View in EDS HTML Full Text PDF Full Text

Data sharing and big data in health professions education: Ottawa consensus statement and recommendations for scholarship.

Saved in:
Bibliographic Details
Title: Data sharing and big data in health professions education: Ottawa consensus statement and recommendations for scholarship.
Authors: Kulasegaram, Kulamakan1 mahan.kulasegaram@utoronto.ca, Grierson, Lawrence2, Barber, Cassandra3, Chahine, Saad4, Chou, Fremen Chichen5, Cleland, Jennifer6, Ellis, Ricky7, Holmboe, Eric S.8, Pusic, Martin9, Schumacher, Daniel10, Tolsgaard, Martin G.11, Tsai, Chin-Chung12, Wenghofer, Elizabeth13, Touchie, Claire14
Source: Medical Teacher. Apr2024, Vol. 46 Issue 4, p471-485. 15p.
Subject Terms: *Medical education, *Database management, *Scholarly method, *Interprofessional relations, *Goal (Psychology), Consensus (Social sciences), Medical protocols, Medical quality control, Data analytics, Employee participation in management, Trust, Medical research, Stakeholder analysis, Health care teams
Geographic Terms: Canada
Abstract: Changes in digital technology, increasing volume of data collection, and advances in methods have the potential to unleash the value of big data generated through the education of health professionals. Coupled with this potential are legitimate concerns about how data can be used or misused in ways that limit autonomy, equity, or harm stakeholders. This consensus statement is intended to address these issues by foregrounding the ethical imperatives for engaging with big data as well as the potential risks and challenges. Recognizing the wide and ever evolving scope of big data scholarship, we focus on foundational issues for framing and engaging in research. We ground our recommendations in the context of big data created through data sharing across and within the stages of the continuum of the education and training of health professionals. Ultimately, the goal of this statement is to support a culture of trust and quality for big data research to deliver on its promises for health professions education (HPE) and the health of society. Based on expert consensus and review of the literature, we report 19 recommendations in (1) framing scholarship and research through research, (2) considering unique ethical practices, (3) governance of data sharing collaborations that engage stakeholders, (4) data sharing processes best practices, (5) the importance of knowledge translation, and (6) advancing the quality of scholarship through multidisciplinary collaboration. The recommendations were modified and refined based on feedback from the 2022 Ottawa Conference attendees and subsequent public engagement. Adoption of these recommendations can help HPE scholars share data ethically and engage in high impact big data scholarship, which in turn can help the field meet the ultimate goal: high-quality education that leads to high-quality healthcare. [ABSTRACT FROM AUTHOR]
Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: ehh
DbLabel: Education Research Complete
An: 177037630
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Data sharing and big data in health professions education: Ottawa consensus statement and recommendations for scholarship.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kulasegaram%2C+Kulamakan%22">Kulasegaram, Kulamakan</searchLink><relatesTo>1</relatesTo><i> mahan.kulasegaram@utoronto.ca</i><br /><searchLink fieldCode="AR" term="%22Grierson%2C+Lawrence%22">Grierson, Lawrence</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Barber%2C+Cassandra%22">Barber, Cassandra</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Chahine%2C+Saad%22">Chahine, Saad</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Chou%2C+Fremen+Chichen%22">Chou, Fremen Chichen</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Cleland%2C+Jennifer%22">Cleland, Jennifer</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Ellis%2C+Ricky%22">Ellis, Ricky</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Holmboe%2C+Eric+S%2E%22">Holmboe, Eric S.</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Pusic%2C+Martin%22">Pusic, Martin</searchLink><relatesTo>9</relatesTo><br /><searchLink fieldCode="AR" term="%22Schumacher%2C+Daniel%22">Schumacher, Daniel</searchLink><relatesTo>10</relatesTo><br /><searchLink fieldCode="AR" term="%22Tolsgaard%2C+Martin+G%2E%22">Tolsgaard, Martin G.</searchLink><relatesTo>11</relatesTo><br /><searchLink fieldCode="AR" term="%22Tsai%2C+Chin-Chung%22">Tsai, Chin-Chung</searchLink><relatesTo>12</relatesTo><br /><searchLink fieldCode="AR" term="%22Wenghofer%2C+Elizabeth%22">Wenghofer, Elizabeth</searchLink><relatesTo>13</relatesTo><br /><searchLink fieldCode="AR" term="%22Touchie%2C+Claire%22">Touchie, Claire</searchLink><relatesTo>14</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Medical+Teacher%22">Medical Teacher</searchLink>. Apr2024, Vol. 46 Issue 4, p471-485. 