Health Data Lab

At the Health Data Lab, we turn health data into a catalyst for change. We believe that data should do more than sit in health records and in reports—it should drive meaningful impact in the lives of people receiving care. Our mission is to empower healthcare providers, policymakers, and communities to make informed, data-driven decisions using high-quality data, with a particular focus on national Medical Quality Indicators (MQIs) and interRAI assessment systems.

Approach

Switzerland, like many health systems worldwide, generates a wealth of structured clinical and administrative data. Yet, data alone doesn’t lead to better outcomes. Routinely recorded clinical date serve often only a single-use. Our Lab bridges the gap between routinely recorded clinical data and real-world impact. We empower healthcare institutions to translate complex health information into actionable insights that improve quality of care, support accountability, and foster continuous learning across the health sector.

Missions

Our vision is a health system where every data point contributes to better care—and where care providers are equipped not just to measure, but to reflect and improve.

We are dedicated to advancing data-informed improvement across healthcare settings. Our work focuses on:

  • Making health data meaningful: transforming routine assessments and national quality indicators into understandable, usable information
  • Strengthening capacity-building: providing training, tools, and coaching to empower healthcare teams, management, leadership and frontline staff to transform their own data into fitting quality improvement initiatives
  • Support for implementation of data systems, quality checks and improvement initiatives
  • Fostering learning systems: cultivating a culture of reflection, feedback, and continuous quality improvement, where data is not just collected, but acted upon
  • Enabling community building: supporting organizations to benchmark and learn from one another across facilities, regions and care settings in peer learning cycles
  • Scientific foundation: Conducting participative action-research grounded in implementation science, to ensure our methods are evidence-based, context-sensitive, and scalable

Recherche

Building on practical experience with initiatives like the NIP-Q-UPGRADE program – where long-term care facilities successfully used MQI data to launch their own quality improvement (QI) projects – we have developed a scalable and adaptable model of data use.

  • INTERCARE is a nurse-led interprofessional care model specifically designed for long-term care facilities (LTCFs), aiming to reduce unplanned hospital transfers. Based on implementation science principles, INTERCARE has proven effective in improving continuity of care.
  • The INTERSCALE project, funded by the Stiftung Pflegewissenschaft Schweiz Foundation and the Swiss National Science Foundation (SNSF), seeks to scale up the INTERCARE model and ensure its sustainable implementation

Teaching

A postgraduate training program is currently being developed.

Team

We work collaboratively with care institutions, researchers, and health authorities to tailor our support to local contexts, ensuring readiness and relevance. Whether it’s helping a facility launch its first QI project or supporting a health system-wide strategy for structured assessments, we are there to guide and empower.

Partners

Contact

Nathalie Wellens
Full professor UAS – Head of Health Data Lab
n [dot] wellens [at] ecolelasource [dot] ch

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