Oral Implications of Polypharmacy in Older Adults.

Over the next several decades, rates of aged populations will increase rapidly. These populations are susceptible to multimorbidities and polypharmacy (concurrently, prescribed 5 or more medications). Many medications have side effects that manifest orally. Therefore, it essential to possess current pharmacologic knowledge to diagnose and treat oral implications of commonly prescribed medications. This article details common medication-induced oral lesions and patient assessment of risk factors for polypharmacy and provides a template to integrate medication reconciliation into dental clinical practice.

Oral Implications of Polypharmacy in Older Adults.

Over the next several decades, rates of aged populations will increase rapidly. These populations are susceptible to multimorbidities and polypharmacy (concurrently, prescribed 5 or more medications). Many medications have side effects that manifest orally. Therefore, it essential to possess current pharmacologic knowledge to diagnose and treat oral implications of commonly prescribed medications. This article details common medication-induced oral lesions and patient assessment of risk factors for polypharmacy and provides a template to integrate medication reconciliation into dental clinical practice.

Toward precision public health.

OBJECTIVES: The information in this article is based on a presentation given at the American Institute of Dental Public Health's 2018 Colloquium on Precision Public Health (PPH). A brief introduction to precision medicine provides context for PPH. Precision medicine tailors treatment and prevention strategies for individual patients based on variability of genetic, lifestyle, and environmental factors. An overview of PPH with examples of pilot studies with different research approaches bridges a discussion on an initiative undertaken by the University of Florida to build infrastructure and expertise for PPH research. METHODS: PPH use better and more precise data to target disease prevention and control in the right population at the right time. To facilitate the identification of relevant open access data sources for PPH research a "one-stop" shop was created and tested. Case studies were conducted to validate the data portal's usefulness in identifying at-risk populations. RESULTS: Details of portal data types, research challenges, and university-wide integrated programs are included. Case studies indicated that providing a "one-stop shop" of relevant data sources is an effective tool to aid researchers in identifying at-risk populations. CONCLUSIONS: Research studies undertaken by University of Florida graduate students illustrate how PPH aligns with essential public health services including community engagement to reduce disparities in health care. Assurance of a competent workforce in PPH research approaches may be improved by training new researchers graduating from health science programs with knowledge of data and tools. The move toward PPH is in early stages and much work lies ahead.

Towards implementing SNOMED CT in nursing practice: A scoping review.

BACKGROUND: Currently, it is rare for nursing data to be available in data repositories due to the quality of nursing data collected in clinical practice. To improve the quality of nursing data, the American Nurses Association recommends the use of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for coding nursing problems, interventions, and observations in electronic health records. OBJECTIVE: To determine "what is known about the use of SNOMED terminology (Pre-SNOMED CT and SNOMED CT) in nursing". METHODS: We searched four databases and two search engines. We identified 29 articles for review. A modified version of System Development Life Cycle (SDLC), and Mapping Evaluation Assessment (MEA), created by the authors were used for quality assessment. RESULTS: All 29 studies mapped standardized (n = 19) or local nursing terms (n = 10) to the SNOMED terminology. MEA scores ranged from 2-8 (range 0-11) with 25 receiving scores from 5-8. On the modified SDLC (range 0-5), all studies exhibited activities of stage 0 (pre-application integration), with two studies describing integration and preliminary testing of SNOMED CT coded nursing content in applications (stage 2). CONCLUSION: Though efforts are underway to ensure adequate coverage of nursing in SNOMED CT, there were no studies indicating use in nursing practice. The authors offer recommendations for achieving the widespread collection of interoperable SNOMED CT coded nursing data in clinical applications to evaluate nursing's impact on patient outcomes. These include creating a clear professional vision and path to our data goals that builds on sound rationale and evidence, abundant stakeholder engagement, and sufficient resources.