Creating FHIR-native analytics platform for a US-based healthtech startup to transform specialty practice EHR data into commercially viable intelligence

Building an end-to-end FHIR-native analytics platform

Outcomes for end-clients:

9X higher match

of patients for clinical trials compared to regular screening

$35K/year

per each extra clinical-trial patient enrolled

Project summary Business goal Solution Innovation Value delivered

Project summary

Zoadigm, a US-based healthtech startup focused on transforming fragmented specialty practice EHR data into actionable intelligence, engaged Edenlab to design and deliver its flagship product. We built an end-to-end FHIR semantic-layer analytics platform that consolidates disparate healthcare data and equips providers with intuitive no-code analytics and real-time dashboards, enabling data-driven clinical and financial decision-making.

Location

USA

Partnership period

2019 – Ongoing

Industry

Healthcare

Client type

IT Vendor | Analytics Startup

Associated services

Analytics product development HL7 FHIR solution development services Data platform development Product development Data & Analytics

Edenlab consistently displays traits that are exceptionally valuable and rare in the software development industry — commitment, competence, creativity, and integrity. Their dedication to projects is commendable, and their technical expertise is evident in the results. With a creative approach to challenges and a strong sense of integrity in all dealings, they’ve proven to be a reliable and innovative partner.

James Maldonado

Zoadigm, Chief Platform Officer

Business goal
and challenge

Zoadigm envisioned a new generation of healthcare analytics, where specialty practices could transform clinical, financial, and life sciences data into commercially viable intelligence, and generate shared insights across a wider professional community.

Their initial attempt with another vendor fell short, as the chosen architecture couldn’t support the envisioned functionality. To realise this innovation, Zoadigm needed a scalable, FHIR-native solution that could unify diverse data sources and deliver advanced analytics through an accessible, clinician-friendly platform.

The solution

The platform enables clinicians to build reproducible cohorts and explore care pathways without technical expertise, while gaining access to interactive dashboards that highlight both clinical patterns and financial performance. Zoadigm’s platform lowers the entry barrier to advanced healthcare analytics and helps practices unlock insights that were previously out of reach.

Key features of the platform include:

Cohort & Pathway Builder

A no-code tool for creating reproducible, computable cohorts from EHR, claims, and life sciences data, updated on schedule.

Cohort & Pathway Explorer

Interactive dashboards and tables to analyse cohorts, compare pathways, and identify treatment patterns.

FHIR Semantic Analytics Engine

The core of the platform that consolidates diverse healthcare data from multiple sources, harmonises it into a single consistent model, and makes it accessible through clear business concepts that clinicians and administrators can easily use for analysis and decision-making.

ELT Module

Custom integration engine with the connectors for various EHRs.

Use cases for end-clients (specialty practices):

Accelerated identification of clinical trial candidates

Removing the rate-limiting step of physicians manually spotting candidates, enabling faster identification and a much larger pool of eligible patients.

Care pathway optimisation

Analysing treatment journeys across specialties, comparing pathways, and discovering variations that impact outcomes or costs.

Population health insights

Building reproducible cohorts (chronic conditions, high-risk patients) to support preventive care strategies and value-based care initiatives

Financial and operational analytics

Linking clinical and claims data to track reimbursement models, evaluate service utilisation, and improve practice revenue management.

Edenlab’s innovation

Edenlab devised a unique architecture that allows Zoadigm’s platform to translate complex, nested FHIR clinical, financial, and life-science data into a unified, intelligible model, making advanced analytics possible without requiring users to know SQL.

Challenges Solutions

Challenge

Making sense of complex FHIR data

The FHIR standard was chosen for its interoperability, but its highly nested structure made it extremely difficult to run meaningful analytics.

Solution

Data materialization for analytics

Edenlab engineered the physical data layer based on the FHIR standard, enabling the further creation of semantic layer on top of it. This makes the information consistent and ready for analysis, while preserving clinical meaning.

Challenge

Data quality gaps and inconsistencies

Source systems often lacked complete timestamps, discharge data, or used inconsistent coding. Without addressing these gaps, any cohort or pathway analysis would be unreliable.

Solution

Data validation and enrichment rules

We implemented data validation and enrichment rules. Algorithms inferred missing attributes (such as treatment end dates) and harmonised inconsistent fields, ensuring that analytics delivered clinically trustworthy results.

Challenge

Making analytics accessible for non-technical users

Clinicians and administrators should be able to explore pathways or build cohorts without SQL knowledge or technical training. A purely developer-driven interface would have blocked adoption.

Solution

Semantic layer with no-code tools

We introduced a semantic layer that translates raw FHIR data into business concepts, combined with no-code tools (“liveboards”) that allow users to build cohorts, apply filters, and explore care pathways visually. This reduced dependency on technical teams, ensured consistent metrics across the organisation, and gave clinicians self-service access to insights.

