Electronic Health Record Tools Research Articles

Development of an Electronic Health Record Self-Referral Tool for Lung Cancer Screening: One-Group Posttest Study.

Approximately 14 million individuals in the United States are eligible for lung cancer screening (LCS), but only 5.8% completed screening in 2021. Given the low uptake despite the potential great health benefit of LCS, interventions aimed at increasing uptake are warranted. The use of a patient-facing electronic health record (EHR) patient portal direct messaging tool offers a new opportunity to both engage eligible patients in preventative screening and provide a unique referral pathway for tobacco treatment. This study sought to develop and pilot an EHR patient-facing self-referral tool for an established LCS program in an academic medical center. Guided by constructs of the Health Belief Model associated with LCS uptake (eg, knowledge and self-efficacy), formative development of an EHR-delivered engagement message, infographic, and self-referring survey was conducted. The survey submits eligible self-reported patient information to a scheduler for the LCS program. The materials were pretested using an interviewer-administered mixed methods survey captured through venue-day-time sampling in 5 network-affiliated pulmonology clinics. Materials were then integrated into the secure patient messaging feature in the EHR system. Next, a one-group posttest quality improvement pilot test was conducted. A total of 17 individuals presenting for lung screening shared-decision visits completed the pretest survey. More than half were newly referred for LCS (n=10, 60%), and the remaining were returning patients. When asked if they would use a self-referring tool through their EHR messaging portal, 94% (n=16) reported yes. In it, 15 participants provided oral feedback that led to refinement in the tool and infographic prior to pilot-testing. When the initial application of the tool was sent to a convenience sample of 150 random patients, 13% (n=20) opened the self-referring survey. Of the 20 who completed the pilot survey, 45% (n=9) were eligible for LCS based on self-reported smoking data. A total of 3 self-referring individuals scheduled an LCS. Pretest and initial application data suggest this tool is a positive stimulus to trigger the decision-making process to engage in a self-referral process to LCS among eligible patients. This self-referral tool may increase the number of patients engaging in LCS and could also be used to aid in self-referral to other preventative health screenings. This tool has implications for clinical practice. Tobacco treatment clinical services or health care systems should consider using EHR messaging for LCS self-referral. This approach may be cost-effective to improve LCS engagement and uptake. Additional referral pathways could be built into this EHR tool to not only refer patients who currently smoke to LCS but also simultaneously trigger a referral to clinical tobacco treatment.

Implementing Adult Hepatitis B Immunization and Screening Using Electronic Health Records: A Practical Guide.

Hepatitis B is a serious problem in the United States (US), with up to 2.4 million Americans living with a chronic infection. Only 26-32% of people living with hepatitis B in the US are diagnosed. Additionally, just 30% of all adults are vaccinated against the virus. In 2022, the Advisory Committee on Immunization Practices of the Centers for Disease Control and Prevention (CDC) updated adult hepatitis B vaccination recommendations to include all adults aged 19-59 years and those 60 years and older with risk factors for hepatitis B. Subsequently, in 2023, the CDC recommended that all adults be screened at least one time in their lives. Electronic health record (EHR) tools (prompts, order sets, etc.) have proven to be an effective method of increasing hepatitis B screening and vaccination, but longstanding challenges and questions around hepatitis B vaccines and tests could prevent effectual EHR implementation. As the new recommendations directly impact providers who may have limited familiarity with hepatitis B, guidance on how to identify eligible patients and triggers, order sets to facilitate vaccine/test selection, and proper documentation and patient follow-up is necessary. This communication offers a practical framework for health systems to build an effective EHR strategy for the updated adult hepatitis B recommendations. We also provide comprehensive responses to clinicians' questions that are frequently asked prior to screening or vaccinating for hepatitis B.

Improving rates of adolescent suicide risk screening in a primary pediatric clinic, a quality improvement project

In recent years, adolescents have experienced rising rates of suicidal ideation. Though pediatricians in our clinic were screening for depression, suicide risk screens were not completed. We designed a quality improvement (QI) project with the goal to increase the rate of suicide risk screening by 20 %, and improve clinicians’ attitudes toward the electronic health record (EHR) for mental health screening by 20 %. Baseline analyses included chart review and a provider survey. Suicide risk screen tools were built with decision-support into the EHR. After provider education was completed, the EHR-based interventions were implemented. Post-intervention, suicide risk screening completion increased from 8.8 % to 95 %. Provider attitudes towards the EHR also improved. This QI project demonstrates that implementing EHR tools that are provider-informed can help to improve suicide risk screening rates, streamline workflows, and help improve clinicians’ attitudes towards the EHR.

