Data trust strengthens collaboration and performance

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In almost every hospital, we hear the same mixed message: we want to be more efficient, and we want to better collaborate across disciplines. Many organizations therefore invest in dashboards, audits and KPIs. But then disappointment often follows: the figures are there, but little changes in practice.

The missing link is strikingly consistent in international research: data credibility. It is not the amount of data that makes the difference, but the extent to which teams understand, trust and can use the figures together. Only then can real collective improvement take place.

You can see this very clearly in our customer reference case AZ Groeninge (link to the case: Customer testimonial AZ Groeninge). With OR Insights, Value4Health's analysis module for the operating room, room occupancy has increased by more than 11% since 2021. But just as important: doctors, OR planners and nurses now speak of one shared reality, rather than competing gut feelings.¹

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Unreliable data hinders improvement

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Implementation research shows that many improvement initiatives get stuck in good intentions. In a qualitative study in Implementation Science, Desveaux et al. describe how doctors receive audit reports, understand the message, but still fail to act. A key finding: "Recipients often cite data credibility and limited resources as barriers impeding their ability to act upon A&F (Audit& Feedback)."

In other words, even if the feedback itself is well designed, little will happen if professionals doubt the origin, completeness or honesty of the figures. This leads to defensive discussions within teams: "Our patients are more complex, those records are incorrect, that's an administrative bias."

Implementation research sums this up nicely in terms of The Normalisation Process Theory: teams go through a process of sense-making, via cognitive participation, to collective action. New routines only become embedded when people find them meaningful and legitimate. Data that does not feel credible blocks that process – the discussion then gets stuck in dispute rather than improvement.

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Metrics quality: from a surveillance tool to a shared learning platform

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Recent European research in healthcare organizations goes one step further. Van Elten and Vander Kolk show in The British Accounting Review that it is not performance management in itself, but rather the quality of the metrics used that determines whether professionals perceive the system as supportive or threatening. They define metric quality as "the quality of metrics (i.e., their accuracy, sensitivity, and verifiability)".

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Their survey of healthcare managers reveals three things:

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• When metrics appear inaccurate, raw or unverifiable, performance management raises mistrust and undermines the relationship between management and healthcare professionals.
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• When metrics are accurate, sensitive, and verifiable, interpersonal trust grows and professionals feel taken seriously and recognize their reality in the figures.
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• This increased trust is then linked to better reported performance at team and organizational level.

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In other words, high-quality, explainable metrics transform performance management from a surveillance tool into a shared learning platform.

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At AZ Groeninge, we observed a similar pattern: doctors have not suddenly become 'fans of KPIs, but they do appreciate tools that support their own clinical expertise with robust data – and that help them use their scarce operating room time more wisely.

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Make data understandable: credibility also arises from the user experience

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Even the best dataset loses its persuasive power if the way it is presented is confusing. TheQualDash study in the NHS (Randell et al.)⁴ shows how interactive dashboards for national audits were only really used when teams understood exactly what they were seeing.

A crucial design choice was surprisingly simple: "clear labels had to be added so that staff were confident about what information was being displayed." Once labels, definitions and filters were clear, teams dared to make decisions based on the dashboard. This had two consequences:

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1. Efficiency
   a. Less time wasted on Excel exports, ad hoc reports and discussions about definitions.
   b. More time for planning and implementing concrete improvement actions.
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2. Collaboration
   a. Clinical and administrative teams looked at the same graphs with the same understanding of what exactly an indicator measured.
   b. Meeting reports became more concrete: "We see 20% more cancellations in room X, what can we change?" instead of "Your figures are wrong."

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This ties in seamlessly with the experience at AZ Groeninge: when surgeons, anesthetists, OR planners and head nurses see the same, well-labelled indicators in OR Insights,the dashboard meeting becomes a joint problem-solving session instead of a blame game. ¹

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Data credibility in practice: how Value4Health builds datasets

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For Value4Health, data credibility is the foundation on which every module – from OR Insights to other tools – is built. In concrete terms, this means:

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1. Joint data definitions
   ‍We start from clinical and operational co-design: we work with doctors, nurses and staff to clarify what 'block occupancy', 'late start', 'changeover time' or 'out-of-hours' means in their context.
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2. Multiple sources, one truth
   Datasets are built by linking various source systems (EHR, operating room planning, HR, logistics, etc.) with consistent keys and business rules. Outliers and inconsistencies are automatically flagged and discussed with the hospital team.
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3. Transparent traceability
   Every KPI in the Value4Health cockpit is clickable:teams can move from an aggregated level to underlying lists and, if desired, to the case level. This makes it possible to quickly end a debate about definitions or exceptions: the source is visible.
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4. Continuous quality monitoring
   ‍Data quality is not a one-off project, but a continuous process. New registration rules, modified workflows or additional modules are constantly tested. Anomalies are identified and clarified together with the hospital.
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5. Documentation and training
   Definitions, filters and calculation rules are explicitly documented and included in training courses and governance structures (e.g. OR steering group at AZ Groeninge). This increases confidence not only in the tool, but also in the process behind the data.

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The result: datasets that are not only technically correct, but also socially legitimate. They are in line with how healthcare professionals experience their work, and they are robust enough to form the basis for decisions in various governance structures.

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Why this matters: from figures to collective action

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International literature and practical cases such as AZ Groeninge tell the same story:

• Without credible data, performance management gets stuck in reporting, accountability and sometimes even polarization.
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• Validated, explainable data creates a shared language in which teams can identify problems, choose priorities and test solutions together.
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• This combination of trust and willingness to take action translates into both efficiency gains (such as higher bed occupancy) and a stronger culture of collaboration.

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For hospitals that want to manage their operating rooms, nursing wards or care pathways in a future-oriented way, it is not enough to simply do 'something with data'. The real question is: How much confidence do our teams have in the data we use to manage our operations – and what are we doing structurally to earn that confidence?

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Value4Health positions itself precisely there: as a partner that delivers valid, reliable and transparently constructed dashboards, so that healthcare organizations can do the hardest work – getting better together.

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Ready to leverage data to improve your team collaboration and performance?

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At a time when profitability is under pressure, Value4Health offers what hospitals need most: insight, overview and clear action points.

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All data comes together in one place, clearly organized, reliable and with concrete insight into profit potential. You can see immediately where money is being lost, where resources are yielding better returns and how efficiency directly translates into savings.

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Request a demo today and experience it for yourself how Value4Health can make your hospital smarter, more efficient and more profitable.

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‍Sources:

1. Customer reference AZ Groeninge – Value4Health & AZ Groeninge, internal case description OK Insights (2025). Customer testimonial AZ Groeninge
   
   
2. Desveaux, L. et al. (2021). Unpacking the intention to action gap: a qualitative study understanding how physicians engage with audit and feedback. Implementation Science, 16(19). https://link.springer.com/article/10.1186/s13012-021-01088-1
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3. van Elten, H. J., & van der Kolk, B. (2024/2025). Performance Management, Metric Quality, and Trust: Survey Evidence from Healthcare Organisations. The British Accounting Review, 57(6), 101511. https://www.sciencedirect.com/science/article/pii/S0890838924002919
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4.  Randell, R. et al.(2022). Design and evaluation of an interactive quality dashboard for national clinical audit data: a realist evaluation (QualDash). NIHR Journals Library / Health Services and Delivery https://www.journalslibrary.nihr.ac.uk/hsdr/WBKW4927

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