BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//wp-events-plugin.com//7.2.2.1//EN
TZID:Europe/Amsterdam
X-WR-TIMEZONE:Europe/Amsterdam
BEGIN:VEVENT
UID:112@bmi-online.nl
DTSTART:20210630T173000Z
DTEND:20210630T184500Z
DTSTAMP:20210513T132843Z
URL:https://www.bmi-online.nl/events/research-observatory-observing-knowle
 dge-organization-trajectories-in-healthcare-online/
SUMMARY:Research Observatory: Observing knowledge organization trajectories
  in healthcare (Online)
DESCRIPTION:Home care nursing information behavior: expansion of a knowledg
 e base in a time of pandemic\nBy Richard P. Smiraglia\, Edmund Pajarillo\
 , Elizabeth Milonas &amp\; Sergey Zherebchevsky\nHome care nursing has bec
 ome a frontline critical role in pandemic health care. In 2020 as the pand
 emic’s proportions were becoming apparent we turned to research on home 
 care nurses that had yielded a theory called the “nub of Nursing Informa
 tion Behavior (NIB).” A “Core Taxonomy for Nursing Information Behavio
 r\, or CT-NIB was published in June 2020 and subsequently was enhanced wit
 h mappings to the NANDA-International Nursing Diagnoses and Classification
  (NANDA-I) (https://knoworg.org/a-core-taxonomy-of-nursinginformation-beha
 vior-ct-nib-version-1-1/). As the pandemic evolved ethnographic techniques
  were employed to discover ways in which the knowledge base of NIB was aff
 ected over time. A collection of videos was compiled\, transcripts were ge
 nerated and subjected first to co-word analysis and then the narrative ana
 lysis. Co-word analysis revealed larges core regions in the vocabulary of 
 active home care nurses: the community of home health care people\, hospit
 al nurs[ing] service and care taking\, with pointers to the front line of 
 home care for COVID-19 patients. Narrative analysis new contours for the k
 nowledge base. The vocabulary of the pandemic itself becomes part of the k
 nowledge base of the home care nurse together with an emotional layer beyo
 nd the core vocabulary of NIB that reveals the contours of the social impa
 ct of the pandemic.\nMaking healthcare data FAIR data: the ontologies-data
  models-instances conundrum\nBy Ronald Cornet\nExchange of healthcare dat
 a is crucial for providing adequate care\, for monitoring the quality of p
 rovided care\, and to improve healthcare by research on observational data
 . For these\, healthcare data need to be of good quality\, and as much as 
 possible structured and standardized according to agreed-upon data models 
 and ontologies. Increasingly\, healthcare data is represented using ontolo
 gies such as SNOMED CT. This is of great value in well-delineated areas of
  healthcare records\, such as diagnosis or procedures. However\, the benef
 it of reasoning by using the OWL language is underutilized\, and essential
  for application of ontologies on the broader scale of healthcare data. Th
 is talk will briefly summarize the content and structure of SNOMED CT\, de
 scribe its current use in healthcare records\, and concludes with the furt
 her steps needed to establish truly interoperable healthcare data\, to pav
 e the way towards FAIR healthcare data.\n\nMore information.
CATEGORIES:Cursussen en congressen,Symposium
END:VEVENT
END:VCALENDAR