Lannon Carole, Kaplan Heather C, Friar Kelly, Fuller Sandra, Ford Susan, White Beth, Besl John, Paulson John, Marcotte Michael, Krew Michael, Bailit Jennifer, Iams Jay
James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati School of Medicine, Cincinnati, Ohio.
Ohio Public Health Partnership, Columbus, Ohio.
Am J Perinatol. 2017 Aug;34(10):958-965. doi: 10.1055/s-0037-1600898. Epub 2017 Mar 22.
Birth registry data are universally collected, generating large administrative datasets. However, these data are typically not used for quality improvement (QI) initiatives in perinatal medicine because the quality and timeliness of the information is uncertain. We sought to identify and address causes of inaccuracy in recording birth registry information so that birth registry data could support statewide obstetrical quality initiatives in Ohio. The Ohio Perinatal Quality Collaborative and the Ohio Department of Health Vital Statistics used QI techniques in 15 medium-sized maternity hospitals to identify and remove systemic sources of inaccuracy in birth registry data. The primary outcome was the rate of scheduled deliveries without medical indication between 37 and 38 weeks at participating hospitals from birth registry data. Inaccurate birth registry data most commonly resulted from limited communication between clinical and medical record staff. The rate of scheduled births between 37 and 38 weeks' gestation without a documented medical indication as recorded in the birth registry declined by 35%. A QI initiative aimed at increasing the accuracy of birth registry information demonstrated the utility of these data for surveillance of perinatal outcomes and has led to ongoing efforts to support birth registrars in submitting accurate data.
出生登记数据是普遍收集的,从而生成了大量的行政数据集。然而,这些数据通常并不用于围产期医学的质量改进(QI)举措,因为信息的质量和及时性是不确定的。我们试图识别并解决出生登记信息记录不准确的原因,以便出生登记数据能够支持俄亥俄州的全州产科质量举措。俄亥俄围产期质量协作组织和俄亥俄州卫生部生命统计部门在15家中型妇产医院运用质量改进技术,以识别并消除出生登记数据中不准确的系统性来源。主要结果是根据出生登记数据得出的参与医院在37至38周之间无医学指征的计划性分娩率。出生登记数据不准确最常见的原因是临床和病历工作人员之间沟通有限。出生登记记录的妊娠37至38周之间无记录医学指征的计划性分娩率下降了35%。一项旨在提高出生登记信息准确性的质量改进举措证明了这些数据在围产期结局监测中的效用,并促使人们持续努力支持出生登记员提交准确的数据。