| Literature DB >> 31799346 |
Svetlana Ostapenko1, Melissa Schmatz2, Lakshmi Srinivasan2,3, Okan U Elci4,5, Scott L Weiss6, Aaron J Masino1,6, Marissa Tremoglie2, Mary Catherine Harris2,3, Robert W Grundmeier1,3.
Abstract
This article describes the process of extracting electronic health record (EHR) data into a format that supports analyses related to the timeliness of antibiotic administration. The de-identified data that accompanies this article were collected from a cohort of infants who were evaluated for possible sepsis in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia (CHOP). The interpretation of findings from these data are reported in a separate manuscript [1]. For purposes of illustration for interested readers, scripts written in the R programming language related to the creation and use of the dataset have also been provided. Interested researchers are encouraged to contact the research team to discuss opportunities for collaboration.Entities:
Keywords: Anti-bacterial agents; Infant mortality; Neonatal sepsis; Quality improvement; Registries
Year: 2019 PMID: 31799346 PMCID: PMC6881601 DOI: 10.1016/j.dib.2019.104788
Source DB: PubMed Journal: Data Brief ISSN: 2352-3409
Specifications Table
| Subject | Critical Care and Intensive Care Medicine |
| Specific subject area | Sepsis among neonates and infants. |
| Type of data | Table |
| How data were acquired | Episodes of possible sepsis among infants in the neonatal intensive care unit (NICU) were identified from electronic health records. Demographic characteristics, co-morbidity status, treatment, and clinical outcome details were extracted electronically. The outcome of the sepsis evaluation (culture positive sepsis, clinical sepsis with negative cultures, non-bacterial infection, or negative for sepsis) was determined by manual chart review. |
| Data format | Raw |
| Parameters for data collection | Charts for all infants who had one or more blood cultures collected were reviewed for possible inclusion in the infant sepsis cohort. These charts were reviewed manually to identify and categorize distinct episodes of sepsis evaluation. |
| Description of data collection | Data were extracted from electronic health records (Epic Systems Inc., Verona, WI) using the structured query language. Candidate episodes of sepsis evaluation were loaded into a REDCap database (Vanderbilt University, Nashville, TN) for subsequent manual review. Demographic, clinical, treatment and outcome data were extracted for sepsis episodes that were marked for inclusion by manual review. Data were re-formatted to the unit of analysis (one row per sepsis evaluation episode) using the R programming language (version 3.5.3). |
| Data source location | Neonatal Intensive Care Unit, Children's Hospital of Philadelphia, Philadelphia, USA |
| Data accessibility | Repository name: Neonatal Sepsis Registry: Time to Antibiotic Dataset, Mendeley Data |
| Related research article | Melissa Schmatz, M.D., Lakshmi Srinivasan, M.B.B.S., M.T.R., Robert W. Grundmeier, M.D., Okan U. Elci, Ph.D., Scott L. Weiss, M.D., M.S.C.E., Aaron J. Masino, Ph.D., Marissa Tremoglie, B.S., Svetlana Ostapenko, M.S., Mary Catherine Harris, M.D. |
These data contain a curated set of information regarding sepsis evaluations among infants in a quaternary neonatal intensive care unit (NICU) and can be used to understand relationships between baseline risk characteristics, timeliness of antibiotic administration, and mortality. Researchers or quality improvement professionals interested in better understanding the role of timely antibiotic administration and infant mortality may benefit from these data. The dataset includes information about rates of exposures (e.g. presence of central venous lines), neonatal co-morbidities, and mortality outcomes that may be useful for power or sample size calculations to design future studies related to sepsis among infants. These data were extracted from electronic health records from a diverse cohort of critically ill infants in an urban quaternary care facility, and were manually reviewed to verify accuracy. The authors welcome opportunities to collaborate and can be contacted to discuss other types of data that may be available for this cohort of infants. |