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Very low birth weight hospital volume and mortality: an instrumental variables approach
George L Wehby1, Fred Ullrich, Yang Xie
1Department of Health Management and Policy, College of Public Health, University of Iowa, Iowa City, IA 52242, USA. george-wehby@uiowa.edu
Background:
Previous studies of very low birth weight (VLBW) hospital volume effects on in-hospital mortality have used standard risk-adjusted models that only account for observable confounders but not for self-selection bias due to unobservable confounders.
Objective:
To assess the effects of hospital volume of VLBW infants on in-hospital mortality while explicitly accounting for unobservable confounders and self-selection bias using an instrumental variables (IV) model.
Methods:
The sample includes 4553 VLBW infants born in 63 hospitals in 2000-2004 in New Jersey. We use IV analysis with the differences between the patient's distances to the nearest low (<50 VLBW infants annually), moderate (51-100 infants annually), and high (>100 VLBW infants annually)-volume hospitals as instruments. We evaluate several volume measures and adjusted for observable infant and hospital characteristics.
Results:
We find beneficial volume effects on survival that are significantly underestimated in classic risk-adjusted models, under which low and moderate volumes compared with high volumes increase mortality odds by 1.8 and 1.88 times, respectively (risk ratios of 1.4 and 1.5, respectively). However, using the IV approach, we find that low and moderate volumes increase mortality odds by 5.42 and 3.51 times, respectively (risk ratios of 2.76 and 2.21, respectively). These findings suggest unobservable confounders that increase the selection of infants at a greater mortality risk into higher-volume hospitals.
Conclusions:
Accounting for unobserved self-selection bias reveals large survival benefits from delivering and treating VLBW infants at high-volume hospitals. This supports policies regionalizing the delivery and care for pregnancies at risk for VLBW at high-volume hospitals.
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