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Data Governance Playbook
  • Health data governance: a playbook for non-technical leaders
    • Why data governance is important in healthcare
    • Who is this playbook for?
    • How to use this playbook
    • Other related resources
  • Index
  • Play one: Implementing data governance in healthcare
    • The value of data governance for data-informed healthcare projects
    • How to implement a data governance framework for a healthcare organisation or project
      • 1. Data assets
      • 2. People
      • 3. Policies and processes
      • 4. Standards and technologies
    • Resources relating to this play
  • Play two: Understanding and mapping health data ecosystems
    • Data ecosystems in healthcare
    • Data governance and trustworthy data ecosystems
    • Mapping the data ecosystem
      • Use case 1: Mapping the ecosystem of a Covid-19 symptom tracker in the UK
      • Use case 2: Identifying current stakeholders to reduce snakebite mortality and morbidity in India
    • Resources related to this play
  • Play three: Roles and responsibilities in health data governance
    • Roles involved in health data governance
      • Senior data leader
      • Health system leader
      • Policy leader
      • Health project partner
      • Governmental body
      • Senior executive leader
    • How to enlist support from stakeholders
    • Resources relating to this play
  • Play four: Making data interoperable
    • What is interoperability and how is it relevant to healthcare?
    • Standards for data and interoperability
    • Existing standards for data
    • Data adaptors
    • When to use an adaptor
    • Resources relating to this play
  • Play five: Demonstrating the value of health data governance: case studies
    • Primary care data use: MedMij platform
    • Using research data: INSIGHT Health Data Research Hub
    • Using healthcare data for other purposes: Infectious Diseases Data Observatory
  • Play six: Emerging uses of data and technology in the health sector
    • Emerging uses of health data
    • Emerging technologies to support health data management
    • Resources relating to this play
  • Play seven: Assessing the legal, regulatory and policy context for sharing health data
    • Data protection laws and policies
    • Intellectual property
    • Other regulations and laws impacting use of health data
    • Socio-cultural norms
    • Resources relating to this play
  • Play eight: Managing risks when handling personal data
    • Managing personal data responsibly and ethically in healthcare projects
    • What is personal data?
    • Data protection regulations
    • Recognising personal data in healthcare projects
    • Impacts from use of healthcare data
    • Minimising risk - practical approaches
    • Appendix: Risks from personal data exposure and how harms can be mitigated
  • Play nine: How to set up successful data sharing partnerships
    • Understanding how data sharing occurs in the health sector
    • A step-by-step guide to setting up successful data sharing partnerships
      • Step 1. Understand the purpose of sharing data, and with whom
      • Step 2. Define the principles that will guide how data is shared
      • Step 3. Build and maintain relationships with your data sharing partners
    • Appendix: International frameworks for data sharing principles
    • Resources relating to this play
  • Play ten: Sharing health data: data agreements and technologies
    • Common types of data sharing agreements
    • How to choose the best method of sharing data
      • Step 1: Decide how widely you need or want to share data
      • Step 2: Decide on the type of agreement required for sharing data
      • Step 3. Consider how technology can facilitate data sharing and access
    • Appendix: Choosing technology to support data sharing and access
    • Resources relating to this play
  • Play eleven: Cross-border data sharing
    • What is cross-border data sharing?
    • Current trends and global discussions on cross-border data sharing
    • Overcoming challenges with cross-border data sharing
  • How to support trustworthy data sharing: Checklist
  • Slides to communicate the benefits of data governance to key health stakeholders
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  1. Play nine: How to set up successful data sharing partnerships
  2. A step-by-step guide to setting up successful data sharing partnerships

Step 2. Define the principles that will guide how data is shared

PreviousStep 1. Understand the purpose of sharing data, and with whomNextStep 3. Build and maintain relationships with your data sharing partners

Last updated 3 years ago

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Data principles can be helpful as they set out expectations on ways of working to help access, use and share data at regional, international, organisational or project level. There is a wealth of data principles to look to for examples, and they cover different needs; from encouraging best practice to practical application to maximise use of data.

It can be useful to draw on recognised international frameworks that define principles around how data should be shared. Four key international frameworks are:

  • The Five Safes Framework – principles to help manage risk when sharing data.

  • FAIR Framework – principles to help ensure data is findable, accessible, interoperable and reusable (FAIR).

  • CARE Framework – principles that support Indigenous governance of data.

  • WHO Data principles – principles that ensure trust is built between data agencies and those using data.

You can find more information on these international frameworks in the of this play.

When considering your data principles, you could either:

  • select a pre-existing framework of principles to guide data sharing, or

  • develop a unique set of principles, agreeable to all partners, to guide data sharing. In this case it will be important to develop a mutual understanding of each partner’s values and mission to help agree on the principles that work for all.

Key actions to take:

  • Decide what principles will guide your data sharing arrangements and ensure agreement with the organisations involved.

  • Use the principles to help define what data sharing mechanisms and processes you will need to have in place.

  • Consider preparing a one-page summary of the principles you are adopting so that you can explain this to partners or other organisations you are working with in your data ecosystem.

There are also examples of organisations that have developed their own set of principles to guide data sharing. For example, Roche's defines five key principles that then guide data sharing implementation processes. Roche's principles document a commitment to societal benefits, which has led to a focus on ensuring that the purpose of data sharing projects leads to . Other models like the World Health Organization's are intended to affirm trust and provide a foundation for data governance.

Global Policy on Sharing of Clinical Study Information
enhancing personalised healthcare
data principles
Appendix
The Five Safes Framework (left) and the CARE Framework (right)