We use cookies to provide you with the best possible website experience. This includes cookies that are necessary for the operation of the site, as well as cookies used for anonymous statistics, comfort settings, or displaying personalized content. You can decide which categories you want to allow. Please note that depending on your settings, some features of the website may not be available.

Cookie settings

These necessary cookies are required to enable the core functionality of the website. Opting out of these cookies is not possible.

cb-enable
This cookie stores the user's cookie consent status for the current domain. Expiry: 1 year.
laravel_session
Stores the session ID to recognize the user when the page reloads and to restore their login session. Expiry: 2 hours.
XSRF-TOKEN
Provides CSRF protection for forms. Expiry: 2 hours.
IZA Discussion Paper No. 13046
March 2020
Infections, Accidents and Nursing Overtime in a Neonatal Intensive Care Unit: A Bayesian Semiparametric Panel Data Logit Model
Marc Beltempo, Georges Bresson, Jean-Michel Etienne, Guy Lacroix

published as 'Infections, accidents and nursing overtime in a neonatal intensive care unit' in: European Journal of Health Economics, 2022, 23, 627 - 643

The paper investigates the effects of nursing overtime on nosocomial infections and medical accidents in a neonatal intensive care unit (NICU). The literature lacks clear evidence on this issue and we conjecture that this may be due to empirical and methodological factors. We thus focus on a single NICU, thereby removing much variation in specialty mixes such neonatologists, fellows, residents, nurse practitioners that are observed across units. We model the occurrences of both outcomes using a sample of 3,979 neonates which represents over 84,846 observations (infant/days). We use a semiparametric panel data Logit model with random coefficients. The non-parametric components of the model allow to unearth potentially highly non-linear relationships between the outcomes and various policy-relevant covariates. We use the mean field variational Bayes approximation method to estimate the models. Our results show unequivocally that both health outcomes are affected by nursing overtime. Furthermore, they are both highly sensitive to infant and NICU-related characteristics.

Communications
Mark Fallak
mark.fallak@liser.lu
+352 585-855-526
World of Labour
Olga Nottmeyer
olga.nottmeyer@liser.lu
+352 585-855-501
Network Coordination
Christina Gathmann
christina.gathmann@liser.lu

The IZA@LISER Network is a global community of scholars dedicated to excellence in labor economics and related fields, now coordinated at the Luxembourg Institute of Socio-Economic Research (LISER) following its transition from Bonn.

About IZA@LISER Network
Contact
IZA Network (Current Site Operator):

Luxembourg Institute of Socio-Economic Research (LISER)
11, Porte des Sciences
Maison des Sciences Humaines
L-4366 Esch-sur-Alzette / Belval, Luxembourg

IZA Institute (In Liquidation):

Forschungsinstitut zur Zukunft der Arbeit GmbH i. L.
Schaumburg-Lippe-Str. 5-9, 53113 Bonn. Germany
Phone: +49 228 3894-0 | Fax: +49 228 3894-510
E-Mail: info@iza.org | Web: www.iza.org
Represented by: Martin T. Clemens (Liquidator)