Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands.
Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA.
Med Decis Making. 2024 Apr;44(3):346-356. doi: 10.1177/0272989X241231721. Epub 2024 Mar 4.
The occurrence of shared decision making (SDM) in daily practice remains limited. Various patient characteristics have been suggested to potentially influence the extent to which clinicians involve patients in SDM.
To assess associations between patient characteristics and the extent to which clinicians involve patients in SDM.
We conducted a secondary analysis of data pooled from 10 studies comparing the care of adult patients with (intervention) or without (control) a within-encounter SDM conversation tool. We included studies with audio(-visual) recordings of clinical encounters in which decisions about starting or reconsidering treatment were discussed.
In the original studies, the Observing Patient Involvement in Decision Making 12-items (OPTION) scale was used to code the extent to which clinicians involved patients in SDM in clinical encounters. We conducted multivariable analyses with patient characteristics (age, gender, race, education, marital status, number of daily medications, general health status, health literacy) as independent variables and OPTION as a dependent variable.
We included data from 1,614 patients. The between-arm difference in OPTION scores was 7.7 of 100 points ( < 0.001). We found no association between any patient characteristics and the OPTION score except for education level ( = 0.030), an association that was very small (2.8 points between the least and most educated), contributed mostly by, and only significant in, control arms (6.5 points). Subanalyses of a stroke prevention trial showed a positive association between age and OPTION score ( = 0.033).
Most characteristics showed no association with the extent to which clinicians involved patients in SDM. Without an SDM conversation tool, clinicians devoted more efforts to involve patients with higher education, a difference not observed when the tool was used.
Most sociodemographic patient characteristics show no association with the extent to which clinicians involve patients in shared decision making.Clinicians devoted less effort to involve patients with lower education, a difference that was not observed when a shared decision-making conversation tool was used.SDM conversation tools can be useful for clinicians to better involve patients and ensure patients get involved equally regardless of educational background.
共享决策(SDM)在日常实践中的发生仍然有限。各种患者特征被认为可能影响临床医生在多大程度上让患者参与 SDM。
评估患者特征与临床医生在多大程度上让患者参与 SDM 之间的关联。
我们对 10 项比较成年患者接受(干预)或不接受(对照)一次就诊中 SDM 对话工具的护理的研究进行了二次分析。我们纳入了对启动或重新考虑治疗的决策进行讨论的临床就诊的音频(视频)记录的研究。
在原始研究中,使用观察患者参与决策 12 项量表(OPTION)来编码临床就诊中临床医生让患者参与 SDM 的程度。我们对患者特征(年龄、性别、种族、教育程度、婚姻状况、每日服用药物数量、总体健康状况、健康素养)作为自变量和 OPTION 作为因变量进行多变量分析。
我们纳入了 1614 名患者的数据。OPTION 评分的组间差异为 100 分中的 7.7 分(<0.001)。我们发现除了教育程度(=0.030)外,没有任何患者特征与 OPTION 评分相关,这种关联非常小(最受教育和最不受教育的患者之间相差 2.8 分),主要是由对照组(相差 6.5 分)贡献的,并且仅在对照组中具有统计学意义。一项预防中风的试验的亚组分析显示,年龄与 OPTION 评分呈正相关(=0.033)。
大多数特征与临床医生让患者参与 SDM 的程度没有关联。没有 SDM 对话工具时,临床医生更努力地让受教育程度较高的患者参与进来,而在使用工具时则没有观察到这种差异。
大多数社会人口学患者特征与临床医生让患者参与共享决策的程度没有关联。临床医生较少努力让受教育程度较低的患者参与进来,而当使用共享决策对话工具时,这种差异就不会被观察到。SDM 对话工具可帮助临床医生更好地让患者参与,并确保患者平等参与,而不受教育背景的影响。