Education curriculum assessment for teaching electrocardiography: Rationale and design for the prospective, international, randomized controlled EDUCATE trial.

BACKGROUND: Electrocardiogram (ECG) interpretation training is a fundamental component of medical education across disciplines. However, the skill of interpreting ECGs is not universal among medical graduates, and numerous barriers and challenges exist in medical training and clinical practice. An evidence-based and widely accessible learning solution is needed. DESIGN: The EDUcation Curriculum Assessment for Teaching Electrocardiography (EDUCATE) Trial is a prospective, international, investigator-initiated, open-label, randomized controlled trial designed to determine the efficacy of self-directed and active-learning approaches of a web-based educational platform for improving ECG interpretation proficiency. Target enrollment is 1000 medical professionals from a variety of medical disciplines and training levels. Participants will complete a pre-intervention baseline survey and an ECG interpretation proficiency test. After completion, participants will be randomized into one of four groups in a 1:1:1:1 fashion: (i) an online, question-based learning resource, (ii) an online, lecture-based learning resource, (iii) an online, hybrid question- and lecture-based learning resource, or (iv) a control group with no ECG learning resources. The primary endpoint will be the change in overall ECG interpretation performance according to pre- and post-intervention tests, and it will be measured within and compared between medical professional groups. Secondary endpoints will include changes in ECG interpretation time, self-reported confidence, and interpretation accuracy for specific ECG findings. CONCLUSIONS: The EDUCATE Trial is a pioneering initiative aiming to establish a practical, widely available, evidence-based solution to enhance ECG interpretation proficiency among medical professionals. Through its innovative study design, it tackles the currently unaddressed challenges of ECG interpretation education in the modern era. The trial seeks to pinpoint performance gaps across medical professions, compare the effectiveness of different web-based ECG content delivery methods, and create initial evidence for competency-based standards. If successful, the EDUCATE Trial will represent a significant stride towards data-driven solutions for improving ECG interpretation skills in the medical community.

Using medication containers during pharmacist transitional care visits and impact on medication discrepancies identified and hospital readmission risk.

OBJECTIVE: To evaluate the impact of having patients present to a pharmacist-clinician collaborative (PCC) visit after hospital discharge with their medication containers on risk of 30-day readmission. METHODS: This is a retrospective cohort study from July 1, 2013 to June 18, 2018 at 5 primary care clinic sites. We included adult patients on at least 10 total medications at hospital discharge who did and did not present to the PCC visit with medication containers. Patients in both groups met with a pharmacist for 30 minutes, immediately followed by a clinician visit. Thirty-day risk of readmission was assessed using Cox proportional hazards regression. RESULTS: A total of 724 qualifying patients presented for a PCC visit with their medication containers within 30 days of hospital discharge, whereas 636 did not. After adjusting for significant differences in baseline characteristics, there was no statistically significant difference in hospital readmission risk between the groups at 30 days after the visit (hazard ratio 0.94 [95% CI 0.68-1.29], P = 0.69). When patients brought their medication containers, pharmacists identified more medication discrepancies (mean ± SD, 2.2 ± 2.1 vs. 1.5 ± 1.7, P < 0.001) and made more medication therapy recommendations (1.8 ± 1.3 vs. 1.5 ± 1.2, P < 0.001) to the clinician. CONCLUSION: The presence of medication containers did not affect the risk of hospital readmission, although, it did allow pharmacists to identify more medication discrepancies and medication problems. These findings support instructing patients to bring their medication containers to transitional care visits to resolve medication-related issues.

Professionalism and inter-communication skills (ICS): a multi-site validity study assessing proficiency in core competencies and milestones in medical learners.

