Industry: Healthcare
Country: US
Project type: Analytics Platform
Duration: Ongoing
AI-assisted Self-service Privacy-respecting
Conversational Healthcare Analytics based on FHIR
We’re reinventing how decision-makers get insights – moving from rigid dashboards built on inconsistent inputs to dynamic interaction with clear, responsive data. Extract real value from datasets you already own – whenever you need it. It’s that simple.
Designed for:
Clinicians Managers Finance teams Researchers Patients
Kodjin provides an advanced healthcare analytics platform that makes it easy to uncover time-linked insights across multiple use cases – from frontline decision support to big-picture planning. An AI assistant lets you speak directly to your data using business terms, without writing a single SQL query.
The three pillars of democratized access to insights powered by Kodjin
01
Architecture
Kodjin Analytics is a thinking layer over your data, built for strategizing, not only reporting.
Designed for high-performance execution, with a semantic layer for healthcare intelligence and an LLM that enables conversational access to strategic insights.
Turning messy data into an asset
Our healthcare analytics solution runs on high-quality FHIR resources – the result of standardizing and cleansing EHR, PGHD, and other healthcare data ingested from diverse sources. This approach is essential in regulated environments and wherever healthcare data comes in many forms and formats.
Reshaping raw data into intuitive business terms
We turn standard analytical data (flat values and records) into concepts, like “patients”, “episodes of care” – something anyone can deal with. Used through a purpose-driven lens, these concepts unlock deeper insights than raw clinical, financial, or administrative data ever could.
02
Interaction
We make working with healthcare analytics easy and available for anyone who needs answers.
No more complex tools or waiting days for reports. Get insights on demand, in an intuitive reporting interface – no need for SQL-savvy analysts or large analytics departments.
Chat with your data
Write your question in plain language – the AI assistant turns it into a query and delivers the right report, reducing the learning curve. Even if you make mistakes in words or don’t use exact terms.
03
Delivery
Kodjin healthcare data analytics platform is a ready-to-use solution – easy to customize and designed for seamless expansion.
We’ll set everything up, take care of the integrations, and tailor the metrics. No need to involve your tech team.
Out-of-the-box analytics
You can get everything you need for analytics from a single vendor, complete with a full-featured FHIR server, all without extra warehouses or gateways. User-facing UIs are included and available from day one, right after deployment.
API-first solution (Headless BI)
Build or add healthcare data analytics tools on top of our engine with full flexibility to scale your analytics ecosystem, connect familiar tools like Power BI or Tableau for continuous KPI monitoring, and send reports directly into patient or provider apps.
We built first-in-class FHIR analytics to go further than SQL can follow
Many have FHIR data – few know how to “cook” it for analytics. We invented a unique approach to cut through FHIR’s nested complexity and make it truly usable for real-world decision-making.
Kodjin’s solution
Semantic-layer FHIR Analytics
- Turns complex FHIR structures into meaningful clinical concepts – like patient, treatment phase, episode of care – for semantic interoperability between departments and roles.
- Transforms raw records into longitudinal outcomes about care progression, cohort behavior, and clinical timing.
- Designed for real-world scale, optimized for querying millions of FHIR records with consistent speed and reliability.
- No data exposure – analytics runs securely within the FHIR layer, with smart caching and full HIPAA/GDPR compliance to ensure access control and patient trust.
Common starting point
SQL on FHIR
- Limited to schema-level queries (can find procedures, but can’t define clinical events like “chemotherapy course”).
- Focuses on availability, not usability.
- Performance degrades as complexity grows.
- Requires extra effort to ensure security, since FHIR was not designed with native analytics in mind.
Unlock longitudinal insights across care, cost, outcomes, and population trends
Approach 
Kodjin Analytics doesn’t just visualize datasets – it reshapes them. Using cohort logic, temporal modeling, and pathway analysis, our healthcare analytics software empowers clinicians, insurers, and researchers to uncover hidden patterns and pinpoint areas for improvement through easily customizable reports. Build charts and tables effortlessly with a wide range of measures, dimensions, and filters.
Line, bar, and area charts
for temporal trends and progression
Sankey diagrams
to map care pathways and operational flows
Pie charts and treemaps
for categorical distributions
Boolean filters
and temporal operators for precise event logic
Tabular views
for granular inspection
Areas and use cases 
Clinical Analytics
Enhance patient care and treatment strategies
With our hospital analytics software you can gain insights into patients’ demographics, treatment pathways, and frequency of procedures over time using advanced visualization tools like bar and Sankey charts. Identify at-risk individuals with Boolean logic and flexible queries. Evaluate treatment regimens and sequences, from diagnosis to care stages, to optimize resource allocation, health interventions, and screening programs for better patient outcomes.
