A Systems-Based Morbidity and Mortality Conference Was Associated With a Transient Reduction in ECG Completion Times.

BACKGROUND AND OBJECTIVES: During its monthly morbidity and mortality conference (MMC), the University of Colorado Division of Cardiology reviewed a "near-miss" patient safety event involving the delayed completion of a Stat-priority (ie, statim, meaning high priority) electrocardiogram (ECG). Because critical and interprofessional stakeholders participated in the conference, we hypothesized that the MMC would be associated with reduced ECG completion times. METHODS: Data were collected for in-hospital ECGs performed at the University of Colorado Hospital between January 1, 2017, and June 30, 2018. An interrupted time series analysis was used to estimate the immediate and ongoing impact of the MMC (held on February 28, 2018) on ECG completion times, stratified by order priority (Stat, Now, or Routine). The percentage of delayed Stat-priority ECGs was analyzed as a secondary outcome. RESULTS: Before the MMC, ECG completion times were stable for all order priorities ( P > .2), but the proportion of delayed Stat-priority ECGs increased from 5% in January 2017 to 20% in February 2018 ( P < .01). The MMC was associated with an immediate reduction in average daily ECG completion times for Routine (-18.4 minutes, P = .03) and Now (-8 minutes, P = .024) priority ECGs. No reduction was seen for Stat ECGs ( P = .97), though the percentage of delayed Stat ECGs stopped increasing ( P = .63). In the post-MMC period, completion times for Routine-priority ECGs increased and approached pre-MMC levels. CONCLUSIONS: The MMC was associated with an immediate, but temporary, improvement in ECG completion times. Although the observed clinical benefit of the MMC is novel, these data support the need for more durable reforms to sustain initial improvements.

Medication adherence in cardiovascular medicine.

Cardiovascular disease is the leading cause of death globally. While pharmacological advancements have improved the morbidity and mortality associated with cardiovascular disease, non-adherence to prescribed treatment remains a significant barrier to improved patient outcomes. A variety of strategies to improve medication adherence have been tested in clinical trials, and include the following categories: improving patient education, implementing medication reminders, testing cognitive behavioral interventions, reducing medication costs, utilizing healthcare team members, and streamlining medication dosing regimens. In this review, we describe specific trials within each of these categories and highlight the impact of each on medication adherence. We also examine ongoing trials and future lines of inquiry for improving medication adherence in patients with cardiovascular diseases.

Acute Myocardial Infarction Cohorts Defined by International Classification of Diseases, Tenth Revision Versus Diagnosis-Related Groups: Analysis of Diagnostic Agreement and Quality Measures in an Integrated Health System.

BACKGROUND: Among Medicare value-based payment programs for acute myocardial infarction (AMI), the Hospital Readmissions Reduction Program uses International Classification of Diseases, Tenth Revision (ICD-10) codes to identify the program denominator, while the Bundled Payments for Care Improvement Advanced program uses diagnosis-related groups (DRGs). The extent to which these programs target similar patients, whether they target the intended population (type 1 myocardial infarction), and whether outcomes are comparable between cohorts is not known. METHODS: In a retrospective study of 2176 patients hospitalized in an integrated health system, a cohort of patients assigned a principal ICD-10 diagnosis of AMI and a cohort of patients assigned an AMI DRG were compared according to patient-level agreement and outcomes such as mortality and readmission. RESULTS: One thousand nine hundred thirty-five patients were included in the ICD-10 cohort compared with 662 patients in the DRG cohort. Only 421 patients were included in both AMI cohorts (19.3% agreement). DRG cohort patients were older (70 versus 65 years, P<0.001), more often female (48% versus 30%, P<0.001), and had higher rates of heart failure (52% versus 33%, P<0.001) and kidney disease (42% versus 25%, P<0.001). Comparing outcomes, the DRG cohort had significantly higher unadjusted rates of 30-day mortality (6.6% versus 2.5%, P<0.001), 1-year mortality (21% versus 8%, P<0.001), and 90-day readmission (26% versus 19%, P=0.006) than the ICD-10 cohort. Two observations help explain these differences: 61% of ICD-10 cohort patients were assigned procedural DRGs for revascularization instead of an AMI DRG, and type 1 myocardial infarction patients made up a smaller proportion of the DRG cohort (34%) than the ICD-10 cohort (78%). CONCLUSIONS: The method used to identify denominators for value-based payment programs has important implications for the patient characteristics and outcomes of the populations. As national and local quality initiatives mature, an emphasis on ICD-10 codes to define AMI cohorts would better represent type 1 myocardial infarction patients.

The Cardiovascular Quality Improvement and Care Innovation Consortium: Inception of a Multicenter Collaborative to Improve Cardiovascular Care.

