Own Your Data: Transforming Healthcare Through Data Ownership

The "Own Your Data" (OYD) framework empowers healthcare organisations to transform fragmented, underused data into a strategic asset. By aligning operations, governance and architecture, OYD improves efficiency, patient outcomes and innovation. A successful use case in Peru’s healthcare for the employees of the mining sector shows how OYD reduced delays, streamlined reporting and enabled proactive care, demonstrating its global relevance in modernising healthcare systems.

Key Points

• OYD turns disorganised data into a strategic asset for healthcare organisations.
• The framework includes five clear pillars for data alignment and governance.
• It improves efficiency, accuracy and proactive care through structured transformation.
• A Peruvian case showed reduced delays and better health outcomes using OYD.
• OYD supports scalable, sustainable and people-centred data use across health systems.

In today’s data-driven world, the ability to manage and derive value from information is no longer a technical ambition—it is a strategic necessity. Nowhere is this more critical than in the healthcare sector, where lives depend on accurate, timely and accessible data. As healthcare systems grapple with increasing complexity, the "Own Your Data" (OYD) framework offers a structured pathway toward operational excellence, improved patient outcomes and predictive capabilities.

Rather than allowing data to remain fragmented, misunderstood or underused, OYD encourages organisations to reimagine how data is structured, governed and applied. The framework equips healthcare institutions to go beyond digitisation by fostering a genuine data-driven culture. When implemented effectively, it not only improves efficiency but also enables proactive, informed decision-making at all levels of care delivery.

Understanding the OYD Framework

The Own Your Data (OYD) framework is a comprehensive methodology for turning data into a strategic asset. It recognises that data on its own, without organisation, structure and purpose, is insufficient. OYD is designed to address systemic weaknesses in how organisations perceive and manage their information flows, offering a step-by-step approach that can be adapted across sectors, including healthcare.

The framework unfolds through five core pillars:

1. Understanding and Translating Organisational Processes into Data Terms
2. Aligning the Data Model to Reflect Operational Realities
3. Establishing Governance Structures and Policies
4. Designing Scalable and Unified Data Architectures
5. Democratising Data Use and Driving Innovation

This approach ensures that data is not only accurate and centralised but also meaningful and accessible to those who need it—clinicians, administrators, analysts and decision-makers.

The Critical Role of Data in Healthcare

Healthcare is increasingly data-dependent. From electronic health records (EHRs) to diagnostic imaging, from patient monitoring to public health reporting, the volume and variety of healthcare data are vast and growing. Yet, despite this abundance, many healthcare organisations struggle to harness its full potential.

Common issues include:

• Fragmented information systems that store patient data across multiple, incompatible platforms;
• Lack of standardisation, leading to conflicting definitions and interpretations of the same data;
• Manual reporting processes that consume valuable clinical and administrative time;
• Poor data quality, which undermines trust in information and delays decision-making.

In environments where every second matters, these issues create barriers not just to efficiency, but to safety and quality of care. OYD addresses these challenges by helping organisations rethink their data ecosystems, realign systems and processes, and cultivate a shared understanding of data’s role in delivering better healthcare.

OYD in Practice: A Use Case in Peruvian Occupational Health

To understand how OYD can be applied in real-world healthcare settings, consider its implementation within occupational health services for mining workers in Peru. Mining is a high-risk sector with a significant impact on national employment and economic output. In 2024, approximately 240,000 people were employed in the country’s mining sector, many of them in physically demanding and hazardous roles.

Occupational health providers serving this population faced considerable operational challenges:

• Delays in processing medical examinations due to disconnected systems;
• Inconsistent and duplicated data across platforms;
• Manual report generation leading to extended working hours;
• Lack of a standardised approach to service pricing and clinical operations.

This disorganised environment made it difficult to manage risk, respond quickly to emerging health issues or provide high-quality preventive care.

By applying the OYD framework, the healthcare provider undertook a structured transformation that addressed these core issues. The transformation was carried out in collaboration with Ciclus Group, a consultancy specialising in digital transformation, under the guidance of its CEO, Marita, who supported the structured implementation of the OYD framework.

Phase 1: Understanding and Translating Processes into Data Terms

The first step involved mapping the organisation’s value proposition and operational processes. A multidisciplinary team analysed how data flowed across departments and identified disconnects between business expectations and technical implementations.

