Effective Dashboard Governance in NHS Healthcare

Why this topic matters

In a data-rich environment like the NHS, dashboards offer powerful capabilities for monitoring and driving change. From tracking waiting lists and bed occupancy to monitoring clinical indicators and audit compliance, their utility is vast. Yet, poorly governed dashboards can lead to significant problems:

• Misinformed Decisions: Inaccurate or misinterpreted data can lead to inefficient resource allocation, misguided improvement efforts, or incorrect clinical judgements.
• Clinical Safety Risks: Dashboards displaying incorrect patient data, misleading performance metrics, or delayed information can directly impact patient care and safety.
• Loss of Trust: If users consistently find errors or inconsistencies, confidence in the data and the dashboard initiative itself erodes, undermining engagement and adoption.
• Resource Waste: Developing and maintaining dashboards without clear purpose, defined data sources, or agreed ownership can consume valuable time and resource without delivering commensurate value.
• Regulatory Compliance: NHS organisations have obligations around data quality, clinical safety (e.g., DCB0129/0160), and information governance. Dashboards, as digital health tools, must comply.

Effective governance ensures that dashboards are not just visually appealing, but also reliable, secure, and used responsibly to support safe and high-quality care.

Practical explanation

Dashboard governance encompasses the policies, processes, roles, and responsibilities that dictate how dashboards are designed, developed, deployed, used, and maintained within an organisation. It is not about stifling innovation but rather about creating a controlled environment that maximises the utility and trustworthiness of these critical tools. Key aspects include:

Data Source and Quality Control

The foundation of any reliable dashboard is robust, high-quality data. Governance must establish clear guidelines for identifying, validating, and linking data sources. This involves:

• Source Identification: Clearly documenting where data originates (e.g., EPR, PAS, Lab systems, finance systems).
• Data Definitions: Standardising definitions for metrics, ensuring consistent interpretation across different dashboards and teams (e.g., "what constitutes an emergency admission?").
• Quality Assurance: Implementing processes for data validation, reconciliation, and error checking at source and during extraction/transformation. This includes data completeness, accuracy, consistency, and timeliness.
• Data Refresh Cycles: Defining how often data is updated and when users can expect new information.

Roles and Responsibilities

Clarity on who is accountable for what is crucial. Typically, these roles might include:

• Dashboard Sponsor/Owner: A senior clinician or manager accountable for the dashboard's purpose, strategic alignment, and overall success.
• Data Owner: The individual or team responsible for the integrity and accuracy of the source data feeding the dashboard.
• Technical Lead/Developer: Responsible for the technical build, data extraction, transformation, and loading (ETL) processes, and technical maintenance.
• Content Owner: Responsible for the design, metrics, visualisations, and interpretation guidance of a specific dashboard.
• User Support Lead: Provides training, documentation, and first-line support for dashboard users.
• Governance Body/Committee: Oversees the entire process, arbitrates disputes, approves new dashboards, and ensures compliance.

Clinical Safety and Risk Management

Given that many NHS dashboards inform clinical decisions or impact patient care indirectly, clinical safety must be paramount. This aligns with NHS England's Digital Technology Assessment Criteria (DTAC) and clinical safety standards (DCB0129/0160).

• Risk Assessment: Conduct thorough clinical safety risk assessments, identifying potential hazards associated with inaccurate data or misinterpretation.
• Mitigation Strategies: Implement controls such as clear caveats, explicit data definitions, user training, and verification processes.
• Incident Reporting: Establish clear pathways for users to report data discrepancies or potential safety issues arising from dashboard use.
• Human Review: Always emphasise that dashboards support, but do not replace, clinical judgement. Local policy, formulary and specialist advice should be followed.

Access Control and Information Governance

Protecting sensitive patient and organisational data is a legal and ethical imperative.

• Authentication and Authorisation: Implement robust mechanisms to ensure only authorised personnel can access specific dashboards and data levels.
• Role-Based Access: Tailor access based on job roles and need-to-know principles.
• Anonymisation/Pseudonymisation: Ensure that data is appropriately anonymised or pseudonymised where possible, especially for aggregate or public-facing dashboards.
• Audit Trails: Maintain logs of dashboard access and data changes for accountability and security monitoring.
• GDPR and DPA 2018 Compliance: All data handling must comply with relevant data protection legislation.

