Information Model on Pain Management: An Analysis of Big Data

Aline Tsuma Gaedke Nomura, Miriam de Abreu Almeida, Lisiane Pruinelli

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To develop an information model to support secondary use of data using electronic health records. Design: Retrospective observational data-driven study with secondary use of data. The sample was composed of structured data from all adults admitted to clinical and surgical inpatient units of a public university hospital. Data between June 2014 and July 2019 were included, totaling approximately 51,000 unique patients. Methods: Six systematic steps of the Applied Healthcare Data Science Roadmap were applied. Findings: An information model on pain management was developed. Conclusions: The data science methodology used allowed the development of information model in pain management, mapping attributes about pain management and to categorize them into assessment and reassessment, goals, interventions, and outcomes. Clinical Relevance: Based on the information model developed, it is possible to optimize the electronic health system and improve the quality of patient care delivery in pain management.

Original languageEnglish (US)
Pages (from-to)270-277
Number of pages8
JournalJournal of Nursing Scholarship
Volume53
Issue number3
DOIs
StatePublished - May 2021

Bibliographical note

Funding Information:
This study was financed in part by the Coordination for Improvement of Higher Education Personnel?CAPES (Brazilian Federal Agency for the Support and Evaluation of Graduate Education; Finance Code 001); and National Council for Scientific and Technological Development?CNPq (426779/2018-5). This study was also supported by the Research and Events Incentive Fund of the Hospital de Cl?nicas de Porto Alegre (FIPE/HCPA).Clinical Resources Empresa Brasileira de Servi?os Hospitalares. Aplicativo de Gest?o para Hospitais Universit?rios. https://www.gov.br/ebserh/pt-br/governanca/plataformas-e-tecnologias/aghu HL7 International. Clinical Information Modeling Initiative. https://www.hl7.org/Special/Committees/cimi/index.cfm Nursing Center. Informatics. https://www.nursingcenter.com/clinical-resources/practice-specialties/informatics Continuing Professional Development[Journal of Nursing Scholarship/Worldviews on Evidence-Based Nursing] is pleased to offer readers the opportunity to earn Continuing Professional Development contact hours for select articles. This opportunity is valid for three years from each article?s date of publication. Learn more here: https://www.sigmamarketplace.org/journaleducation Empresa Brasileira de Servi?os Hospitalares. Aplicativo de Gest?o para Hospitais Universit?rios. https://www.gov.br/ebserh/pt-br/governanca/plataformas-e-tecnologias/aghu HL7 International. Clinical Information Modeling Initiative. https://www.hl7.org/Special/Committees/cimi/index.cfm Nursing Center. Informatics. https://www.nursingcenter.com/clinical-resources/practice-specialties/informatics [Journal of Nursing Scholarship/Worldviews on Evidence-Based Nursing] is pleased to offer readers the opportunity to earn Continuing Professional Development contact hours for select articles. This opportunity is valid for three years from each article?s date of publication. Learn more here: https://www.sigmamarketplace.org/journaleducation

Funding Information:
This study was financed in part by the Coordination for Improvement of Higher Education Personnel–CAPES (Brazilian Federal Agency for the Support and Evaluation of Graduate Education; Finance Code 001); and National Council for Scientific and Technological Development–CNPq (426779/2018‐5). This study was also supported by the Research and Events Incentive Fund of the Hospital de Clínicas de Porto Alegre (FIPE/HCPA). Clinical Resources

Publisher Copyright:
© 2021 Sigma Theta Tau International

Keywords

  • Big data
  • electronic health records
  • nursing informatics
  • pain

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