Epic Electronic Health Record Research Articles

Advancing Newborn Screening Long-Term Follow-Up: Integration of Epic-Based Registries, Dashboards, and Efficient Workflows.

The Connecticut Newborn Screening (NBS) Network, in partnership with the Connecticut Department of Public Health, strategically utilized the Epic electronic health record (EHR) system to establish registries for tracking long-term follow-up (LTFU) of NBS patients. After launching the LTFU registry in 2019, the Network obtained funding from the Health Resources and Services Administration to address the slow adoption by specialty care teams. An LTFU model was implemented in the three highest-volume specialty care teams at Connecticut Children's, involving an early childhood cohort diagnosed with an NBS-identified disorder since the formation of the Network in March 2019. This cohort grew from 87 to 115 over the two-year project. Methods included optimizing registries, capturing external data from Health Information Exchanges, incorporating evidence-based guidelines, and conducting qualitative and quantitative evaluations. The early childhood cohort demonstrated significant and sustainable improvements in the percentage of visits up-to-date (%UTD) compared to the non-intervention legacy cohort of patients diagnosed with an NBS disorder before the formation of the Network. Positive trends in the early childhood cohort, including %UTD for visits and condition-specific performance metrics, were observed. The qualitative evaluation highlighted the achievability of practice behavior changes for specialty care teams through responsive support from the nurse analyst. The Network's model serves as a use case for applying and achieving the adoption of population health tools within an EHR system to track care delivery and quickly fill identified care gaps, with the aim of improving long-term health for NBS patients.

Pragmatic implementation of comprehensive dementia care management: The Cedars-Sinai C.A.R.E.S. Program preliminary data.

The United States faces a growing challenge with over 6.5 million people living with dementia (PLwD). PLwD and their caregivers struggle with cognitive, functional, behavioral, and psychosocial issues. As dementia care shifts to home settings, caregivers receive inadequate support but bear increasing responsibilities, leading to higher healthcare costs. In response, the Centers for Medicare & Medicaid Services (CMS) introduced the Guiding an Improving Dementia Experience (GUIDE) Model. The study explores the real-world implementation of the Cedars-Sinai C.A.R.E.S. Program, a pragmatic dementia care model, detailing its recruitment process and initial outcomes. The Cedars-Sinai C.A.R.E.S. Program was integrated into the Epic electronic health record system and focused on proactive patient identification, engagement, interdisciplinary collaboration, care transitions, and ongoing care management. Eligible patients with a dementia diagnosis were identified through electronic health record and invited to join the program. Nurse practitioners with specialized training in dementia care performed comprehensive assessments using the CEDARS-6 tool, leading to personalized care plans developed in consultation with primary care providers. Patients benefited from a multidisciplinary team and support from care navigators. Of the 781 eligible patients identified, 431 were enrolled in the C.A.R.E.S. Enrollees were racially diverse, with lower caregiver strain and patient behavioral and psychological symptoms of dementia (BPSD) severity compared to other programs dementia care programs. Healthcare utilization, including hospitalizations, emergency department (ED) admissions, and urgent care visits showed a downward trend over time. Completion of advanced directives and Physician Order of Life-Sustaining Treatment (POLST) increased after enrollment. The Cedars-Sinai C.A.R.E.S. Program offers a promising approach to dementia care. Its real-world implementation demonstrates the feasibility of enrolling a diverse population and achieving positive outcomes for PLwD and their caregivers, supporting the goals of national dementia care initiatives.

Standardizing default electronic health record tools to improve safety for hospitalized patients with Parkinson's disease.

Electronic Health Record (EHR) systems are often configured to address challenges and improve patient safety for persons with Parkinson's disease (PWP). For example, EHR systems can help identify Parkinson's disease (PD) patients across the hospital by flagging a patient's diagnosis in their chart, preventing errors in medication and dosing through the use of clinical decision support, and supplementing staff education through care plans that provide step-by-step road maps for disease-based care of a specific patient population. However, most EHR-based solutions are locally developed and, thus, difficult to scale widely or apply uniformly across hospital systems. In 2020, the Parkinson's Foundation, a national and international leader in PD research, education, and advocacy, and Epic, a leading EHR vendor with more than 35% market share in the United States, launched a partnership to reduce risks to hospitalized PWP using standardized EHR-based solutions. This article discusses that project which included leadership from physician informaticists, movement disorders specialists, hospital quality officers, the Parkinson's Foundation and members of the Parkinson's community. We describe the best practice solutions developed through this project. We highlight those that are currently available as standard defaults or options within the Epic EHR, discuss the successes and limitations of these solutions, and consider opportunities for scalability in environments beyond a single EHR vendor. The Parkinson's Foundation and Epic launched a partnership to develop best practice solutions in the Epic EHR system to improve safety for PWP in the hospital. The goal of the partnership was to create the EHR tools that will have the greatest impact on outcomes for hospitalized PWP.

