interests include the intersection of gender and cardiovascular health, social justice in health care, and
the use of technology to enhance accessibility of botheducation and clinical care.
As a clinician and a scholar, I publish in both peer-reviewed scientific journals and in venues written for a general audience. A few selected pubs are here for you!
Objectives: Delay from symptom onset to hospital arrival drives poor outcomes in acute coronary syndrome (ACS), particularly for women. Primary care clinicians can discuss ACS with high-risk women, potentially reducing delay. We conducted a scoping review to assess what is known about ACS risk communication to women in primary care.
Methods: We used Arksey and O’Malley’s framework. The PubMed, CINAHL, PsycINFO, and Embase databases were searched for relevant articles from inception through September, 2018. No restrictions on study methodology were applied. At least two reviewers assessed each article. Articles addressing risk communication, coronary heart disease, and ACS, related to primary care settings, and including women were retained.
Results: Eleven articles met inclusion criteria. Cardiovascular disease (CVD) risk communication is common in primary care; however, ACS symptoms are rarely discussed. Structured risk calculators are used to frame discussions. Communication styles include patient-centered discussions, paternalistic orders, and “scare tactics;” no single style is more effective. Analysis of gender differences in risk communication is extremely limited.
Conclusion: There is scant evidence that primary care clinicians communicate effectively about ACS risk, symptoms, and appropriate symptom response. Practice implications: Interventions are needed to improve communication about ACS to at-risk women in the primary care setting.
Purpose: This article introduces a framework to (a) guide chronic illness self management interventions through the integration of self-management and nursing informatics, (b) focus self-management research, and (c) promote ethical, patient-empowering technology use by practicing nurses.
Methods: Existing theory and research focusing on chronic illness, self management, health-enabling technology, and nursing informatics were reviewed and examined and key concepts were identified. A care paradigm focusing on concordance, rather than compliance, served as the overall guiding principle.
Findings: This framework identifies key relationships among self management (patient behaviors), health force (patient characteristics), and patient-defined goals. The role of health-enabling technology supporting these relationships is explored in the context of nursing informatics.
Conclusions: The Empowerment Informatics framework can guide intervention design and evaluation and support practicing nurses’ ethical use of technology as part of self-management support.
Clinical Relevance: Nurses worldwide provide support to patients who are living with chronic illnesses. As pressures related to cost and access to care increase, technology-enabled self-management interventions will become increasingly common. This patient-focused framework can guide nursing practice using technology that prioritizes patient needs.
Background—Many patients evaluated for acute coronary syndrome (ACS) in emergency departments (EDs) continue to experience troubling symptoms after discharge—regardless of their ultimate medical diagnosis. However, comprehensive understanding of common postED symptom trajectories is lacking.
Objectives—To identify common trajectories of symptom severity in the six months after an ED visit for potential ACS.
Methods—This was a secondary analysis of data from a larger observational, prospective study conducted in five U.S. emergency departments. Patients (N = 1005) who had electrocardiogram and biomarker testing ordered, and were identified by the triage nurse as potentially having ACS, were enrolled. Symptom severity was assessed in the hospital after initial stabilization and by telephone at 30 days and six months using the validated 13-item ACS Symptom Checklist. Growth mixture modeling was used for the secondary analysis. The eight most commonly reported symptoms (chest discomfort, chest pain, chest pressure, lightheadedness,
shortness of breath, shoulder pain, unusual fatigue, and upper back pain) were modeled across the three study timepoints. Models with increasing numbers of classes were compared, and final model selection was based on a combination of interpretability, theoretical justification, and statistical fit indices.
Results—The sample was 62.6% male with a mean age of 60.2 years (SD = 14.17), and 57.1% ruled out for ACS. Between two and four distinct trajectory classes were identified for each symptom. The seven different types of trajectories identified across the eight symptoms were labeled “tapering off,” “mild/persistent,” “moderate/persistent,” “moderate/worsening,” “moderate/improving,” “late onset, “and “severe/improving.” Trajectories differed on age, sex, and diagnosis.
Discussion—Research on the individual nature of symptom trajectories can contribute to patient-centered, rather than disease-centered, care. Further research is needed to verify the existence of multiple symptoms trajectories in diverse populations, and to assess the antecedents and consequences of individual symptom trajectories.
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