Documentation and Training

Comprehensive documentation and ongoing training are critical for effective adoption and correct usage.

• User Guides: Provide clear, concise guides explaining how to navigate the dashboard, interpret metrics, and understand any limitations.
• Data Dictionaries: Detailed definitions for every metric, including source, calculation methodology, and refresh frequency.
• Training Programmes: Offer initial and refresher training for new users and whenever significant dashboard changes occur.
• Communication Plan: Regular updates on dashboard changes, data quality issues, or new features.

Common pitfalls

Despite good intentions, several challenges can undermine dashboard governance:

• Lack of Clear Ownership: Dashboards are built, but no one is formally accountable for their ongoing accuracy or utility.
• "Build it and they will come" mentality: Dashboards are developed without a clear understanding of user needs, leading to low adoption or misinterpretation.
• Data Silos and Inconsistent Definitions: Different departments use varying definitions for the same metrics, making cross-organisational comparisons unreliable.
• Over-reliance on Automated Data: Believing that because data is automatically extracted, it is inherently accurate, without robust quality checks.
• Ignoring Clinical Safety: Overlooking the potential for dashboards to cause harm if data is wrong or misunderstood.
• Static Governance: Governance processes are established at launch but not reviewed or adapted as needs or data sources change.
• Technical Debt: Poorly documented or maintained ETL processes make future changes difficult and risky.
• "Vanity Metrics": Including metrics that look good but don't drive actionable insights or relate to strategic objectives.

Step-by-step approach for effective dashboard governance

Establishing and maintaining robust dashboard governance requires a systematic approach. Consider these steps:

1. Define Purpose and Scope

• Objective: Clearly articulate why the dashboard is needed. What questions will it answer? What decisions will it inform? What strategic objective does it support?
• Target Audience: Identify who will use the dashboard and their specific information needs.
• Scope: Define the boundaries – what data will be included/excluded? What level of detail is required?

2. Establish Governance Structure and Roles

• Form a Working Group: Bring together key stakeholders: clinical leads, operational managers, data analysts, IG leads, clinical safety officers, and IT representatives.
• Assign Roles: Clearly define and communicate the sponsor, data owner, content owner, technical lead, and user support roles for each significant dashboard or dashboard family.
• Create a Governance Board: For larger organisations, a dedicated committee or existing QI/Clinical Governance committee should oversee dashboard strategy, approval, and standards.

3. Identify and Validate Data Sources

• Map Data Flow: Document the journey of data from its source system to the dashboard.
• Verify Accuracy: Conduct rigorous data quality checks, including sampling, reconciliation, and validation against source systems.
• Standardise Definitions: Create a central data dictionary that defines every metric, its calculation, and its source.

4. Design for Clarity and Safety

• User-Centred Design: Involve end-users in the design process to ensure usability and relevance.
• Visualisation Best Practice: Use appropriate charts and visualisations to convey information clearly and avoid misleading representations.
• Embed Caveats: Clearly state data limitations, refresh rates, and any assumptions made.
• Clinical Safety Assessment: Perform a DCB0129/0160-compliant clinical safety assessment, documenting hazards and mitigations. This applies whether the dashboard directly informs clinical care or impacts it indirectly.

5. Implement Technical Controls

• Robust ETL Processes: Ensure data extraction, transformation, and loading processes are automated, scheduled, and error-handled.
• Security: Implement strong authentication, authorisation, and audit logging.
• Version Control: Manage changes to dashboards and underlying code through version control systems.

6. Document, Train, and Communicate

• Comprehensive Documentation: Create detailed user guides, data dictionaries, and technical documentation.
• Training Programme: Develop and deliver training sessions for all users, emphasising data interpretation, limitations, and appropriate use.
• Communication Plan: Regular updates on changes, performance, and feedback channels.