Implementing a Clinical Decision Support Tool to Improve Physical Activity.

Currently, only about half of U.S. adults achieve current physical activity guidelines. Routine physical activity is not regularly assessed, nor are patients routinely counseled by their healthcare provider on achieving recommended levels. The three-question physical activity vital sign (PAVS) was developed to assess physical activity duration and intensity and identify adults not meeting physical activity guidelines. Clinical decision support provided via a best practice advisory in an electronic health record (EHR) system can be triggered as a prompt, reminding healthcare providers to implement the best practice intervention when appropriate. Remote patient monitoring of physical activity can provide objective data in the EHR. This study aimed to evaluate the feasibility and clinical utility of embedding the PAVS and a triggered best practice advisor into the EHR in an ambulatory preventive cardiology practice setting to alert providers to patients reporting low physical activity and prompt healthcare providers to counsel these patients as needed. Three components based in the EHR were integrated for the purpose of this study: Patients completed the PAVS through their electronic patient portal prior to an office visit, a best practice advisory was created to prompt providers to counsel patients who reported low levels of physical activity, and remote patient monitoring via Fitbit synced to the EHR provided objective physical activity data. The intervention was pilot-tested in the Epic EHR for 1 year (July 1, 2021 to June 30, 2022). Qualitative feedback on the intervention from both providers and patients was obtained at the completion of the study. Monthly assessments of the use of the PAVS and best practice advisory and remote patient monitoring were completed. Patients' completion of the PAVS varied from 35% to 48% per month. The best practice advisory was signed by providers between 2% and 65% and was acknowledged by 2%-22% per month. The majority (58%) of patients were able to sync a Fitbit device to their EHR for remote monitoring. Although uptake of each component needs improvement, this pilot demonstrated the feasibility of incorporating a physical activity promotion intervention into the EHR. Qualitative feedback provided guidance for future implementation.

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review.

Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research. The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences. We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results. We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized. The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Impact on End‐of‐life Planning of a Care Coordination Program for persons living with dementia

AbstractBackgroundAlzheimer’s disease and related dementias (ADRD) afflict over five million persons in the U.S., and persons living with dementia (PLWD) have been shown to receive poor quality care and have worse health outcomes compared to those without ADRD. We developed a population‐based dementia care management program to support the care of PWLD in a large U.S. healthcare system.MethodsIn a large multi‐specialty medical group practice, we identified patients enrolled in a value‐based insurance program (Medicare Advantage) using the EPIC electronic health record (EHR), and eligible patients were invited to enroll in the CARES dementia care program. Patients were eligible if they had an ICD‐10 diagnosis of ADRD in the EHR problem list and/or past medical history, or currently taking an FDA‐approved medication for ADRD. We additionally included patients with ADRD who have a primary care provider in the affiliated academic health system. During an in‐person intake visit, a study‐assigned nurse practitioner (NP) engaged in advance care planning discussion with patients and caregivers and completed advance directives (AD) and Physician Order for Life Sustaining Treatment (POLST). We assessed the rate of completion of the AD and POLST pre‐program and post‐enrollment.ResultsWe enrolled 195 patients in the CARES dementia care program. After enrollment, participants increased completion of advanced directives from 27.7% to 30.8% (p = 0.25) and the POLST from 13.3% to 23.1% (p = 0.006). Of the POLST forms completed, 70.7% indicated that the patient was ‘do not attempt resuscitation’ (DNAR) (65.2% of those who completed the POLST pre‐program, 77.8% for those who completed after enrollment, p = 0.19). Among those who completed the POLST, 55.0% indicated selective medical interventions (63.6% pre‐program, 47.1% post‐enrollment, p = 0.15), 40.0% wanted full medical interventions (31.8% pre‐program, 52.9% post‐enrollment, p = 0.10), and 5.0% wanted comfort‐focused interventions (4.5% pre‐program, 5.9% post‐enrollment, p = 0.43). Trial period of nutritional supports was indicated by 69.2% (72.7% pre‐program, 64.7% post‐enrollment, p = 0.28), while 28.2% wanted no artificial treatment (27.2% pre‐program, 29.4% post‐enrollment, p = 0.45), and 2.6% wanted long‐term nutritional support (0% pre‐program, 5.9% post‐enrollment, p = 0.13).ConclusionA dementia care coordination program shows signs of increased completion of end‐of‐life planning, with the majority choosing ‘do not attempt resuscitation’ (DNAR).