Preparing Future Pediatric Care Providers with a Clinical Informatics Elective.

Clinical informatics (CI) has reshaped how medical information is shared, evaluated, and utilized in health care delivery. The widespread integration of electronic health records (EHRs) mandates proficiency among physicians and practitioners, yet medical trainees face a scarcity of opportunities for CI education. We developed a CI rotation at a tertiary pediatric care center to teach categorical pediatric, pediatric-neurology, and medicine-pediatric residents foundational CI knowledge and applicable EHR skills. Created in 2017 and redesigned in 2020, a CI rotation aimed to provide foundational CI knowledge, promote longitudinal learning, and encourage real-world application of CI skills/tools. Led by a team of five physician informaticist faculty, the curriculum offers personalized rotation schedules and individual sessions with faculty for each trainee. Trainees were tasked with completing an informatics project, knowledge assessment, and self-efficacy perception survey before and after rotation. Paired t-test analyses were used to compare pre- and postcurriculum perception survey. Thirty-one residents have completed the elective with their projects contributing to diverse areas such as medical education, division-specific initiatives, documentation improvement, regulatory compliance, and operating plan goals. The mean knowledge assessment percentage score increased from 77% (11.6) to 92% (10.6; p ≤ 0.05). Residents' perception surveys demonstrated improved understanding and confidence across various informatics concepts and tools (p ≤ 0.05). Medical trainees are increasingly interested in CI education and find it valuable. Our medical education curriculum was successful at increasing residents' understanding, self-efficacy, and confidence in utilizing CI concepts and EHR tools. Future data are needed to assess the impact such curricula have on graduates' proficiency and efficiency in the use of CI tools in the clinical workplace.

Privacy Preservation of Electronic Health Records in the Modern Era: A Systematic Survey

Building a secure and privacy-preserving health data sharing framework is a topic of great interest in the healthcare sector, but its success is subject to ensuring the privacy of user data. We clarified the definitions of privacy, confidentiality and security (PCS) because these three terms have been used interchangeably in the literature. We found that researchers and developers must address the differences of these three terms when developing electronic health record (EHR) solutions. We surveyed 130 studies on EHRs, privacy-preserving techniques, and tools that were published between 2012 and 2022, aiming to preserve the privacy of EHRs. The observations and findings were summarized with the help of the identified studies framed along the survey questions addressed in the literature review. Our findings suggested that the usage of access control, blockchain, cloud-based, and cryptography techniques is common for EHR data sharing. We summarized the commonly used strategies for preserving privacy that are implemented by various EHR tools. Additionally, we collated a comprehensive list of differences and similarities between PCS. Finally, we summarized the findings in a tabular form for all EHR tools and techniques and proposed a fusion of techniques to better preserve the PCS of EHRs.

Health information technology tools to accelerate gastrointestinal evaluation in patients with iron deficiency anaemia: a cluster randomised controlled trial

ObjectiveSystem-level safety measures do not exist to ensure that patients with iron deficiency anaemia (IDA) undergo proper diagnostic evaluations. We sought to determine if a set of EHR (electronic health...

Implementing weight maintenance with existing staff and electronic health record tools in a primary care setting: Baseline results from the MAINTAIN PRIME trial

