Application of Information Value Chain in Gout Management.
Purpose: This study introduces information value chain analysis by identifying essential information for use in gout care management. Part I reviews the essential concepts of information value chain analysis first introduced by Porter. Part II applies the analysis to determine the information values...
| Publicado en: | Korean Journal of Adult Nursing Vol. 34; no. 4; pp. 351 - 360 |
|---|---|
| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Korean Society of Adult Nursing
Aug2022
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158812352&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158812352 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 12254886 BKLA jtl: Korean Journal of Adult Nursing issn: 12254886 maglogo: N pubinfo: dt: Aug2022 vid: 34 iid: 4 pid: 69073 pub: Korean Society of Adult Nursing artinfo: ui: 158812352 158812352 158812352 10.7475/kjan.2022.34.4.351 158812352 ppf: 351 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Application of Information Value Chain in Gout Management. aug: au: Russell, Maranda Kim, Sujin affil: Research Assistant, Department of Internal Medicine, University of Kentucky, Lexington, Kentucky, USA sug: subj: Gout Therapy Health Informatics Patient Education Human Information Technology Lupus Erythematosus, Systemic Machine Learning Algorithms Treatment Outcomes Comparative Studies Descriptive Statistics Middle Age Aged Self Care Decision Making Natural Language Processing Middle Aged: 45-64 years Aged: 65+ years ab: Purpose: This study introduces information value chain analysis by identifying essential information for use in gout care management. Part I reviews the essential concepts of information value chain analysis first introduced by Porter. Part II applies the analysis to determine the information values of patient health information and explores ways in which health information technologies can be best utilized to provide that information to patients with gout. Methods: We combined value chain analysis with natural language processing and machine learning techniques to develop algorithms that can identify patients with gout flares using clinical notes. As one of the first signs that the disease was not being controlled, variables found to be associated with gout flares were considered valuable information for patients with gout. Results: The best performing model, in terms of both gout flare prediction and association identification, was the comprehensive model that not only included concepts from all stages of the value chain but also designated natural language processing concepts from every care stage as surrogate variables. Additionally, all administrative codes traditionally associated with gout and its treatment were included as surrogate outcome variables. Conclusion: This study introduced information value chain analysis and applied it to develop a computer-based method with theoretical underpinnings to identify the concepts associated with gout flares. The findings can be used as a starting point for filtering the vast amounts of information patients must go through and identifying the most valuable information for patient with gout to adequately manage their symptoms. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|