Mid-Atlantic Permanente Research Institute (MAPRI), 2101 East Jefferson Street, Rockville, MD, 20852, USA.
PGY1 Pharmacy Resident, Memorial Hermann Southwest Hospital, Houston, TX, 77074, USA.
Res Social Adm Pharm. 2021 Jul;17(7):1267-1275. doi: 10.1016/j.sapharm.2020.09.010. Epub 2020 Sep 20.
Osteoporosis medication use is suboptimal. Simple interventions personalized to a patients' stage of readiness are needed to encourage osteoporosis medication use.
To estimate interrelationships of sociodemographic factors, perceived fracture risk, health literacy, receipt of medication information, medication trust and readiness to use osteoporosis medication; and apply observed relationships to inform design specifications for a clinical decision support application that can be used for personalized patient counseling.
Data from a national sample of older women (n = 1759) with self-reported history of fractures and no current use of osteoporosis medication treatment were used to estimate an acceptable path model that describes associations among key sociodemographic characteristics, health literacy, perceived fracture risk, receipt of osteoporosis medication information within the past year, trust in osteoporosis medications, and readiness to use osteoporosis medication. Path model results were used to inform an application for personalized patient counseling that can be easily integrated into clinical decision support systems.
Increased age (β = 0.13), trust for medications (β = 0.12), higher perceived fracture risk (β = 0.21), and having received medication information within the past year (β = 0.21) were all positively associated with readiness to use osteoporosis medication (p < 0.0001). Whereas, health literacy (β = -0.09) was inversely associated with readiness to use osteoporosis medication (p < 0.0001). Using these results, a brief 6-item question set was constructed for simple integration into clinical decision support applications. Patient responses were used to inform a provider dashboard that integrates a patient's stage of readiness for osteoporosis medication use, predictors of readiness, and personalized counseling points appropriate to their stage of readiness.
Content of counseling strategies must be aligned with a patient's stage of readiness to use treatment. Path modeling can be effectively used to identify factors for inclusion in an evidenced-based clinical decision support application designed to assist providers with personalized patient counseling and osteoporosis medication use decisions.
骨质疏松症药物的使用并不理想。需要针对患者的准备阶段进行简单的干预，以鼓励使用骨质疏松症药物。
评估社会人口统计学因素、感知骨折风险、健康素养、药物信息的获取、药物信任和使用骨质疏松症药物的准备情况之间的相互关系；并将观察到的关系应用于为临床决策支持应用程序提供信息，该应用程序可用于个性化患者咨询。
使用来自有骨折史且目前未使用骨质疏松症药物治疗的老年女性（n=1759）的全国性样本数据，估计一个可接受的路径模型，该模型描述了关键社会人口统计学特征、健康素养、感知骨折风险、过去一年内骨质疏松症药物信息的获取、对骨质疏松症药物的信任与使用骨质疏松症药物的准备情况之间的关联。路径模型结果用于为个性化患者咨询提供信息，该咨询可轻松集成到临床决策支持系统中。
年龄增加（β=0.13）、对药物的信任（β=0.12）、感知骨折风险增加（β=0.21）和过去一年内获得药物信息（β=0.21）与使用骨质疏松症药物的准备情况呈正相关（p<0.0001）。而健康素养（β=-0.09）与使用骨质疏松症药物的准备情况呈负相关（p<0.0001）。利用这些结果，构建了一个简短的 6 项问题集，以便简单地集成到临床决策支持应用程序中。患者的回答用于为提供者仪表板提供信息，该仪表板集成了患者使用骨质疏松症药物的准备情况、准备情况的预测因素以及与他们的准备情况相对应的个性化咨询要点。
咨询策略的内容必须与患者使用治疗的准备阶段相匹配。路径建模可有效地用于确定纳入基于证据的临床决策支持应用程序的因素，该应用程序旨在帮助提供者进行个性化患者咨询和骨质疏松症药物使用决策。