BACKGROUND: Interpersonal and Communication Skills (ICS) and Professionalism milestones are challenging to evaluate during medical training. Paucity in proficiency, direction and validity evidence of assessment tools of these milestones warrants further research. We validated the reliability of the previously-piloted Instrument for Communication skills and Professionalism Assessment (InCoPrA) in medical learners. METHODS: This validity approach was guided by the rigorous Kane's Framework. Faculty-raters and standardized patients (SPs) used their respective InCoPrA sub-component to assess distinctive domains pertinent to ICS and Professionalism through multiple expert-built simulated-scenarios comparable to usual care. Evaluations included; inter-rater reliability of the faculty total score; the correlation between the total score by the SPs; and the average of the total score by two-faculty members. Participants were surveyed regarding acceptability, realism, and applicability of this experience. RESULTS: Eighty trainees and 25 faculty-raters from five medical residency training sites participated. ICC of the total score between faculty-raters was generally moderate (ICC range 0.44-0.58). There was on average a moderate linear relationship between the SPs and faculty total scores (Pearson correlations range 0.23-0.44). Majority of participants ascertained receiving a meaningful, immediate, and comprehensive patient-faculty feedback. CONCLUSIONS: This work substantiated that InCoPrA was a reliable, standardized, evidence-based, and user-friendly assessment tool for ICS and Professionalism milestones. Validating InCoPrA showed generally-moderate agreeability and high acceptability. Using InCoPrA also promoted engaging all stakeholders in medical education and training-faculty, learners, and SPs-using simulation-media as pathway for comprehensive feedback of milestones growth.

Impact of rural address and distance from clinic on depression outcomes within a primary care medical home practice.

BACKGROUND: Depression is the second leading cause of death among young adults and a major cause of disability worldwide. Some studies suggest a disparity between rural and urban outcomes for depression. Collaborative Care Management (CCM) is effective in improving recovery from depression, but its effect within rural and urban populations has not been studied. METHODS: A retrospective cohort study of 3870 patients diagnosed with depression in a multi-site primary care practice that provided optional, free CCM was conducted. US Census data classified patients as living in an Urban Area, Urban Cluster, or Rural area and the distance they resided from their primary care clinic was calculated. Baseline demographics, clinical data, and standardized psychiatric assessments were collected. Six month Patient Health Questionnaire (PHQ 9) scores were used to judge remission (PHQ9 < 5) or Persistent Depressive Symptoms (PDS) (PHQ9 ≥ 10) in a multivariate model with interaction terms. RESULTS: Rural patients had improved adjusted odds of remission (AOR = 2.8) and PDS (AOR = 0.36) compared to urban area patients. The natural logarithm transformed distance to primary care clinic was significant for rural patients resulting in a lower odds of remission and increased odds of PDS with increasing distance from clinic. The marginal probability of remission or PDS for rural patients equaled that of urban area patients at a distance of 34 or 40 km respectively. Distance did not have an effect for urban cluster or urban area patients nor did distance interact with CCM. CONCLUSION: Residing in a rural area had a beneficial effect on the recovery from depression. However this effect declined with increasing distance from the primary care clinic perhaps related to greater social isolation or difficulty accessing care. This distance effect was not seen for urban area or urban cluster patients. CCM was universally beneficial and did not interact with distance.

Increased medical cost metrics for patients 50 years of age and older in the collaborate care model of treatment for depression.

BACKGROUND: The collaborative care model (CCM) has been consistently shown to achieve effectiveness in depression management compared to usual care. In the present study, we aimed to determine the impact of age on cost metrics in patients who were treated with CCM for 6 months after a diagnosis of depression. METHODS: The upper quartile of age was 50 years and older (n = 56), and the comparison group was composed of patients in the three younger quartiles, aged 18-49 years (n = 163). RESULTS: Patients in the older age group had an elevated median Current Procedure Terminology cost rank of 255.5 compared to 168.0 for the younger patients (P < 0.001). Multiple logistic regression analysis revealed that being in the upper quartile of age (≥ 50 years) (odds ratio = 2.272, 95% confidence interval: 1.064-4.851; P = 0.034) and having higher numbers of clinical visits 6 months prior to index (odds ratio = 1.209, 95% confidence interval: 1.118-1.307; P < 0.001) were significant predictor variables of being cost rank outliers (>80th percentile) in patients with CCM. CONCLUSION: Medical cost utilization in the 6 months after diagnosis of depression was significantly higher in patients in the upper age quartile (≥ 50 years) enrolled in CCM than those in the lower quartiles (age < 50).

