Commercial Electronic Health Record Research Articles

Lessons learned in migrating from one commercial genetics decision-support tool to another: Assessment of data integrity and utilization readiness.

e23232 Background: Rapid advancements in health information technology have greatly influenced how clinicians engage with patient health data. In the context of clinical genetics, the electronic health record (EHR) often contains a wide array of data to identify patients at elevated risk for hereditary cancer syndromes. However, these data often exist in multiple forms and disparate locations, which in the presence of numerous commercial EHR solutions, results in significant variations in how institutions codify genetic data. Furthermore, within an institution, there is often internal pressure to migrate from one support tool to another, necessitating a focus on data integrity during such a transition. Methods: Fred Hutchinson Cancer Center (Fred Hutch) is a large academic cancer care center associated with the University of Washington. Between July and December 2023, the Fred Hutch Clinical Cancer Genetics and Genetic Counseling Service migrated their family history database from commercial pedigree software, Progeny, to another commercial pedigree and decision-support tool, CancerIQ. Following completion of the data migration on more than 13,000 patient records, study team planned to review a total of 500 randomly selected patient charts in both support tools. Each chart was reviewed to determine: (1) the presence of genetic intake information, (2) the presence and results of genetic testing, if available, and (3) whether the patient met National Comprehensive Cancer Network (NCCN) criteria for testing. A chart was noted to be concordant between the two support tools if there was agreement in all three of the above. Results: So far, a total of 240 patient charts were reviewed between the two support tools. Of these, 226 (94.2%) were noted to be fully concordant. Of the 14 charts that were noted to be discordant, the distribution of the discordant data was: 5 charts differed on whether genetic testing had been ordered, 5 charts differed on the results of the testing (often omitting one or more variants), and 4 differed on whether the patient met NCCN criteria for testing. Conclusions: At our institution, there was high data integrity following migration from one commercial and pedigree-generating software solution to another. While these results can ease clinician concerns following such support tools transitions, it also highlights areas for improvement in how family and patient genetic data is recorded.

Assessing Electronic Health Record (EHR) Use during a Major EHR Transition: An Innovative Mixed Methods Approach

BackgroundElectronic health record (EHR) transitions are inherently disruptive to healthcare workers who must rapidly learn a new EHR and adapt to altered clinical workflows. Healthcare workers’ perceptions of EHR usability and their EHR use patterns following transitions are poorly understood. The Department of Veterans Affairs (VA) is currently replacing its homegrown EHR with a commercial Cerner EHR, presenting a unique opportunity to examine EHR use trends and usability perceptions.ObjectiveTo assess EHR usability and uptake up to 1-year post-transition at the first VA EHR transition site using a novel longitudinal, mixed methods approach.DesignA concurrent mixed methods strategy using EHR use metrics and qualitative interview data.Participants141 clinicians with data from select EHR use metrics in Cerner Lights On Network®. Interviews with 25 healthcare workers in various clinical and administrative roles.ApproachWe assessed changes in total EHR time, documentation time, and order time per patient post-transition. Interview transcripts (n = 90) were coded and analyzed for content specific to EHR usability.Key ResultsTotal EHR time, documentation time, and order time all decreased precipitously within the first four months after go-live and demonstrated gradual improvements over 12 months. Interview participants expressed ongoing concerns with the EHR’s usability and functionality up to a year after go-live such as tasks taking longer than the old system and inefficiencies related to inadequate training and inherent features of the new system. These sentiments did not seem to reflect the observed improvements in EHR use metrics.ConclusionsThe integration of quantitative and qualitative data yielded a complex picture of EHR usability. Participants described persistent challenges with EHR usability 1 year after go-live contrasting with observed improvements in EHR use metrics. Combining findings across methods can provide a clearer, contextualized understanding of EHR adoption and use patterns during EHR transitions.

"Everything's so Role-Specific": VA Employee Perspectives' on Electronic Health Record (EHR) Transition Implications for Roles and Responsibilities.