BackgroundThere is need for interventions that can assist with long-term maintenance of healthy body weight and be sustainably integrated into existing primary care teams. The goal of MAINTAIN PRIME (Promoting Real (World) IMplEmentation) is to evaluate whether a successful electronic health record (EHR)-based weight maintenance intervention can be adapted to a new clinical setting with primary care staff serving as coaches. MethodsEHR tools include tracking tools, standardized surveys, and standardized “SmartPhrases” for coaching. Inclusion criteria were age 18–75 years, voluntary 5% weight loss in the past 2 years with prior BMI ≥ 25 kg/m2, and no bariatric procedures in past 2 years. Participants were randomized 1:1 to tailored online coaching with EHR tracking tools (coaching) or EHR tracking tools alone (tracking). ResultsWe screened 405 individuals between September 2021 and April 2023; 269 participants enrolled (134 coaching; 135 tracking). The most common reason for not enrolling was ineligibility (55%). At baseline, participants were 50.3 (SD 15.02) years old, 66.4% female, and 84% White; 83.7% reported moderate physical activity. Average weight and BMI at baseline were 205.0 (SD 48.9) lbs. and 33.2 (6.8) kg/m2, respectively. Participants lost an average of 10.7% (SD 5.2) of their body weight before enrolling. We recruited 39 primary care coaches over the same period.ConclusionThe study successfully identified and recruited primary care patients with recent intentional weight loss for participation in a weight maintenance program that uses EHR-based tools. We also successfully recruited and trained primary care staff as coaches.

Exploring the Feasibility of Applying Deep Learning for the Early Prediction of Arthritis

Introduction: Arthritis is one of the most common chronic diseases. Early detection of arthritis and its progression can facilitate early intervention measures, lowering disease severity in patients. As electronic health records (EHR) become more accessible, this study assesses whether general health information and arthritis-related questionnaires can be used in arthritis diagnosis, without the involvement of costly imaging methods. Therefore, we created deep learning (DL) and machine learning (ML) models to explore the feasibility of combining EHR and modern computational tools to diagnose arthritis. Methods: A total of 782 arthritis patients and 4014 control patients were identified from the Osteoarthritis Initiative (OAI) – a ten-year-long observational study that included patient EHR in five time points. Six hundred variables were filtered by random forest classifier followed by manual filtering. Data were split properly to training, testing and validation set, and the training set was balanced. Sequential, nonsequential DL models, and five independent DL models for each time points were used. The accuracy, positive prevalence value (PPV), negative prevalence value (NPV), and area under curve (AUC), were assessed and compared with four classical ML models. SHAP (SHapley Additive exPlanations) summary analysis was also conducted. Results: Sequential and non-sequential deep learning models showed accuracies of ~ 0.97, and the four classical machine learning approaches showed accuracies of above 0.9. High positive and negative predicted values (> 0.90) for all of the models suggested the potential clinical applicability of the model, while the SHAP analysis demonstrated its interpretability. Discussion: We tested various models and showed the ability to use machine learning methods for early diagnosis of arthritis with EHR. The models can be used as a screening tool to select susceptible patients for confirmatory tests such as X-ray and MRI. Identification of early disease states could facilitate protective measures that slow disease progression.

Clinician Needs for Electronic Health Record Pediatric and Adolescent Weight Management Tools: A Mixed-Methods Study.

Clinicians play an important role in addressing pediatric and adolescent obesity, but their effectiveness is restricted by time constraints, competing clinical demands, and the lack of effective electronic health record (EHR) tools. EHR tools are rarely developed with provider input. We conducted a mixed method study of clinicians who provide weight management care to children and adolescents to determine current barriers for effective care and explore the role of EHR weight management tools to overcome these barriers. In this mixed-methods study, we conducted three 1-hour long virtual focus groups at one medium-sized academic health center in Missouri and analyzed the focus group scripts using thematic analysis. We sequentially conducted a descriptive statistical analysis of a survey emailed to pediatric and family medicine primary care clinicians (n = 52) at two private and two academic health centers in Missouri. Surveyed clinicians reported that they effectively provided health behavior lifestyle counseling at well-child visits (mean of 60 on a scale of 1-100) and child obesity visits (63); however, most felt the current health care system (27) and EHR tools (41) do not adequately support pediatric weight management. Major themes from the clinician focus groups were that EHR weight management tools should display data in a way that (1) improves clinical efficiency, (2) supports patient-centered communication, (3) improves patient continuity between visits, and (4) reduces documentation burdens. An additional theme was (5) clinicians trust patient data entered in real time over patient recalled data. Study participants report that the health care system status quo and currently available EHR tools do not sufficiently support clinicians working to manage pediatric or adolescent obesity and provide health behavior counseling. Clinician input in the development and testing of EHR weight management tools provides opportunities to address barriers, inform content, and improve efficiencies of EHR use.