Minority Primary Care Patients With Depression: Outcome Disparities Improve With Collaborative Care Management.

BACKGROUND/OBJECTIVES: Racial and ethnic disparities in depression incidence, prevalence, treatment, and outcomes still persist. The hypothesis of this study was that use of collaborative care management (CCM) in treating depressed primary care patients would decrease racial disparities in 6-month clinical outcomes compared with those patients treated with usual primary care (UC). RESEARCH DESIGN/SUBJECTS: In a retrospective chart review analysis, 3588 (51.2%) patients received UC and 3422 (48.8%) patients were enrolled in CCM. Logistic regression analyses were used to examine disparities in 6-month outcomes. RESULTS: Minority patients enrolled in CCM were more likely to be participating in depression care at 6 months than minority patients in UC (61.8% vs. 14.4%; P≤0.001). After adjustment for demographic and clinical covariates, this difference remained statistically significant (odds ratio=9.929; 95% CI, 6.539-15.077, P≤0.001).The 568 minority UC patients with 6-month follow-up PHQ-9 data demonstrated a much lower odds ratio of a PHQ-9 score of <5 (0.220; 95% CI, 0.085-0.570; P=0.002) and a much higher odds ratio of PHQ-9 score of ≥10 (3.068; 95% CI, 1.622-5.804; P<0.001) when compared with the white, non-Hispanic patients. In contrast, the 2329 patients treated with CCM, the odds ratio for a PHQ-9 score of <5 or ≥10 after 6 months, demonstrated no significance of minority status. CONCLUSIONS: Utilization of CCM for depression was associated with a significant reduction of the disparities for outcomes of compliance, remission, or persistence of depressive symptoms for minority patients with depression versus those treated with UC.

Diabetes and obesity not associated with 6-month remission rates for primary care patients with depression.

BACKGROUND: Complex interrelationships appear to exist among depression, diabetes, and obesity, and it has been proposed that both diabetes and obesity have an association with depression. OBJECTIVE: The purpose of our study was to explore the effect of obesity and diabetes on response to the treatment of depression. Our hypothesis was that obesity and the diagnosis of diabetes in primary care patients with depression would have no effects on depression remission rates 6 months after diagnosis. METHODS: A retrospective chart review analysis of 1894 adult (age ≥18y) primary care patients diagnosed with major depressive disorder or dysthymia and a Patient Health Questionnaire-9 score ≥10 from January 1, 2008, through September 30, 2012. Multiple logistic regression modeling retaining all independent variables was performed for the outcome of remission (Patient Health Questionnaire-9 < 5) 6 months after diagnosis. RESULTS: The presence of obesity (odds ratio = 0.937, 95% CI: 0.770-1.140, p = 0.514) or the diagnosis of diabetes (odds ratio = 0.740, 95% CI: 0.535-1.022, p = 0.068) did not affect the likelihood of remission, while controlling for the other independent variables. CONCLUSIONS: In primary care patients treated for depression, the presence of diabetes or obesity at the time of diagnosis of depression does not appear to significantly affect remission of depressive symptoms 6 months after diagnosis.

Continuity of Care: A Primer for Family Medicine Residencies.

