Electronic Health Record Design Research Articles

Examining Pediatric Resident Electronic Health Records Use During Prerounding: Mixed Methods Observational Study

Electronic health records (EHRs) play a substantial role in modern health care, especially during prerounding, when residents gather patient information to inform daily care decisions of the care team. The effective use of the EHR system is crucial for efficient and frustration-free prerounding. Ideally, the system should be designed to support efficient user interactions by presenting data effectively and providing easy navigation between different pages. Additionally, training on the system should aim to make user interactions more efficient by familiarizing the users with best practices that minimize interaction time while using the full potential of the system's capabilities. However, formal training on EHR systems often falls short of providing residents with all the necessary EHR-related skills, leading to the adoption of inefficient practices and the underuse of the system's full range of capabilities. This study aims to examine the efficiency of EHR use during prerounding among pediatric residents, assess the effect of experience level on EHR use, and identify areas for improvement in EHR design and training. A mixed methods approach was used, involving a self-reported survey and video analysis of prerounding practices of the entire population of pediatric residents from a large teaching hospital in the South Atlantic Region. The residents were stratified by experience level by postgraduate year. Data were collected on the number of pages accessed, duration of prerounding, task completion rates, and effective use of data sources. Observational and qualitative data complemented the quantitative analysis. Our study followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guidelines, ensuring completeness and transparency of reporting. Of the 30 pediatric residents, 20 were included in the analyses; of these, 16 (80%) missed at least 1 step during prerounding. Although more experienced residents on average omitted fewer steps, 4 (57%) of the 7 most experienced residents still omitted at least 1 step. On average, residents took 6.5 minutes to round each patient and accessed 21 pages within the EHR during prerounding; no statistically significant differences were observed between experience levels for prerounding times (P=.48) or number of pages accessed (P=.92). The use of aggregated data pages within the EHR system neither seem to improve prerounding times nor decrease the number of pages accessed. The findings suggest that EHR design should be improved to better support user needs, and hospitals should adopt more effective training programs to familiarize residents with the system's capabilities. We recommend implementing prerounding checklists and providing ongoing EHR training programs for health care practitioners. Despite the generalizability of limitations of our study in terms of sample size and specialization, it offers valuable insights for future research to investigate the impact of EHR use on patient outcomes and satisfaction, as well as identify factors that contribute to efficient and effective EHR usage.

Using Clinical Data Visualizations in Electronic Health Record User Interfaces to Enhance Medical Student Diagnostic Reasoning: Randomized Experiment.

In medicine, the clinical decision-making process can be described using the dual-process theory consisting of the fast, intuitive "System 1," commonly seen in seasoned physicians, and the slow, deliberative "System 2," associated with medical students. System-1-type diagnostic reasoning is thought to be less cognitively burdensome, thereby reducing physician error. To date, limited literature exists on inducing System-1-type diagnosis in medical students through cognitive heuristics, particularly while using modern electronic health record (EHR) interfaces. In this experimental pilot study, we aimed to (1) attempt to induce System-1-type diagnostic reasoning in inexperienced medical students through the acquisition of cognitive user interface heuristics and (2) understand the impact of clinical patient data visualizations on students' cognitive load and medical education. The participants were third- and fourth-year medical students recruited from the University of Pittsburgh School of Medicine who had completed 1+ clinical rotations. The students were presented 8 patient cases on a novel EHR, featuring a prominent data visualization designed to foster at-a-glance rapid case assessment, and asked to diagnose the patient. Half of the participants were shown 4 of the 8 cases repeatedly, up to 4 times with 30 seconds per case (Group A), and the other half of the participants were shown cases twice with 2 minutes per case (Group B). All participants were then asked to provide full diagnoses of all 8 cases. Finally, the participants were asked to evaluate and elaborate on their experience with the system; content analysis was subsequently performed on these user experience interviews. A total of 15 students participated. The participants in Group A scored slightly higher on average than those in Group B, with a mean percentage correct of 76% (95% CI 0.68-0.84) versus 69% (95% CI 0.58-0.80), and spent on average 50% less time per question than Group B diagnosing patients (13.98 seconds vs 19.13 seconds, P=.03, respectively). When comparing the novel EHR design to previously used EHRs, 73% (n=11) of participants rated the new version on par or higher (3+/5). Ease of use and intuitiveness of this new system rated similarly high (mean score 3.73/5 and 4.2/5, respectively). In qualitative thematic analysis of poststudy interviews, most participants (n=11, 73%) spoke to "pattern-recognition" cognitive heuristic strategies consistent with System 1 decision-making. These results support the possibility of inducing type-1 diagnostics in learners and the potential for data visualization and user design heuristics to reduce cognitive burden in clinical settings. Clinical data presentation in the diagnostic reasoning process is ripe for innovation, and further research is needed to explore the benefit of using such visualizations in medical education.

