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Clinical Data Diagnosis

A strategic evaluation of your organisation's clinical data foundation. Designed to identify exactly what needs to be resolved before your next AI, analytics or interoperability project fails at the base.

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  • Documented diagnosis: you know exactly what's failing and why
  • Roadmap prioritised by impact, what to resolve first to unblock what comes next
  • Recommendations you can take to an executive meeting and defend
Only 1-2 active projects per month
Pablo Chanivet

Pablo Chanivet

Biomedical engineer specialised in clinical data architecture. Before assessing platforms independently, he took part in designing them for healthcare and pharmaceutical organisations.

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What we analyse

  • Current data architecture: pipeline structure, operational/analytical separation, scalability.
  • Clinical data model: model consistency, schema evolution, and alignment with standards like FHIR (Patient, Encounter, Observation, Condition, MedicationRequest resources) or the OMOP CDM (person, visit_occurrence, condition_occurrence, drug_exposure, measurement tables).
  • Interoperability strategy: integration with hospitals and clinical systems, terminologies in use (SNOMED CT, LOINC, ICD-10/11, RxNorm) and the mapping strategy between them.
  • Analytics and AI readiness: readiness for advanced analytics, machine learning and data availability for models, including, if your platform is OMOP-based, use of OHDSI ecosystem tools (ATLAS, Achilles) for data characterisation and quality.

¿Es este servicio para ti?

  • Healthcare organisation with active data projects

    You have a data team and active use cases, but every new project requires rebuilding logic that should already exist. The technical debt is visible, but no-one has the full picture of what needs to be resolved.

  • Every new data source requires rebuilding logic from scratch

    Every new integration, hospital, RWE, or external clinical system, becomes a bespoke project. There is no common semantic foundation to reuse what was already built, and cost and time spiral with every new project.

  • Your AI or analytics project is taking longer than expected

    The data team is working, the models exist, but implementation is blocked because the data wasn't what the model needed. You've been stuck for months, or you've already missed a deliverable.

This service isn't suitable if…

  • You only need a dashboard developed.
  • You need to add a programmer by the hour.
  • There is no system or data source to assess yet.
  • You expect a formal regulatory or legal audit.

How timelines work

  • Only 1-2 active projects at a time to guarantee quality.
  • The timeline starts once scope and content are validated.
  • Changes outside the agreed scope may incur an extra charge.
  • I don't take on urgent work.

Packages

Strategic evaluation with concrete deliverables and an actionable roadmap.

Most popular

Clinical Data Diagnosis

6,000–12,000 €

Complete evaluation of your organisation's clinical data foundation. Final price depends on system complexity.

Includes

  • Current data architecture analysis
  • Clinical data model evaluation
  • Interoperability strategy review

Key deliverable

Technical evaluation report with documented findings

Request proposal

Want to start smaller?

EHDS Readiness Check

If all you need right now is EHDS dataset cataloguing and quality, there's a faster, cheaper option: delivered in 5-7 days from €3,000.

View EHDS Readiness Check

Sources and standards cited

Frequently asked questions

Healthcare organisations, hospital groups, regional health services, mid-large pharma or real-scale HealthTechs, that have AI, analytics or interoperability projects underway and discover the data foundation isn't ready to support them. You don't need formal architecture documentation: the discovery process helps us build it.
Existing architecture documentation (even if basic), data model description, current integrations with external systems and medium-term objectives. If you don't have formal documentation, the discovery process helps us structure it.
FHIR (Fast Healthcare Interoperability Resources) is the modern standard for clinical data exchange, organised into resources such as Patient, Encounter, Observation or Condition. OMOP is a standardised data model (tables such as person, visit_occurrence or condition_occurrence) for clinical research and real world data, with an ecosystem of tools, OHDSI: ATLAS, Achilles, for characterisation and quality. Evaluating whether your platform is aligned with these standards, and with terminologies like SNOMED CT, LOINC or ICD-10/11, is key to scaling integrations and enabling analytics.
The Diagnosis is a strategic evaluation with documented deliverables. If after the evaluation you need help implementing the proposed architecture, we can discuss a second engagement for the implementation phase.
The full process takes 2-3 weeks: one week of discovery, one of technical evaluation and one week to prepare the deliverables and the presentation session.
The price depends on system complexity: number of data sources, hospital integrations, data volume, number of environments and depth of analysis required. We confirm this after an initial conversation.

Is your next data, AI or analytics project taking longer than it should?

Tell me what your organisation is trying to do with its data, and where the blockage is.

Assess my case

Request a Clinical Data Diagnosis

Tell me about your organisation: what clinical data you manage, what projects you have underway, and where the main blockage is.

What happens next?

I will reply within 2–3 business days with a personalised proposal and the next steps for your project.

I work with limited availability and do not take on urgent projects. I will confirm availability before starting.

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