Continuity of care has been an identifying characteristic of family medicine since its inception and is an essential ingredient for high-functioning health care teams. Many benefits, including the quadruple aim of enhancing patient experience, improving population health, reducing costs, and improving care team well-being, are ascribed to continuity of care. In 2023, the Accreditation Council for Graduate Medical Education (ACGME) added two new continuity requirements-annual patient-sided continuity and annual resident-sided continuity-in family medicine training programs. This article reviews continuity of care as it applies to family medicine training programs. We discuss the various types of continuity and issues surrounding the measurement of continuity. A generally agreed upon definition of patient-sided and resident-sided continuity is presented to allow programs to begin to collect the necessary data. Especially within resident training programs, intricacies associated with maintaining continuity of care, such as empanelment, resident turnover, and scheduling, are discussed. The importance of right-sizing resident panels is highlighted, and a mechanism for accomplishing this is presented. The recent ACGME requirements represent a cultural shift from measuring resident experience based on volume to measuring resident continuity. This cultural shift forces family medicine training programs to adapt their various systems, policies, and procedures to emphasize continuity. We hope this manuscript's review of several facets of contuinuity, some unique to training programs, helps programs ensure compliance with the ACGME requirements.

Emergency department risk model: timely identification of patients for outpatient care coordination.

OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patients for CoCM to prevent frequent ED utilization remains unclear. This study aimed to develop and validate a risk identification model to proactively detect patients with MDD in CoCM at high risk of frequent (≥ 3) ED visits. STUDY DESIGN: This retrospective cohort study utilized electronic health records from Mayo Clinic's primary care system to develop and validate a machine learning-based risk identification model. The model predicts the likelihood of frequent ED visits among patients with MDD within a 12-month period. METHODS: Data were collected from Mayo Clinic's primary care system between May 1, 2006, and December 19, 2018. Risk identification models were developed and validated using machine learning classifiers to estimate frequent ED visit risks over 12 months. The Shapley Additive Explanations model identified variables driving frequent ED visits. RESULTS: The patient population had a mean (SD) age of 39.78 (16.66) years, with 30.3% being male and 6.1% experiencing frequent ED visits. The best-performing algorithm (elastic-net logistic regression) achieved an area under the curve of 0.79 (95% CI, 0.74-0.84), a sensitivity of 0.71 (95% CI, 0.57-0.82), and a specificity of 0.76 (95% CI, 0.64-0.85) in the development data set. In the validation data set, the best-performing algorithm (random forest) achieved an area under the curve of 0.79, a sensitivity of 0.83, and a specificity of 0.61. Significant variables included male gender, prior frequent ED visits, high Patient Health Questionnaire-9 score, low education level, unemployment, and use of multiple medications. CONCLUSIONS: The risk identification model has potential for clinical application in triaging primary care patients with MDD in CoCM, aiming to reduce future ED utilization.

EDUCATE: An international, randomized controlled trial for teaching electrocardiography.

INTRODUCTION: Despite the critical role of electrocardiograms (ECGs) in patient care, evident gaps exist in ECG interpretation competency among healthcare professionals across various medical disciplines and training levels. Currently, no practical, evidence-based, and easily accessible ECG learning solution is available for healthcare professionals. The aim of this study was to assess the effectiveness of web-based, learner-directed interventions in improving ECG interpretation skills in a diverse group of healthcare professionals. METHODS: In an international, prospective, randomized controlled trial, 1206 healthcare professionals from various disciplines and training levels were enrolled. They underwent a pre-intervention test featuring 30 12-lead ECGs with common urgent and non-urgent findings. Participants were randomly assigned to four groups: (i) practice ECG interpretation question bank (question bank), (ii) lecture-based learning resource (lectures), (iii) hybrid question- and lecture-based learning resource (hybrid), or (iv) no ECG learning resources (control). After four months, a post-intervention test was administered. The primary outcome was the overall change in ECG interpretation performance, with secondary outcomes including changes in interpretation time, self-reported confidence, and accuracy for specific ECG findings. Both unadjusted and adjusted scores were used for performance assessment. RESULTS: Among 1206 participants, 863 (72 %) completed the trial. Following the intervention, the question bank, lectures, and hybrid intervention groups each exhibited significant improvements, with average unadjusted score increases of 11.4 % (95 % CI, 9.1 to 13.7; P<0.01), 9.8 % (95 % CI, 7.8 to 11.9; P<0.01), and 11.0 % (95 % CI, 9.2 to 12.9; P<0.01), respectively. In contrast, the control group demonstrated a non-significant improvement of 0.8 % (95 % CI, -1.2 to 2.8; P=0.54). While no differences were observed among intervention groups, all outperformed the control group significantly (P<0.01). Intervention groups also excelled in adjusted scores, confidence, and proficiency for specific ECG findings. CONCLUSION: Web-based, self-directed interventions markedly enhanced ECG interpretation skills across a diverse range of healthcare professionals, providing an accessible and evidence-based solution.