Challenge

Enabling real-time interactivity at scale

The platform needed to provide instant insights even when running across millions of records from multiple practices. Traditional database queries on FHIR data could take minutes, which was unacceptable for an interactive tool.

Solution

Pre-aggregation, indexing and caching strategies

Edenlab optimized query execution by introducing pre-aggregation, indexing and caching strategies within a high-performance columnar database. This ensured sub-second responses on complex multidimensional queries and enabled interactive dashboards.

Challenge

HIPAA compliance

Handling sensitive patient information meant the platform had to fully comply with HIPAA and safeguard Protected Health Information (PHI). Any gaps in privacy or security would undermine adoption and trust.

Solution

Data access controls, de-identification

The semantic layer enforces data access controls, de-identification where necessary, logging, and audit trails. Sensitive data is handled through controlled access, and all data transformations abide by HIPAA requirements.

Kodjin FHIR Server for data validation, consolidation and high-performance processing

ClickHouse as the columnar analytics engine to decompose (materialize) nested FHIR data

Kubernetes for scalability and modular deployment

Prometheus, Grafana for monitoring & observability

React for interactive dashboards (liveboards)

Value delivered

Edenlab delivered a full-cycle product development project for Zoadigm, covering business analysis, software architecture, development, and implementation.

Through our proven methodology, responsiveness, and technical innovation, Edenlab brought Zoadigm’s vision to market and remains a trusted partner in scaling the platform and expanding its capabilities.

Efficient discovery and fast delivery

Through a structured discovery process, we quickly aligned with Zoadigm’s product vision and translated it into a clear technical roadmap. Within the first three months, our team delivered a validated architecture and working prototypes, reducing the initial time-to-market by 40% compared to the client’s previous vendor.

Innovative technology fit

Edenlab identified the right technical approach to realise Zoadigm’s vision: a FHIR-native analytics engine that harmonises EHR, financial, and life sciences data into a unified semantic format. This innovation enabled the platform to achieve self-service access to insights, high query performance and supporting millions of patient records, making it future-proof and easy to extend.

Long-term business impact

For Zoadigm’s clients, the platform streamlines how eligible study participants are surfaced, enabling significantly higher match volumes and faster identification. Each additional enrolled patient generates ~$35K in annual sponsor-funded revenue, while quicker pathway analysis helps clinicians spot treatment variations and improve outcomes.

Future plans

Zoadigm’s next growth stage is focused on enabling value-based and episodic care models, helping providers move from volume-driven services to outcome-driven healthcare. The platform will empower practices to manage episodic care contracts, coordinate treatment across teams, and improve patient experiences while reducing inefficiencies.

By expanding data connectivity through the FHIR Patient API, Zoadigm will integrate insights from external clinics, providing a truly holistic, 360-degree view of patient journeys and enabling providers to make more informed, data-driven decisions.

Related tags

Healthcare analytics Specialty practices Value-based care Clinical trials Patient matching Cohort analytics Care pathways FHIR Analytics Semantic layer EHR integration No-code analytics Population health analytics

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Creating FHIR-native analytics platform for a US-based healthtech startup to transform specialty practice EHR data into commercially viable intelligence

9X higher match

$35K/year

Project summary

Business goal
and challenge

The solution

Key features of the platform include:

Use cases for end-clients (specialty practices):

Edenlab’s innovation

Making sense of complex FHIR data

Data materialization for analytics

Data quality gaps and inconsistencies

Data validation and enrichment rules

Making analytics accessible for non-technical users

Semantic layer with no-code tools

Enabling real-time interactivity at scale

Pre-aggregation, indexing and caching strategies

HIPAA compliance

Data access controls, de-identification

Value delivered

Efficient discovery and fast delivery

Innovative technology fit

Long-term business impact

Future plans

Related tags

More success stories

National E-Health system

FHIR-based claims auto-adjudication engine

Let’s talk about your goals

Creating FHIR-native analytics platform for a US-based healthtech startup to transform specialty practice EHR data into commercially viable intelligence

9X higher match

$35K/year

Project summary

Business goal and challenge

The solution

Key features of the platform include:

Use cases for end-clients (specialty practices):

Edenlab’s innovation

Making sense of complex FHIR data

Data materialization for analytics

Data quality gaps and inconsistencies

Data validation and enrichment rules

Making analytics accessible for non-technical users

Semantic layer with no-code tools

Enabling real-time interactivity at scale

Pre-aggregation, indexing and caching strategies

HIPAA compliance

Data access controls, de-identification

Value delivered

Efficient discovery and fast delivery

Innovative technology fit

Long-term business impact

Future plans

Related tags

More success stories

National E-Health system

FHIR-based claims auto-adjudication engine

Let’s talk about your goals

Business goal
and challenge