Identifying a Clinical Informatics or Electronic Health Record Expert Witness for Medical Professional Liability Cases.

The health care field is experiencing widespread electronic health record (EHR) adoption. New medical professional liability (i.e., malpractice) cases will likely involve the review of data extracted from EHRs as well as EHR workflows, audit logs, and even the potential role of the EHR in causing harm. Reviewing printed versions of a patient's EHRs can be difficult due to differences in printed versus on-screen presentations, redundancies, and the way printouts are often grouped by document or information type rather than chronologically. Simply recreating an accurate timeline often requires experts with training and experience in designing, developing, using, and reviewing EHRs and audit logs. Additional expertise is required if questions arise about data's meaning, completeness, accuracy, and timeliness or ways that the EHR's user interface or automated clinical decision support tools may have contributed to alleged events. Such experts often come from the sociotechnical field of clinical informatics that studies the design, development, implementation, use, and evaluation of information and communications technology, specifically, EHRs. Identifying well-qualified EHR experts to aid a legal team is challenging. Based on literature review and experience reviewing cases, we identified seven criteria to help in this assessment. The criteria are education in clinical informatics; clinical informatics knowledge; experience with EHR design, development, implementation, and use; communication skills; academic publications on clinical informatics; clinical informatics certification; and membership in informatics-related professional organizations. While none of these criteria are essential, understanding the breadth and depth of an individual's qualifications in each of these areas can help identify a high-quality, clinical informatics expert witness.

Measurement and automation of workflows for improved clinician interaction: upgrading EHRs for 21st century healthcare value.

In this editorial, we highlight 5 manuscripts that address aspects of clinician interaction with the electronic health record (EHR). A Perspective describes the efforts of the Office of the National Coordinator for Health Information Technology (ONC) in establishing priorities for workflow automation in healthcare settings.1 A second Perspective summarizes a panel sponsored by the American College of Medical Informatics (ACMI) at the 2021 AMIA Symposium that examined a provocative question: Are EHRs dumbing down clinicians?2 Three manuscripts focus on what can be learned from EHR audit log data.3–5 First, Zayas-Cabán et al1 describe how the ONC led a multidisciplinary effort of stakeholders from industrial engineering, computer science, and finance to investigate automation in health care. They define automation as “the creation and application of technology to monitor and control the delivery of products and services.”6 The process of key informant interviews, focus groups, and a review of pertinent literature identified 6 priorities and their related strategies for advancing workflow automation. These priorities focused on leveraging high quality, interoperable data, and engaging clinicians in the EHR design, implementation, and evaluation processes. Then, relevant, and effective workflows could be identified that add value, not a burden, in clinician processes. The supporting strategies revolved around education, convening multiple interested parties, prioritizing appropriate workflows, and using policies and the market to incentivize automated solutions' development, testing, and evaluation. Examples of priority workflows for automation include reimbursement and prior authorizations, medication reconciliation, care management for newly diagnosed patients, and public health and adverse event reporting. The goal is to upgrade EHR technology to increase efficiency, improve health outcomes, and deliver more value for patients, caregivers, clinicians, and staff involved in healthcare. These priorities and strategies provide some solutions to the inadequacies of EHRs as outlined by Melton et al.2

Electronic Health Records That Support Health Professional Reflective Practice: a Missed Opportunity in Digital Health

A foundational component of digital health involves collecting and leveraging electronic health data to improve health and wellbeing. One of the central technologies for collecting these data are electronic health records (EHRs). In this commentary, the authors explore intersection between digital health and data-driven reflective practice that is described, including an overview of the role of EHRs underpinning technology innovation in healthcare. Subsequently, they argue that EHRs are a rich but under-utilised source of information on the performance of health professionals and healthcare teams that could be harnessed to support reflective practice and behaviour change. EHRs currently act as systems of data collection, not systems of data engagement and reflection by end users such as health professionals and healthcare organisations. Further consideration should be given to supporting reflective practice by health professionals in the design of EHRs and other clinical information systems.

