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Factors relating to patient visit time with a physician

机译:与医生就诊时间有关的因素

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摘要

This study sought to identify factors that increase or decrease patient time with a physician, determine which combinations of factors are associated with the shortest and longest visits to physicians, quantify how much physicians contribute to variation in the time they spend with patients, and assess how well patient time with a physician can be predicted. Data were acquired from a modified replication of the 1997-1998 National Ambulatory Medical Care Survey, administered by the Kentucky Ambulatory Network to 56 primary care clinicians at 24 practice sites in 2001 and 2002. A regression tree and a linear mixed model (LMM) were used to discover multivariate associations between patient time with a physician and 22 potentially predictive factors. Patient time with a physician was related to the number of diagnoses, whether non-illness care was received, and whether the patient had been seen before by the physician or someone at the practice. Approximately 38% of the variation in patient time with a physician was accounted for by predictive factors in the tree; roughly 33% was explained by predictive factors in the LMM, with another 12% linked to physicians. Knowledge of patient characteristics and needs could be used to schedule office visits, potentially improving patient flow through a clinic and reducing waiting times.
机译:这项研究试图确定增加或减少与医生见面的时间的因素,确定哪些因素组合与最短和最长的就诊时间相关,量化医生对与患者相处时间变化的贡献程度,以及如何评估可以预计到医生的病人时间。数据来自修改后的1997-1998年国家门诊医疗调查,该调查是由肯塔基州门诊网络在2001年和2002年对24个诊所的56位初级保健临床医生进行管理的。回归树和线性混合模型(LMM)是用于发现医生的患者时间与22种潜在预测因素之间的多元关联。患者在医师处的时间与诊断次数,是否接受非疾病护理以及患者是否曾被医师或执业医师看过有关。树中的预测因素解释了约38%的医生时间变化。 LMM中的预测因素解释了大约33%,另外12%与医生有关。有关患者特征和需求的知识可用于安排上门诊治时间,从而有可能改善通过诊所的患者流量并减少等待时间。

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