Enhancing Implementation of the I-PASS Handoff Tool Using a Provider Handoff Task Force at a Comprehensive Cancer Center

Communication failures are among the most common causes of harmful medical errors. At one Comprehensive Cancer Center, patient handoffs varied among services. The authors describe the implementation and results of an Organization-wide project to improve handoffs and implement an evidence-based handoff tool across all inpatient services. The research team created a task force composed of members from 22 hospital services-advanced practice providers (APPs), trainees, some faculty members, electronic health record (EHR) staff, education and training specialists, and nocturnal providers. Over two years, the task force expanded to include consulting services and Anesthesiology. Factors contributing to ineffective handoffs were identified and organized into categories. The EHR I-PASS tool was used to standardize handoff documentation. Training was provided to staff on its use, and compliance was monitored using a customized dashboard. I-PASS champions in each service were responsible for the rollout of I-PASS in their respective services. The data were reported quarterly to the Quality Assessment and Performance Improvement (QAPI) governing committee. Provider handoff perception was assessed through the biennial Institution-wide safety culture survey. All fellows, residents, APPs, and physician assistants were trained in the use of I-PASS, either online or in person. Adherence to the I-PASS written tool improved from 41.6% in 2019 to 70.5% in 2022 (p < 0.05), with improvements seen in most services. The frequency of updating I-PASS elements and the action list in the handoff tool also increased over time. The handoff favorability score on the safety culture survey improved from 38% in 2018 to 59% in 2022. The implementation approach developed by the Provider Handoff Task Force led to increased use of the I-PASS EHR tool and improved safety culture survey handoff favorability.

Improve Advance Care Planning: A Brief Report Discussing Goals of Care Interventions to Improve Communication Among Health Care Teams and Patients Maximizing the Use of the Electronic Health Record Tools.

Introduction: A key element of advance care planning (ACP) is the goals of care (GOC) conversation between the provider and the patient. The value of meaningful GOC conversations for the patient, provider, and health care institution is well documented. However, if the GOC documentation is buried in the medical record, not well defined, or poorly documented, that value is squandered. The Improvement Process: Interventions were implemented with oncology physicians and nurse practitioners (NPs). These included education, system reform including improving the ease and consistency of documentation of ACP, and regular feedback. Results: Participants reported increased confidence in communication skills about GOC conversations postworkshops. Data results for the tracked metrics, health care power of attorney, code status, and GOC, all showed improvement. Conclusion: Physicians and NPs recognized the importance of GOC conversations as part of ACP. Considerable progress was made by focusing on GOC conversations, maximizing information technology, participating in coaching, and ongoing data monitoring.

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.

Safety-Net Primary Care and Endocrinology Clinicians’ Knowledge and Perspectives on Screening for Nonalcoholic Fatty Liver Disease: A Mixed-Methods Evaluation

ObjectiveClinical guidelines have expanded the indications for nonalcoholic fatty liver disease (NAFLD) screening to type 2 diabetes mellitus and obesity, which are conditions common in populations who receive care in urban safety-net settings. This study aimed to evaluate safety-net primary care and endocrinology clinicians’ knowledge of NAFLD, determine barriers and facilitators to screening, and examine perspectives on the use of electronic health record tools for risk assessment. MethodsSequential explanatory mixed methods using survey and qualitative interviews with primary care, primary care subspecialty, and endocrinology clinicians in an urban safety-net health care system. ResultsA total of 109 participants completed the survey (36.5% response rate), and 13 participated in interviews. Most respondents underestimated or did not know the prevalence of NAFLD (68%), did not use the recommended noninvasive tests for risk stratification (65%), and few were comfortable with screening for (27%) or managing (17%) NAFLD. Endocrinologists had greater knowledge of risk factors but lower rates of comfort and more often felt that screening was not their responsibility. The qualitative themes included the following: (1) lack of knowledge about screening, (2) concern for underdiagnosing NAFLD, (3) perception of severity impacts beliefs about screening, (4) screening should occur in primary care but is not normative practice, (5) concerns exist about benefit, (6) competing demands with a complex population hinder screening, and (7) a need for easier ways to integrate screening into practice. ConclusionKnowledge gaps may hamper uptake of new guidelines for NAFLD screening in primary care and endocrinology clinics in an urban safety-net health care system. Implementation strategies focused on training and educating clinicians and informed by behavioral economics may increase screening.

Improving Diabetes Screening in the Primary Care Clinic.