The 21st Century Cures Act and Multiuser Electronic Health Record Access: Potential Pitfalls of Information Release.

Although the Office of The National Coordinator for Health Information Technology’s (ONC) Information Blocking Provision in the Cures Act Final Rule is an important step forward in providing patients free and unfettered access to their electronic health information (EHI), in the contexts of multiuser electronic health record (EHR) access and proxy access, concerns on the potential for harm in adolescent care contexts exist. We describe how the provision could erode patients’ (both adolescent and older patients alike) trust and willingness to seek care. The rule’s preventing harm exception does not apply to situations where the patient is a minor and the health care provider wishes to restrict a parent’s or guardian’s access to the minor’s EHI to avoid violating the minor’s confidentiality and potentially harming patient-clinician trust. This may violate previously developed government principles in the design and implementation of EHRs for pediatric care. Creating legally acceptable workarounds by means such as duplicate “shadow charting” will be burdensome (and prohibitive) for health care providers. Under the privacy exception, patients have the opportunity to request information to not be shared; however, depending on institutional practices, providers and patients may have limited awareness of this exception. Notably, the privacy exception states that providers cannot “improperly encourage or induce a patient’s request to block information.” Fearing being found in violation of the information blocking provisions, providers may feel that they are unable to guide patients navigating the release of their EHI in the multiuser or proxy access setting. ONC should provide more detailed guidance on their website and targeted outreach to providers and their specialty organizations that care for adolescents and other individuals affected by the Cures Act, and researchers should carefully monitor charting habits in these multiuser or proxy access situations.

Usability challenges with electronic health records (EHRs) during prerounding on pediatric inpatients.

ObjectivePrerounding is critical for a healthcare team to develop a shared understanding of the patient’s condition and to develop a care plan. However, the design of electronic health records (EHRs) often makes prerounding inefficient, ineffective, and time consuming. The goal of this study was to observe how residents use the EHR while prerounding to identify usability challenges associated with the design of EHRs.Materials and MethodsThirty residents were tasked to preround 2 pediatric patients using the think-aloud protocol. The data from the surveys, video recordings, and think-aloud comments were analyzed to identify usability issues related to EHR. The time it took for participants to complete the 6 required prerounding tasks were calculated and the pages most commonly accessed were noted.ResultsParticipants spent on average 6.5 min prerounding each patient with the most time spent on checking lab results and reviewing notes. Twenty-eight distinct pages were visited by at least 2 participants, mostly due to a lack of interconnectivity between related data across pages. Usability issues with the most commonly used pages include: data overload, missing/hidden information, difficulty identifying trends, and having to conduct manual calculations.ConclusionsWe list usability issues and provide a set of recommendations to remedy these issues that include: reducing information access cost, creating a checklist, automate calculations, and standardizing notes and EHR training. Ideally, the outcome of this work will help improve EHR design to maximize the time clinicians spend interacting with and providing care to their patients.

An Approach to Family-Centered Electronic Health Records in Pediatrics.

Over the years, family-centered care in the field of pediatrics has become more prevalent and has improved the patient experience. Recent innovations within electronic health records (EHR), such as patient portals, have provided a more “patient-centered” approach by allowing patients to be interactive with the EHR and have greater agency of their own healthcare. There are also ample opportunities within an EHR to improve the patient experience with delivery of family-centered care. In this perspective, we discuss the design and use of a family-centered EHR for the purposes of optimizing the pediatric patient experience.