15p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Medical+education%22">Medical education</searchLink><br />*<searchLink fieldCode="DE" term="%22Database+management%22">Database management</searchLink><br />*<searchLink fieldCode="DE" term="%22Scholarly+method%22">Scholarly method</searchLink><br />*<searchLink fieldCode="DE" term="%22Interprofessional+relations%22">Interprofessional relations</searchLink><br />*<searchLink fieldCode="DE" term="%22Goal+%28Psychology%29%22">Goal (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Consensus+%28Social+sciences%29%22">Consensus (Social sciences)</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+protocols%22">Medical protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+quality+control%22">Medical quality control</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analytics%22">Data analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Employee+participation+in+management%22">Employee participation in management</searchLink><br /><searchLink fieldCode="DE" term="%22Trust%22">Trust</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+research%22">Medical research</searchLink><br /><searchLink fieldCode="DE" term="%22Stakeholder+analysis%22">Stakeholder analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Health+care+teams%22">Health care teams</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Canada%22">Canada</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Changes in digital technology, increasing volume of data collection, and advances in methods have the potential to unleash the value of big data generated through the education of health professionals. Coupled with this potential are legitimate concerns about how data can be used or misused in ways that limit autonomy, equity, or harm stakeholders. This consensus statement is intended to address these issues by foregrounding the ethical imperatives for engaging with big data as well as the potential risks and challenges. Recognizing the wide and ever evolving scope of big data scholarship, we focus on foundational issues for framing and engaging in research. We ground our recommendations in the context of big data created through data sharing across and within the stages of the continuum of the education and training of health professionals. Ultimately, the goal of this statement is to support a culture of trust and quality for big data research to deliver on its promises for health professions education (HPE) and the health of society. Based on expert consensus and review of the literature, we report 19 recommendations in (1) framing scholarship and research through research, (2) considering unique ethical practices, (3) governance of data sharing collaborations that engage stakeholders, (4) data sharing processes best practices, (5) the importance of knowledge translation, and (6) advancing the quality of scholarship through multidisciplinary collaboration. The recommendations were modified and refined based on feedback from the 2022 Ottawa Conference attendees and subsequent public engagement. Adoption of these recommendations can help HPE scholars share data ethically and engage in high impact big data scholarship, which in turn can help the field meet the ultimate goal: high-quality education that leads to high-quality healthcare. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Medical Teacher is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=177037630
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/0142159X.2023.2298762
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 471
    Subjects:
      – SubjectFull: Medical education
        Type: general
      – SubjectFull: Database management
        Type: general
      – SubjectFull: Scholarly method
        Type: general
      – SubjectFull: Interprofessional relations
        Type: general
      – SubjectFull: Goal (Psychology)
        Type: general
      – SubjectFull: Consensus (Social sciences)
        Type: general
      – SubjectFull: Medical protocols
        Type: general
      – SubjectFull: Medical quality control
        Type: general
      – SubjectFull: Data analytics
        Type: general
      – SubjectFull: Employee participation in management
        Type: general
      – SubjectFull: Trust
        Type: general
      – SubjectFull: Medical research
        Type: general
      – SubjectFull: Stakeholder analysis
        Type: general
      – SubjectFull: Health care teams
        Type: general
      – SubjectFull: Canada
        Type: general
    Titles:
      – TitleFull: Data sharing and big data in health professions education: Ottawa consensus statement and recommendations for scholarship.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kulasegaram, Kulamakan
      – PersonEntity:
          Name:
            NameFull: Grierson, Lawrence
      – PersonEntity:
          Name:
            NameFull: Barber, Cassandra
      – PersonEntity:
          Name:
            NameFull: Chahine, Saad
      – PersonEntity:
          Name:
            NameFull: Chou, Fremen Chichen
      – PersonEntity:
          Name:
            NameFull: Cleland, Jennifer
      – PersonEntity:
          Name:
            NameFull: Ellis, Ricky
      – PersonEntity:
          Name:
            NameFull: Holmboe, Eric S.
      – PersonEntity:
          Name:
            NameFull: Pusic, Martin
      – PersonEntity:
          Name:
            NameFull: Schumacher, Daniel
      – PersonEntity:
          Name:
            NameFull: Tolsgaard, Martin G.
      – PersonEntity:
          Name:
            NameFull: Tsai, Chin-Chung
      – PersonEntity:
          Name:
            NameFull: Wenghofer, Elizabeth
      – PersonEntity:
          Name:
            NameFull: Touchie, Claire
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: Apr2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0142159X
          Numbering:
            – Type: volume
              Value: 46
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Medical Teacher
              Type: main
ResultId 1