Evaluating an Intervention to Lower Health Literacy Demand of Graduate Student Clinician Summary Cover Letters to Patients

The American Speech-Language-Hearing Association encourages university programs to cultivate skills related to client health literacy among students. One means of doing so is to train students to write in a way that places lower health literacy demands on clients and their families. This study tested the effectiveness of a health literacy module for improving students’ skills in writing client letters to accompany diagnostic reports. Students in two sections of an advanced graduate seminar in Speech Pathology course were assigned to write cover letters to be sent to a hypothetical client at the UCF Communication Disorders Clinic. Reading grade level calculators of the pretest indicated students wrote at a college level, and the Patient Education Materials Assessment Tool (PEMAT) revealed that students performed worst on literacy elements which are not regularly associated with letter writing, but which can dramatically assist with readability and comprehension: breaking information into chunks, using informative headers, and using visual cues like bullet points, bolding, and font size. Fewer than half of students regularly used plain language and active voice. After completing the module, grade level of student writing had lowered to high school, but no statistically significant differences were found in use of specific literacy elements

Source Characteristics Influence AI-Enabled Orthopaedic Text Simplification: Recommendations for the Future.

BACKGROUND: This study assesses the effectiveness of large language models (LLMs) in simplifying complex language within orthopaedic patient education materials (PEMs) and identifies predictive factors for successful text transformation. METHODS: We transformed 48 orthopaedic PEMs using GPT-4, GPT-3.5, Claude 2, and Llama 2. The readability, quantified by the Flesch-Kincaid Reading Ease (FKRE) and Flesch-Kincaid Grade Level (FKGL) scores, was measured before and after transformation. Analysis included text characteristics such as syllable count, word length, and sentence length. Statistical and machine learning methods evaluated the correlations and predictive capacity of these features for transformation success. RESULTS: All LLMs improved FKRE and FKGL scores (p < 0.01). GPT-4 showed superior performance, transforming PEMs to a seventh-grade reading level (mean FKGL, 6.72 ± 0.99), with higher FKRE and lower FKGL than other models. GPT-3.5, Claude 2, and Llama 2 significantly shortened sentences and overall text length (p < 0.01). Importantly, correlation analysis revealed that transformation success varied substantially with the model used, depending on original text factors such as word length and sentence complexity. CONCLUSIONS: LLMs successfully simplify orthopaedic PEMs, with GPT-4 leading in readability improvement. This study highlights the importance of initial text characteristics in determining the effectiveness of LLM transformations, offering insights for optimizing orthopaedic health literacy initiatives using artificial intelligence (AI). CLINICAL RELEVANCE: This study provides critical insights into the ability of LLMs to simplify complex orthopaedic PEMs, enhancing their readability without compromising informational integrity. By identifying predictive factors for successful text transformation, this research supports the application of AI in improving health literacy, potentially leading to better patient comprehension and outcomes in orthopaedic care

Leveraging GPT-4 enables patient comprehension of radiology reports

Objective: To assess the feasibility of using GPT-4 to simplify radiology reports into B1-level Dutch for enhanced patient comprehension. Methods: This study utilised GPT-4, optimised through prompt engineering in Microsoft Azure. The researchers iteratively refined prompts to ensure accurate and comprehensive translations of radiology reports. Two radiologists assessed the simplified outputs for accuracy, completeness, and patient suitability. A third radiologist independently validated the final versions. Twelve colorectal cancer patients were recruited from two hospitals in the Netherlands. Semi-structured interviews were conducted to evaluate patients’ comprehension and satisfaction with AI-generated reports. Results: The optimised GPT-4 tool produced simplified reports with high accuracy (mean score 3.33/4). Patient comprehension improved significantly from 2.00 (original reports) to 3.28 (simplified reports) and 3.50 (summaries). Correct classification of report outcomes increased from 63.9% to 83.3%. Patient satisfaction was high (mean 8.30/10), with most preferring the long simplified report. Conclusion: RADiANT successfully enhances patient understanding and satisfaction through automated AI-driven report simplification, offering a scalable solution for patient-centred communication in clinical practice. This tool reduces clinician workload and supports informed patient decision-making, demonstrating the potential of LLMs beyond English-based healthcare contexts.</p

The Relationship between Health Literacy and COVID-19 Vaccination Prevalence during a Rapidly Evolving Pandemic and Infodemic

The gap between how health information is communicated and what people understand and can use to make informed health decisions is called health literacy. This gap was exacerbated by the rapidly changing and excessive volume of information, misinformation, and disinformation during the COVID-19 pandemic. People with lower health literacy may not have understood the importance of COVID-19 vaccination for themselves or for their communities. Our aim was to understand health literacy levels within Fulton County, Georgia, and their relationship to vaccine prevalence. Fulton county residents ages 18 and over (n = 425) completed an on-line Health Literacy Questionnaire. Individual, organizational, functional, interactive, and critical health literacy scales were created. Vaccination prevalence data were collected from the Georgia Vaccine Distribution Dashboard. All data were divided into one of three county areas. There were statistically significant variations in vaccine prevalence χ2(3) = 29.325, p \u3c 0.001 among the three county areas. All levels of health literacy predicted overall county vaccination prevalence F (4,420) = 85.941, p \u3c 0.001, There were significant differences in health literacy levels among two of the three county area pairs; the lowest resourced county area had the lowest vaccination prevalence and health literacy rates. This is the first example of relating direct health literacy measures across a major metropolitan US county with vaccine prevalence data

