived that their net revenues and productivity have declined and that practice costs are higher with EHR use. Of those who attested for stage 1 of the EHR incentive program, 83% had already or were planning to attest to stage 2, but 9% had no plans.

Conclusions and Relevance

The adoption of EHRs by ophthalmologists has more than doubled since a 2011 survey and is similar to that of primary care physicians (79%). In comparison with 2 previous surveys of ophthalmologists, respondents had more negative perceptions of EHR productivity outcomes and effect on practice costs, although financial data were not collected in this survey to support these opinions. These negative perceptions suggest that more attention should be placed on improving the efficiency and usability of EHR systems.

Building a tobacco user registry by extracting multiple smoking behaviors from clinical notes

Background

Usage of structured fields in Electronic Health Records (EHRs) to ascertain smoking history is important but fails in capturing the nuances of smoking behaviors. Knowledge of smoking behaviors, such as pack year history and most recent cessation date, allows care providers to select the best care plan for patients at risk of smoking attributable diseases.

Methods

We developed and evaluated a health informatics pipeline for identifying complete smoking history from clinical notes in EHRs. We utilized 758 patient-visit notes (from visits between 03/28/2016 and 04/04/2016) from our local EHR in addition to a public dataset of 502 clinical notes from the 2006 i2b2 Challenge to assess the performance of this pipeline. We used a machine-learning classifier to extract smoking status and a comprehensive set of text processing regular expressions to extract pack years and cessation date information from these clinical notes.

Results

We identified smoking status with an F1 score of 0.90 on both the i2b2 and local data sets. Regular expression identification of pack year history in the local test set was 91.7% sensitive and 95.2% specific, but due to variable context the pack year extraction was incomplete in 25% of cases, extracting packs per day or years smoked only. Regular expression identification of cessation date was 63.2% sensitive and 94.6% specific.

Conclusions

Our work indicates that the development of an EHR-based Smokers’ Registry containing information relating to smoking behaviors, not just status, from free-text clinical notes using an informatics pipeline is feasible. This pipeline is capable of functioning in external EHRs, reducing the amount of time and money needed at the institute-level to create a Smokers’ Registry for improved identification of patient risk and eligibility for preventative and early detection services.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0863-3) contains supplementary material, which is available to authorized users.

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.

Assessing the Readability of Freely Available ICU Notes

Unstructured data stored in an electronic health record (EHR) system can be very informative but require techniques such as natural language processing to extract the information. Developing such techniques requires shared data, but clinical data are often not easy to access. A freely available intensive care unit database, MIMIC-III, was released in 2016 to address this issue and benefit the informatics research community. While the database has been utilized by a few studies, the text characteristics of the notes have not been summarized. In this study, we present the summary of the basic text characteristics and the readability of the MIMIC-III ICU notes. We further compare the results with our previous study where proprietary EHR notes were used. The results show that the text characteristics of MIMIC-III notes were comparable with proprietary EHR notes, although the note readability index was slightly lower. The clinical notes in MIMIC-III can be a viable option for researchers who are interested in clinicians' language use but have no access to proprietary EHR systems.

Breadcrumbs: Assessing the Feasibility of Automating Provider Documentation Using Electronic Health Record Activity

This study assessed the feasibility of automating the generation of the outpatient encounter summary. We reviewed screen tracking video and log-file metadata from electronic health record (EHR) interactions based on two simulated encounters. We mapped the sequence of metadata to key concepts in the video to assess the precision with which the log files aligned with user activity and to generate the Breadcrumbs encounter summary (BES). The BES captured all interactions documented in clinical notes with the exception of the physical exam. The videos addressed all Evaluation and Management (E/M) requirements, while the log files did not contain the physical exam. The BES was as comprehensive as the gold standard visit summary. The BES offers a promising method for the collection and compilation of necessary elements of outpatient clinical documentation. The combination of log files and video could provide evidence of EHR activity satisfying documentation requirements.

An Evidence-Based Tool for Safe Configuration of Electronic Health Records: The eSafety Checklist

BACKGROUND

Electronic health records (EHRs) are transforming the way health care is delivered. They are central to improving the quality of patient care and have been attributed to making health care more accessible, reliable, and safe. However, in recent years, evidence suggests that specific features and functions of EHRs can introduce new, unanticipated patient safety concerns that can be mitigated by safe configuration practices.

OBJECTIVE

This article outlines the development of a detailed and comprehensive evidence-based checklist of safe configuration practices for use by clinical informatics professionals when configuring hospital-based EHRs.

METHODS

A literature review was conducted to synthesize evidence on safe configuration practices; data were analyzed to elicit themes of common EHR system capabilities. Two rounds of testing were completed with end users to inform checklist design and usability. This was followed by a four-member expert panel review, where each item was rated for clarity (clear, not clear), and importance (high, medium, low).

RESULTS

An expert panel consisting of three clinical informatics professionals and one health information technology expert reviewed the checklist for clarity and importance. Medium and high importance ratings were considered affirmative responses. Of the 870 items contained in the original checklist, 535 (61.4%) received 100% affirmative agreement among all four panelists. Clinical panelists had a higher affirmative agreement rate of 75.5% (656 items). Upon detailed analysis, items with 100% clinician agreement were retained in the checklist with the exception of 47 items and the addition of 33 items, resulting in a total of 642 items in the final checklist.

