Pediatric MSK Care Access & Equity

Although the readability of online materials has been thoroughly studied across different orthopaedic surgery disorders, inadequacy in information exists regarding the readability of the websites pertaining to femoroacetabular impingement (FAI). Given its high prevalence and the importance of providing appropriate online education materials in its prognosis, the primary aim of this study was to assess the readability of web-based patient education materials regarding this disease. “Femoroacetabular impingement,” “FAI,” and “hip impingement” were used as search queries in this study. Readability was evaluated based on five established algorithms, and the readability of contents was compared by website type and also search query. In this study of 59 unique websites on FAI, using five different validated readability formulas, we demonstrated that none of the top 30 webpages were written at the recommended reading level. They were found through three different search queries on the three most used search engines. Current FAI online education materials accessible to patients are written above the recommended levels, and it seems that to improve equity and accessibility in healthcare, universities, hospitals, and healthcare professional societies have a responsibility to ensure that the online materials are provided at more appropriate levels. Early detection and treatment of FAI play a key role in preventing the progression to hip osteoarthritis. Thus, providing appropriate online education materials is of great importance in this prevention by increasing patients' understanding of the disease and the advantages and disadvantages of the treatment options.

Proper codification of medical diagnoses and procedures is essential for optimized health care management, quality improvement, research, and reimbursement tasks within large healthcare systems. Assignment of diagnostic or procedure codes is a tedious manual process, often prone to human error. Natural Language Processing (NLP) have been suggested to facilitate these manual codification process. Yet, little is known on best practices to utilize NLP for such applications. Here we comprehensively assessed the performance of common NLP techniques to predict current procedural terminology (CPT) from operative notes. CPT codes are commonly used to track surgical procedures and interventions and are the primary means for reimbursement. The direct links between operative notes and CPT codes makes them a perfect vehicle to test the feasibility and performance of NLP for clinical codification. Our analysis of 100 most common musculoskeletal CPT codes suggest that traditional approaches (i.e., TF-IDF) can outperform resource intensive approaches like BERT, in addition to providing interpretability which can be very helpful and even crucial in the clinical domain. We also proposed a complexity measure to quantify the complexity of a classification task and how this measure could influence the effect of dataset size on model’s performance. Finally, we provide preliminary evidence that NLP can help minimize the codification error, including mislabeling due to human error.

The legalizations of medical and recreational cannabis have generated a great deal of interest in studying the health impacts of cannabis products. Despite increases in cannabis use, its documentation during clinical visits is not yet mainstream. This lack of information hampers efforts to study cannabis effects on health outcomes. A clear and in-depth understanding of current trends in cannabis use documentation is necessary to develop proper guidelines to screen and document cannabis use. Here we have developed and used a hierarchical natural language processing pipeline (AUROC=0.94) to evaluate the trends and disparities in cannabis documentation on more than 23 million notes from a large cohort of 370,087 patients seen in a high-volume multi-site pediatric and young adult clinic over a period of 21 years. Our findings show a very low but growing rate of cannabis use documentation (<2%) in electronic health records with significant demographic and socioeconomic disparities in both documentation and use, which requires further attention.

Given the long-term complications of undiagnosed slipped capital femoral epiphysis (SCFE) and the importance of readable health information materials on positive, equitable health outcomes, the objective of this study was to determine if the online patient education materials regarding SCFE are written at or below accepted recommendations. The secondary objective was to determine whether the readability of these materials varied when stratified by the type of website. 'Slipped capital femoral epiphysis', 'SCFE', and 'slipped femoral head' were used as search queries in three common search engines. The readability of each website was evaluated using five established metrics, and the scores were compared by website type and by the complexity of the search query. In this study of 53 unique websites about SCFE, we demonstrated that only one of the web pages was written at the recommended sixth-grade level, and the mean reading level of the online material was above the 10th-grade level. Post hoc testing showed that only websites associated with pediatric academic institutions were written at a significantly lower grade level than general health websites [P < 0.05 for all, range (0.003, 0.04)]. The materials about SCFE that are available to patients and their families continue to be written at an inappropriate level. To increase accessibility and allow for equitable long-term health outcomes, physicians, universities, hospitals and medical societies must ensure that they produce readable education to increase patients' understanding of SCFE, its symptoms and available treatment options. Future studies evaluating progress regarding these metrics are warranted.