Data engineering, clinical AI, FHIR interoperability, and health informatics for ACOs, hospitals, health systems, laboratories, global health programs, and Ministries of Health — built by an MD-trained biomedical informatics scientist, not a software company that hired healthcare consultants.
LEAD launches January 2027. Every REACH and MSSP ACO needs updated equity reporting, new attribution logic, and BCDA-native pipelines. Most are still running CCLF reconciliation in Excel. Integris solves this — at a price small-to-mid ACOs can actually afford.
“Every pipeline we build is also a contribution to the published literature. Every publication is preliminary data for the next product. The flywheel is the differentiator.”
— Integris Health Data Systems · Research-to-Product PhilosophyIntegris Health Data Systems helps ACOs reduce manual reporting burden, hospitals improve data reliability, laboratories deploy AI-assisted diagnostics, and health systems modernize their data infrastructure — delivering the outcomes that matter to clinical and financial leadership, not just technical teams.
Founded by an MD-trained biomedical informatics scientist with a doctorate in Biomedical Informatics, an MBA in Healthcare Administration, FAMIA and ACHIP credentials, 200+ scholarly citations, and hands-on ACO REACH and MSSP operational experience — Integris offers a combination of domain expertise, informatics science, and engineering execution that no generalist data firm can replicate.
MD and PhD training in Biomedical Informatics with active research. We understand what the data means for patients and programs, not just pipelines.
Production-grade BCDA pipelines, dbt models, and equity dashboards — not proof-of-concept demos.
Every product starts as peer-reviewed science. Published, reproducible, and citable.
Most healthcare data firms have engineers who learned healthcare, or clinicians who learned to code. Integris has both in the same person. An MD who understands what a care gap means from a clinical informatics and population health standpoint. A PhD in Biomedical Informatics who knows how to model it in a data system. An ACO REACH practitioner who has run these pipelines in production. A published researcher whose preliminary data is the code we deploy for clients. That combination — clinical, informatics, engineering, and academic — is the reason our solutions work in settings where generic consultants fail.
MD-trained biomedical informatics scientist with a doctorate in Biomedical Informatics and a decade of national health data program leadership. Founder of Integris Health Data Systems and published researcher across health AI, digital pathology informatics, population health analytics, and health equity.
Integris works with organizations across the healthcare and life sciences ecosystem — from community health programs to academic medical centers, wherever expert data engineering and clinical AI can make a meaningful difference.
BCDA pipelines, CCLF reconciliation, attribution analytics, and LEAD model transition infrastructure for small-to-mid ACOs.
Population health analytics, quality reporting, care gap registries, and clinical AI tools for community hospitals, VA facilities, and safety-net systems.
HEDIS and eCQM reporting, HCC risk stratification, EHR data integration, and value-based care analytics for independent and community practices.
Digital pathology data pipelines, AI-assisted morphology classification, whole-slide image infrastructure, and LIS data integration and analytics. In West Africa, our ClinForge LIMS serves labs from patient registration through electronic sign-out and PDF report delivery.
Multi-omics data pipelines, RNA-seq and methylation analysis, FAIR data infrastructure, and translational biomarker discovery workflows.
Research data engineering, IRB-compliant de-identification pipelines, FHIR-based clinical data repositories, and co-investigator partnerships for NIH-funded studies.
FHIR API development, HL7 interoperability, Azure cloud architecture, and AI model development for early-stage health tech companies building clinical products.
Health information system (HMIS) strengthening, FHIR interoperability, digital health assessments, and AI-assisted diagnostics for Ministries of Health, WHO, World Bank, and implementing partners in low- and middle-income countries.
Population surveillance analytics, SDoH data integration, maternal and infant health reporting, program monitoring and evaluation (M&E), and epidemiologic data infrastructure for federal, state, and global health programs.
Custom AI feasibility assessments, data governance frameworks, claims analytics, and health equity audit frameworks for organizations building next-generation care models.
See how Integris helped a mid-Atlantic REACH ACO close critical data infrastructure gaps and achieve LEAD model readiness before the January 2027 launch.