Operational & Revenue Cycle Analytics
Develop efficient payment models
By way of illustration, identify patients with healthcare costs over N and analyze primary cost drivers like surgery, chemotherapy, and hospital stays to develop cost-mitigation strategies. With Kodjin’s medical data analysis software you can track net costs of different procedures over the last N years to evaluate financial impact, aiding in cost management and financial planning with detailed tracking and analysis features.
Population Health Analytics
Monitor diseases and protect public health
For example, evaluate and compare survival rates for different types of cancer over the past decade to understand treatment outcomes and enhance care strategies. Utilize line charts to visualize survival rates, facilitating trend analysis.
Health Monitoring Analytics
Share health data with patients
Our data analytics software for healthcare lets you gain and share insights into the progression of specific test results over time to enhance patient engagement and transparency in their healthcare journey. Utilize time-series visualization with line charts for clear insights into trends and changes in key laboratory values. Monitor patient progress, identify anomalies, and make informed clinical decisions based on temporal patterns.
Explore the Kodjin Data Platform
Kodjin Health Analytics Platform integrates seamlessly with the Kodjin stack, utilizing its historization capabilities. This ensures that data is systematically tracked and managed for accurate, up-to-date analytics.
Transform Validate
Kodjin ELT Solution
A tool created to retrieve data from diverse sources, then transform, validate, and store it in FHIR, HL7v2, or other medical formats. We offer ready-made pipelines tailored to customize to your unique business requirements, streamlining the setup process and saving you time.
Schedule a Demo
Download Kodjin Interoperability Suite
FAQ
What is advanced analytics, and how is it different from traditional BI?
Advanced analytics offers more than healthcare analytics solutions for reporting. Unlike traditional BI tools that track historical KPIs and static dashboards, advanced analytics helps you understand why things happen and model different scenarios. In healthcare, this means not just viewing data, but interpreting it through a clinical, financial, or operational point of view, for example, identifying at-risk patients across time.
How does conversational analytics change the way teams interact with data?
Kodjin healthcare data analytics software brings a new level of flexibility powered by an agentic LLM. Instead of rigid dashboards or waiting on analysts, users can ask questions in natural language and instantly get the right reports. This AI-driven interaction bridges the gap between teams and data, making analytics accessible for clinicians, managers, and researchers alike, without needing technical expertise or SQL skills.
Can FHIR data be used directly for analytics?
Yes, but not out of the box. While FHIR is ideal for storing and exchanging healthcare data in a standardized way, its deeply nested and fragmented structure makes it hard to use for analytics directly. Kodjin Analytics solves this by transforming FHIR records into streamlined, analysis-ready datasets and then into intuitive business concepts that are easy to explore, reason with, and act on.
How does a semantic layer change the game in healthcare analytics?
It marks a true paradigm shift. Kodjin’s semantic layer transforms raw, fragmented healthcare data into clear business concepts like “patient,” “episode of care,” or “treatment phase.” This lets clinicians, managers, and analysts speak the same language and work together without technical translation. With Kodjin, medical analytics software becomes not just accessible, but truly collaborative, turning complexity into clarity and data into decisions.
What is longitudinal analytics in healthcare?
Longitudinal analytics helps you see the full story of a patient or population over time. Instead of isolated events, it connects data points – diagnoses, lab results, treatments – into timelines that show trends, gaps, and progress. This approach is key for understanding care quality, treatment outcomes, and long-term costs.
What is pathway analytics, and why does it matter in healthcare?
Pathway clinical analytics software maps out how patients move through the healthcare system: from diagnosis to treatment and follow-up. It shows which paths are typical, where delays or drop-offs occur, and what leads to better outcomes.
What is temporal analytics, and how is it used in healthcare?
Temporal analytics focuses on the “when.” It looks at the timing and sequence of events like how long it took between diagnosis and surgery, or what happened within 30 days of discharge. In clinical and financial settings, such healthcare data analytics solutions help detect early warnings, monitor standards of care, and spot patterns that impact results.
What is cohort-based analytics software in healthcare?
Cohort analytics groups patients with shared traits — like condition, age, or treatment type — so you can study how those groups behave over time. It’s used for clinical trials, population health, and care optimization, helping you understand what works for whom, and when.