Electronic health record (EHR) transitions are increasingly widespread and often highly disruptive. It is imperative we learn from past experiences to anticipate and mitigate such disruptions. Veterans Affairs (VA) is undergoing a large-scale transition from its homegrown EHR (CPRS/Vista) to a commercial EHR (Cerner), creating a unique opportunity of shedding light on large-scale EHR-to-EHR transition challenges. To explore one facet of the organizational impact of VA's EHR transition: its implications for employees' roles and responsibilities at the first VA site to implement Cerner Millennium EHR. As part of a formative evaluation of frontline staff experiences with VA's EHR transition, we conducted brief (~ 15min) and full-length interviews (~ 60min) with clinicians and staff at Mann-Grandstaff VA Medical Center in Spokane, WA, before, during, and after transition (July 2020-November 2021). We conducted 111 interviews with 26 Spokane clinicians and staff, recruited via snowball sampling. We conducted audio interviews using a semi-structured guide with grounded prompts. We coded interview transcripts using a priori and emergent codes, followed by qualitative content analysis. Unlike VA's previous EHR, Cerner imposes additional restrictions on access to its EHR functionality based upon "roles" assigned to users. Participants described a mismatch between established institutional duties and their EHR permissions, unanticipated changes in scope of duties brought upon by the transition, as well as impediments to communication and collaboration due to different role-based views. Health systems should anticipate substantive impacts on professional workflows when EHR role settings do not reflect prior workflows. Such changes may increase user error, dissatisfaction, and patient care disruptions. To mitigate employee dissatisfaction and safety risks, health systems should proactively plan for and communicate about expected modifications and monitor for unintended role-related consequences of EHR transitions, while vendors should ensure accurate role configuration and assignment.

ROAD2H: Development and evaluation of an open-source explainable artificial intelligence approach for managing co-morbidity and clinical guidelines.

Clinical decision support (CDS) systems (CDSSs) that integrate clinical guidelines need to reflect real-world co-morbidity. In patient-specific clinical contexts, transparent recommendations that allow for contraindications and other conflicts arising from co-morbidity are a requirement. In this work, we develop and evaluate a non-proprietary, standards-based approach to the deployment of computable guidelines with explainable argumentation, integrated with a commercial electronic health record (EHR) system in Serbia, a middle-income country in West Balkans. We used an ontological framework, the Transition-based Medical Recommendation (TMR) model, to represent, and reason about, guideline concepts, and chose the 2017 International global initiative for chronic obstructive lung disease (GOLD) guideline and a Serbian hospital as the deployment and evaluation site, respectively. To mitigate potential guideline conflicts, we used a TMR-based implementation of the Assumptions-Based Argumentation framework extended with preferences and Goals (ABA+G). Remote EHR integration of computable guidelines was via a microservice architecture based on HL7 FHIR and CDS Hooks. A prototype integration was developed to manage chronic obstructive pulmonary disease (COPD) with comorbid cardiovascular or chronic kidney diseases, and a mixed-methods evaluation was conducted with 20 simulated cases and five pulmonologists. Pulmonologists agreed 97% of the time with the GOLD-based COPD symptom severity assessment assigned to each patient by the CDSS, and 98% of the time with one of the proposed COPD care plans. Comments were favourable on the principles of explainable argumentation; inclusion of additional co-morbidities was suggested in the future along with customisation of the level of explanation with expertise. An ontological model provided a flexible means of providing argumentation and explainable artificial intelligence for a long-term condition. Extension to other guidelines and multiple co-morbidities is needed to test the approach further.

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

The national developmental-behavioral pediatric (DBP) workforce struggles to meet current service demands because of several factors. Lengthy and inefficient documentation processes are likely to contribute to service demand challenges, but DBP documentation patterns have not been sufficiently studied. Identifying clinical practice patterns may inform strategies to address documentation burden in DBP practice. Nearly 500 DBP physicians in the United States use a single commercial electronic health record (EHR) system (EpicCare Ambulatory, Epic Systems Corporation, Verona WI). We evaluated descriptive statistics using the US Epic DBP provider data set. We then compared DBP documentation metrics against those of pediatric primary care and selected pediatric subspecialty providers who provide similar types of care. One-way analyses of variance (ANOVAs) were conducted to determine whether outcomes differed among provider specialties. We identified 4 groups for analysis from November 2019 through February 2020: DBP (n = 483), primary care (n = 76,423), pediatric psychiatry (n = 783), and child neurology (n = 8589). Post hoc pairwise comparisons revealed statistically significant differences between multiple outcome-specialty combinations. Time in notes per appointment and progress note length demonstrated the strongest evidence of an increased burden on DBP providers compared with other similar provider groups. DBP providers spend a significant amount of time documenting progress notes both during and outside of normal clinic hours. This preliminary analysis highlights the utility of using EHR user activity data to quantitatively measure documentation burden.