Identification of Persons Living with Dementia Using the Electronic Health Record

AbstractBackgroundAlzheimer’s disease and related dementias (ADRD) are underdiagnosed in the primary care setting. Proactive screening for cognitive impairment and subsequent evaluation and diagnosis of patients who screen positive are not routinely and reliably performed. As a result, identification of persons living with dementia (PLWD) for enrollment in clinical programs, clinical trials, and research studies can be challenging. The electronic health record (EHR) represents a potentially viable tool to efficiently and accurate identify PLWD.MethodsIn a large academic health care system in the U.S., we performed an EPIC EHR search for PLWD with the intent of enrolling them in an outpatient dementia care management program. The EHR algorithm used the following criteria for dementia: (1) an ICD‐10 dementia diagnosis in the problem list or past medical history or (2) an FDA‐approved drug on their active medication list. We performed chart review for patients who were identified to have potential dementia using this algorithm to confirm dementia diagnosis is documented in clinical notes.ResultsA total of 985 patients were identified by EHR criteria as potentially having dementia. After chart review, 747 (75.8%) were confirmed to have dementia documented in their clinical history and progress notes. One hundred thirty (13.2%) did not have a confirmed dementia diagnosis, 58 (5.9%) had an incomplete dementia evaluation, and 50 (5.0%) had only mild cognitive impairment. In addition, 55 (5.6%) were deceased.ConclusionWe found that an EHR algorithm can identify patients with dementia in a health plan population. This model may be a useful tool for a focused recruitment of potential participants in clinical trials, research studies, and clinical programs.

Contemporary Intravenous Iron Usage and Safety Patterns

Introduction: Intravenous (IV) iron is routinely used throughout various medical specialties in addition to hematology, including nephrology, cardiology, obstetrics, gastroenterology, and neurology. While all formulations are considered safe, those with iron dextran (ID) are reported to have a relatively higher incidence of anaphylaxis, often prompting a test-dose prior to full administration. Recently, there has been an ongoing national shortage of ID, leading to higher usage of alternate formulations and need for further characterization of usage and safety. Methods: The Epic electronic health record was searched using the Slicer Dicer function to obtain information regarding intravenous iron administrations from 01/01/2021 to 08/31/2022 at the various Mayo Clinic sites throughout the United States. Adverse events were evaluated through the internal patient safety reporting system for adverse drug reactions. Serious adverse events (SAEs) were defined as those events requiring epinephrine administration, anaphylaxis, hypotension, tachycardia, or an allergic reaction (hives, rash, chest tightness, eye swelling) within 24 hours of IV iron infusion. Non-serious adverse events (NSAEs) were defined as those events requiring administration of an antihistamine, steroid, or reported gastrointestinal disturbance within 24 hours of IV iron infusion. Results: A total of 49,310 infusions were administered during the analyzed period and included the use of five formulations: ID, iron sucrose (IS), ferumoxytol (FM), ferric carboxymaltose (FC), and ferric gluconate (FG). Infusions were distributed amongst Rochester (n=23,899; 16%ID, 77%IS, 5%FM, 2%FC, 0%FG), Florida (n=5,755; 6%ID, 43%IS, 34%FM, 9%FC, 8%FG), Arizona (n=5,123; 4%ID, 81%IS, 3%FM, 11%FC, 1%FG), and the Health System (n=14,533; 3%ID, 85%IS, 9%FM, 2%FC, 1%FG). A total of 49 AEs were reported (59% SAEs; 41% NSAEs), representing 0.099% of all infusions. Most AEs were from IS (n=20; 41%), with ID (19; 39%), FM (9; 18%), and FC (1; 2%) accounting for the remainder. Both SAEs (n=13) and NSAEs (n=7) were reported with IS, with most SAEs occurring on the first dose (85%) and classified as hypotension (39%), allergic (31%), anaphylaxis requiring epinephrine (15%), and tachycardia (15%); no pre-medications were given. These IS AEs were dose independent (Table 1). The incidence of AEs for all IV iron formulations was less than 0.01% (Table 2). Conclusions: While ID was found to have a relatively higher incidence of AEs, all IV iron formulations were found to be safe. The most frequently used formulation was IS, which had a low incidence of AEs even at higher doses, suggesting feasibility for minimizing the number of infusions required to achieve therapeutic levels. Although all formulations demonstrated safety, each institution will likely individualize formulary preferences based upon location of administration (inpatient vs. outpatient), input from the various medical specialties, patient comorbidities, reimbursement patterns, and logistical constraints such as infusion chair time.

