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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 one: Implementing data governance in healthcare

The value of data governance for data-informed healthcare projects

PreviousPlay one: Implementing data governance in healthcareNextHow to implement a data governance framework for a healthcare organisation or project

Last updated 3 years ago

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Data governance is about having the people, policies, processes, standards and technologies in place to manage data. It can be considered at a project or organisational level, or as part of a wider data sharing ecosystem.

This playbook aims to increase access to healthcare data and we refer to the : ‘the interplay of rules, standards, tools, principles, processes and decisions that influence what data is opened up, how and by whom.’

Data-informed healthcare projects often rely on accessing, using and sharing data from a variety of third party actors. Assessing, building and demonstrating trust in data and trustworthiness of data practices across this ecosystem can be a challenge. Implementing a robust data governance framework is one of the mechanisms by which trust can be built and trustworthiness can be assessed and demonstrated.

Considering data governance through the lens of accessing, using and sharing data as widely as possible helps to ensure the required skills, policies and processes to manage data in trustworthy, ethical and equitable ways throughout its lifecycle are implemented. This also leads to positive outcomes and value creation across the health data ecosystem, while avoiding harmful impacts.

Specifically, ensuring good governance of data in healthcare projects will help to:

  • create efficiencies by streamlining operational models and processes to collect, use and share data across an organisation or wider ecosystem

  • enable collaboration across the healthcare data ecosystem, from research to patient care, through trustworthy data access, use and sharing

  • build trust between health data partners and data subjects

  • ensure data-informed decision making, creating better healthcare outcomes and optimised health services throughout the patient journey

  • optimise business models, resulting in increased private and public revenue

  • enhance research and innovation in healthcare service delivery.

Conversely, without good data governance in place, projects and organisations are exposed to a number of risks, including:

  • Legal risks, for example liabilities not being well understood or well managed, potentially leaving data stewards exposed to expensive compliance failures.

  • Financial risks, for example inefficiently managed data leading to higher costs and/or data not being available to users when required.

  • Reputational risks, for example poor security processes leaving important datasets vulnerable and hindering data sharing or breaking trust between data partners, and thwarting innovation efforts.

  • Operational risks, for example not having timely discussions and agreements about roles, responsibilities and processes for collecting, sharing and using data assets.

Open Knowledge Foundation’s definition of data governance