Internal Medicine Residents’ Experience Performing Routine Assessment of What Matters Most to Patients Upon Hospital Admission

Problem Failure to elicit patients’ values, goals, and priorities can result in missed opportunities to provide patient-centered care. Little is known about resident physicians’ direct experience of eliciting patients’ values, goals, and priorities and integrating them into routine hospital care. Intervention In 2017, we asked resident physicians on general internal medicine wards rotations to elicit and document a “Personal History” from patients upon hospital admission, in addition to a traditional social history. We defined a Personal History as documenting “what matters most to the patient and why.” The purpose of the Personal History was to understand and consider patients’ values, goals, and priorities. We then conducted qualitative interviews of the resident physicians to understand their experiences eliciting and integrating patients’ values, goals, and priorities in routine hospital care. Context We performed this exploratory intervention at a large high-volume urban hospital. Two teams from general medicine wards participated in the Personal History intervention. We conducted voluntary interviews of eligible residents (n = 14/15; 93%) about their experience after they completed their general wards rotations. Using the coproduction model, our aim was to explore how patients’ self-expertise can be combined with physicians’ medical expertise to achieve patient-centered care. Impact Four major themes were identified: 1) Taking a Personal History had value, and eliciting patients’ self-expertise had the potential to change medical decision making, 2) Situational and relational factors created barriers to obtaining a Personal History, 3) Variability in buy-in with the proposed intervention affected effort, and 4) Meaningful Personal History taking could be an adaptive and longitudinal process. Perceived benefits included improved rapport with patients, helpful for patients with complex medical history, and improved physician-patient communication. Barriers included patient distress, lack of rapport, and responses from patients which did not add new insights. Accountability from attending physicians affected resident effort. Suggested future applications were for patients with serious illness, integration into electronic health records, and skills taught in medical education. Lessons Learned Resident physicians had generally positive views of eliciting a Personal History from patients upon admission to the hospital. Overall, many residents conveyed the perceived ability to elicit and consider patient’s values, goals, and priorities in certain situations (e.g., patient not in distress, adequate rapport, lack of competing priorities such as medical emergencies or overwhelming workloads). External factors, such as electronic health record design and accountability from attending physicians, may further promote residents’ efforts to routinely incorporate patients’ values, goals, and priorities in clinical care. Increasing familiarity among both resident physicians and patients in routinely discussing patients’ values, goals, and priorities may facilitate patient-centered practice.

Electronic Health Records as Biased Tools or Tools Against Bias: A Conceptual Model.

Health care delivery is now inextricably linked to the use of electronic health records (EHRs), which exert considerable influence over providers, patients, and organizations. This article offers a conceptual model showing how the design and subsequent use of EHRs can be subject to bias and can either encode and perpetuate systemic racism or be used to challenge it. Using structuration theory, the model demonstrates how a social structure, like an EHR, creates a cyclical relationship between the environment and people, either advancing or undermining important social values. The model illustrates how the implicit bias of individuals, both developers and end-user clinical providers, influence the platform and its associated information. Biased information can then lead to inequitable outcomes in clinical care, organizational decisions, and public policy. The biased information also influences subsequent users, amplifying their own implicit biases and potentially compounding the level of bias in the information itself. The conceptual model is used to explain how this concern is fundamentally a matter of quality. Relying on the Donabedian model, it explains how elements of the EHR design (structure), use (process), and the ends for which it is used (outcome) can first be used to evaluate where bias may become embedded in the system itself, but then also identify opportunities to resist and actively challenge bias. Our conceptual model may be able to redefine and improve the value of technology to health by modifying EHRs to support more equitable data that can be used for better patient care and public policy. For EHRs to do this, further work is needed to develop measures that assess bias in structure, process, and outcome, as well as policies to persuade vendors and health systems to prioritize systemic equity as a core goal of EHRs.

Usability issues with electronic health records: Is it even worth it for human factors practitioners?

Despite the need for addressing usability issues within Electronic Health Records (EHR), health care organizationshave struggled to systemically involvehuman factors practitioners (HFP). Thereare several challenges to supporting EHR-related work as HFP. Simple design changes mayhavedependencies or create downstream consequences that are not typical of other software systems, or not be feasible to change without overhaul of functionality from theEHR vendor. This panel will present successes and lessons learned bya group of HFP embeddedin healthcare systemswho have extendedexperience working on EHR configurationand design changes. They will discuss challengesand strategies in adopting human factorstechniquesto improve EHR design and related outcomes. By the end of the panel, audience members will learn not only howhuman factors is having animpact in this aspect ofhealthcare delivery, but also learn approaches that may be applicable to other complextechnical systems.

