Developing a sampling method and preliminary taxonomy for classifying COVID-19 public health guidance for healthcare organizations and the general public.

BACKGROUND: Development and dissemination of public health (PH) guidance to healthcare organizations and the general public (e.g., businesses, schools, individuals) during emergencies like the COVID-19 pandemic is vital for policy, clinical, and public decision-making. Yet, the rapidly evolving nature of these events poses significant challenges for guidance development and dissemination strategies predicated on well-understood concepts and clearly defined access and distribution pathways. Taxonomies are an important but underutilized tool for guidance authoring, dissemination and updating in such dynamic scenarios. OBJECTIVE: To design a rapid, semi-automated method for sampling and developing a PH guidance taxonomy using widely available Web crawling tools and streamlined manual content analysis. METHODS: Iterative samples of guidance documents were taken from four state PH agency websites, the US Center for Disease Control and Prevention, and the World Health Organization. Documents were used to derive and refine a preliminary taxonomy of COVID-19 PH guidance via content analysis. RESULTS: Eight iterations of guidance document sampling and taxonomy revisions were performed, with a final corpus of 226 documents. The preliminary taxonomy contains 110 branches distributed between three major domains: stakeholders (24 branches), settings (25 branches) and topics (61 branches). Thematic saturation measures indicated rapid saturation (≤5% change) for the domains of "stakeholders" and "settings", and "topic"-related branches for clinical decision-making. Branches related to business reopening and economic consequences remained dynamic throughout sampling iterations. CONCLUSION: The PH guidance taxonomy can support public health agencies by aligning guidance development with curation and indexing strategies; supporting targeted dissemination; increasing the speed of updates; and enhancing public-facing guidance repositories and information retrieval tools. Taxonomies are essential to support knowledge management activities during rapidly evolving scenarios such as disease outbreaks and natural disasters.

Safety risks and workflow implications associated with nursing-related free-text communication orders.

OBJECTIVE: We evaluated nursing-related free-text communication orders to identify potential safety hazards and describe patterns and scope of care domains addressed that may reveal preventable workarounds and potential gaps in electronic health record (EHR) functionality. MATERIALS AND METHODS: A retrospective analysis of free-text EHR-based communication orders sent to or by nurses providing inpatient care at a major academic health system. Using built-in EHR tools and selection criteria, 13 193 orders were extracted, including 1373 unique orders. Using the Clinical Care Classification system standardized framework, we classified content by care domain and identified unique requests within each order. We reviewed each order for error-prone textual features based on standard patient safety guidance. We describe the distribution of domains, co-occurrence when 2 domains were present, and common patterns. RESULTS: The 1373 unique orders included a single request (65.3%), 2 requests related to 1 or 2 domains (19%), or 3 or more requests (15.7%). No orders included terms on the Joint Commission's "Do Not Use" list. However, 13.6% of unique orders, and 16.7% of those related to medications, included error-prone symbols or abbreviations according to Institute for Safe Medication Practices guidance. Order content spanned 20 different care components but physical regulation, fluid volume, nutritional, safety, and medication were most frequently identified as single or co-occurring topics. Patterns were heterogenous. DISCUSSION: Free-text communication orders reveal workarounds, responses to upstream workarounds, and design constraints that should be further investigated. Remediation strategies are needed to reduce safety hazards and workflow impediments. CONCLUSIONS: Analysis of free-text communication orders revealed opportunities for improvement.

Game-Based Quality Improvement Teaching: Using Taters in Nursing Education.

BACKGROUND: Quality improvement (QI) is difficult to teach in the classroom; therefore, nursing students are often under-prepared to participate in such projects after graduation. The Plan-Do-Study-Act method is commonplace in QI instruction and is often used in nursing. This study proposed and evaluated a gameful learning approach to improve understanding and engagement of a QI process using Potato Head figures. METHOD: An observational design was utilized. Following classroom activity, students self-selected to join focus groups to discuss gameful learning experiences in learning QI techniques. Transcripts were analyzed using thematic analysis. RESULTS: Overall, learners found the activity was effective in teaching QI. Positive and negative themes were identified, including fun and competitive, interactive and communication, and teamwork; disconnection between QI topic and game, and unclear instruction, respectively. CONCLUSION: Using gameful learning helped students understand and engage with QI projects that may translate to clinical practice for new graduate nurses. [J Nurs Educ. 2021;60(10):590-593.].