“The attribution gap alone — 301 beneficiaries we weren’t tracking — justified the entire engagement. Those are real patients who were attributed to us but invisible in our care management system.”
— ACO Executive Director (representative, illustrative engagement)All data is synthetic and representative. No PHI was used. This engagement illustrates Integris’s ACO data infrastructure methodology.
Illustrative engagement using synthetic data. Representative of Integris’s BCDA automation methodology.
Illustrative engagement using synthetic data. Representative of Integris’s ACO analytics methodology.
The Long-term Enhanced ACO Design (LEAD) Model launches January 2027 as a 10-year CMS program with new equity reporting requirements, updated attribution methodology, and enhanced care management data needs. Every ACO in REACH or MSSP needs updated infrastructure before that launch — and most don't have it.
A Python library for the CMS Beneficiary Claims Data API with sandbox credentials built in, full CCLF field mapping, and automated reconciliation. Built for ACO data teams moving beyond manual Excel workflows.
PythonBCDACCLFAn open-source gap analysis tool that ingests REACH or MSSP data and outputs a LEAD readiness score with a prioritized remediation checklist — equity fields, attribution methodology, care management requirements.
Open SourceREACH → LEADLiveFull-stack ACO data infrastructure — BCDA ingestion, dbt transformation models, care gap registry, equity dashboard, and utilization analytics. Enterprise-grade capability without enterprise pricing.
AirflowdbtFHIR R4Azure FabricWe offer a complimentary 30-minute LEAD readiness review — a plain-language assessment of what your current data infrastructure needs before January 2027. No sales pitch, no obligation. We show you your actual gaps using real CMS data methods.
Senior-level expertise across the full spectrum of healthcare data science — from production ACO data engineering to clinical AI research and digital pathology informatics.
Eliminate manual CCLF processing and reduce reconciliation errors. Your team gets reliable weekly beneficiary data, automated equity reporting, and LEAD-ready attribution analytics — without expanding headcount.
Give your clinical and financial leadership the dashboards they need to act. Quality measure performance, HCC risk gaps, cost trends, and population health summaries — built from your actual data, not generic templates.
Replace fragmented, unreliable data pipelines with infrastructure that your team can trust and your leadership can act on. Scalable cloud architecture, automated data flows, and a single source of truth for your organization’s health data.
Stop losing data between systems. We connect EHRs, payers, labs, and care management platforms so information flows where it needs to go — meeting CMS and ONC mandates without disrupting your existing workflows.
Translate clinical knowledge into data systems that actually support care decisions. From clinical decision support design to EHR optimization — grounded in both the clinical reality and the informatics science.
Know where your data comes from, trust that it is accurate, and demonstrate compliance when auditors ask. Data governance frameworks built for healthcare — practical, documented, and audit-ready.
AI that improves decisions, not just benchmarks. Predictive risk models that flag the right patients, NLP tools that surface insights from clinical notes, and imaging AI with explanations clinicians can verify — not black boxes.
Give community pathology labs and cancer centers the AI-assisted diagnostic tools previously available only at academic medical centers. Bone marrow cytomorphology AI with 87.6% Top-1 accuracy, whole-slide image pipelines, and explainable outputs clinicians can trust. Approximately 700,000 bone marrow examinations are performed annually in the US — the majority reviewed without AI assistance.
A modular, offline-tolerant Laboratory Information System built for clinical labs in sub-Saharan Africa. Complete specimen lifecycle management — patient registration, order entry, accessioning, result entry, two-level validation, and PDF report generation with electronic signature. Bilingual English/French interface, auto-flagging, delta check, and result notification built in.
Switch to French inside the app — full bilingual ClinForge interface for Francophone labs.
↗ Live Demo · clinforge.integrishds.comDemo access: demo@integrishds.com / ClinForge2026! — no signup required
Delivers laboratory results securely to patients’ phones — no app to install, no account to create. When a lab releases a report through ClinForge, the patient receives a secure link and a one-time code. Results are presented in plain language in English or French, with guidance to follow up with their clinician and the option to download the full signed report.
Interactive demo — sample data only, no real patient information. Works in English and French.
