Gruzd D C, Shear C L, Rodney W M
Fam Med. 1986 Jul-Aug;18(4):217-20.
A multitude of determinants have been identified as predictive of broken appointments. The majority of prior studies have been limited to univariate analysis of the relationship between predictors and appointment keeping behavior. The present report studied 25 independent predictors of no-show behavior using both univariate and multivariate analyses. A total of 579 kept appointments and 84 failed appointments were analyzed. Results of univariate analysis indicated the following significant relationships with appointment behavior: age, ethnicity, marital status, mode of payment, chronic illness, telephone in house, type of care, prior visits to center, cost of care, transportation to center, physician ethnicity, and linguistic capability. However, multiple logistic function analysis revealed only six significant associations: type of care, chronic illness, linguistic capability, mode of payment, physician-patient sex differences, and marital status of the patient. Multivariate analysis may yield a more accurate and clinically useful model of no-show behavior. For example, language barrier may be more of a problem than the race of the patient. Prospective studies might benefit from these considerations.
众多因素已被确定为预约失约的预测指标。大多数先前的研究仅限于对预测因素与预约遵守行为之间关系的单变量分析。本报告使用单变量和多变量分析研究了25个与爽约行为相关的独立预测因素。总共分析了579次守约预约和84次失约预约。单变量分析结果表明，以下因素与预约行为存在显著关系：年龄、种族、婚姻状况、支付方式、慢性病、家中是否有电话、护理类型、之前到中心就诊的次数、护理费用、前往中心的交通方式、医生的种族以及语言能力。然而，多元逻辑函数分析仅揭示了六个显著关联：护理类型、慢性病、语言能力、支付方式、医患性别差异以及患者的婚姻状况。多变量分析可能会产生一个更准确且临床上有用的爽约行为模型。例如，语言障碍可能比患者的种族问题更大。前瞻性研究可能会从这些考虑因素中受益。