Oncologist-driven development of an electronic health record (EHR) clinical data visualization tool for prostate cancer.

267 Background: Clinical information management is a burdensome process for oncology providers owing to the complexity of modern cancer data. The results that a clinician needs to review are often spread across several areas within the EHR, making it cumbersome to sense a broad overview of patient status. The purpose of this study is to describe a framework for oncologist-driven development of a data visualization tool to trend cancer biomarkers and assess the feasibility of this tool to query and display EHR data relevant for the treatment of prostate cancer. Methods: A clinical sponsor is selected to identify data elements necessary to make treatment decisions for patients receiving therapy for prostate cancer and to provide rapid feedback for the clinical tool interface. The commercial EHR database is queried to determine identifying codes for relevant laboratory tests, medications, and procedures. Data elements are assembled using the EHR platform for clinical synopsis and the clinical tool is made available to five genitourinary medical oncologists for initial pilot. Results: Oral prostate cancer medications were queried based on medication therapeutic and pharmaceutical class. In addition, androgen deprivation therapy (ADT) injections were separately identified based on route of administration. Prostate specific antigen (PSA) and testosterone result values were queried using laboratory base and/or common name codes. However, many duplicate entities are found varying by hospital/laboratory site and test assay. The assembled clinical data visualization tool can overlay temporal trends in PSA and testosterone over medication start/stop dates to convey treatment response and signs of early medication resistance. The clinician also has the option to overlay vital signs or other laboratory information to visualize treatment related adverse events (ex. weight gain related to ADT, anemia related to PARP inhibitor therapy, etc.) Lastly, the tool can also highlight the dates of the patient’s last imaging tests to allow clinicians to determine if the patient is due for any follow up imaging. Conclusions: The EHR can support novel data visualization tools for cancer biomarkers that can reasonably support clinical workflows. Development requires an intimate knowledge of EHR data but may still be limited by duplicate or erroneous codes for laboratory results. This issue may be addressed by using standard nomenclature for laboratory results such as LOINC codes but is not currently supported by the commercial EHR. Future work in this area will include formal usability testing from the perspective of oncology providers and patients.

Problem-oriented documentation: design and widespread adoption of a novel toolkit in a commercial electronic health record.

Problem-oriented documentation is an accepted method of note construction which facilitates clinical thought processes. However, problem-oriented documentation is challenging to put into practice using commercially available electronic health record (EHR) systems. Our goal was to create, iterate, and distribute a problem-oriented documentation toolkit within a commercial EHR that maximally supported clinicians' thinking, was intuitive to use, and produced clear documentation. We used an iterative design process that stressed visual simplicity, data integration, a predictable interface, data reuse, and clinician efficiency. Creation of the problem-oriented documentation toolkit required the use of EHR-provided tools and custom programming. We developed a problem-oriented documentation interface with a 3-column view showing (1) a list of visit diagnoses, (2) the current overview and assessment and plan for a selected diagnosis, and (3) a list of medications, labs, data, and orders relevant to that diagnosis. We also created a series of macros to bring information collected through the interface into clinicians' notes. This toolkit was put into a live environment in February 2019. Over the first 9 months, the custom problem-oriented documentation toolkit was used in a total of 8385 discrete visits by 28 clinicians in 13 ambulatory departments. After 9 months, the go-live education and EHR optimization teams in our health system began promoting the toolkit to new and existing users of our EHR resulting in a significantly increased uptake by outpatient clinicians. In April 2022 alone, the toolkit was used in more than 92000 ambulatory visits by 894 users in 271 departments across our health system. As a health-system client of a commercial EHR, we developed and deployed a revised problem-oriented documentation toolkit that is used by clinicians more than 92000 times a month. Key success elements include an emphasis on usability and an effective training effort.

