JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 283
Type: Invited
Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
Sponsor: Committee on Applied Statisticians
Abstract - #307072
Title: Using Complications to Evaluate Neonatal Health Care: Controlling for Censoring by Death
Author(s): Dylan S Small*+ and Fan Yang and Jing Cheng and Scott Lorch
Companies: University of Pennsylvania and University of Pennsylvania and University of California, San Francisco and Children's Hospital of Philadelphia
Keywords: causal inference ; censoring by death
Abstract:

The Institute of Medicine has suggested the use of complication rates as a measure of the quality of care provided by an institution. We consider the use of complication rates as a measure of the quality of care provided by a neonatal intensive care unit (NICU). Two difficulties with using complications are: (1) censoring by death - many complications in neonatal care are not assessed until a newborn is at least 36 weeks old (e.g., bronchopulmonary dysplasia ) and consequently such complications are censored by death if a newborn dies before 36 weeks old; (2) substantial differences on measured and unmeasured patient risk factors between different NICUs. We develop a novel approach to control for censoring by death and unmeasured patient risk factors. Our approach to controlling for censoring by death makes use of multiple possible complications and the fact that there are multiple causal pathways along which a newborn might die, e.g., a child who dies from an intraventricular hemorrhage would not necessarily have later developed bronchopulmonary dysplasia if she had survived. Our approach to controlling for unmeasured patient risk factors makes use of instrumental variables.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2013 program




2013 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.