A High-Resolution Analysis of Process Improvement: Use of Quantile Regression for Wait Time
Article first published online: 20 JUN 2012
© Health Research and Educational Trust
Health Services Research
Volume 48, Issue 1, pages 333–347, February 2013
How to Cite
Choi, D., Hoffman, K. A., Kim, M.-O. and McCarty, D. (2013), A High-Resolution Analysis of Process Improvement: Use of Quantile Regression for Wait Time. Health Services Research, 48: 333–347. doi: 10.1111/j.1475-6773.2012.01436.x
- Issue published online: 7 JAN 2013
- Article first published online: 20 JUN 2012
- National Institute on Drug Abuse. Grant Numbers: R01 DA018282, R01 DA020832, R03 DA027946
- National Cancer Institute. Grant Number: R03 CA133944
- Wait time;
- process improvement;
- quantile regression;
- Network for the Improvement of Addiction Treatment (NIATx)
Apply quantile regression for a high-resolution analysis of changes in wait time to treatment and assess its applicability to quality improvement data compared with least-squares regression.
Addiction treatment programs participating in the Network for the Improvement of Addiction Treatment.
We used quantile regression to estimate wait time changes at 5, 50, and 95 percent and compared the results with mean trends by least-squares regression.
Quantile regression analysis found statistically significant changes in the 5 and 95 percent quantiles of wait time that were not identified using least-squares regression.
Quantile regression enabled estimating changes specific to different percentiles of the wait time distribution. It provided a high-resolution analysis that was more sensitive to changes in quantiles of the wait time distributions.