Iron Overload and Treatment Outcome in an Adult Sickle Cell Disease Cohort

Objective. Blood transfusion plays a prominent role in the management of patients with sickle cell disease (SCD) and has a compounded effect on iron overload, especially when simple top-off transfusions are given. Adults with sickle cell anemia (SCA: HbSS or HbSβ 0-thalassemia), often require episodic blood transfusions on a chronic basis and, hence, are at risk of developing transfusional iron overload. We monitored 83 adult SCD patients with a diagnosis of iron overload during routine treatment and follow up at our clinical center. The aim of this study was to observe and describe treatment outcomes for individuals with iron overload seen at the University of Illinois adult sickle cell center between 2010 and 2023. Method. Patients eligible for the study were aged 18 years or above at the time of their initial visit. Patients were identified from our institutional clinical and translational research informatics data warehouse using computable phenotype algorithms as well as SCD outpatient encounter information to improve accuracy of abstracted data. Results of our queries were abstracted in the form of identified patient data and subsequently reviewed in Epic electronic health record (Epic, Verona, WI). We retrospectively studied adult subjects with SCD seen during routine clinical care between 2010 and 2023. Selected subjects had a diagnosis of iron overload, determined by 2 consecutive ferritin levels >1000ng/ml in steady state plus a significant transfusion history. We extracted data on clinical laboratory markers, abdominal imaging, use of iron chelation at baseline and in the final year of follow up, whether patients were receiving chronic erythrapheresis treatment at baseline and at end of follow up, and if alive at the end of the follow up period. Subjects have variable start date and follow up period, beginning at the start of diagnosis of iron overload and ending in June 2023 or last identifiable follow up visit, or mortality. Result. Baseline characteristics of 83 adult patients included in our study are summarized in table 1. Seventy percent of the patients were female and just about everyone had HbSS disease. The females had older median age (39.5year; IQR 32-50 years) than males. The mean ferritin value was significantly higher than the initial measure after a median follows up period of 5.3 years. During the follow up period, 40% of male patients discontinued iron chelation therapy whereas only 5.6% of females did the same. Multivariable analyses were performed for association between change in ferritin measure (between follow up period) with demographic data and other covariates presented in Table 1. Covariates were eliminated by backward selection. Predictors retained in the final model include follow-up period, initial ferritin value, gender, ALT, AST, and albumin. Females had a higher drop in their follow up ferritin, but this was not significant. Neither use of iron chelation therapy at baseline nor erythrapheresis at baseline predicted a change in ferritin value, however we did not collect information on compliance or duration of therapy. Patients followed up for longer duration, or who have higher ALT, had subsequent higher measure for follow up ferritin. Higher albumin predicted a lower ferritin at follow up. The effects of liver markers on ferritin are likely correlative only. After a median follow up period of 5.3years, about 22% of the patients were confirmed to be deceased. Some patients lost to follow up have an indeterminate alive status. Predictors of mortality in multivariate analysis include follow up ferritin value, albumin, and HCV status. Positive HCV status had a strong association with cirrhosis (p=0.001) as 71% of HCV positive individuals had cirrhosis. In turn 53% of the cirrhotic patients died in the follow up period. Conclusion. Here we present an overview of the clinical outcomes of adult patients with SCD and iron overload during a median follow up period of 5.3 years. Despite limitations of a typical retrospective study, our study illustrates the difficulty associated with the management of transfusional iron overload during routine treatment follow up, especially in patients continuing to undergo episodic transfusion treatment. We also continue to underline the low adherence with chelation therapy in adult populations with SCD and iron overload, and the high mortality associated with the condition.

Survey of Pulmonary Embolism Risk Stratification Methods in the Emergency Department and Barriers to Electronic Health Record Documentation

