Use of path modeling to inform a clinical decision support application to encourage osteoporosis medication use.
Use of path modeling to inform a clinical decision support application to encourage osteoporosis medication use.
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DOI：
10.1016/j.sapharm.2020.09.010
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发表时间：
2021-07
影响因子：
3.9
通讯作者：
Saag, Kenneth G.
中科院分区：
文献类型：
--
作者：
Miller, Michael J.;Jou, Tzuchen;Danila, Maria, I;Mudano, Amy S.;Rahn, Elizabeth J.;Outman, Ryan C.;Saag, Kenneth G.
骨质疏松症药物使用不理想。需要针对患者准备阶段进行简单的个性化干预，以鼓励骨质疏松症药物的使用。估计社会人口因素、骨折风险感知、健康素养、药物信息接收、药物信任和骨质疏松药物使用准备的相互关系;并应用观察到的关系为可用于个性化患者咨询的临床决策支持应用程序的设计规范提供信息。全国老年妇女抽样数据（n = 1759），自我报告骨折史，目前未使用骨质疏松症药物治疗，用于估计可接受的路径模型，该模型描述了关键社会人口学特征，健康素养，感知骨折风险，过去一年内接受骨质疏松症药物信息，对骨质疏松症药物的信任，并准备好使用骨质疏松症药物。路径模型的结果被用来通知个性化的患者咨询，可以很容易地集成到临床决策支持系统的应用程序。年龄增加（β = 0.13）、对药物的信任（β = 0.12）、更高的骨折风险（β = 0.21）和在过去一年内接受过药物信息（β = 0.21）都与准备使用骨质疏松药物呈正相关（p <0.0001）。然而，健康素养（β =-0.09）与准备使用骨质疏松症药物呈负相关（p <0.0001）。使用这些结果，一个简短的6项问题集被构造成简单的集成到临床决策支持应用程序。患者的反应被用来通知提供者仪表板，该仪表板集成了患者对骨质疏松症药物使用的准备阶段、准备程度的预测因素以及适合于其准备阶段的个性化咨询点。咨询策略的内容必须与患者准备使用治疗的阶段相一致。路径建模可以有效地用于识别纳入循证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的患者咨询和骨质疏松症药物使用决策。
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.
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DOI：
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发表时间：
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影响因子：
3.9
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