Extract meaningful biological signals from complex multi-omics datasets. Reproducible pipelines that go from raw sequencing data to publication-ready biomarker findings — built on the same academic infrastructure that drives our peer-reviewed research.
Get the right health data expert for your project without a permanent hire. Senior data engineers, FHIR specialists, AI engineers, and informatics consultants placed into your team — vetted for healthcare domain knowledge, not just technical skills.
Not sure what you need? Here are the most common ways organizations engage Integris. Every engagement starts with a discovery conversation to scope the right approach for your situation.
2-week diagnostic — BCDA audit, CCLF gap analysis, six-domain readiness score, written remediation roadmap.
End-to-end automation of CMS Beneficiary Claims Data API ingestion, CCLF reconciliation, and data refresh.
Cloud-native data lake architecture, dbt transformation models, and production analytics layer on Azure.
Evaluate your current interoperability posture against FHIR R4 and USCDI V3 standards with a prioritized implementation plan.
Automate HEDIS, eCQM, and MSSP APP measure calculation and submission from EHR and claims data sources.
Care gap registry, HCC risk stratification, utilization trends, and equity dashboard for a defined patient population.
Evaluate your data readiness, identify the highest-value AI use case, and design a Phase I proof-of-concept.
Whole-slide image ingestion, AI-assisted cell classification, and quality control infrastructure for laboratory AI programs.
Establish data ownership, quality standards, lineage tracking, and compliance documentation for healthcare data assets.
Reproducible, FAIR-compliant pipelines for RNA-seq, proteomics, and methylation data integration and biomarker discovery.
Automated beneficiary alignment pipeline ensuring accurate monthly roster vs. BCDA reconciliation and attribution gap closure.
IRB-compliant data infrastructure for clinical research programs — de-identification, FHIR repositories, and analytic datasets.
Every organization is different. We offer four engagement models so you can start where it makes sense for your budget, timeline, and internal capacity — and evolve the relationship as your needs grow.
Fixed scope, defined deliverables, clear timeline. Best for organizations with a specific problem to solve and a defined budget. You know exactly what you are getting before work begins.
Senior informatics leadership without the overhead of a full-time hire. Fractional Chief Data Officer or Informatics Advisor engagement — strategic guidance, architecture review, and decision support on a retained hourly or monthly basis.
Ongoing operational support for organizations that need continuous data infrastructure — weekly pipeline runs, monthly equity reporting, care gap refreshes, and platform maintenance without building an internal team.
Access senior health data talent on demand. We place and support data engineers, FHIR specialists, AI engineers, bioinformaticians, and health informatics consultants directly within your team — with 70–80% of billing going to the consultant.
Book a 30-minute discovery call. We’ll listen to your situation and recommend the engagement model that makes the most sense — no sales pitch, no obligation.
Enterprise ACO analytics platforms charge six figures annually and require multi-year commitments before you see a single dashboard. Integris delivers production-grade BCDA pipelines, equity reporting, and LEAD-ready infrastructure at a fraction of that cost — with a senior informatics expert, not a junior implementation team, doing the work.
Hours & scope disclosure: Estimated hours reflect a standard engagement at the stated beneficiary range. Actual hours vary with data complexity, existing infrastructure, number of practice sites, and required modules. Integris does not bill hourly — all engagements are project-based or retainer-based with defined deliverables agreed before work begins. A discovery call is required before any Monthly Retainer or Annual Partnership engagement begins.
Integris is not a software company that produces tools and moves on. We are a research-driven organization where every pipeline we build is also a contribution to the published literature, and every publication becomes preliminary data for the next product.
This research-to-product flywheel means our clients benefit from solutions that have been academically validated before deployment — and that the infrastructure we build for you contributes to knowledge that advances the entire field.
Active NIH SBIR research programs include interpretable deep learning for bone marrow cytomorphology (NCI) and Azure-native FHIR + explainable AI governance infrastructure (NLM). The research-to-product pipeline is already in motion: ClinForge, our modular LIMS for sub-Saharan Africa, is live in production — an offline-first, bilingual (EN/FR) laboratory information system built for clinical labs in West Africa. The ClinForge Patient Portal extends this directly to patients: secure, plain-language results on any phone, no app required, in English or French. Academic collaborations and co-investigator partnerships are actively sought.