Introduction Pulmonary Embolism (PE) is a major cause of morbidity and mortality worldwide. Diagnosis is essential as untreated PE has a 30% mortality rate. Currently, computer tomography pulmonary angiogram (CTPA) is the standard of care to diagnose PE. However, this modality is expensive, exposes patients to radiation and increases risk of contrast induced nephropathy. Furthermore, only 5% of CTPAs performed are positive for PE signifying that many unnecessary tests are being performed. To address this gap, Pre-Test Probability (PTP) tools have been developed to safely exclude patients with low risk of PE and limit iatrogenic harm from over testing. Despite the tools being developed over 20 years ago, they are not widely available in electronic health record (EHR) systems and even when they are built in, uptake remains low. Methods Three large integrated health systems using Epic EHR systems across five states (MA, WI. MN, AZ, FL) built electronic PTP assessments into their EHR systems to safely exclude patients with low risk of PE and limit over testing. Two sites made the PTP optional, and one site made it a forced function (providers were forced to complete PTP prior to ordering CTPA unless a D-dimer result was present in the prior 48 hours). To assess the usability of these EHR tools, the team conducted a survey with ED clinicians across the three test sites. The survey was created to identify which PE risk stratification methods were employed by ED clinicians (EHR embedded PTP tool, apps on their phone, web applications like MDcalc, calculations from memory, or if they relied on clinical gestalt), and to identify barriers to using the EHR embedded PTP. Results Site 1 had 47 respondents, Site 2 had 94 respondents, and Site 3 had 16 respondents. Two key findings emerged from the survey (Figure 1). First, clinicians used a variety of risk stratification approaches and few of them documented their risk assessments in structured fields in the medical record. Second, clinical gestalt was the most used PE risk stratification approach, and this was true across all three test sites. In addition, the health system with a PTP prompt before clinicians could proceed with CTPA orders (Site 3) did not have a higher percentage of clinicians who reported using the EHR embedded tool than sites that did not prompt clinicians to fill in the PTP. Clinicians cited a variety of different barriers to using the EHR embedded PTP tool (Table 1). Conclusion While many clinicians indicated intermittent use of PTP criteria to aid in the diagnosis of PE, risk factors and scores from phone apps, web tools, and calculations from memory are unlikely to be documented in the patient's medical record, which means that they are not accessible to all members of the ED care team and cannot be used for electronic clinical quality measure. The biggest hurdles to increasing the use of structured PTP assessments in the ED setting to safely exclude PE and limit iatrogenic harm from over testing are (1) obtaining buy-in from ED clinicians that the PTP tools provide value over clinical gestalt, at least for a subset of patients who could most benefit, and (2) identifying best practices for incorporating PTP tools into EHR systems that make the tools easier to access and use 3) developing and implementing effective education and awareness programs around the PTP tools. This survey adds to the body of literature on PTP assessments in the ED setting and can help inform further research that is needed to continue to improve the diagnosis of PE. Funding: This project is funded in part by the Gordon and Betty Moore Foundation through Grant GBMF10778 to the American Society of Hematology.

Alerting providers to hospitalized persons with dementia using the electronic health record.

While patients with dementia entering the hospital have worse outcomes than those without dementia, early detection of dementia in the inpatient setting is less than 50%. We developed and assessed the positive predictive value (PPV) and feasibility of a novel electronic health record (EHR) banner to identify patients with dementia who present to the inpatient setting using data from the medical record. We developed and implemented an EHR algorithm to flag hospitalized patients age ≥65 years with potential cognitive impairment in the Epic EHR system using dementia ICD-10 codes, FDA-approved medications, and the use of the term "dementia" in the emergency department physician note. Medical records were reviewed for all patients who were flagged with an EHR banner from October 2022 to May 2023. A total of 344 individuals were identified who had a banner on their chart of which 280 (81.4%) were either diagnosed with dementia or were on an FDA-approved dementia medication. Forty-three individuals who had confirmed dementia were identified by a medication only (15.4%). Of the patients without confirmed dementia, the majority (N = 33, 9.6%) had a diagnosis of altered mental status, cognitive dysfunction, or mild cognitive impairment. Only 31 individuals (9.0%) had no indication of dementia or cognitive decline in their problem list, past medical history, or medication list. We found that it was feasible to implement an EHR algorithm for prospective dementia identification with a high PPV. These types of algorithms provide an opportunity to accurately identify hospitalized older individuals for inclusion in quality improvement projects, clinical trials, pay-for-performance programs, and other initiatives.

The Use of Electronic Health Record Data to Identify Variation in Referral, Consent, and Engagement in a Pediatric Intervention for Overweight and Obesity: A Cross-Sectional Study.

Clinical weight management programs face low participation. The authors assessed whether using electronic health record (EHR) data can identify variation in referral, consent, and engagement in a pediatric overweight and obesity (OW/OB) intervention. Using Epic EHR data collected between August 2020 and April 2021, sociodemographic and clinical diagnostic data (ie, International Classification of Disease [ICD] codes from visit and problem list [PL]) were analyzed to determine their association with referral, consent, and engagement in an OW/OB intervention. Bivariate analyses and multivariable logistic regression modeling were performed, with Bayesian inclusion criterion score used for model selection. Compared with the 581 eligible patients, referred patients were more likely to be boys (60% vs. 54%, respectively; P = 0.04) and have a higher %BMIp95 (119% vs. 112%, respectively; P < 0.01); consented patients were more likely to have a higher %BMIp95 (120% vs. 112%, respectively; P < 0.01) and speak Spanish (71% vs. 59%, respectively; P = 0.02); and engaged patients were more likely to have a higher %BMIp95 (117% vs. 112%, respectively; P = 0.03) and speak Spanish (78% vs. 59%, respectively; P < 0.01). The regression model without either ICD codes or PL diagnoses was the best fit across all outcomes, which were associated with baseline %BMIp95 and health clinic location. Neither visit nor PL diagnoses helped to identify variation in referral, consent, and engagement in a pediatric OW/OB intervention, and their role in understanding participation in such interventions remains unclear. However, additional efforts are needed to refer and engage younger girls with less extreme cases of OW/OB, and to support non-Hispanic families to consent.

