To Thicken or Not to Thicken: Exploring the Use of Math-Based Clinical Decision Making

Abstract

Purpose: The goal of this clinical focus article was to explore the utility of a mathematical prediction model (Bayes' theorem) in dysphagia management. Conclusions: Bayes' theorem shows promise as a means of incorporating evidence-based care into individual patient consultations by predicting both the risk of pneumonia and the impact of speech-language pathology and care team interventions on that risk. However, more research is needed on risk factors for pneumonia and the prevalence of pneumonia before the model can be accurately applied to clinical decision-making for patients with dysphagia. Supplemental Material: https://doi.org/10.23641/asha.19393802

Speech-language pathologists’ experience with nursing initiated texture modified diets in health care settings

“…Dysphagia, particularly in older adults, is associated with disability, malnutrition, dehydration, pneumonia, institutionalization, hospital length of stay and cost, and mortality (Alagiakrishnan et al, 2013;Makhnevich et al, 2022;Namasivayam-Macdonald et al, 2019;O'Keeffe et al, 2023;Paranji et al, 2016;Thiyagalingam et al, 2021). A widely used, even most widely used by some accounts, compensatory measure for dysphagia is texture-modified diet [TMD] (Benson & Barnes, 2022;Ciucci et al, 2016;Logemann et al, 2008;McCurtin et al, 2020;O'Keeffe, 2018;O'Keeffe et al, 2023;Streicher et al, 2018;Thiyagalingam et al, 2021). In long-term care, estimates of residents on TMDs range from 30% to 47% (Keller et al, 2012;Namasivayam-Macdonald et al, 2019;Vucea et al, 2019), with some concerns about the overprescription of this intervention (e.g., Groher & McKaig, 1995;Logemann et al, 2008;Milte et al, 2017).…”