Despite decades of improvement in the quality and outcomes of cardiovascular care, significant gaps remain. Existing quality improvement strategies are often limited in scope to specific clinical conditions and episodic care. Health services and outcomes research is essential to inform gaps in care but rarely results in the development and implementation of care delivery solutions. Although individual health systems are engaged in projects to improve the quality of care delivery, these efforts often lack a robust study design or implementation evaluation that can inform generalizability and further dissemination. Aligning the work of health care systems and health services and outcomes researchers could serve as a strategy to overcome persisting gaps in cardiovascular quality and outcomes. We describe the inception of the Cardiovascular Quality Improvement and Care Innovation Consortium that seeks to rapidly improve cardiovascular care by (1) developing, implementing, and evaluating multicenter quality improvement projects using innovative care designs; (2) serving as a resource for quality improvement and care innovation partners; and (3) establishing a presence within existing quality improvement and care innovation structures. Success of the collaborative will be defined by projects that result in changes to care delivery with demonstrable impacts on the quality and outcomes of care across multiple health systems. Furthermore, insights gained from implementation of these projects across sites in Cardiovascular Quality Improvement and Care Innovation Consortium will inform and promote broad dissemination for greater impact.

Expanding Training in Quality Improvement and Patient Safety Through a Multispecialty Graduate Medical Education Curriculum Designed for Fellows.

Introduction: Although the Accreditation Council for Graduate Medical Education requires quality improvement and patient safety (QIPS) training for fellow-level trainees, this experience is often insufficient due to lack of faculty time and expertise within fellowship training programs. We developed a centralized GME curriculum targeted to an integrated, multispecialty audience of fellow-level trainees with the goal of promoting leadership and scholarship in QIPS. Methods: The University of Colorado implemented the Fellows' Quality and Safety Academy, a three-seminar curriculum in patient safety and health systems improvement. As most participants had prior training in QIPS during medical school or residency, educational strategies emphasized application of QIPS concepts through focused didactic content review paired with small-group case-based exercises and coaching of experiential project work to promote content mastery as well as practice of leadership and scholarship strategies. Results: Since the curriculum's inception in 2017, there have been 106 participants in the Foundations in Patient Safety seminar, 49 participants in the Adverse Events Into Quality Improvement seminar, and 48 participants in the Quality in Academics seminar. These participants represented 44 separate fellowship disciplines from both adult and pediatric subspecialties. Learners reported improved attitudes and confidence and demonstrated objective knowledge acquisition across QIPS content domains. Discussion: Our pedagogical approach of centralizing QIPS training and harnessing faculty expertise to teach fellow-level trainees across specialties through interdisciplinary collaboration and interactive project-based work is an effective strategy to promote development of QIPS competencies during fellowship training.

Supporting Parents During Cardiology Fellowship: Because Life Happens.

See Article Mwakyanjala et al.

Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools.

BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this risk, yet it is unknown whether reports contain adequate descriptive data to use NLP. METHODS: Among VA patients who underwent stress MPI and coronary angiography between January 1, 2009 and December 31, 2011, 99 stress test reports were randomly selected for analysis. Two reviewers independently categorized each report for the presence of critical data elements essential to describing post-test ischemic risk. RESULTS: Few stress MPI reports provided a formal assessment of post-test risk within the impression section (3%) or the entire document (4%). In most cases, risk was determinable by combining critical data elements (74% impression, 98% whole). If ischemic risk was not determinable (25% impression, 2% whole), inadequate description of systolic function (9% impression, 1% whole) and inadequate description of ischemia (5% impression, 1% whole) were most commonly implicated. CONCLUSIONS: Post-test ischemic risk was determinable but rarely reported in this sample of stress MPI reports. This supports the potential use of NLP to help clarify risk. Further study of NLP in this context is needed.

Applications of machine learning in decision analysis for dose management for dofetilide.

BACKGROUND: Initiation of the antiarrhythmic medication dofetilide requires an FDA-mandated 3 days of telemetry monitoring due to heightened risk of toxicity within this time period. Although a recommended dose management algorithm for dofetilide exists, there is a range of real-world approaches to dosing the medication. METHODS AND RESULTS: In this multicenter investigation, clinical data from the Antiarrhythmic Drug Genetic (AADGEN) study was examined for 354 patients undergoing dofetilide initiation. Univariate logistic regression identified a starting dofetilide dose of 500 mcg (OR 5.0, 95%CI 2.5-10.0, p<0.001) and sinus rhythm at the start of dofetilide loading (OR 2.8, 95%CI 1.8-4.2, p<0.001) as strong positive predictors of successful loading. Any dose-adjustment during loading (OR 0.19, 95%CI 0.12-0.31, p<0.001) and a history coronary artery disease (OR 0.33, 95%CI 0.19-0.59, p<0.001) were strong negative predictors of successful dofetilide loading. Based on the observation that any dose adjustment was a significant negative predictor of successful initiation, we applied multiple supervised approaches to attempt to predict the dose adjustment decision, but none of these approaches identified dose adjustments better than a probabilistic guess. Principal component analysis and cluster analysis identified 8 clusters as a reasonable data reduction method. These 8 clusters were then used to define patient states in a tabular reinforcement learning model trained on 80% of dosing decisions. Testing of this model on the remaining 20% of dosing decisions revealed good accuracy of the reinforcement learning model, with only 16/410 (3.9%) instances of disagreement. CONCLUSIONS: Dose adjustments are a strong determinant of whether patients are able to successfully initiate dofetilide. A reinforcement learning algorithm informed by unsupervised learning was able to predict dosing decisions with 96.1% accuracy. Future studies will apply this algorithm prospectively as a data-driven decision aid.

