LIUC Business School, LIUC- University Cattaneo, Healthcare Datascience LAB, Corso Matteotti 22, 21053, Castellanza, Varese, Italy.
ASST Ovest Milanese Hospital, Legnano, Milano, Italy.
Sci Rep. 2023 Apr 4;13(1):5544. doi: 10.1038/s41598-023-32844-6.
The study aims at defining the factors affecting the clinicians' decision of changing or confirming the treatment options for frail patients in polytherapy, supporting prescribing patterns, thus also figuring out if the inclination of the clinicians towards digital solutions (INTERCheckWEB) and specific guidelines, could play a role in their decision. A literature review was performed, revealing the main individual, organizational and decisional factors, impacting on the clinicians' propensity to change the current patients' therapy: the clinician perceptions of support in case of clinical guidelines use or INTERCheckWEB use were studied. A qualitative approach was implemented, and thirty-five clinicians completed a questionnaire, aimed at evaluating fifteen different clinical cases, defining if they would change the patient's current therapy depending on the level of information received. Three methodological approaches were implemented. (1) Bivariate correlations to test the relationships between variables. (2) Hierarchical sequential linear regression model to define the predictors of the clinician propensity to change therapy. (3) Fuzzy Qualitative Comparative Analysis-fsQCA, to figure out the combination of variables leading to the outcome. Patient's age and autonomy (p value = 0.000), as well as clinician's perception regarding IT ease of use (p value = 0.043) and seniority (p value = 0.009), number of drugs assumed by the patients (p value = 0.000) and number of concomitant diseases (p value = 0.000) are factors influencing a potential change in the current therapy. The fsQCA-crisp confirms that the clinical conditions of the patients are the driving factors that prompt the clinicians towards a therapy change.
本研究旨在确定影响多疗法中临床医生改变或确认虚弱患者治疗方案的因素，支持处方模式，从而确定临床医生对数字解决方案（INTERCheckWEB）和特定指南的倾向是否会影响他们的决策。进行了文献回顾，揭示了影响临床医生改变当前患者治疗方案倾向的主要个体、组织和决策因素：研究了临床医生对使用临床指南或 INTERCheckWEB 时获得支持的看法。实施了定性方法，35 名临床医生完成了一份问卷，旨在评估 15 个不同的临床病例，根据收到的信息水平确定是否会改变患者的当前治疗方案。实施了三种方法学方法。（1）双变量相关性分析以检验变量之间的关系。（2）分层序贯线性回归模型以确定临床医生改变治疗方案倾向的预测因素。（3）模糊定性比较分析-fsQCA，以确定导致结果的变量组合。患者年龄和自主性（p 值=0.000），以及临床医生对 IT 易用性的看法（p 值=0.043）和经验（p 值=0.009）、患者服用的药物数量（p 值=0.000）和同时存在的疾病数量（p 值=0.000）是影响当前治疗方案潜在变化的因素。fsQCA 清晰地证实了患者的临床状况是促使临床医生改变治疗方案的驱动因素。
