Citations

AbstractCardiovascular disease (CVD) remains the leading cause of death in the United States. However, percutaneous interventional cardiovascular therapies are often underutilized in Blacks, Hispanics, and women and may contribute to excess morbidity and mortality in these vulnerable populations. The Society for Cardiovascular Angiography and Interventions (SCAI) is committed to reducing racial, ethnic, and sex‐based treatment disparities in interventional cardiology patients. Accordingly, each of the SCAI Clinical Interest Councils (coronary, peripheral, structural, and congenital heart disease [CHD]) participated in the development of this whitepaper addressing disparities in diagnosis, treatment, and outcomes in underserved populations. The councils were charged with summarizing the available data on prevalence, treatment, and outcomes and elucidating potential reasons for any disparities. Given the huge changes in racial and ethnic composition by age in the United States (Figure 1), it was difficult to determine disparities in rates of diagnosis and we expected to find some racial differences in prevalence of disease. For example, since the average age of patients undergoing transcatheter aortic valve replacement (TAVR) is 80 years, one may expect 80% of TAVR patients to be non‐Hispanic White. Conversely, only 50% of congenital heart interventions would be expected to be performed in non‐Hispanic Whites. Finally, we identified opportunities for SCAI to advance clinical care and equity for our patients, regardless of sex, ethnicity, or race.

AbstractClinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention—the starting point for delivery of “All the right care, but only the right care,” an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.