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1.
Appl Clin Inform ; 9(1): 185-198, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29539649

RESUMO

BACKGROUND: Secondary use of electronic health record (EHR) data can reduce costs of research and quality reporting. However, EHR data must be consistent within and across organizations. Flowsheet data provide a rich source of interprofessional data and represents a high volume of documentation; however, content is not standardized. Health care organizations design and implement customized content for different care areas creating duplicative data that is noncomparable. In a prior study, 10 information models (IMs) were derived from an EHR that included 2.4 million patients. There was a need to evaluate the generalizability of the models across organizations. The pain IM was selected for evaluation and refinement because pain is a commonly occurring problem associated with high costs for pain management. OBJECTIVE: The purpose of our study was to validate and further refine a pain IM from EHR flowsheet data that standardizes pain concepts, definitions, and associated value sets for assessments, goals, interventions, and outcomes. METHODS: A retrospective observational study was conducted using an iterative consensus-based approach to map, analyze, and evaluate data from 10 organizations. RESULTS: The aggregated metadata from the EHRs of 8 large health care organizations and the design build in 2 additional organizations represented flowsheet data from 6.6 million patients, 27 million encounters, and 683 million observations. The final pain IM has 30 concepts, 4 panels (classes), and 396 value set items. Results are built on Logical Observation Identifiers Names and Codes (LOINC) pain assessment terms and extend the need for additional terms to support interoperability. CONCLUSION: The resulting pain IM is a consensus model based on actual EHR documentation in the participating health systems. The IM captures the most important concepts related to pain.


Assuntos
Registros Eletrônicos de Saúde , Modelos Teóricos , Dor/patologia , Documentação , Humanos , Logical Observation Identifiers Names and Codes , Reprodutibilidade dos Testes
2.
AMIA Annu Symp Proc ; 2017: 421-429, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29854106

RESUMO

Reference models are an essential instrument to provide structure and guidance in the creation and use of data elements within an organizations' electronic health record (EHR). Standardization of data elements is imperative to ensure clinical data is consistently and reliably captured for use in clinical documentation, care communication, and a variety of downstream data uses. Ongoing assessment and refinement of reference models and data elements are necessary to ascertain clinical data capture is applicable and inclusive across a variety of caregivers and domains. We performed a gap analysis on current state nursing data elements against two validated interprofessional reference models: skin alteration and pressure ulcer assessments. We present our findings along with recommendations for reference model refinements. We also highlight additional findings of inconsistencies and redundancies within data elements used for nursing documentation and highlight recommendations for improvement.


Assuntos
Coleta de Dados , Registros Eletrônicos de Saúde , Registros de Enfermagem , Úlcera por Pressão/diagnóstico , Pele/patologia , Elementos de Dados Comuns , Humanos , Modelos Teóricos , Exame Físico
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