When a Short-Term Outlook Is the Best Long-Term Strategy: Time-Varying Risk of Readmission After Acute Myocardial Infarction.

See Article by Khot et al.

Recent Approaches to Improve Medication Adherence in Patients with Coronary Heart Disease: Progress Towards a Learning Healthcare System.

PURPOSE OF REVIEW: Non-adherence to medications for the secondary prevention of myocardial infarction (MI) is a major contributor to morbidity and mortality in these patients. This review describes recent advances in promoting adherence to therapies for coronary artery disease (CAD). RECENT FINDINGS: Two large randomized controlled trials to "incentivize" adherence were somewhat disappointing; neither financial incentives nor "peer pressure" successfully increased rates of adherence in the post-MI population. Patient education and provider engagement appear to be critical aspects of improving adherence to CAD therapies, where the provider is a physician, pharmacist, or nurse and follow-up is performed in person or by telephone. Fixed-dose combinations of CAD medications, formulated as a so-called "polypill," have shown some early efficacy in increasing adherence. Technological advances that automate monitoring and/or encouragement of adherence are promising but seem universally dependent on patient engagement. For example, medication reminders via text message perform better if patients are required to respond. Multifaceted interventions, in which these and other interventions are combined together, appear to be most effective. There are several available types of proven interventions through which providers, and the health system at large, can advance patient adherence to CAD therapies. No single intervention to promote adherence will be successful in all patients. Further study of multifaceted interventions and the interactions between different interventions will be important to advancing the field. The goal is a learning healthcare system in which a network of interventions responds and adapts to patients' needs over time.

Wisdom of the crowd: bright ideas and innovations from the teaching value and choosing wisely challenge.

PROBLEM: Medical education has been cited as both part of the problems facing, and part of the solution to reforming, the increasingly challenging U.S. health care system which is fraught with concerns regarding the quality and affordability of care. To teach value in ways that are impactful, sustainable, and scalable, the best and brightest ideas need to be shared such that educators can build on successful existing innovations. APPROACH: To identify the most promising innovations and bright ideas for teaching value to clinical trainees, the authors hosted the "Teaching Value and Choosing Wisely Challenge." The challenge used crowdsourcing methods to solicit scalable, pedagogical approaches from across North America, and then draw generalizable lessons. OUTCOMES: The authors received 74 submissions (28 innovations; 46 bright ideas) from 14 students, 20 residents/fellows, 38 faculty members (ranging from instructors to full professors), and 2 nonclinical administrators. Submissions represented 14 clinical disciplines including internal medicine, emergency medicine, surgery, pediatrics, obstetrics-gynecology, laboratory medicine, and pharmacy. Thirty-nine abstracts focused on graduate medical education, 15 addressed undergraduate medical education, and 20 applied to both. NEXT STEPS: The authors have solicited, shared, and described solutions for teaching high-value care to medical trainees. Challenge participants demonstrated commitment to improving value and ingenuity in addressing professional barriers to change. Further success requires strong local faculty champions and willing trainee participants. Additionally, the use of data to demonstrate the collective positive impact of these ideas and programs will be critical for sustaining pedagogical changes in the health professions.

Connexin40 abnormalities and atrial fibrillation in the human heart.

Normal atrial conduction requires similar abundances and homogeneous/overlapping distributions of two connexins (Cx40 and Cx43). The remodeling of myocyte connections and altered electrical conduction associated with atrial fibrillation (AF) likely involves perturbations of these connexins. We conducted a comprehensive series of experiments to examine the abundances and distributions of Cx40 and Cx43 in the atria of AF patients. Atrial appendage tissues were obtained from patients with lone AF (paroxysmal or chronic) or normal controls. Connexins were localized by double label immunofluorescence confocal microscopy, and their overlap was quantified. Connexin proteins and mRNAs were quantified by immunoblotting and qRT-PCR. PCR amplified genomic DNA was sequenced to screen for connexin gene mutations or polymorphisms. Immunoblotting showed reductions of Cx40 protein (to 77% or 49% of control values in samples from patients with paroxysmal and chronic AF, respectively), but no significant changes of Cx43 protein levels in samples from AF patients. The extent of Cx43 immunostaining and its distribution relative to N-cadherin were preserved in the AF patient samples. Although there was variability of Cx40 staining among paroxysmal AF patients, all had some fields with substantial Cx40 heterogeneity and reduced overlap with Cx43. Cx40 immunostaining was severely reduced in all chronic AF patients. qRT-PCR showed no change in Cx43 mRNA levels, but reductions in total Cx40 mRNA (to <50%) and Cx40 transcripts A (to ~50%) and B (to <25%) as compared to controls. No Cx40 coding region mutations were identified. The frequency of promoter polymorphisms did not differ between AF patient samples and controls. Our data suggest that reduced Cx40 levels and heterogeneity of its distribution (relative to Cx43) are common in AF. Multiple mechanisms likely lead to reductions of functional Cx40 in atrial gap junctions and contribute to the pathogenesis of AF in different patients.