Nicolet Anna, Peytremann-Bridevaux Isabelle, Wagner Joël, Perraudin Clémence, Bagnoud Christophe, Marti Joachim
Center for Primary Care and Public Health (Unisanté), Lausanne, Switzerland.
University of Lausanne, Lausanne, Vaud, Switzerland.
Integr Healthc J. 2022 Mar 24;4(1):e000105. doi: 10.1136/ihj-2021-000105. eCollection 2022.
Continuity of care (COC) should be measured for healthcare quality monitoring and evaluation and is a key process indicator for integrated care. Measurement of COC using routinely collected data is widespread, but there is no consensus on which indicator to use and the relevant time horizon to apply. Information about COC is especially warranted in highly fragmented healthcare systems, such as in Switzerland. Our study aimed to compare COC measures in Swiss residents aged 50+ obtained with various indices and time horizons.
Using insurance claims data, we computed and compared several commonly used visit-based Continuity of Care Indices (COCIs): Bice-Boxerman Index, Usual Provider of Care, Herfindahl-Hirschman Index, Modified, Modified Continuity Index and Modified Continuity Index, based on all doctor visits and on primary care (PC) visits only. Indices were computed over short (1 year) and medium (4 years) terms.
The mean indices based on all visits varied between 0.51 and 0.77, while PC indices presented less variation with a median of 1.00 for all but one index. Indices focusing on a variety of individual providers decreased with time horizon, while indices focusing on the overall number of visits and providers showed the opposite trend. These findings suggest fundamental differences in the interpretation of COCIs.
Broad COC appeared moderately low in Switzerland, although comparable to other countries, and PC COC was close to one. The choice of indices and time horizon influenced their interpretation. Understanding these differences is key to select the appropriate index for the monitoring of COC.
为进行医疗质量监测与评估,应衡量医疗连续性(COC),它是综合医疗的关键过程指标。利用常规收集的数据来衡量COC十分普遍,但对于使用何种指标以及适用的相关时间范围尚无共识。在高度分散的医疗体系中,如瑞士,尤其需要有关COC的信息。我们的研究旨在比较使用各种指数和时间范围得出的瑞士50岁及以上居民的COC指标。
利用保险理赔数据,我们计算并比较了几种常用的基于就诊次数的医疗连续性指数(COCIs):比塞-博克斯曼指数、常规医疗服务提供者指数、赫芬达尔-赫希曼指数、修正版、修正连续性指数以及仅基于所有医生就诊和初级保健(PC)就诊的修正连续性指数。指数在短期(1年)和中期(4年)内进行计算。
基于所有就诊次数的平均指数在0.51至0.77之间变化,而PC指数的变化较小,除一个指数外,其他指数的中位数均为1.00。关注各类个体医疗服务提供者的指数随时间范围的增加而下降,而关注就诊次数和医疗服务提供者总数的指数则呈现相反趋势。这些发现表明在对COCIs的解释上存在根本差异。
在瑞士,广义的COC似乎处于中等偏低水平,尽管与其他国家相当,且PC COC接近1。指数和时间范围的选择会影响对它们的解释。理解这些差异是选择合适的指数来监测COC的关键。