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Published in: Health Economics Review 1/2017

Open Access 01-12-2017 | Research

Assessing the impact of state “opt-out” policy on access to and costs of surgeries and other procedures requiring anesthesia services

Authors: John E. Schneider, Robert Ohsfeldt, Pengxiang Li, Thomas R. Miller, Cara Scheibling

Published in: Health Economics Review | Issue 1/2017

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Abstract

In 2001, the U.S. government released a rule that allowed states to “opt-out” of the federal requirement that a physician supervise the administration of anesthesia by a nurse anesthetist. To date, 17 states have opted out. The majority of the opt-out states cited increased access to anesthesia care as the primary rationale for their decision. In this study, we assess the impact of state opt-out policy on access to and costs of surgeries and other procedures requiring anesthesia services. Our null hypothesis is that opt-out rule adoption had little or no effect on surgery access or costs. We estimate an inpatient model of surgeries and costs and an outpatient model of surgeries. Each model uses data from multiple years of U.S. inpatient hospital discharges and outpatient surgeries. For inpatient cost models, the coefficient of the opt-out variable was consistently positive and also statistically significant in most model specifications. In terms of access to inpatient surgical care, the opt-out rules did not increase or decrease access in opt-out states. The results for the outpatient access models are less consistent, with some model specifications indicating a reduction in access associated with opt-out status, while other model specifications suggesting no discernable change in access. Given the sensitivity of model findings to changes in model specification, the results do not provide support for the belief that opt-out policy improves access to outpatient surgical care, and may even reduce access to outpatient surgical care (among freestanding facilities).
Appendix
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Footnotes
1
In NIS, the total number of all surgeries was the sum of all hospitalizations with surgical DRG in a facility (excluding records with patients age younger than 1); In SASD, it was the total number of visits in the facility.
 
2
We used the size classification defined by HCUP, for which specific bed-size thresholds for size categories vary across Census regions, and by urban/rural and teaching status (https://​www.​hcup-us.​ahrq.​gov/​db/​vars/​hosp_​bedsize/​nisnote.​jsp).
 
3
These facility level variables were almost fixed over the sample time period. Dropping the facility variables from the facility fixed-effects model does not change model results.
 
4
The market area definition recommended by HCUP was used (see HCUP Hospital Market Structure File: 2009 Central Distributor SID, NIS, and KID User Guide [https://​www.​hcup-us.​ahrq.​gov/​toolssoftware/​hms/​HMSUserGuide2009​.​pdf].) Years with missing HHI values were imputed using a time trend.
 
5
The source for these data is county-level data from the Area Resource File (ARF).
 
6
Estimated as \( {\upbeta}^{*}=\left[ \exp \left[\widehat{\upbeta}\hbox{-} \frac{1}{2}\operatorname{var}\left(\widehat{\upbeta}\right)\right]-1\right] \). See Kennedy [12].
 
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Metadata
Title
Assessing the impact of state “opt-out” policy on access to and costs of surgeries and other procedures requiring anesthesia services
Authors
John E. Schneider
Robert Ohsfeldt
Pengxiang Li
Thomas R. Miller
Cara Scheibling
Publication date
01-12-2017
Publisher
Springer Berlin Heidelberg
Published in
Health Economics Review / Issue 1/2017
Electronic ISSN: 2191-1991
DOI
https://doi.org/10.1186/s13561-017-0146-6

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