Building a haemophilia-specific navigator in Epic® Electronic Health Records: Single-centre preliminary experience.

With the increasing complexity of haemophilia care and the advent of numerous therapeutic innovations, there is an unmet need for documentation and data collection tools tailored to people with haemophilia (PwH). To date, no fully integrated haemophilia-specific electronic health record (EHR) has been described in the literature. To evaluate the feasibility of integrating a haemophilia-specific navigator into the Epic EHR. Based on clinical experience and registry datasets, we identified key variables describing both PwH and carriers of haemophilia. These were then incorporated into a REDCap database, which served as a starting point for the development of a comprehensive haemophilia flowsheet. We built a dedicated haemophilia navigator within Epic that includes a flowsheet featuring up to 212 variables, as well as customised note templates and patient lists integrating data from the haemophilia flowsheet. It was feasible to develop a haemophilia navigator within Epic over the course of 12 months. The navigator's flowsheet enables systematic and comprehensive clinical assessment of PwH and carriers, while customised patient lists provide a quick summary of each patient's profile to the haemophilia treatment centre staff and highlight issues that require an intervention. In our clinical practice, patients actively participated in the new documentation process and responded positively to the navigator. Adapting EHRs to the needs of PwH and carriers promotes holistic care for this population and provides an opportunity for patient empowerment. Such haemophilia-specific EHRs are expected to promote standardisation of care and facilitate the collection of registry data on a national and international level.

Report of the Skin Research Workgroups From the IDEOM Breakout at the GRAPPA 2022 Annual Meeting.

The International Dermatology Outcome Measures (IDEOM) organization presented an update on its progress related to patient-centered outcome measures for psoriasis (PsO) and psoriatic arthritis (PsA) at the 2022 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA). The Musculoskeletal (MSK) Symptoms working group presented an update on the development of the IDEOM Musculoskeletal Questionnaire (IDEOM MSK-Q). The IDEOM MSK-Q is a patient-reported outcome measure intended to capture MSK symptoms and describe their intensity and impact on health-related quality of life in patients with psoriatic disease. IDEOM also presented the progress of the integration of the Psoriasis Epidemiology Screening Tool (PEST) and Psoriatic Arthritis Impact of Disease (PsAID) questionnaires into the Epic electronic health record system. This will allow for automated PsA screening and symptom measurement in the hopes of improving disease detection and treat-to-target strategies. The Treatment Satisfaction working group discussed the development of the DermSat-7, a 7-item treatment satisfaction questionnaire specific for dermatological conditions. The DermSat-7 is currently being validated in a multicenter study of patients with PsO.

Effectiveness of a cardiovascular health EHR application for cancer survivors in community oncology practice: Results from WF-1804CD.

LBA12007 Background: Practice guidelines recommend cardiovascular risk assessment and counseling for cancer survivors. The Automated Heart-Health Assessment study (AH-HA: WF-1804CD, NCT# 03935282) evaluated a novel electronic health record (EHR) clinical decision support tool based on American Heart Association Simple 7 cardiovascular health (CVH) factors to promote provider-patient CVH discussions in outpatient oncology. Methods: This clinic-randomized trial (R01CA226078), coordinated by the Wake Forest NCORP Research Base (UG1CA189824), randomized NCORP oncology practices using the Epic EHR to the AH-HA tool or usual care and enrolled survivors receiving routine care at least 6 months post-curative cancer treatment. The tool rendered an interactive display of risk factors, automatically populated from the EHR, alongside a tab indicating receipt of cancer treatments with cardiotoxic potential. Survivors at AH-HA sites had tool access during a routine visit; survivors at usual care sites did not. Immediately post-visit, each survivor was asked about counseling on 7 CVH factors [body mass index, physical activity, diet, smoking status, blood pressure, cholesterol, and glucose]. The primary endpoint is survivor-reported discussion of non-ideal or missing CVH factors; with 8 randomized practices (ICC=0.03), the study design had 82% power to detect a difference of 20% reported discussions in usual care versus 40% in AH-HA. Additional clinical endpoints were documentation of CVH discussions, referrals to primary care and cardiology, and change in CVH factors over 12 months (ongoing). A mixed effects logistic regression model assessed the effect of AH-HA on CVH discussions between the arms, with study arm as a fixed effect and practice as a random effect. Results: 5 usual care and 4 AH-HA practices enrolled 645 survivors from 10/1/2020- 2/28/2023. The majority had breast cancer (82%; 8% endometrial, 5% colorectal, 5% prostate, lymphoma or multiple types). Most survivors were female (96%; 84% White/non-Hispanic, 8% Black; 3% Hispanic; mean age= 62 yrs and median time since diagnosis=3.6 yrs). 18 participants (3%) did not complete necessary assessments, leaving 627 evaluable. 87% of providers (n=15) rated the tool utility and ease of use positively. Conclusions: The AH-HA tool was acceptable and effective at promoting CVH discussions during routine follow-up care for survivors and referrals to primary care. Clinical trial information: NCT03935282 . [Table: see text]

