A high-resolution analysis of process improvement: use of quantile regression for wait time.

Abstract:

OBJECTIVE: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. DATA SOURCE:Addiction treatment programs participating in the Network for the Improvement of Addiction Treatment. METHODS: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. PRINCIPAL FINDINGS: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. CONCLUSIONS: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.

journal_name

Health Serv Res

journal_title

Health services research

authors

Choi D,Hoffman KA,Kim MO,McCarty D

doi

10.1111/j.1475-6773.2012.01436.x

subject

Has Abstract

pub_date

2013-02-01 00:00:00

pages

333-47

issue

1

eissn

0017-9124

issn

1475-6773

journal_volume

48

pub_type

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