Real-World Evidence (RWE) Studies Supported Hematologic Oncology United States Food and Drug Administration (US FDA) Approval: What Do They Look like?

Introduction/Background: Although randomized controlled trials are considered the gold standard of evidence for safety and efficacy of a drug, they are subject to several limitations such as difficulty in recruiting patients with rare diseases or randomization of patients to studies with treatments that lack an established standard of care owing to efficacy or toxicity concerns. RWE can help overcome these challenges. RWE collects patient data from historical trials or retrospective observational studies and compares or contextualizes these data to experimental treatments by using proper statistical adjustments. The 21st Century Cures Act inspired the framework for the US FDA to use RWE to assess product effectiveness of approved drugs to support regulatory decision-making. Consequently, RWE is increasingly used in New Drug Applications (NDAs) and Biologics License Applications (BLAs) for hematologic malignancies, and findings suggest that submissions using RWE may receive faster approval. However, data are lacking on adoption of RWE for regulatory submissions and its use in regulatory decision-making. Here, we outline RWE utilization and limitations of regulatory submissions for hematologic malignancy therapeutics, which received accelerated or full approval in the US. Methods: Between 2017 and 2021, all NDA and BLA approvals from the Division of Hematological Malignancies were reviewed for hematology/oncology drugs or indications. The FDA Oncology Drug Advisory Committee (ODAC) briefing and/or multidisciplinary review documents were evaluated to identify the drug approvals using RWE. This assessment was performed by 4 independent reviewers who evaluated FDA comments regarding RWE. RWE sources, study methodology, drug indications, pivotal trial information, statistical analyses, and results were summarized. Results: A total of 74 hematologic malignancy approvals were identified, of which 7 (9.4%) provided RWE that supported regulatory approval. Detailed analyses of the FDA ODAC briefing and/or multidisciplinary review documents for these 7 drug compounds including comparison of trial and RWE data source, patient population, clinical endpoints and outcomes, comparison strategy, and FDA comments are shown in the Table. The FDA identified several key considerations for RWE use for drug applications based on single-arm studies. These included pivotal trials that demonstrated a high response or large treatment effect, an improved drug toxicity profile, or a novel drug mechanism of action. The most common RWE sources included retrospective observational studies from medical records, data from other clinical trials, commercial electronic health record databases, and literature reviews. The most common hematologic indications for RWE submissions were relapsed/refractory (R/R) large B-cell lymphoma and R/R multiple myeloma. The most common endpoints for RWE included presence of measurable residual disease, complete response rate, and duration of response. In contrast, the most common endpoints in pivotal trials included survival endpoints (eg, progression-free survival). The most common statistical methods used to adjust for baseline imbalances included propensity-score matching and inverse-probability of treatment weighting. The FDA identified several areas that may compromise the reliability of RWE: lack of early engagement and discussion of the study design with the FDA, absence of a prespecified statistical analysis plan or protocol, lack of transparency in data collection methods, dissimilar inclusion/exclusion criteria, dissimilar study endpoints, and an inconsistent method or frequency of outcome assessments. Comparator arms often missed baseline covariates, had selection bias, and used different outcome assessment criteria. Conclusion: Good data quality, comparable patient populations, consistent endpoints, prespecified protocols, and the establishment of statistical analysis plans before the start of a study may be the most important factors in the FDA's approval of RWE regulatory submissions. Although the use of RWE to define a direct comparator was limited by flaws in study design and statistical analyses, RWE can be used to establish historical outcomes for patients with currently available treatment. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Prediction Algorithms: Is Peer Review Enough?

Prediction Algorithms: Is Peer Review Enough?

Reducing Volatile Anesthetic Waste Using a Commercial Electronic Health Record Clinical Decision Support Tool to Lower Fresh Gas Flows.