Patient self-assessment factors predictive of persistent depressive symptoms 6 months after enrollment in collaborative care management.

BACKGROUND: Collaborative care management (CCM) is effective for improving depression outcomes. However, a subset of patients will still have symptoms after 6 months. This study sought to determine whether routinely obtained baseline clinical, demographic, and self-assessment variables would predict which patients endorse persistent depressive symptoms (PDS) after 6 months. By estimating the relative risk associated with the patient variables, we aimed to outline the combinations of factors predictive of PDS after CCM enrollment. METHODS: We retrospectively reviewed 1,110 adult primary care patients with the diagnosis of major depressive disorder enrolled in a CCM program and evaluated those with PDS (defined as patient health questionnaire-9score ≥10) 6 months after enrollment. RESULTS: At baseline, an increased depression severity, worsening symptoms of generalized anxiety, an abnormal screening on the mood disorder questionnaire (MDQ) and the diagnosis of recurrent episode of depression were independent predictors of PDS. A patient with severe, recurrent depression, an abnormal MDQ screen, and severe anxiety at baseline had a predicted 42.1% probability of PDS at 6 months. In contrast, a patient with a moderate, first episode of depression, normal MDQ screen, and no anxiety symptoms had a low probability of PDS at 6.6%. CONCLUSIONS: This study identified several patient self-assessment scores and clinical diagnosis that markedly predicted the probability of PDS 6 months after diagnosis and enrollment into CCM. Knowledge of these high-risk attributes should alert the clinician to monitor select patients more closely and consider altering therapy appropriately.

Antidepressant Medication Use Among Patients with Depression: Comparison between Usual Care and Collaborative Care Using Care Managers.

Depression poses a significant economic and health burden, yet it remains underdiagnosed and inadequately treated. The STAR*D trial funded by the National Institute of Mental Health showed that more than one antidepressant medication is often necessary to achieve disease remission among patients seen in both psychiatric and primary care settings. The collaborative care model (CCM), using care managers, has been shown to be effective in numerous studies in achieving sustained outcomes in depression management compared to usual care. This model was adopted in a statewide depression treatment improvement initiative among primary care clinics in Minnesota, which was launched in March 2008. In this study, records of patients who were enrolled in CCM from March 2008 until March 2009 were reviewed and compared to those under usual care. Patients who were followed under the CCM had a significantly greater number of antidepressant medication utilizations when compared to those under usual care. After 6 months, mean PHQ-9 score of patients under CCM was statistically lower than those in usual care. There was no significant difference in both mean PHQ-9 scores at 6 months and antidepressant utilization between the 2 groups among patients aged 65 years and older.

Application of a case-control design to the analysis of drop-outs from integrated behavioural health care.

BACKGROUND: Case-control designs are rarely employed in quality improvement investigations. The reason for the study was two-fold: (1) to demonstrate the feasibility of the method in a practice setting, and (2) because drop-outs from this programme had not previously been investigated. METHODS: Drop-out was defined as termination due to non-contact after two consecutive months. Fifty drop-outs were randomly selected from all cases discharged from the programme during the period 1 March 2008 to 28 February 2012. Fifty controls were randomly selected from among those discharged patients who did not drop out due to non-contact. RESULTS: Dropping out was significantly associated with female sex (P = 0.015), younger age (P = 0.000) and treatment site (P = 0.004). Sites still in the shake-down period had higher drop-out rates. Depression diagnosis and severity were not significant. CONCLUSIONS: The case-control design is an efficient approach to retrospective analysis of discrete quality indicators.