Sex Differences in Electronic Health Record Navigation Strategies: Secondary Data Analysis.

BackgroundUse of electronic health records (EHRs) has increased dramatically over the past decade. Their widespread adoption has been plagued with numerous complaints about usability, with subsequent impacts on patient safety and provider well-being. Data in other fields suggest biological sex impacts basic patterns of navigation in electronic media.ObjectiveThis study aimed to determine whether biological sex impacted physicians’ navigational strategies while using EHRs.MethodsThis is a secondary analysis of a prior study where physicians were given verbal and written signout, and then, while being monitored with an eye tracker, were asked to review a simulated record in our institution’s EHR system, which contained 14 patient safety items. Afterward, the number of safety items recognized was recorded.ResultsA total of 93 physicians (female: n=46, male: n=47) participated in the study. Two gaze patterns were identified: one characterized more so by saccadic (“scanning”) eye movements and the other characterized more so by longer fixations (“staring”). Female physicians were more likely to use the scanning pattern; they had a shorter mean fixation duration (P=.005), traveled more distance per minute of screen time (P=.03), had more saccades per minute of screen time (P=.02), and had longer periods of saccadic movement (P=.03). The average proportion of time spent staring compared to scanning (the Gaze Index [GI]) across all participants was approximately 3:1. Females were more likely than males to have a GI value <3.0 (P=.003). At the extremes, males were more likely to have a GI value >5, while females were more likely to have a GI value <1. Differences in navigational strategy had no impact on task performance.ConclusionsFemales and males demonstrate fundamentally different navigational strategies while navigating the EHR. This has potentially significant impacts for usability testing in EHR training and design. Further studies are needed to determine if the detected differences in gaze patterns produce meaningful differences in cognitive load while using EHRs.

Nursing Documentation Variation Across Different Medical Facilities Within an Integrated Healthcare System.

The purpose of this study was to demonstrate nursing documentation variation based on electronic health record design and its relationship with different levels of care by reviewing how various flowsheet measures, within the same electronic health record across an integrated healthcare system, are documented in different types of medical facilities. Flowsheet data with information on patients who were admitted to academic medical centers, community hospitals, and rehabilitation centers were used to calculate the frequency of flowsheet entries documented. We then compared the distinct flowsheet measures documented in five flowsheet templates across the different facilities. We observed that each type of healthcare facility appeared to have distinct clinical care foci and flowsheet measures documented differed within the same template based on facility type. Designing flowsheets tailored to study settings can meet the needs of end users and increase documentation efficiency by reducing time spent on unrelated flowsheet measures. Furthermore, this process can save nurses time for direct patient care.

Using the Electronic Health Record to Characterize the Hepatitis C Virus Care Cascade.

Chronic hepatitis C virus (HCV) infection is one of the main causes of hepatocellular carcinoma. Before initiating a multilevel HCV screening intervention, we sought to (1) describe concordance between the electronic health record (EHR) data warehouse and manual medical record review in recording aspects of HCV testing and treatment and (2) estimate the percentage of patients with chronic HCV infection who initiated and completed HCV treatment using manual medical record review. We examined the medical records for 177 patients (100 randomly selected patients born during 1945-1965 without evidence of HCV testing and 77 adult patients of any birth cohort who had completed HCV testing) with a primary care or relevant specialist visit at an academic health care system in Tampa, Florida, from 2015 through 2018. We used the Cohen κ coefficient to examine the degree of concordance between the searchable data warehouse and the medical record review abstractions. Descriptive statistics characterized referral to and receipt of treatment among patients with chronic HCV infection from medical record review. We found generally good concordance between the data warehouse abstraction and medical record review for HCV testing data (κ ranged from 0.66 to 0.87). However, the data warehouse failed to capture data on HCV treatment variables. According to medical record review, 28 patients had chronic HCV infection; 16 patients were prescribed treatment, 14 initiated treatment, and 9 achieved and had a reported posttreatment undetected HCV viral load. Using data warehouse data provides generally reliable HCV testing information. However, without the use of natural language processing and purposeful EHR design, manual medical record reviews will likely be required to characterize treatment initiation and completion.