Key findings included:

• Varying interpretations of key terms and metrics across departments;
• Four separate IT systems with little interoperability;
• Gaps between clinical workflows and how data was captured.

These insights provided the foundation for realigning processes and data models around shared definitions and priorities.

Phase 2: Aligning the Data Model to the Organisational Model

Once a shared understanding was achieved, attention shifted to the data model. This involved examining how well the structure of databases reflected actual business operations.

The analysis revealed:

• Missing entities in the data model—critical components that were invisible to the system;
• Redundant tables creating conflicts and undermining referential integrity.

Addressing these issues ensured that the data systems were capable of accurately representing and supporting the provider’s core functions, such as patient intake, follow-up care and compliance reporting.

Phase 3: Establishing Data Governance

With structure in place, the next priority was governance—ensuring the consistency, security and usability of data across its lifecycle. A governance framework was introduced, covering:

• Data quality standards;
• Access control policies;
• Cybersecurity and regulatory compliance.

In parallel, a cultural change effort focused on improving data literacy within the workforce. Staff at all levels were trained not just in new tools, but in understanding the significance of data in their day-to-day work.

This combination of technical and cultural measures helped embed data governance as a shared organisational value, rather than a top-down mandate.

Phase 4: Designing a Unified Data Architecture

To eliminate fragmentation and streamline operations, a centralised data architecture was implemented. This included a data warehouse for structured operational reporting and a data lakehouse to handle larger, more diverse datasets.

Benefits included:

• Consolidated access to patient records and clinical history;
• Real-time generation of reports previously compiled manually;
• Simplified monitoring of health indicators across the workforce.

This architectural upgrade also laid the groundwork for scalability, allowing new functionalities and datasets to be incorporated without requiring a complete system overhaul.

Phase 5: Democratising Data Use and Enabling Innovation

The final phase focused on enabling healthcare teams to apply data insights in real time. Through internal training programmes, teams learned to access, interpret and act on the data available to them.

Examples of resulting innovations included:

• Early detection of health risks through data patterns in examination results;
• Alerts for follow-up appointments based on individual medical histories;
• Development of new clinical services based on observed needs and trends.

These improvements marked a shift from reactive care to proactive, personalised health management.

Results: Tangible and Strategic Benefits

The application of the OYD framework in this case led to measurable improvements:

• Operational efficiency: Automated systems reduced the time and effort needed for report generation and data processing;
• Accuracy and integrity: Standardised records helped eliminate duplications and conflicting information;
• Improved patient outcomes: Faster diagnostics and personalised alerts improved the quality of care;
• Transparency: Consistent data supported fair and predictable service pricing;
• Strategic agility: With reliable information, the provider could better forecast needs and allocate resources.

What emerged was not only a more functional information system but also a more agile and confident healthcare operation. By owning their data, the provider gained the clarity and control needed to support workers in a demanding, high-risk sector.

The Broader Implications for Healthcare

While the case in Peru is context-specific, the lessons are broadly applicable. Healthcare providers around the world face similar challenges: disjointed systems, data overload and limited ability to generate actionable insights.

The OYD framework offers a scalable solution to these issues. It is not dependent on specific technologies or vendor platforms but is instead a strategic methodology that can be adapted to different organisational contexts.

By investing in OYD, healthcare providers can:

• Enhance care quality through timely, accurate information;
• Streamline operations by eliminating manual, redundant tasks;
• Support regulatory compliance through well-governed data practices;
• Empower clinicians and staff to make evidence-based decisions.

Crucially, the cultural component of OYD ensures that improvements are sustainable. It’s not just about systems—it’s about people understanding, trusting and using the data at their fingertips.

Conclusion: From Data Chaos to Clarity

The Own Your Data framework is not simply a trend—it is a roadmap to modernising healthcare. In an increasingly digital world, the ability to manage and use data effectively will define the leaders of tomorrow’s health systems.

The Peruvian use case demonstrates what is possible when healthcare organisations commit to structured, comprehensive data transformation. With OYD, information becomes an enabler of strategic care, not a bottleneck.

As healthcare continues to evolve under pressure from ageing populations, chronic diseases and rising costs, data must move from the periphery to the centre of operations. OYD offers a pathway to get there.

The question for healthcare leaders is no longer whether to embrace a data strategy, but how quickly they can implement one that empowers their teams, improves outcomes and sustains impact.

Conflict of Interests

None