Outcomes for collaborative care versus routine care in the management of postpartum depression.

BACKGROUND: Even with routine screening, women diagnosed with postpartum depression (PPD) often experience delays in treatment with consequences affecting mother, infant, families and communities. A collaborative care management (CCM) approach may provide more timely, effective and higher quality of care for women suffering from postpartum depression. AIMS: This study compared the outcomes of women diagnosed with depression within a year of giving birth, comparing management using a collaborative care model with routine primary care. METHODS: In a retrospective quantitative cohort pilot study (n = 78), the outcomes of days to first follow-up, one-year healthcare utilisation, remission rates and other quality metrics were investigated. RESULTS: Those who were managed with CCM had fewer days to first follow-up (6.1 versus 31.4; P < 0.01), were more likely to meet the quality metrics of three or more related contacts in the three months after diagnosis (P < 0.01), and had documented Patient Health Questionnaire (PHQ-9) or Edinburgh Postnatal Depression Scale (EPDS) measurements at 3 (P < 0.01), 6 (P < 0.01) and 12 (P < 0.01) months. With an intention to treat model, 6-month remission rates were improved with CCM (46.7 vs. 6.3%, P <0.01). Those managed collaboratively versus routinely used healthcare in the year following diagnosis at similar rates. CONCLUSIONS: A CCM model offers timelier and higher quality care to women suffering from PPD, without contributing to higher healthcare utilisation.

Comparison of Ambulatory Quality Measures Between Shared Practice Panels and Independent Practice Panels.

Objective: To assess for differences in patient care outcomes in the primary care setting for patients assigned to an independent practice panel (IPP) or a shared practice panel (SPP). Patients and Methods: We retrospectively reviewed the electronic health records of patients of 2 Mayo Clinic family medicine primary care clinics from January 1, 2019 to December 31, 2019. Patients were assigned to either an IPP (physician or advanced practice provider [APP]) or an SPP (physician and ≥1 APP). We assessed 6 measures of quality care and compared them between IPP and SPP groups: diabetes optimal care, hypertension control, depression remission at 6 months, breast cancer screening, cervical cancer screening, and colon cancer screening. Results: The study included 114,438 patients assigned to 140 family medicine panels during the study period: 87 IPPs and 53 SPPs. The IPP clinicians showed improved quality metrics compared with the SPP clinicians for the percentage of assigned patients achieving depression remission (16.6% vs 11.1%; P<.01). The SPP clinicians showed improved quality metrics compared with that of the IPP clinicians for the percentage of patients with cervical cancer screening (79.1% vs 74.2%; P<.01). The mean percentage of the panels achieving optimal diabetes control, hypertension control, colon cancer screening, and breast cancer screening were not significantly different between IPP and SPP panels. Conclusion: This study shows a considerable improvement in depression remission among IPP panels and in cervical cancer screening rates among SPP panels. This information may help to inform primary care team configuration.

ECG Interpretation Proficiency of Healthcare Professionals.

ECG interpretation is essential in modern medicine, yet achieving and maintaining competency can be challenging for healthcare professionals. Quantifying proficiency gaps can inform educational interventions for addressing these challenges. Medical professionals from diverse disciplines and training levels interpreted 30 12-lead ECGs with common urgent and nonurgent findings. Average accuracy (percentage of correctly identified findings), interpretation time per ECG, and self-reported confidence (rated on a scale of 0 [not confident], 1 [somewhat confident], or 2 [confident]) were evaluated. Among the 1206 participants, there were 72 (6%) primary care physicians (PCPs), 146 (12%) cardiology fellows-in-training (FITs), 353 (29%) resident physicians, 182 (15%) medical students, 84 (7%) advanced practice providers (APPs), 120 (10%) nurses, and 249 (21%) allied health professionals (AHPs). Overall, participants achieved an average overall accuracy of 56.4% ± 17.2%, interpretation time of 142 ± 67 seconds, and confidence of 0.83 ± 0.53. Cardiology FITs demonstrated superior performance across all metrics. PCPs had a higher accuracy compared to nurses and APPs (58.1% vs 46.8% and 50.6%; P < 0.01), but a lower accuracy than resident physicians (58.1% vs 59.7%; P < 0.01). AHPs outperformed nurses and APPs in every metric and showed comparable performance to resident physicians and PCPs. Our findings highlight significant gaps in the ECG interpretation proficiency among healthcare professionals.