In our suburban primary care clinic, the average rate of screening for diabetes among eligible patients was only 51%, similar to national screening data. We conducted a quality improvement project to increase this rate. During the 6-month preintervention phase, we collected baseline data on the percentage of eligible patients screened per week (percentage of patients with hemoglobin A1c checked in the prior 3 years out of patients eligible for screening who completed a visit during the week). We then implemented a two-phase intervention. In phase 1 (approximately 8 months), we generated an electronic health record (EHR) report to identify eligible patients and pended laboratory orders for physicians to sign. In phase 2 (approximately 3 months), we replaced the phase 1 intervention with an EHR clinical decision support tool that automatically identifies eligible patients. We compared screening rates in the preintervention vs. intervention period. For phase 1, we also assessed laboratory completion rates and the laboratory results. We surveyed physicians regarding intervention acceptability and satisfaction at 3, 6, 9, and 12 months during the intervention period. The weekly percentage of patients screened increased from an average of 51% in the preintervention phase to 65% in the intervention phase (p < 0.001). During phase 1, most patients underwent laboratory blood testing as recommended (83% within 3 months), and results were consistent with prediabetes in 23% and with diabetes in 4%. Overall, most physicians believed that the intervention appropriately identified patients due for screening and was helpful (100% of respondents agreed at 9 months vs. 71% at 3 months). We successfully implemented a systematic screening intervention involving a manual workflow and EHR tool and improved diabetes screening rates in our clinic.

Increasing Cognitive Evaluations in Primary Care: Implementing the GSA KAER Model at a Large Healthcare System

AbstractThere is widespread recognition that patients with Alzheimer’s disease and related dementias (ADRD) receive better care if they receive an earlier diagnosis. In 2022, the Alzheimer’s Association published a survey of primary care providers (PCPs) indicating that a large majority agree that making an early diagnosis of ADRD is important. However, more than half of PCPs said that they lack the knowledge and confidence to assist in making such a diagnosis.Starting in 2021, the University of Washington launched the Cognition in Primary Care Program to meet that need. Developed with funding from the Centers for Disease Control and Prevention, as an adaptation of the Gerontological Society of America’s KAER Toolkit, the primary goals of the Cognition in Primary Care Program are to increase cognitive evaluations by PCPs and to increase the number of patients diagnosed with ADRD and mild cognitive impairment (MCI).Using practical training modules for PCPs with concise, evidence‐based checklists embedded in the electronic health record (EHR), the program has now been widely adopted by PCPs in a wide variety of clinics serving diverse populations of patients. Evaluations by PCPs describe the program as being of high quality and relevant to their practice. Results on the General Practitioners’ Attitude and Confidence Scale for Dementia (GPACS‐D) six months after the intervention show confidence in evaluating cognition. In addition, the number of MoCA tests uploaded to the EHR increased from 2.7 per month to 5.8 per month, and there was high utilization of the EHR checklist tools. Preliminary data also show that the number of visits in which PCPs have billed a diagnosis of MCI increased from 7.5 per month to 14.4 per month.The strengths of the Cognition in Primary Care Program include its emphasis on actions that PCPs can take to promote brain health and the implementation of innovative EHR tools which PCPs can use in their clinical practice. The Cognition in Primary Care Program is an effective model, shown to be acceptable to PCPs, easy to integrate into a large health system, and successful at increasing cognitive evaluations in the primary care setting.

Integrating Care for Mother-Infant Dyads After Preterm Birth: A Qualitative Study of Clinician Perspectives on Feasibility.

There are gaps in receipt of maternal preventive services in the interconception period. Yet mother-infant dyads have frequent health care visits. Health systems have opportunities to better capitalize on existing visits to address dyad needs, but this possibility has not been fully explored. In this qualitative study we conducted semistructured interviews with clinical team members involved with birthing parents or infants after preterm birth. We conducted snowball sampling from teams in pediatrics, obstetrics, and family medicine at two geographically adjacent health systems. Interviews explored perspectives on existing barriers and facilitators to integrating dyad care across adult and infant teams. Interviews were audio-recorded, professionally transcribed, and coded using an integrated approach. We interviewed 24 physicians, nurses, midwives, and social workers (March-November 2021). Participants identified barriers to integrated care including infrequent communication between clinical teams, which was generalizable to care of the birthing parent or infant as individuals, and additional barriers related to privacy, credentialing, and visit design that were specific to dyad care. To improve integration of dyad care, clinicians proposed adapting a variety tools and procedures currently used in their practices, including electronic health record tools for communication, dedicated roles to support communication or navigation, centralized information on resources for dyad care, referral protocols, identifying dyads for proactive outreach, and opportunities for clinicians to connect face-to-face about shared patients or families. Clinicians believe existing health care structures and processes can be adapted to address current substantial barriers to integrated dyad care.