7. Monitor, Review, and Iterate

• Performance Monitoring: Track dashboard usage, data refresh success rates, and user feedback.
• Regular Review: Schedule periodic reviews of dashboards with the governance board and content owners to ensure continued relevance, accuracy, and compliance.
• Feedback Mechanism: Provide an easy way for users to report issues, suggest improvements, or ask questions.
• Continuous Improvement: Treat dashboard governance as an iterative process, adapting to new data sources, user needs, and organisational priorities.

Example in clinical practice

Consider an NHS Trust developing a new 'Sepsis Pathway Compliance Dashboard'.

Initial State: Different wards manually track sepsis screening and management. Data is fragmented, inconsistent, and delayed.

Governance Implementation:

1. Purpose Defined: To monitor compliance with the national sepsis screening and management pathway, identify areas for improvement, and reduce delays to treatment.
2. Governance Structure: A multidisciplinary Sepsis Steering Group (clinical leads, QI, IT, data analysts) becomes the governance body. A senior Sepsis Nurse is the Content Owner, the Clinical Lead for Acute Medicine is the Sponsor, and a BI Analyst is the Technical Lead.
3. Data Sources Identified: Data extracted from EPR (electronic patient record) for observations, prescriptions (antibiotics), and time stamps for key interventions. Specific data fields are agreed upon.
4. Data Quality: Automated scripts are developed to pull data. Daily checks compare a sample against manual records for the first month. Definitions for 'sepsis screening completion' and 'antibiotic administration within 1 hour' are standardised.
5. Clinical Safety: A DCB0129 assessment identifies risks, e.g., miscalculation of time to antibiotics leading to false assurance. Mitigation: Dashboard includes a clear disclaimer, a "Data Last Updated" timestamp, and a feedback button for discrepancies. Clinical users are trained to cross-reference with EPR for individual patient decisions.
6. Access and IG: Access limited to clinical leads, ward managers, and QI team members involved in sepsis improvement, via role-based authentication. Aggregate data is displayed at ward level, never individual patient identifiable data.
7. Documentation and Training: A user guide is developed, and mandatory training sessions are run for all key users, focusing on interpreting metrics like 'percentage of patients with sepsis receiving antibiotics within 1 hour' and 'number of patients requiring a rapid response call post-sepsis recognition'.
8. Monitoring and Review: The Sepsis Steering Group reviews the dashboard monthly, analysing trends, acting on improvement opportunities, and providing feedback to the BI team on enhancements or identified data issues.

This structured approach ensures the dashboard is a trustworthy, safe, and effective tool for improving sepsis care rather than a source of confusion or risk.

How Lazomis can help

Lazomis provides a structured framework and tools that can significantly streamline and enhance your dashboard governance efforts:

• QI Project Setup: Use Lazomis to define your dashboard's purpose, objectives, and scope as a structured QI project. Document your stakeholder group, assign roles, and set clear goals.
• Documentation & Knowledge Base: Lazomis can serve as a centralised repository for your dashboard documentation, including user guides, data dictionaries, clinical safety assessments, and governance meeting minutes. This ensures all critical information is easily accessible and version-controlled.
• Stakeholder Engagement & Communication: Track stakeholder engagement, communication plans, and training schedules within Lazomis. This helps ensure all relevant personnel are informed and trained.
• Progress Tracking & Reporting: If your dashboard is part of a larger QI initiative, use Lazomis to track the impact of the dashboard on your improvement metrics, linking the data directly to your governance objectives.
• Feedback Loops: Integrate feedback mechanisms, allowing users to report issues or suggest improvements directly, creating an auditable trail for continuous improvement.

By leveraging Lazomis, NHS teams can systematise the governance process, reduce administrative burden, and ensure that their dashboards remain reliable, safe, and impactful for driving quality improvement.

Key takeaways

• Robust dashboard governance is crucial for ensuring data accuracy, clinical safety, and user trust in NHS healthcare.
• It involves defining clear roles, managing data quality, assessing clinical risks, and implementing strong information governance.
• Without proper governance, dashboards can lead to misinformed decisions, clinical safety risks, and wasted resources.
• A structured approach covering purpose definition, stakeholder engagement, data validation, and continuous review is essential.
• Always remember that dashboards are decision-support tools; they do not replace professional clinical judgement.