Time savings from integrating discrete, genomic data into the electronic health record using the Epic Aura Network.

e13568 Background: The capability to deliver, order, and receive discrete genomics data from external pathology laboratories into the electronic health record (EHR) has improved dramatically. As opposed to unstructured PDF integrations, discrete genomic results allow physicians real-time receipt of results which may trigger rapid clinical actions and expedite patient care. However, these genomic integrations, traditionally point-to-point (P2P), can be time consuming. On the other hand, Epic’s order and results network (Aura) connects pathology labs directly to Epic, which has pre-existing connections to Epic EHR sites. This eliminates the need to create a new connection, and is designed to provide a faster and simpler approach. Tempus was the first vendor to use the Epic genomics module for delivery of discrete, somatic mutational data and now is also the first company to leverage Aura for this purpose. Here, we report on our early Aura integration experiences. Methods: Using the Tempus Database, we retrospectively analyzed medical systems that were all Epic customers and determined their EHR genomic integration time using Aura. Integration time was defined as the time between initial start date of creating “orderables” to time of site testing. The number of EHR medical center analysts was also quantified. We used our prior P2P EHR deployments as a historical control. Results: Six bidirectional Tempus genomic integrations using Aura were performed from July 2022 to December 2022. All medical centers were expansive, multisite hospital systems. Mean number of integrated departments per hospital was 249 (range: 19-699). In 17 P2P integrations prior to Aura, mean integration time was 6.7m (range: 4m-18m). In contrast, mean integration time using Aura over the 6 sites was 1.5m (range: 0.75m-2m), which is a 78% improvement. No correlation was noted between the integration time and number of EHR analysts staffed or departments integrated. The two slowest integration sites (2m and 2.5m) had competing EHR deployment priorities. Conclusions: Using Aura, the speed of Tempus EHR integration was improved by 78% for bidirectional, discrete genomic data. Dedicated EHR integration resourcing reduced deployment times to as low as 3 weeks. This reduction in integration time may further the adoption of genomic EHR integrations and improve patient care by expediting time to appropriate, targeted treatments.

Vaccine Effectiveness of JYNNEOS against Mpox Disease in the United States

BackgroundIn the United States, more than 30,000 cases of mpox (formerly known as monkeypox) had occurred as of March 1, 2023, in an outbreak disproportionately affecting transgender persons and gay, bisexual, and other men who have sex with men. In 2019, the JYNNEOS vaccine was approved for subcutaneous administration (0.5 ml per dose) to prevent mpox infection. On August 9, 2022, an emergency use authorization was issued for intradermal administration (0.1 ml per dose); however, real-world effectiveness data are limited for either route.MethodsWe conducted a case–control study based on data from Cosmos, a nationwide Epic electronic health record (EHR) database, to assess the effectiveness of JYNNEOS vaccination in preventing medically attended mpox disease among adults. Case patients had an mpox diagnosis code or positive orthopoxvirus or mpox virus laboratory result, and control patients had an incident diagnosis of human immunodeficiency virus (HIV) infection or a new or refill order for preexposure prophylaxis against HIV infection between August 15, 2022, and November 19, 2022. Odds ratios and 95% confidence intervals were estimated from conditional logistic-regression models, adjusted for confounders; vaccine effectiveness was calculated as (1−odds ratio for vaccination in case patients vs. controls)×100.ResultsAmong 2193 case patients and 8319 control patients, 25 case patients and 335 control patients received two doses (full vaccination), among whom the estimated adjusted vaccine effectiveness was 66.0% (95% confidence interval [CI], 47.4 to 78.1), and 146 case patients and 1000 control patients received one dose (partial vaccination), among whom the estimated adjusted vaccine effectiveness was 35.8% (95% CI, 22.1 to 47.1).ConclusionsIn this study using nationwide EHR data, patients with mpox were less likely to have received one or two doses of JYNNEOS vaccine than control patients. The findings suggest that JYNNEOS vaccine was effective in preventing mpox disease, and a two-dose series appeared to provide better protection. (Funded by the Centers for Disease Control and Prevention and Epic Research.)