Volatile anesthetic consumption can be reduced by minimizing excessive fresh gas flows (FGFs). Currently, it is unknown whether decision support tools embedded within commercial electronic health record systems can be successfully adopted to achieve long-term reductions in FGF rates. The authors describe the implementation of an electronic health record-based clinical decision support tool aimed at reducing FGF and evaluate the effectiveness of this intervention in achieving sustained reductions in FGF rates and volatile anesthetic consumption. On August 29, 2018, we implemented a decision support tool within the Epic Anesthesia Information Management System (AIMS) to alert providers of high FGF (>0.7 L/min for desflurane and >1 L/min for sevoflurane) during maintenance of anesthesia. July 22, 2015, to July 10, 2018, served as our baseline period before the intervention. The intervention period spanned from August 29, 2018, to December 31, 2019. Our primary outcomes were mean FGF (L/min) and volatile agent consumption (mL/MAC-h). Because a simple comparison of 2 time periods may result in false conclusions due to underlying trends independent of the intervention, we performed segmented regression of the interrupted time series to assess the change in level at the start of the intervention and the differences in slopes before and after the intervention. The analysis was also adjusted for potential confounding variables. Data included 44,899 cases using sevoflurane preintervention with 26,911 cases postintervention, and 17,472 cases using desflurane with 1185 cases postintervention. Segmented regression of the interrupted times series demonstrated a decrease in mean FGF by 0.6 L/min (95% CI, 0.6-0.6 L/min; P < .0001) for sevoflurane and 0.2 L/min (95% CI, 0.2-0.3 L/min; P < .0001) for desflurane immediately after implementation of the intervention. For sevoflurane, mL/MAC-h decreased by 3.8 mL/MAC-h (95% CI, 3.6-4.1 mL/MAC-h; P < .0001) after implementation of the intervention and decreased by 4.1 mL/MAC-h (95% CI, 2.6-5.6 mL/MAC-h; P < .0001) for desflurane. Slopes for both FGF and mL/MAC-h in the postintervention period were statistically less negative than the preintervention slopes (P < .0001 for sevoflurane and P < .01 for desflurane). A commercial AIMS-based decision support tool can be adopted to change provider FGF management patterns and reduce volatile anesthetic consumption in a sustainable fashion.

Design, Implementation, Utilization, and Sustainability of a Fast Healthcare Interoperability Resources-Based Inpatient Rounding List.

We designed and implemented an application programming interface (API)-based electronic health record (EHR)-integrated rounding list and evaluated acceptability, clinician satisfaction, information accuracy, and efficiency related to the application. We developed and integrated an application, employing iterative design techniques with user feedback. EHR and application user action logs, as well as hospital safety reports, were evaluated. Rounding preparation characteristics were obtained through surveys before and after application integration. To evaluate usability, inpatient providers, including residents, fellows, and attendings were surveyed 2 weeks prior to and 6 months after enterprise-wide EHR application integration. Our primary outcome was provider time savings measured by user action logs; secondary outcomes include provider satisfaction. The application was widely adopted by inpatient providers, with more than 69% of all inpatients queried by the application within 6 months of deployment. Application utilization was sustained throughout the study period with 79% (interquartile range [IQR]: 76, 82) of enterprise-wide unique patients accessed per weekday. EHR action logs showed application users spent -3.24 minutes per day (95% confidence interval [CI]: -6.8, 0.33), p = 0.07 within the EHR compared with nonusers. Median self-reported chart review time for attendings decreased from 30 minutes (IQR: 15, 60) to 20 minutes (IQR: 10, 45) after application integration (p = 0.04). Self-reported sign-out preparation time decreased by a median of 5 minutes (p < 0.01), and providers were better prepared for hand-offs (p = 0.02). There were no increased safety reports during the study period. This study demonstrates successful integration of a rounding application within a commercial EHR using APIs. We demonstrate increasing both provider-reported satisfaction and time savings. Rounding lists provided more accurate and timely information for rounds. Application usage was sustained across multiple specialties at 42 months. Other application designers should consider data density, optimization of provider workflows, and using real-time data transfer using novel tools when designing an application.

Building an information system to facilitate pharmacogenomics clinical translation with clinical decision support.

