Support of Perinatal and Neonatal Research

Chapter
Part of the Translational Bioinformatics book series (TRBIO, volume 2)

Abstract

The emergence of the field of biomedical informatics has enabled the development of computerization within the Neonatal Intensive Care Unit (NICU); however, the unique population encountered in this setting requires special consideration beyond minor adaptations from an adult Intensive Care Unit (ICU) or even a Pediatric Intensive Care Unit (PICU). Deficiencies in data capture of the traditional Electronic Health Record must be addressed to support research of NICU populations. Additional precision is required for the measurement of data elements such as age and weight where day-to-day changes can be clinically relevant. Obtaining gestational age, a key measure in neonatal research, has its own unique array of challenges. Although gestational age has a precise definition, numerous opportunities for error are introduced in documenting the variable, as measures are necessarily based upon estimates. Another challenge to neonatal data collection is the integration of information from parental medical records. The prenatal record and maternal medical history, though pertinent to the neonate, are contained in the mother’s medical chart. Access to prenatal data may be limited by barriers between institutions where care was provided, the transition between types of care providers (obstetrics to neonatology), concerns for the mother’s privacy, and the absence or unreliability of traditional identifiers used in record linking such as name and social security number. The development of neonatal terminologies allows for standardization in the description and communication of concepts specific to neonatology, and thereby facilitates research networks that study rare neonatal conditions across national and international landscapes.

Keywords

Preterm Birth Neonatal Intensive Care Unit Electronic Health Record Electronic Health Record System Last Menstrual Period 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of PediatricsUniversity of Cincinnati College of MedicineCincinnatiUSA
  2. 2.Perinatal Institute & Division of Biomedical InformaticsCincinnati Children’s Hospital Medical CenterCincinnatiUSA

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