DuGoff Eva H, Bandeen-Roche Karen, Anderson Gerard F
Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
J Comorb. 2016 Jun 3;6(2):65-72. doi: 10.15256/joc.2016.6.76. eCollection 2016.
Continuity of care is a basic tenant of primary care practice. However, the evidence on the importance of continuity of care for older adults with complex conditions is mixed.
To assess the relationship between measurement of continuity of care, number of chronic conditions, and health outcomes.
We analyzed data from a cohort of 1,600 US older adults with diabetes and ≥1 other chronic condition in a private Medicare health plan from July 2010 to December 2011. Multivariate regression models were used to examine the association of baseline continuity (the first 6 months) and the composite outcome of any emergency room use or inpatient hospitalization occurring in the following 12-month period.
After adjusting for baseline covariates, high known provider continuity (KPC) was associated with an 84% (adjusted odds ratio 0.16; 95% confidence interval 0.09-0.26) reduction in the risk of the composite outcome. High KPC was significantly associated with a lower risk of the composite outcome among individuals with ≥6 conditions. However, the usual provider of care and continuity of care indices were not significantly related with the composite outcome in the overall sample or in those with ≥6 conditions.
The relationship between continuity of care and adverse outcomes depends on the measure of continuity of care employed. High morbidity patients are more likely to benefit from continuity of care interventions as measured by the KPC, which measures the proportion of a patient's visits that are with the same providers over time.
连续性医疗是初级医疗实践的一项基本原则。然而,关于连续性医疗对患有复杂疾病的老年人的重要性的证据并不一致。
评估连续性医疗的测量、慢性病数量与健康结局之间的关系。
我们分析了2010年7月至2011年12月期间参加私人医疗保险健康计划的1600名患有糖尿病且患有≥1种其他慢性病的美国老年人队列的数据。使用多变量回归模型来检验基线连续性(前6个月)与接下来12个月内发生的任何急诊室就诊或住院治疗的综合结局之间的关联。
在对基线协变量进行调整后,高已知提供者连续性(KPC)与综合结局风险降低84%(调整后的优势比为0.16;95%置信区间为0.09 - 0.26)相关。在患有≥6种疾病的个体中,高KPC与综合结局风险较低显著相关。然而,在总体样本或患有≥6种疾病的个体中,常规护理提供者和连续性护理指数与综合结局没有显著相关性。
连续性医疗与不良结局之间的关系取决于所采用的连续性医疗测量方法。高发病率患者更有可能从以KPC衡量的连续性医疗干预中受益,KPC衡量的是患者随时间与同一提供者就诊的比例。