The same clinical informatics and AI expertise that serves US ACOs and hospitals translates directly to health system strengthening, HMIS modernization, digital health program design, and diagnostic AI deployment in global health settings.
Most global health programs lack access to the combination of clinical knowledge, biomedical informatics expertise, and practical data engineering that Integris provides. We bridge that gap — working with Ministries of Health, multilateral agencies, and implementing partners to design, evaluate, and strengthen health data systems in resource-limited settings.
With operational presence in West Africa and deep familiarity with both US healthcare data standards and global health program contexts, Integris is positioned to deliver services that neither generalist IT consultants nor traditional global health firms can offer.
Integris actively seeks engagements with the following organizations across West and Central Africa and globally. Our expertise in health informatics, FHIR, digital health, and clinical AI is directly applicable to their program mandates.
Evaluate and strengthen health management information systems. Gap analysis, interoperability assessment, data quality audits, and roadmap development for national digital health programs.
Design and implement FHIR-based data exchange between facility-level systems, national registries, and reporting platforms. HL7, OpenHIE, DHIS2 integration experience.
Design indicator frameworks, build data collection and reporting systems, and develop dashboards for M&E of health programs. Supports donor reporting for World Bank, EU, and bilateral programs.
Train health workers and informatics staff on data quality, reporting standards, and digital tools. Develop SOPs and data governance frameworks for district and national health programs.
Build or strengthen disease surveillance systems, outbreak data pipelines, and epidemiologic dashboards. Experience with maternal health, infectious disease, and non-communicable disease programs.
Support Ministries of Health and implementing partners with digital health strategy documents, technical proposal writing, RFP responses, and grant applications for global health programs.
Available for short-term technical assignments with multilateral agencies, implementing partners, and bilateral donors. Biomedical informatics, digital health, data systems, and AI feasibility assessments.
Incorporate social determinants of health into program analytics and reporting. Experience with maternal health disparities, SDoH data infrastructure, and equity-centered performance measurement.
ClinForge, our deployed LIMS, provides the lab-side data infrastructure. The ClinForge Patient Portal closes the loop — delivering results directly to patients’ phones in plain language, in English or French, with no app required. Together they form the basis for clinical AI tools that require to function in resource-limited settings. Integris is also developing interpretable AI tools for diagnostic support in those same environments — where hematopathology expertise is scarce and enterprise diagnostic platforms are inaccessible. Our published research in bone marrow cytomorphology classification (EfficientNet-B3, 87.6% Top-1 accuracy, 21 morphologic classes, with Grad-CAM and SHAP explainability) provides the scientific foundation for a clinical decision-support tool currently under NIH SBIR development. Approximately 700,000 bone marrow examinations are performed annually in the US alone — the vast majority at large academic centers. In West Africa, hematopathology expertise is even more concentrated and inaccessible. Our research agenda explicitly includes validating interpretable diagnostic AI in low-resource settings, including district hospitals and reference laboratories in West Africa, as part of our global health and commercialization strategy.
Every Integris product starts as peer-reviewed science. Our tools are grounded in published, reproducible research using publicly available data.
20+ peer-reviewed publications spanning hematopathology AI, population health analytics, social determinants, maternal morbidity, kidney aging, and clinical informatics. Full list on PubMed.
View All on PubMed →We actively seek co-investigator relationships, pilot partnerships, and academic collaborations that advance the research-to-product pipeline — particularly at AMCs with ACO programs.
Integris brings real-world data pipeline expertise, published preliminary data, and NIH grant experience to academic partnerships. Actively seeking co-PI roles for NIH R01, R21, and AHRQ applications in digital pathology, ACO analytics, and health equity AI.
We welcome computational pathology fellows, clinical informatics residents, and biomedical informatics PhD students seeking industry research partnerships. Projects are publication-focused, use public and synthetic data, and advance both academic and commercial goals simultaneously.
Community hospitals, VA facilities, FQHCs, and ACOs can partner with Integris as validation sites for ongoing research programs. Pilot partners receive early access to tools and contribute to product design — and may be eligible for co-authorship on resulting publications.
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