VA Boston Healthcare System, Boston, MA.
Boston University School of Medicine, Boston, MA.
Med Care. 2023 Jun 1;61(6):392-399. doi: 10.1097/MLR.0000000000001849. Epub 2023 Apr 17.
Identifying whether differences in health care disparities are due to within-facility or between-facility differences is key to disparity reductions. The Kitagawa decomposition divides the difference between 2 means into within-facility differences and between-facility differences that are measured on the same scale as the original disparity. It also enables the identification of facilities that contribute most to within-facility differences (based on facility-level disparities and the proportion of patient population served) and between-facility differences.
Illustrate the value of a 2-stage Kitagawa decomposition to partition a disparity into within-facility and between-facility differences and to measure the contribution of individual facilities to each type of difference.
Veterans receiving a new outpatient consult for cardiology or orthopedic services during fiscal years 2019-2021.
Wait time for a new-patient consult.
In stage 1, we predicted wait time for each Veteran from a multivariable model; in stage 2, we aggregated individual predictions to determine mean adjusted wait times for Hispanic, Black, and White Veterans and then decomposed differences in wait times between White Veterans and each of the other groups.
Noticeably longer wait times were experienced by Hispanic Veterans for cardiology (2.32 d, 6.8% longer) and Black Veterans for orthopedics (3.49 d, 10.3% longer) in both cases due entirely to within-facility differences. The results for Hispanic Veterans using orthopedics illustrate how positive within-facility differences (0.57 d) can be offset by negative between-facility differences (-0.34 d), resulting in a smaller overall disparity (0.23 d). Selecting 10 facilities for interventions in orthopedics based on the largest contributions to within-in facility differences instead of the largest disparities resulted in a higher percentage of Veterans impacted (31% and 12% of Black and White Veterans, respectively, versus 9% and 10% of Black and White Veterans, respectively) and explained 21% of the overall within-facility difference versus 11%.
The Kitagawa approach allows the identification of disparities that might otherwise be undetected. It also allows the targeting of interventions at those facilities where improvements will have the largest impact on the overall disparity.
确定医疗保健差距的差异是由于设施内还是设施之间的差异对于减少差距至关重要。Kitagawa 分解将两个均值之间的差异分为设施内差异和设施间差异，这些差异以与原始差距相同的规模进行测量。它还能够确定对设施内差异（基于设施层面的差异和服务的患者人群比例）和设施间差异贡献最大的设施。
说明两阶段 Kitagawa 分解的价值，即将差距分解为设施内和设施间差异，并衡量各个设施对每种差异的贡献。
在 2019-2021 财年期间接受心脏病学或骨科新门诊咨询的退伍军人。
新患者咨询的等待时间。
在第一阶段，我们从多变量模型中预测每位退伍军人的等待时间；在第二阶段，我们汇总个体预测值，以确定西班牙裔、非裔和白人退伍军人的平均调整等待时间，然后分解白人退伍军人与其他组之间的等待时间差异。
西班牙裔退伍军人在心脏病学方面的等待时间明显较长（2.32 天，长 6.8%），而非裔退伍军人在骨科方面的等待时间更长（3.49 天，长 10.3%），这两种情况完全是由于设施内的差异造成的。西班牙裔退伍军人使用骨科的结果说明了积极的设施内差异（0.57 天）如何被消极的设施间差异（-0.34 天）抵消，从而导致整体差距更小（0.23 天）。选择 10 家设施进行骨科干预，而不是根据最大差距选择设施，这样可以影响更多的退伍军人（分别有 31%和 12%的非裔和白人退伍军人，而分别有 9%和 10%的非裔和白人退伍军人），并解释了整体设施内差异的 21%，而不是 11%。
Kitagawa 方法可以识别否则可能无法检测到的差距。它还可以针对那些改进将对整体差距产生最大影响的设施进行干预。