Impact of Computer-Interpreted ECGs on the Accuracy of Healthcare Professionals.

The interpretation of electrocardiograms (ECGs) involves a dynamic interplay between computerized ECG interpretation (CEI) software and human overread. However, the impact of computer ECG interpretation on the performance of healthcare professionals remains largely unexplored. The aim of this study was to evaluate the interpretation proficiency of various medical professional groups, with and without access to the CEI report. Healthcare professionals from diverse disciplines, training levels, and countries sequentially interpreted 60 standard 12-lead ECGs, demonstrating both urgent and nonurgent findings. The interpretation process consisted of 2 phases. In the first phase, participants interpreted 30 ECGs with clinical statements. In the second phase, the same 30 ECGs and clinical statements were randomized and accompanied by a CEI report. Diagnostic performance was evaluated based on interpretation accuracy, time per ECG (in seconds [s]), and self-reported confidence (rated 0 [not confident], 1 [somewhat confident], or 2 [confident]). A total of 892 participants from various medical professional groups participated in the study. This cohort included 44 (4.9%) primary care physicians, 123 (13.8%) cardiology fellows-in-training, 259 (29.0%) resident physicians, 137 (15.4%) medical students, 56 (6.3%) advanced practice providers, 82 (9.2%) nurses, and 191 (21.4%) allied health professionals. The inclusion of the CEI was associated with a significant improvement in interpretation accuracy by 15.1% (95% confidence interval, 14.3-16.0; P < 0.001), decrease in interpretation time by 52 s (-56 to -48; P < 0.001), and increase in confidence by 0.06 (0.03-0.09; P = 0.003). Improvement in interpretation accuracy was seen across all professional subgroups, including primary care physicians by 12.9% (9.4-16.3; P = 0.003), cardiology fellows-in-training by 10.9% (9.1-12.7; P < 0.001), resident physicians by 14.4% (13.0-15.8; P < 0.001), medical students by 19.9% (16.8-23.0; P < 0.001), advanced practice providers by 17.1% (13.3-21.0; P < 0.001), nurses by 16.2% (13.4-18.9; P < 0.001), allied health professionals by 15% (13.4-16.6; P < 0.001), physicians by 13.2% (12.2-14.3; P < 0.001), and nonphysicians by 15.6% (14.3-17.0; P < 0.001).CEI integration improves ECG interpretation accuracy, efficiency, and confidence among healthcare professionals.

Predictors of ECG Interpretation Proficiency in Healthcare Professionals.