Electronic Health Record Tools to Facilitate Diagnosis of Cognitive Impairment in Primary Care

AbstractWith novel biomarkers and treatments for dementia on the horizon, the need to detect cognitive impairment at early stages is urgent. The role of primary care providers (PCPs) in the diagnosis of mild cognitive impairment and dementia is essential in meeting this need. Cognition in Primary Care (CPC) is a quality improvement program developed at the University of Washington (UW), Seattle, which includes a three‐part Continuing Medical Education (CME), clinical workflow, and electronic health record toolset to support PCPs in early diagnosis of mild cognitive impairment and dementia. This program was developed using input from UW providers in primary care practice and elements from the KAER (Kickstart, Assess, Evaluate, Refer) Toolkit developed by the Gerontological Society of America (GSA). Our pragmatic approach involved the development of tools integrated into Epic, the electronic health record system in place at UW, that can be used during a patient visit to guide PCPs through the process of evaluating cognitive function. The toolset includes 1) a list of signs that may trigger the need for a dedicated follow‐up visit to evaluate cognition; 2) a cognitive checklist for related conditions affecting cognition (e.g., potentially harmful medications, depressive symptoms, alcohol use, and obstructive sleep apnea); 3) a structured framework for cognitive evaluation including validated instruments (e.g., MoCA and AD8); 4) referrals to specialty care; 5) billing guidelines; and 6) community resources and materials that patients and care partners can use both pre‐ and post‐diagnosis. We have pilot‐tested these tools in UW primary care clinics and found high utilization both within and outside of targeted clinics indicating a halo effect of usage beyond those who attended the CME training. In this presentation, we will provide detailed descriptions of these Epic tools focusing on clinical application to total patient care. We plan to publish these workflow tools onto the Epic Digital Library to be downloaded and used by other health systems. Future plans include producing on‐demand CME training modules, a post‐diagnosis checklist, and applications for use of these tools in systems outside of Epic.

The Design of the Electronic Health Record in Type 1 Diabetes Centers: Implications for Metrics and Data Availability for a Quality Collaborative.

Systematic and comprehensive data acquisition from the electronic health record (EHR) is critical to the quality of data used to improve patient care. We described EHR tools, workflows, and data elements that contribute to core quality metrics in the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI). We conducted interviews with quality improvement (QI) representatives at 13 T1DX-QI centers about their EHR tools, clinic workflows, and data elements. All centers had access to structured data tools, nine had access to patient questionnaires and two had integration with a device platform. There was significant variability in EHR tools, workflows, and data elements, thus the number of available metrics per center ranged from four to 17 at each site. Thirteen centers had information about glycemic outcomes and diabetes technology use. Seven centers had measurements of additional self-management behaviors. Centers captured patient-reported outcomes including social determinants of health (n = 9), depression (n = 11), transition to adult care (n = 7), and diabetes distress (n = 3). Various stakeholders captured data including health care professionals, educators, medical assistants, and QI coordinators. Centers that had a paired staffing model in clinic encounters distributed the burden of data capture across the health care team and was associated with a higher number of available data elements. The lack of standardization in EHR tools, workflows, and data elements captured resulted in variability in available metrics across centers. Further work is needed to support measurement and subsequent improvement in quality of care for individuals with type 1 diabetes.

