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terminologies. Given the growing emphasis on using existing health care datasets, there is a need for new statistical, computational, and visualization methods to analyze EHRs data, given their complexity and volume.6 For nursing to join this effort, an important first step is to identify and examine the studies that analyze EHR data coded with SNTs.17
To date, there are few reviews that report secondary analysis of SNTs nursing data. One recently published systematic review18 described study focus, sample characteristics and frequency of publications that studied SNTs. The authors also identified a limited set of studies in which SNTs nursing data were being analyzed.18 However, substantial evaluation and discussion on the analysis of SNTs nursing data were not performed. Another review19 described characteristics of nursing research data (ranging from patient demographics, social history, medical history, medications, among others) and evaluated if a specific index metadata system represents sufficiently nursing data. Our systematic review differentiates from the previous investigations as we focused only on studies that analyzed nursing data coded with SNTs retrieved from EHRs. The earlier literature review19 included all types of unstructured nursing data, and different types of studies, such as controlled clinical trials. The authors also did not restrict their selection criteria for nursing data retrieved from EHRs.19
The systematic review presented below was conducted to describe and critically analyze the body of studies in which secondary analyses of data coded with the ANA recognized SNTs was performed. These nursing data were documented during the delivery of nursing care and retrieved from EHRs. We believe that the findings from the present systematic review will emphasize the importance of coded nursing data and will encourage a wider use of SNTs that will allow greater participation of nursing in big data science initiatives.
Objective
The objective of this systematic review was to uncover the state of the science related to the use of standardized nursing data (coded with SNTs) retrieved from EHRs to answer research questions, describe the analytical techniques employed, and outline the lessons learned applicable big data science and nursing.
Methods
Search strategy
A comprehensive literature search was conducted to identify publications in which secondary analysis was performed on data extracted from EHRs and documented using terms from the ANA recognized nursing terminologies (or sets). There were two phases us
ed in this process: 1) study selection and 2) data collection process.
Building from the work of Tastan et al.18 that reported secondary uses of SNTs documentation in studies up to 2011, the databases PubMed and CINAHL were searched using keywords encompassing all ANA recognized SNTs, along with “nursing” and “electronic health records” from 2010 to 2017. Keywords were defined for each database with the help of a librarian, who was a specialist in Consumer Health, Nursing and Health Education and Behavior. The limiters since 2010, abstract available and published in English were used. Potential publications identified in both databases were downloaded into a reference management program (EndNote X7, Thompson Reuters ISI ResearchSoft), in which duplicates were deleted and abstracts were reviewed. Finally, grey literature search was conducted using Google Scholar to identify possible publications not captured by the traditional search methods, including relevant publications not in PubMed or CINAHL, but in computer science databases like IEEE. Name of authors of publications already reviewed and included in this study’s sample were individually searched in Google Scholar. Publications pertinent to the subject were reviewed and included.
Study selection
The studies identified using the specified search strategy were submitted to abstract review according to the following inclusion criteria: 1) publications that conducted secondary analysis of nursing data retrieved from EHRs, 2) nursing data were coded with one of the ANA recognized nursing terminologies and documented at the point-of-care, as part of the institution’s routine, and 3) publications were published in English. Following PRISMA guidelines20, Figure 1 shows the number of publications first identified, retained after selection from abstracts, and reviewed as full text.
The team utilized a two-stage selection process. In the first stage, two doctoral students in nursing informatics (TM, ND) independently conducted the literature search in the databases using the same keywords and found the same number of studies. A guide created by the authors was used to systematically review the abstracts. The reviewers first identified if the article contained at least one of the ANA recognized SNTs. If the abstract described the use of a SNT, the reviewer would continue to verify if the data analyzed were retrieved from EHRs. In the case of an affirmative answer, the reviewers would further analyze the abstract to assess if the SNT coded nursing data were documented as
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