Standardizing nursing data extracted from electronic health records for integration into a statewide clinical data research network

BACKGROUND

Care plans documented by nurses in electronic health records (EHR) are a rich source of data to generate knowledge and measure the impact of nursing care. Unfortunately, there is a lack of integration of these data in clinical data research networks (CDRN) data trusts, due in large part to nursing care being documented with local vocabulary, resulting in non-standardized data. The absence of high-quality nursing care plan data in data trusts limits the investigation of interdisciplinary care aimed at improving patient outcomes.

OBJECTIVE

To map local nursing care plan terms for patients' problems and goals in the EHR of one large health system to the standardized nursing terminologies (SNTs), NANDA International (NANDA-I), and Nursing Outcomes Classification (NOC).

METHODS

We extracted local problems and goals used by nurses to document care plans from two hospitals. After removing duplicates, the terms were independently mapped to NANDA-I and NOC by five mappers. Four nurses who regularly use the local vocabulary validated the mapping.

RESULTS

83% of local problem terms were mapped to NANDA-I labels and 93% of local goal terms were mapped to NOC labels. The nurses agreed with 95% of the mapping. Local terms not mapped to labels were mapped to the domains or classes of the respective terminologies.

CONCLUSION

Mapping local vocabularies used by nurses in EHRs to SNTs is a foundational step to making interoperable nursing data available for research and other secondary purposes in large data trusts. This study is the first phase of a larger project building, for the first time, a pipeline to standardize, harmonize, and integrate nursing care plan data from multiple Florida hospitals into the statewide CDRN OneFlorida+ Clinical Research Network data trust.

Phylogenetic and phylogeographic analyses of porcine circovirus type 2 among pig farms in Vietnam

This study demonstrated the prevalence of Porcine circovirus type 2 (PCV2) among pig farms in Vietnam. Analyses of the genome, capsid protein and phylogeny classified all 30 Vietnamese PCV2 strains as the PCV2b genotype, belonging to the clusters of 1A, 1B, 1C and recombinant forms. Each viral genome was 1767 nucleotides long and shared 96.0-100% nucleotide sequence identity. The amino acid substitutions in the capsid protein of the Vietnamese PCV2 strains were in immunodominant regions, and the majority of strains (24/30) contained a lysine extension at the C-terminus. Bayesian phylogeographic analysis revealed epidemic links of the PCV2 recombinant cluster within and among countries, which supports a circulating recombinant form of PCV2. Further analysis by the Jameson-Wolf antigenic index indicated antigenic alterations at important sites in the capsid protein (sites 131-133) among the recombinant cluster and the other clusters of PCV2b.