Text readability: its impact on reading comprehension and reading time

Recently, the readability of texts has become the focus of reading research because it is believed to have implications for reading comprehension, which is of utmost importance in the field of English as a foreign language (EFL), particularly in the teaching, learning and assessment of reading comprehension. Unfortunately, the influence of text readability on reading comprehension (and reading time) has not been well studied in the EFL context. Most text readability studies are conducted in medical contexts, but these studies are often limited in predicting readability scores for sample texts. To address this gap, the current study aimed to evaluate the influence of text readability levels (based on the Flesch-Kincaid grade level (FKGL)) on students’ reading comprehension and reading time. Data were collected through reading test and analyzed using SPSS version 22. The Friedman test revealed that the distribution of students' reading comprehension score (X2=197.532, p=0.000) and reading time (X2=215.323, p=0.000) are different in each text, suggesting that the readability of texts has a significant influence on both. This study contributed to the practices of reading instruction and assessment. Limitations and suggestions for further research are briefly discussed

Emergency Room Nurses Knowledge of and Experience with Health Literacy and their Patient Teaching Methods

Health literacy (HL) is the ability one has to understand health information and navigate within the health system. Health literacy is linked to health knowledge and acute and chronic health outcomes. The conceptual model of health literacy outlines the contextual factors related to individual health literacy throughout the health system and the mitigating influence on outcomes. Education is a key factor to health knowledge and behavior changes. Nurses are the primary educators for providing patient teaching and yet research indicates nurses are lacking in knowledge regarding this. One area in the health system where health literacy has a strong effect on patient outcomes is the emergency department (ED). Identifying the association between emergency department nurses knowledge of, and experience with health literacy, and their use of patient education strategies is important for future patient outcomes. This descriptive, exploratory, correlational study examined the HL knowledge, experience and most frequently used teaching methods of ED nurses as well as relationships between and among emergency department nurses’ health literacy knowledge, health literacy experience and their patient teaching methods. Results of this study indicated that ED nurse participants knew less basic facts about HL than about evaluating HL interventions and the consequences associated with low HL. Overall the participants answered 62% of the knowledge questions correctly. There were correlations found between HL knowledge and age, years as a licensed registered nurse (RN) and years worked in the ED with the strongest predictor of HL knowledge being nurses level of education (β = .21, p = .012). A number of ED nurses (49.8%) indicated they never participated in HL strategies such as HL screening, evaluating reading level of written materials or illustrations and very few (4.6%) indicated they always participate. The participants indicated the most frequently used teaching methods in the ED were providing written materials, avoiding medical jargon and encouraging questions. Further research is needed to explore methods to increase health literacy knowledge of ED nurses and strategies to facilitate experiences with health literacy in the ED. Communication is an important component of the relationship between nurses and low health literate patients in the ED. Methods to enhance communication and facilitate patient understanding and retention of patient teaching should also be explored

Methods to Facilitate the Capture, Use, and Reuse of Structured and Unstructured Clinical Data.

Electronic health records (EHRs) have great potential to improve quality of care and to support clinical and translational research. While EHRs are being increasingly implemented in U.S. hospitals and clinics, their anticipated benefits have been largely unachieved or underachieved. Among many factors, tedious documentation requirements and the lack of effective information retrieval tools to access and reuse data are two key reasons accounting for this deficiency. In this dissertation, I describe my research on developing novel methods to facilitate the capture, use, and reuse of both structured and unstructured clinical data. Specifically, I develop a framework to investigate potential issues in this research topic, with a focus on three significant challenges. The first challenge is structured data entry (SDE), which can be facilitated by four effective strategies based on my systematic review. I further propose a multi-strategy model to guide the development of future SDE applications. In the follow-up study, I focus on workflow integration and evaluate the feasibility of using EHR audit trail logs for clinical workflow analysis. The second challenge is the use of clinical narratives, which can be supported by my innovative information retrieval (IR) technique called “semantically-based query recommendation (SBQR)”. My user experiment shows that SBQR can help improve the perceived performance of a medical IR system, and may work better on search tasks with average difficulty. The third challenge involves reusing EHR data as a reference standard to benchmark the quality of other health-related information. My study assesses the readability of trial descriptions on ClinicalTrials.gov and found that trial descriptions are very hard to read, even harder than clinical notes. My dissertation has several contributions. First, it conducts pioneer studies with innovative methods to improve the capture, use, and reuse of clinical data. Second, my dissertation provides successful examples for investigators who would like to conduct interdisciplinary research in the field of health informatics. Third, the framework of my research can be a great tool to generate future research agenda in clinical documentation and EHRs. I will continue exploring innovative and effective methods to maximize the value of EHRs.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135845/1/tzuyu_1.pd