A national heart failure initiative is associated with improved use of quadruple guideline-directed medical therapy

Abstract Background Heart Failure (HF) is projected to impact over 8 million people in the US by 2030. The 2022 AHA/ACC/HFSA Guideline for the Management of HF recommend four foundational medication classes for treating HFrEF patients: RAAS inhibitors, preferably angiotensin receptor/neprilysin inhibitor (ARNi), evidence-based beta-blockers (EBBB), sodium-glucose cotransporter-2 inhibitor (SGLT2i) and mineralocorticoid receptor antagonist (MRA) referred to as Quadruple Guideline-Directed Medical Therapy (Q-GDMT). Q-GDMT has shown an estimated 73% relative and 26% absolute reduction in all-cause mortality over 2 years. Yet, despite remarkable clinical potential, these therapies are patently underutilized in clinical practice. It is unknown whether an implementation science strategy may enhance adherence to Q-GDMT for HF. Methods IMPLEMENT-HF (IHF) is a national HF quality improvement initiative composed of a multidisciplinary learning collaborative and resource repository across seven U.S regions. IHF promotes adherence to Q-GDMT by focusing on early adoption and rapid adherence to prescribing at hospital discharge and within 30 days post discharge. Multi-disciplinary participation in the learning collaborative includes pharmacy, provider groups, nursing, quality, social services, outpatient clinics and others. Shared interventions to promote Q-GDMT include formulary changes (e.g., adding SGLT2i), optimizing electronic health record tools (disease-specific order sets, dot phrases), clinician education, and user-friendly patient resources to address medication access. IHF sites receive educational materials, including webinars, learning modules, pocket guideline booklets, and reminder cards to reinforce Q-GDMT. IHF participating hospitals collect Q-GDMT data at discharge and at 30 days post discharge in Get With The Guidelines®-Heart Failure (GWTG-HF). These data were analyzed from baseline (Q1 Q2 2021 aggregate) through Q3 2022. Results Data from 71 IHF participating sites of 13,858 HFrEF patient hospitalization episodes (median age 69, 34% females, median LVEF 24%), demonstrated Q-GDMT prescription at discharge increased from 14% at baseline to 47% in Q3 2022 (p value &amp;lt;0.001). 30-day post discharge data from 52 IHF sites demonstrated an increase in Q-GDMT from 9% at baseline to 58% in Q3 2022 (p value &amp;lt;0.001) as seen in Figure 1. Conclusions Among sites participating in IHF, the use of an implementation science strategy suggest a rapid increase in prescribing Q-GDMT for eligible HFrEF patients at discharge and 30-days post discharge. This multi-region quality improvement initiative demonstrates the potential for this learning collaborative model to drive improvement in adherence to Q-GDMT prescribing, using shared implementation strategies to overcome barriers. Ongoing study will assess continued compliance and clinical outcomes with Q-GDMT beyond the timeframe of this analysis.Quadruple Medication Therapy baseline-Q3

Abstract 17875: Quality Improvement Initiative to Improve Screening and Diagnosis Rates of Iron Deficiency in Patients Hospitalized for Acute Heart Failure With Reduced Ejection Fraction

Introduction: Despite being associated with reduced exercise capacity and poor quality of life in HFrEF, iron deficiency (ID) is underdiagnosed and undertreated. The 2022 ACC/AHA guidelines define ID in HFrEF as either a serum ferritin level &lt; 100 ng/ml or 100-299 ng/ml with transferrin saturation (TSAT) &lt;20 %. Treatment with IV iron is associated with a reduced risk of hospitalizations for HFrEF. A review of 20 inpatient acute HFrEF records revealed 10 had iron studies ordered, and 9 of them met criteria for ID, but only 1 patient received IV iron. Aim statement: To improve the testing rates for ID in hospitalized acute HFrEF patients at our hospital by 10% from January through March 2023. Methods: QI project included the implementation of an electronic health record (EHR) alert (Fig. 1) and resident education. The EHR alert was designed to be activated at the time of admission for patients with specific ICD codes for acute HFrEF to aid in ordering iron studies. A 20-minute educational session was delivered to residents, and handouts were provided to residents with reference material. Results: Pre-intervention data from January-December 2022 revealed a testing rate of 68% (154/194). ID was present in 58% (113/194). Post-intervention data from January 2023-March 2023 showed an improvement in the testing rate to 91% (67/73) and a concurrent increase in the diagnosis rate to 72% (53/73) (Fig. 2). Before discharge, 43.4% of patients (23/53) with ID received IV iron sucrose. Conclusion: Education and implementation of EHR alert were successful in increasing the testing rates for ID in acute HFrEF irrespective of anemia status. EHR tools should enhance sustainability compared to education alone.