Journal of evaluation in clinical practice
-
Limited health literacy (HL) leads to poor health outcomes, psychological stress, and misutilization of medical resources. Although interventions aimed at improving HL may be effective, identifying patients at risk of limited HL in the clinical workflow is challenging. With machine learning (ML) algorithms based on readily available data, healthcare professionals would be enabled to incorporate HL screening without the need for administering in-person HL screening tools. ⋯ Elastic-Net Penalized Logistic Regression had the best performance when compared with other ML algorithms with a c-statistic of 0.766, calibration slope/intercept of 1.044/-0.037, and a Brier score of 0.179. Over one-third of patients presenting to an outpatient spine center were found to have limited HL. While this algorithm is far from being used in clinical practice, ML algorithms offer a potential opportunity for identifying patients at risk for limited HL without administering in-person HL assessments. This could possibly enable screening and early intervention to mitigate the potential negative consequences of limited HL without taxing the existing clinical workflow.
-
Clinical practice guidelines (CPGs) are moving toward greater consideration of population-level differences, like health inequities, when creating management recommendations. CPGs have the potential to reduce or perpetuate health inequities. The intrinsic design factors of electronic interfaces that contain CPGs are known barriers to guideline use. There is little existing guidance on supporting the uptake of equity-specific recommendations within CPGs by end users. ⋯ This research extends existing literature by showing that including equity information tailored to the articulated purpose of each CPG, as perceived by end users, may maximise uptake. Our outlined strategies could be used by CPG developers to make equity-focused management recommendations more accessible. This may increase the implementation of equity-focused recommendations by clinicians, supporting current primary care strategies in achieving more equitable outcomes.
-
Traditionally, health information has been created from the perspective of the providers with minimum patient consultation, hindering engagement and adherence. The rate of shoulder replacements has increased over the past decade, is associated with shorter hospital stays, and patients are relying on education to be able to participate in shared decision-making. Therefore, to ensure creation of accessible education programs for shoulder replacement procedures, we explored patient and clinician preferences regarding content and device choices for a preoperative shoulder replacement education program. ⋯ A multimodal program of a website with videos and a written booklet, that covers basic information regarding the surgery, timelines for recovery, sling use, use of therapeutic devices/aids post-surgery, patient expectations to improve surgery satisfaction, postoperative restrictions, pain management, rehabilitation and home supports is desired by both patients and clinicians.
-
Bariatric metabolic surgery has emerged as a pivotal intervention for managing obesity, with strict adherence to postoperative nutritional guidelines being paramount for patient outcomes. This study seeks to evaluate dietary compliance levels and the factors that influence them among patients who have undergone bariatric surgery, offering insights to enhance clinical strategies. ⋯ The high incidence of poor dietary compliance among patients following bariatric metabolic surgery is a significant concern and is notably influenced by demographic variables such as age, gender, education and economic status. It is imperative for healthcare professionals to consider these variables when developing personalised interventions aimed at improving dietary compliance within this patient group.