Pharmacogenomics clinical decision support (PGx-CDS) is an important tool to incorporate PGx information into existing clinical workflows and facilitate PGx clinical translation. However, due to the lack of a computable formalization to represent the primary PGx knowledge, the complexity of genomics information and the lag of current commercial electronic health record (EHR) system for precision medicine, it is difficult to develop computerized PGx-CDS. Therefore, we explored a novel approach to build an information system, named the Pharmacogenomics Clinical Translation Platform (PCTP), for PGx clinical implementation. The PCTP can represent, store, and manage the primary PGx knowledge in a structured and computable format. Moreover, it has the potential to provide various PGx-CDS services and simplify the integration of PGx-CDS into EHRs.

Pilot Testing of Simulation in the Evaluation of a Novel, Rapidly Deployable Electronic Health Record for use in Disaster Intensive Care.

The SARS-CoV-2 pandemic has highlighted the need for rapid creation and management of ICU field hospitals with effective remote monitoring which is dependent on the rapid deployment and integration of an Electronic Health Record (EHR). We describe the use of simulation to evaluate a rapidly scalable hub-and-spoke model for EHR deployment and monitoring using asynchronous training. We adapted existing commercial EHR products to serve as the point of entry from a simulated hospital and a separate system for tele-ICU support and monitoring of the interfaced data. To train our users we created a modular video-based curriculum to facilitate asynchronous training. Effectiveness of the curriculum was assessed through completion of common ICU documentation tasks in a high-fidelity simulation. Additional endpoints include assessment of EHR navigation, user satisfaction (Net Promoter), system usability (System Usability Scale-SUS), and cognitive load (NASA-TLX). A total of 5 participants achieved a 100% task completion on all domains except ventilator data (91%). Systems demonstrated high degrees of satisfaction (Net Promoter = 65.2), acceptable usability (SUS = 66.5), and acceptable cognitive load (NASA-TLX = 41.5); with higher levels of cognitive load correlating with the number of screens employed. Clinical usability of a comprehensive and rapidly deployable EHR was acceptable in an intensive care simulation which was preceded by < 1 hour of video education about the EHR. This model should be considered in plans for integrated clinical response with remote and accessory facilities.

Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts.

ObjectiveTo assess the appropriateness of medication-related clinical decision support (CDS) alerts associated with renal insufficiency and the potential/actual harm from overriding the alerts.Materials and MethodsOverride rate frequency was recorded for all inpatients who had a renal CDS alert trigger between 05/2017 and 04/2018. Two random samples of 300 for each of 2 types of medication-related CDS alerts associated with renal insufficiency—“dose change” and “avoid medication”—were evaluated by 2 independent reviewers using predetermined criteria for appropriateness of alert trigger, appropriateness of override, and patient harm.ResultsWe identified 37 100 “dose change” and 5095 “avoid medication” alerts in the population evaluated, and 100% of each were overridden. Dose change triggers were classified as 12.5% appropriate and overrides of these alerts classified as 90.5% appropriate. Avoid medication triggers were classified as 29.6% appropriate and overrides 76.5% appropriate. We identified 5 adverse drug events, and, of these, 4 of the 5 were due to inappropriately overridden alerts.ConclusionAlerts were nearly always presented inappropriately and were all overridden during the 1-year period studied. Alert fatigue resulting from receiving too many poor-quality alerts may result in failure to recognize errors that could lead to patient harm. Although medication-related CDS alerts associated with renal insufficiency had previously been found to be the most clinically beneficial alerts in a legacy system, in this system they were ineffective. These findings underscore the need for improvements in alert design, implementation, and monitoring of alert performance to make alerts more patient-specific and clinically appropriate.