Culturally Competent Gender, Sex, and Sexual Orientation Information Practices and Electronic Health Records: Rapid Review.

BackgroundOutdated gender, sex, and sexual orientation (GSSO) information practices in health care contribute to health inequities for sexual and gender minorities (SGMs). Governments, statistics agencies, and health care organizations are developing and implementing modernized practices that support health equity for SGMs. Extending our work, we conducted a rapid review of grey literature to explore information practices that support quality health care for SGMs.ObjectiveThe aim of this rapid review of grey literature was to elucidate modern GSSO information practices from leading agencies for adaptation, adoption, and application by health care providers and organizations seeking to modernize outdated GSSO information practices that contribute to health inequities among SGMs.MethodsWe searched MEDLINE and Google from 2015 to 2020 with terms related to gender, sex, sexual orientation, and electronic health/medical records for English-language grey literature resources including government and nongovernment organization publications, whitepapers, data standards, toolkits, health care organization and health quality practice and policy guides, conference proceedings, unpublished academic work, and statistical papers. Peer-reviewed journal articles were excluded, as were resources irrelevant to information practices. We also screened the reference sections of included articles for additional resources, and canvassed a working group of international topic experts for additional relevant resources. Duplicates were eliminated. ATLAS.ti was used to support analysis. Themes and codes were developed through an iterative process of writing and discussion with the research team.ResultsTwenty-six grey literature resources met the inclusion criteria. The overarching themes that emerged from the literature were the interrelated behaviors, attitudes, and policies that constitute SGM cultural competence as follows: shared language with unambiguous definitions of GSSO concepts; welcoming and inclusive care environments and affirming practices to reduce barriers to access; health care policy that supports competent health care; and adoption of modernized GSSO information practices and electronic health record design requirements that address invisibility in health data.ConclusionsHealth equity for SGMs requires systemic change. Binary representation of sex and gender in electronic health records (EHRs) obfuscates natural and cultural diversity and, in the context of health care, places SGM patients at risk of clinical harm because it leads to clinical assumptions. Agencies and agents in health care need to be equipped with the knowledge and tools needed to cultivate modern attitudes, policies, and practices that enable health equity for SGMs. Adopting small but important changes in the language and terminology used in technical and social health care systems is essential for institutionalizing SGM competency. Modern GSSO information practices depend on and reinforce SGM competency in health care.

A Retrospective Analysis Demonstrates That a Failure to Document Key Comorbid Diseases in the Anesthesia Preoperative Evaluation Associates With Increased Length of Stay and Mortality.

The introduction of electronic health records (EHRs) has helped physicians access relevant medical information on their patients. However, the design of EHRs can make it hard for clinicians to easily find, review, and document all of the relevant data, leading to documentation that is not fully reflective of the complete history. We hypothesized that the incidence of undocumented key comorbid diseases (atrial fibrillation [afib], congestive heart failure [CHF], chronic obstructive pulmonary disease [COPD], diabetes, and chronic kidney disease [CKD]) in the anesthesia preoperative evaluation was associated with increased postoperative length of stay (LOS) and mortality. Charts of patients >18 years who received anesthesia in an inpatient facility were reviewed in this retrospective study. For each disease, a precise algorithm was developed to look for key structured data (medications, lab results, structured medical history, etc) in the EHR. Additionally, the checkboxes from the anesthesia preoperative evaluation were queried to determine the presence or absence of the documentation of the disease. Differences in mortality were modeled with logistic regression, and LOS was analyzed using linear regression. A total of 91,011 cases met inclusion criteria (age 18-89 years; 52% women, 48% men; 70% admitted from home). Agreement between the algorithms and the preoperative note was >84% for all comorbidities other than chronic pain (63.5%). The algorithm-detected disease not documented by the anesthesia team in 34.5% of cases for chronic pain (vs 1.9% of cases where chronic pain was documented but not detected by the algorithm), 4.0% of cases for diabetes (vs 2.1%), 4.3% of cases for CHF (vs 0.7%), 4.3% of cases for COPD (vs 1.1%), 7.7% of cases for afib (vs 0.3%), and 10.8% of cases for CKD (vs 1.7%). To assess the association of missed documentation with outcomes, we compared patients where the disease was detected by the algorithm but not documented (A+/P-) with patients where the disease was documented (A+/P+). For all diseases except chronic pain, the missed documentation was associated with a longer LOS. For mortality, the discrepancy was associated with increased mortality for afib, while the differences were insignificant for the other diseases. For each missed disease, the odds of mortality increased 1.52 (95% confidence interval [CI], 1.42-1.63) and the LOS increased by approximately 11%, geometric mean ratio of 1.11 (95% CI, 1.10-1.12). Anesthesia preoperative evaluations not infrequently fail to document disease for which there is evidence of disease in the EHR data. This missed documentation is associated with an increased LOS and mortality in perioperative patients.