CONCLUSION

Safe implementation of EHRs requires consideration of both technical and sociotechnical factors through close collaboration of health information technology and clinical informatics professionals. The recommended practices described in this checklist provide systems implementation guidance that should be considered when EHRs are being configured, implemented, audited, or updated, to improve system safety and usability.

Integrated Electronic Discharge Summaries-Experience of a Tertiary Pediatric Institution

OBJECTIVE

Succinct and timely discharge summaries (DSs) facilitate ongoing care for patients discharged from acute care settings. Many institutions have introduced electronic DS (eDS) templates to improve quality and timeliness of clinical correspondence. However, significant intrahospital and intraunit variability and application exists. A review of the literature and guidelines revealed 13 key elements that should be included in a best practice DS. This was compared against our pediatric institution's eDS template-housed within an integrated electronic medical record (EMR) and used across most inpatient hospital units.

METHODS

Uptake and adherence to the suggested key elements was measured by comparing all DSs for long stay inpatients (> 21-day admission) during the first year of the EMR eDS template's usage (May 2016-April 2017).

RESULTS

A total of 472 DSs were evaluated. Six of 13 key elements were completed in > 98.0% of DSs. Conversely, only < 5.0% included allergies or adverse reaction data, and < 11.0% included ceased medications or pending laboratory results. Inclusion of procedure information and pending laboratory results significantly improved with time (p = 0.05 and p < 0.04, respectively), likely as doctors became more familiar with EMR and autopopulation functions. Inclusion of "discharge diagnosis" differed significantly between medical (n = 406/472; 99.0%) and surgical (n = 32/472; 51.6%) DSs.

CONCLUSION

Uptake and adherence to an EMR eDS template designed to meet best practice guidelines in a pediatric institution was strong, although significant improvements in specific data elements are needed. Strategies can include a modification of existing eDS templates and junior medical staff education around best practice.

Electronic Health Record Interactions through Voice: A Review

BACKGROUND

Usability problems in the electronic health record (EHR) lead to workflow inefficiencies when navigating charts and entering or retrieving data using standard keyboard and mouse interfaces. Voice input technology has been used to overcome some of the challenges associated with conventional interfaces and continues to evolve as a promising way to interact with the EHR.

OBJECTIVE

This article reviews the literature and evidence on voice input technology used to facilitate work in the EHR. It also reviews the benefits and challenges of implementation and use of voice technologies, and discusses emerging opportunities with voice assistant technology.

METHODS

We performed a systematic review of the literature to identify articles that discuss the use of voice technology to facilitate health care work. We searched MEDLINE and the Google search engine to identify relevant articles. We evaluated articles that discussed the strengths and limitations of voice technology to facilitate health care work. Consumer articles from leading technology publications addressing emerging use of voice assistants were reviewed to ascertain functionalities in existing consumer applications.

RESULTS

Using a MEDLINE search, we identified 683 articles that were reviewed for inclusion eligibility. The references of included articles were also reviewed. Sixty-one papers that discussed the use of voice tools in health care were included, of which 32 detailed the use of voice technologies in production environments. Articles were organized into three domains: Voice for (1) documentation, (2) commands, and (3) interactive response and navigation for patients. Of 31 articles that discussed usability attributes of consumer voice assistant technology, 12 were included in the review.

CONCLUSION

We highlight the successes and challenges of voice input technologies in health care and discuss opportunities to incorporate emerging voice assistant technologies used in the consumer domain.

Nurses’ Experience With Health Information Technology: Longitudinal Qualitative Study

Background

Nurses are the largest group of health information technology (HIT) users. As such, nurses’ adaptations are critical for HIT implementation success. However, longitudinal approaches to understanding nurses’ perceptions of HIT remain underexplored. Previous studies of nurses’ perceptions demonstrate that the progress and timing for acceptance of and adaptation to HIT varies.

Objective

This study aimed to explore nurses’ experience regarding implementation of HIT over time.

Methods

A phenomenological approach was used for this longitudinal qualitative study to explore nurses’ perceptions of HIT implementation over time, focusing on three time points (rounds) at 3, 9, and 18 months after implementation of electronic health records and bar code medication administration. The purposive sample was comprised of clinical nurses who worked on a medical-surgical unit in an academic center.

Results

Major findings were categorized into 7 main themes with 54 subthemes. Nurses reported personal-level and organizational-level factors that facilitated HIT adaptation. We also generated network graphs to illustrate the occurrence of themes. Thematic interconnectivity differed due to nurses’ concerns and satisfaction at different time points. Equipment and workflow were the most frequent themes across all three rounds. Nurses were the most dissatisfied approximately 9 months after HIT implementation. Eighteen months after HIT implementation, nurses’ perceptions appeared more balanced.

Conclusions

It is recommended that organizations invest in equipment (ie, wireless barcode scanners), refine policies to reflect nursing practice, and improve systems to focus on patient safety. Future research is necessary to confirm patterns of nurses’ adaptation to HIT in other samples.

Characterizing the Source of Text in Electronic Health Record Progress Notes

This study analyzes inpatient progress notes to determine the documentation practices of medical students, residents, and hospitalists.