Can disability accommodation needs stored in electronic health records help providers prepare for patient visits? A qualitative study

BackgroundEmbedding patient accommodation need in the electronic health record (EHR) has been proposed as one means to improve health care delivery to patients with disabilities. Accommodation need is not a standard field in commercial EHR software. However, some medical practices ask about accommodation need and store it in the EHR. Little is known about how the information is used, or barriers to its use. This exploratory-descriptive study examines whether and how information about patients’ disability-related accommodation needs stored in patient records is used in a primary health care center to plan for care.MethodsFour focus groups (n = 35) were conducted with staff of a Federally Qualified Health Center that asks four accommodation questions at intake for the EHR. Respondents were asked how they learned about patient accommodation need, whether and how they used the information in the EHR, barriers to its use, and recommendations for where accommodation information should reside. A brief semi-structured interview was conducted with patients who had indicated an accommodation need (n = 12) to learn their experience at their most recent appointment. The qualitative data were coded using structural coding and themes extracted.ResultsFive themes were identified from the focus groups: (1) staff often do not know accommodation needs before the patient’s arrival; (2) electronic patient information systems offer helpful information, but their structure creates challenges and information gaps; (3) accommodations for a patient’s disability occur, but are developed at the time of visit; (4) provider knowledge of a regular patient is often the basis for accommodation preparation; and (5) staff recognize benefits to advance knowledge of accommodation needs and are supportive of methods to enable it. Most patients did not recall indicating accommodation need on the intake form. However, they expected to be accommodated based upon the medical practice’s knowledge of them.ConclusionsPatient accommodation information in the EHR can be useful for visit planning. However, the structure must enable transfer of information between scheduling and direct care and be updatable as needs change. Flexibility to record a variety of needs, visibility to differentiate accommodation need from other alerts, and staff education about needs were recommended.

Clinical Decision Support for Worker Health: A Five-Site Qualitative Needs Assessment in Primary Care Settings.

Although patients who work and have related health issues are usually first seen in primary care, providers in these settings do not routinely ask questions about work. Guidelines to help manage such patients are rarely used in primary care. Electronic health record (EHR) systems with worker health clinical decision support (CDS) tools have potential for assisting these practices. This study aimed to identify the need for, and barriers and facilitators related to, implementation of CDS tools for the clinical management of working patients in a variety of primary care settings. We used a qualitative design that included analysis of interview transcripts and observational field notes from 10 clinics in five organizations. We interviewed 83 providers, staff members, managers, informatics and information technology experts, and leaders and spent 35 hours observing. We identified eight themes in four categories related to CDS for worker health (operational issues, usefulness of proposed CDS, effort and time-related issues, and topic-specific issues). These categories were classified as facilitators or barriers to the use of the CDS tools. Facilitators related to operational issues include current technical feasibility and new work patterns associated with the coordinated care model. Facilitators concerning usefulness include users' need for awareness and evidence-based tools, appropriateness of the proposed CDS for their patients, and the benefits of population health data. Barriers that are effort-related include additional time this proposed CDS might take, and other pressing organizational priorities. Barriers that are topic-specific include sensitive issues related to health and work and the complexities of information about work. We discovered several themes not previously described that can guide future CDS development: technical feasibility of the proposed CDS within commercial EHRs, the sensitive nature of some CDS content, and the need to assist the entire health care team in managing worker health.

Improving Allergy Documentation: A Retrospective Electronic Health Record System-Wide Patient Safety Initiative.

Documentation of allergies in a coded, non-free-text format in the electronic health record (EHR) triggers clinical decision support to prevent adverse events. Health system-wide patient safety initiatives to improve EHR allergy documentation by specifically decreasing free-text allergy entries have not been reported. The goal of this initiative was to systematically reduce free-text allergen entries in the EHR allergy module. We assessed free-text allergy entries in a commercial EHR used at a multihospital integrated health care system in the greater Boston area. Using both manual and automated methods, a multidisciplinary consensus group prioritized high-risk and frequently used free-text allergens for conversion to coded entries, added new allergen entries, and deleted duplicate allergen entries. Environmental allergies were moved to the patient problem list. We identified 242,330 free-text entries, which included a variety of environmental allergies (42%), food allergies (18%), contrast media allergies (13%), "no known allergy" (12%), drug allergies (2%), and "no contrast allergy" (2%). Most free-text entries were entered by medical assistants in ambulatory settings (34%) and registered nurses in perioperative settings (20%). We remediated a total of 52,206 free-text entries with automated methods and 79,578 free-text entries with manual methods. Through this multidisciplinary intervention, we identified and remediated 131,784 free-text entries in our EHR to improve clinical decision support and patient safety. Additional strategies are required to completely eliminate free-text allergy entry, and establish systematic, consistent, and safe guidelines for documenting allergies.