Analysis of the cognitive demands of electronic health record use

The goal of this study was to elicit the cognitive demands facing clinicians when using an electronic health record (EHR) system and learn the cues and strategies expert clinicians rely on to manage those demands. This study differs from prior research by applying a joint cognitive systems perspective to examining the cognitive aspects of clinical work. We used a cognitive task analysis (CTA) method specifically tailored to elicit the cognitive demands of an EHR system from expert clinicians from different sites in a variety of inpatient and outpatient roles. The analysis of the interviews revealed 145 unique cognitive demands of using an EHR, which were organized into 22 distinct themes across seven broad categories. In addition to confirming previously published themes of cognitive demands, the main emergent themes of this study are: 1) The EHR does not help clinicians develop and maintain awareness of the big picture; 2) The EHR does not support clinicians’ need to reason about patients’ current and future states, including effects of potential treatments; and 3) The EHR limits agency of clinicians to work individually and collaboratively. Implications for theory and EHR design and evaluation are discussed.

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.

The Electronic Health Record in Ophthalmology: Usability Evaluation Tools for Health Care Professionals.

IntroductionThe adoption of the electronic health record (EHR) has grown rapidly in ophthalmology. However, despite its potential advantages, its implementation has often led to dissatisfaction amongst health care professionals (HCP). This can be addressed using a user centred design (UCD) which is based on the philosophy that ‘the final product should suit the users, rather than making the users suit the product’. There is often no agreed best practice on the role of HCPs in the UCD process. In this paper, we describe practical qualitative methodologies that can be used by HCPs in the design, implementation and evaluation of ophthalmology EHRs.MethodsA review of current qualitative usability methodologies was conducted by practising ophthalmologists who are also qualified health informaticians.ResultsWe identified several qualitative methodologies that could be used for EHR evaluation. These include:Tools for user centred design: shadowing and autoethnography, semi-structured interviews and questionnairesTools for summative testing: card sort and reverse card sort, retrospective think aloud protocol, wireframing, screenshot testing and heat mapsConclusionHigh-yield, low-fidelity tools can be used to engage HCPs with the process of ophthalmology EHR design, implementation and evaluation. These methods can be used by HCPs without the requirement for prior training in usability science, and by clinical centres without significant technical requirements.

Usability and the Rapid Deployable Infectious Disease Decision Support System.

Health information technology-guided clinical decision support has demonstrated decreases in patient safety errors in the electronic health record. Unknown and re-emerging infectious diseases are a growing concern for many healthcare facilities. The purpose of this project was to develop a modular approach to integrate rapid deployment of clinical decision support for infectious diseases into the clinical workflow and evaluate the usability of the design. This article reports on the results of a quality improvement project to develop, implement, and evaluate rapid deployment of a clinical decision support module using a tuberculosis use case. Important lessons learned from the electronic health record build with previous Ebola and Zika decision support alert strategy are discussed as foundational in guiding the overall design, implementation, and evaluation of improvement strategies. Subject matter expert feedback was sought throughout the project for electronic health record design and build considerations. Usability evaluation was conducted using the classic Task, User, Representation, and Function unified framework of electronic health record usability. Usability satisfaction for both providers and nurses remained high. Tuberculosis cases pre-alert and post-alert had decreased order times for diagnostic studies. Results suggest satisfied clinicians coupled with usable systems create a more efficient workflow resulting in safer and timelier diagnostic testing.