Improving Communication in a Large Urban Academic Safety Net Hospital System: Implementation of Secure Messaging.

Given the complexities of communication within health systems, we investigated how the implementation of secure messaging in addition to traditional paging would impact hospital communication. This study was implemented at Grady Health System (GHS), a large safety net academic hospital system in metro Atlanta that includes inpatient and ambulatory settings. GHS uses Epic Electronic Health Record (EHR), and secure messaging was performed using Epic Haiku Platform. To assess states of communication, we implemented pre- and post-surveys. The secure messaging data tracked from 2018 to 2022 demonstrated a rise in usage from 9,378 chats per month when it went live in August 2018 to greater than 200,000 monthly messages during the pandemic when social distancing measures were enacted. Monthly usage peaked in March 2022 with 378,932 messages. Pre-and-post survey questions using a Likert scale (1-4) showed increased agreement in the ability to reach all team members through secure chat amongst healthcare workers. Within our unit staff, communication improved by being more rapid and reliable, as the Likert scale means increased from 2.18 pre-survey to 2.63 post survey. Pre-and-post survey analysis indicates improved satisfaction across GHS stakeholders with the implementation of secure chat in addition to the existing direct-paging system. Next steps could include exchanging digital media through secure messaging to facilitate faster diagnosis and treatment of certain medical conditions. Secure messaging integrated within the EHR (including mobile devices) enhances communication between healthcare team members in a HIPAA-compliant way reducing the number of pages and phone calls.

Social Risk Screening and Response Equity: Assessment by Race, Ethnicity, and Language in Community Health Centers

Little has previously been reported about the implementation of social risk screening across racial/ethnic/language groups. To address this knowledge gap, the associations between race/ethnicity/language, social risk screening, and patient-reported social risks were examined among adult patients at community health centers. Patient- and encounter-level data from 2016 to 2020 from 651 community health centers in 21 U.S. states were used; data were extracted from a shared Epic electronic health record and analyzed between December 2020 and February 2022. In adjusted logistic regression analyses stratified by language, robust sandwich variance SE estimators were applied with clustering on patient's primary care facility. Social risk screening occurred at 30% of health centers; 11% of eligible adult patients were screened. Screening and reported needs varied significantly by race/ethnicity/language. Black Hispanic and Black non-Hispanic patients were approximately twice as likely to be screened, and Hispanic White patients were 28% less likely to be screened than non-Hispanic White patients. Hispanic Black patients were 87% less likely to report social risks than non-Hispanic White patients. Among patients who preferred a language other than English or Spanish, Black Hispanic patients were 90% less likely to report social needs than non-Hispanic White patients. Social risk screening documentation and patient reports of social risks differed by race/ethnicity/language in community health centers. Although social care initiatives are intended to promote health equity, inequitable screening practices could inadvertently undermine this goal. Future implementation research should explore strategies for equitable screening and related interventions.

A Retrospective Cohort Analysis of Two Computerized Insulin Infusion Protocols.

The primary objective of this analysis was to compare the safety and efficacy of a novel computerized insulin infusion protocol (CIIP), the Lalani Insulin Infusion Protocol (LIIP), with an established CIIP, Glucommander. We conducted a 10-month retrospective analysis of 778 patients in whom LIIP was used (August 18, 2020 to June 25, 2021) at six HonorHealth Hospitals in the Phoenix metropolitan area. These data were compared with Glucommander that was used at those same hospitals from January 1, 2018 to August 17, 2020, n = 4700. Primary end points of the project included average time to euglycemia and average time in hyperglycemia (>180 mg/dL) and hypoglycemia (<70 mg/dL). Additional subgroup analysis was done to evaluate CIIP performance in patients in whom maintenance of euglycemia was more challenging. The LIIP had a faster time to euglycemia (191 vs 222 minutes, P < .001) and similar time in hypoglycemia (2.79 vs 2.76 minutes, P = .50) for all patients, when compared with Glucommander. Similar observations were made for the following subgroups: diabetic ketoacidosis/hyperosmolar hyperglycemic state (DKA/HHS) patients, COVID-19 patients, patients on steroids, patients with ≥60 glomerular filtration rate (GFR), patients with renal insufficiency, and patients with sepsis. The LIIP is a safe and effective CIIP in managing intravenous insulin infusion rates. Utilization of LIIP resulted in reduced time to euglycemia, P < .001, when compared with Glucommander and did not cause increased hypoglycemia during the project period. Contributing factors to the success of LIIP may include improved clinical workflow, learnability and ease of use, compatibility with the Epic electronic health record (EHR), and its unique, dynamic and adaptive algorithm.