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

Objectives This study aimed to understand if and how homegrown electronic health record (EHR) systems are used in the post–Meaningful Use (MU) era according to the experience of six traditional EHR developers. Methods We invited informatics leaders from a convenience sample of six health care organizations that have recently replaced their long used homegrown systems with commercial EHRs. Participants were asked to complete a written questionnaire with open-ended questions designed to explore if and how their homegrown system(s) is being used and maintained after adoption of a commercial EHR. We used snowball sampling to identify other potential respondents and institutions. Results Participants from all six organizations included in our initial sample completed the questionnaire and provided referrals to four other organizations; from these, two did not respond to our invitations and two had not yet replaced their system and were excluded. Two organizations (Columbia University and University of Alabama at Birmingham) still use their homegrown system for direct patient care and as a downtime system. Four organizations (Intermountain Healthcare, Partners Healthcare, Regenstrief Institute, and Vanderbilt University) kept their systems primarily to access historical data. All organizations reported the need to continue to develop or maintain local applications despite having adopted a commercial EHR. The most common applications developed include display and visualization tools and clinical decision support systems. Conclusion Homegrown EHR systems continue to be used for different purposes according to the experience of six traditional homegrown EHR developers. The annual cost to maintain these systems varies from $21,000 to over 1 million. The collective experience of these organizations indicates that commercial EHRs have not been able to provide all functionality needed for patient care and local applications are often developed for multiple purposes, which presents opportunities for future research and EHR development.

Staff expectations for the implementation of an electronic health record system: a qualitative study using normalisation process theory

BackgroundGlobal evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This study explored staff expectations for change and outcome following procurement of a commercial EHR system by a large academic acute NHS hospital in the UK.MethodsQualitative interviews were conducted with 14 members of hospital staff who represented a variety of user groups across different specialities within the hospital. The four components of Normalisation Process Theory (Coherence, Cognitive participation, Collective action and Reflexive monitoring) provided a theoretical framework to interpret and report study findings.ResultsHealth professionals had a common understanding for the rationale for EHR implementation (Coherence). There was variation in willingness to engage with and invest time into EHR (Cognitive participation) at an individual, professional and organisational level. Collective action (whether staff feel able to use the EHR) was influenced by context and perceived user-involvement in EHR design and planning of the implementation strategy. When appraising EHR (Reflexive monitoring), staff anticipated short and long-term benefits. Staff perceived that quality and safety of patient care would be improved with EHR implementation, but that these benefits may not be immediate. Some staff perceived that use of the system may negatively impact patient care. The findings indicate that preparedness for EHR use could mitigate perceived threats to the quality and safety of care.ConclusionsHealth professionals looked forward to reaping the benefits from EHR use. Variations in level of engagement suggest early components of the implementation strategy were effective, and that more work was needed to involve users in preparing them for use. A clearer understanding as to how staff groups and services differentially interact with the EHR as they go about their daily work was required. The findings may inform other hospitals and healthcare systems on actions that can be taken prior to EHR implementation to reduce concerns for quality and safety of patient care and improve the chance of successful implementation.

Integrating pharmacogenomics into the electronic health record by implementing genomic indicators.

Pharmacogenomics (PGx) clinical decision support integrated into the electronic health record (EHR) has the potential to provide relevant knowledge to clinicians to enable individualized care. However, past experience implementing PGx clinical decision support into multiple EHR platforms has identified important clinical, procedural, and technical challenges. Commercial EHRs have been widely criticized for the lack of readiness to implement precision medicine. Herein, we share our experiences and lessons learned implementing new EHR functionality charting PGx phenotypes in a unique repository, genomic indicators, instead of using the problem or allergy list. The Gen-Ind has additional features including a brief description of the clinical impact, a hyperlink to the original laboratory report, and links to additional educational resources. The automatic generation of genomic indicators from interfaced PGx test results facilitates implementation and long-term maintenance of PGx data in the EHR and can be used as criteria for synchronous and asynchronous CDS.