The Feasibility of Tracking Elective Deliveries Prior to 39 Gestational Weeks: Lessons From Three California Projects
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The Feasibility of Tracking Elective Deliveries Prior to 39 Gestational Weeks: Lessons From Three California Projects Lisa M. Korst • Moshe Fridman • Melanie Estarziau Kimberly D. Gregory • Connie Mitchell
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Ó Springer Science+Business Media New York 2015
Abstract The tracking of elective deliveries (ED) prior to 39 gestational weeks has become a mandatory requirement for all hospitals with C1,100 deliveries for accreditation by The Joint Commission (TJC); however, the feasibility and accuracy of monitoring efforts remain problematic for many hospitals. Here, we evaluated the feasibility of three operational approaches to tracking ED. We used mixed methods to evaluate the feasibility of 3 different approaches to tracking ED: (1) using administrative data, (2) using electronic medical record (EMR) data, and (3) using targeted data collection in a county-wide quality improvement (QI) effort. For (1), we analyzed data from the California 2009 linked birth cohort dataset, and calculated hospital rates of ED using TJC technical specifications. For (2), we performed a case study of a project that
recruited hospitals to provide EMR data for the TJC measure calculation. For (3), we performed a case study of a project that recruited hospitals to prospectively track elective inductions of labor. For (1), hospital discharge data were insufficient without supplementation from the EMR or birth certificate. For (2), legal and operational issues surrounding data sharing, and non-standardized data elements prohibited hospital participation. For (3), the QI approach successfully established policies and data collection systems yet lacked infrastructure to assure sustainability at a hospital or regional level. In summary, ED tracking required the coordination and support of multiple resources to enable hospitals to satisfactorily report on this measure. Keywords Elective delivery Quality indicators Pregnancy Childbirth Administrative data Benchmarking
Melanie Estarziau: under contract with the University of California San Francisco
Electronic supplementary material The online version of this article (doi:10.1007/s10995-015-1725-y) contains supplementary material, which is available to authorized users.
M. Fridman AMF Consulting, Los Angeles, CA, USA
K. D. Gregory (&) Department of Obstetrics and Gynecology, Burns Allen Research Institute, Cedars-Sinai Medical Center, 8635 West 3rd Street, Suite 160 West Tower, Los Angeles, CA 90048, USA e-mail: [email protected]; [email protected]
M. Estarziau Maternal, Child and Adolescent Health Division, California Department of Public Health, Sacramento, CA, USA
C. Mitchell Office of Health Equity, California Department of Public Health, Sacramento, CA, USA
L. M. Korst Childbirth Research Associates, North Hollywood, CA, USA
K. D. Gregory Department of Obstetrics and Gynecology, David Geffen School of Medicine and Department of Community Health Sciences, School of Public Health, UCLA, Los Angeles, CA, USA
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Matern Child Health J
Introduction In contrast to the
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