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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 eight: Managing risks when handling personal data

Impacts from use of healthcare data

PreviousRecognising personal data in healthcare projectsNextMinimising risk - practical approaches

Last updated 3 years ago

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When considering risk, it is important to assess any possible broader harmful impacts as well as legal risks, for example impact on individuals, sections of society or whole nations. are especially relevant when data activities have the potential to directly or indirectly impact people and society.

For example, population-wide data is often used to allocate health resources, but this can entrench and widen health inequalities. At the start of the COVID-19 pandemic across the United States, population-wide data showed surging rates of infection, but testing facilities and other healthcare supports were not located in the African-American and Latinx communities . In Europe, hides the disproportionate health burden faced by these populations. When data is used at a population-wide level to plan healthcare and allocate resources, it can indirectly impact on those facing the greatest health burden.

When considering broader impacts, think about the people the data is about, people or communities impacted by its use, and organisations using the data. For example, could this data create bias in decisions drawn from it?

In healthcare projects, examples of potentially harmful impacts through unethical collection, use or sharing of data include:

  • denial of access to healthcare, or higher treatment costs, for subsets of the population

  • discrimination against patients with certain medical conditions or characteristics

  • prioritisation of healthcare solutions for subsets of the population.

Key questions to ask:

  • What are you trying to achieve by collecting, using or sharing data?

  • What harmful or positive impacts might there be from this?

  • How will you minimise potentially harmful impacts?

Understanding the potential risks involved when collecting, using or sharing personal data also helps identify what mechanisms can be put in place to mitigate those risks and potential harms. Tools such as the can help you to identify potential harmful or positive impacts. The to this play includes examples of potentially harmful impacts that could occur to people, organisations and society, and sets out potential mitigating actions.

Data Ethics Canvas
appendix
Data ethics
where the majority of infections were occurring
the lack of data on migrant healthcare access and outcomes
The ODI's , which outlines how impact is created from data
theory of change