Accurate ECG interpretation is vital, but variations in skills exist among healthcare professionals. This study aims to identify factors contributing to ECG interpretation proficiency. Survey data and ECG interpretation test scores from participants in the EDUCATE Trial were analyzed to identify predictors of performance for 30 sequential 12-lead ECGs. Nonmodifiable factors (being a physician, clinical experience, patient care impact) and modifiable factors (weekly interpretation volume, training hours, expert supervision frequency) were analyzed. Bivariate and multivariate analyses were used to generate a Comprehensive Model (incorporating all factors) and Actionable Model (incorporating modifiable factors only). Among 1206 participants analyzed, there were 72 (6.0%) primary care physicians, 146 (12.1%) cardiology fellows-in-training, 353 (29.3%) resident physicians, 182 (15.1%) medical students, 84 (7.0%) advanced practice providers, 120 (9.9%) nurses, and 249 (20.7%) allied health professionals. Among them, 571 (47.3%) were physicians and 453 (37.6%) were nonphysicians. The average test score was 56.4% ± 17.2%. Bivariate analysis demonstrated significant associations between test scores and >10 weekly ECG interpretations, being a physician, >5 training hours, patient care impact, and expert supervision but not clinical experience. In the Comprehensive Model, independent associations were found with weekly interpretation volume (9.9 score increase; 95% CI, 7.9-11.8; P < 0.001), being a physician (9.0 score increase; 95% CI, 7.2-10.8; P < 0.001), and training hours (5.7 score increase; 95% CI, 3.7-7.6; P < 0.001). In the Actionable Model, scores were independently associated with weekly interpretation volume (12.0 score increase; 95% CI, 10.0-14.0; P < 0.001) and training hours (4.7 score increase; 95% CI, 2.6-6.7; P < 0.001). The Comprehensive and Actionable Models explained 18.7% and 12.3% of the variance in test scores, respectively. Predictors of ECG interpretation proficiency include nonmodifiable factors like physician status and modifiable factors such as training hours and weekly ECG interpretation volume.

Exploring Factors Influencing ECG Interpretation Proficiency of Medical Professionals.

The electrocardiogram (ECG) is a crucial diagnostic tool in medicine with concerns about its interpretation proficiency across various medical disciplines. Our study aimed to explore potential causes of these issues and identify areas requiring improvement. A survey was conducted among medical professionals to understand their experiences with ECG interpretation and education. A total of 2515 participants from diverse medical backgrounds were surveyed. A total of 1989 (79%) participants reported ECG interpretation as part of their practice. However, 45% expressed discomfort with independent interpretation. A significant 73% received less than 5 hours of ECG-specific education, with 45% reporting no education at all. Also, 87% reported limited or no expert supervision. Nearly all medical professionals (2461, 98%) expressed a desire for more ECG education. These findings were consistent across all groups and did not vary between primary care physicians, cardiology FIT, resident physicians, medical students, APPs, nurses, physicians, and nonphysicians. This study reveals substantial deficiencies in ECG interpretation training, supervision, and confidence among medical professionals, despite a strong interest in increased ECG education.

Pre-Anesthetic Medical Evaluations: Criteria Considerations for Telemedicine Alternatives to Face to Face Visits.

BACKGROUND: The number of pre-anesthetic medical evaluations (PAMEs) being conducted in primary care is increasing. Due to the COVID-19 pandemic, the use of telemedicine has surged, providing a feasible way to conduct some of these visits. This study aimed to identify patient-related factors where a face to face (FTF) evaluation is indicated, measured by the need for pre-operative testing. METHODS: A retrospective chart review was conducted on patients age ≥ 18 years who had a PAME between January 2019-June 2020 at a rural primary care clinic in Southeast Minnesota. Data collected included age, gender, Charlson Comorbidity Index Score, medications, revised cardiac risk index (RCRI), smoking status, exercise capacity, body mass index, and pre-operative testing. Logistical regression modeling for odds ratios of outcomes was performed. RESULTS: 254 patients were included, with an average age of 64.1 years; 43.7% were female. Most were obese (mean BMI 31.6), non-smoking (93.7%) with excellent functional capacity (87.8% ≥ 5 METs). 76.8% of the planned surgeries were intermediate or high risk. 35.0% (n = 89) of visits resulted in medication adjustments and 76.7% (n = 195) in pre-operative testing. Age ≥ 65 years, ≥7 current medications, and diabetes all significantly increased the odds of requiring pre-operative testing (P < .05). CONCLUSIONS: This study was able to identify patient-related factors that increased the likelihood of requiring pre-operative testing. Patients who are age ≥ 65 years, ≥7 current medications, and those with diabetes could be scheduled for a FTF evaluation. Others could be scheduled for a telemedicine visit to minimize health-care exposures.