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Healthcare OMOP Implementation Services

Healthcare OMOP implementation services convert observational health data into the OMOP Common Data Model (CDM), so it can be analyzed with standardized tools and shared for research and real-world evidence. An OMOP implementation combines ETL from source systems, mapping to standardized vocabularies, data quality assessment, and OHDSI analytics tooling, so organizations transform EHR and claims data into a standardized, research-ready model that supports reproducible studies and participation in research networks.

Observational research and real-world evidence need standardized data, and the OMOP Common Data Model is the leading open standard for it. Taction Software builds OMOP implementation services that convert source data to the CDM with standardized vocabularies and quality assessment. We have delivered healthcare data engineering since 2013, and this builds on our broader healthcare software development practice.

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What Is OMOP Implementation

OMOP is the Observational Medical Outcomes Partnership Common Data Model (CDM), an open standard maintained by the OHDSI community for representing observational health data, EHR, claims, and registries, in a consistent structure with standardized vocabularies. Implementing OMOP means building ETL that transforms source data into the CDM and maps local codes to standardized vocabularies such as SNOMED, RxNorm, and LOINC. The payoff is significant: once data is in the CDM, it can be analyzed with the OHDSI open-source tool ecosystem, and studies become reproducible and portable across institutions, enabling participation in research networks and federated studies. OMOP standardization powers observational research and real-world evidence, complements clinical registries, and depends on strong data quality to produce trustworthy results.

Common Data Model

The OMOP CDM represents observational data in a consistent structure, so data from different sources and institutions can be analyzed the same way.

ETL to OMOP

Implementation builds ETL that transforms EHR, claims, and other source data into the CDM, the core technical work of an OMOP project.

Standardized Vocabularies

It maps local codes to standardized vocabularies such as SNOMED, RxNorm, and LOINC, so concepts mean the same thing across sources and studies.

OHDSI Tooling

Once in the CDM, data works with OHDSI open-source tools for cohort building, analysis, and characterization, enabling standardized, reproducible research.

Reproducible Research

The CDM makes studies reproducible and portable across institutions, so analyses run consistently and can be shared and validated by others.

Network Research

It enables participation in research networks and federated studies, so an organization’s data contributes to multi-site observational research.

Core OMOP Implementation Services

Taction Software builds OMOP implementation as a full engagement shaped to your data and research goals, whether you are an academic medical center, a research organization, a life sciences company, or a research-active health system. We assess your source data and goals first, then build the implementation that fits. The consistent theme is a quality-validated CDM, because a poorly mapped OMOP database produces unreliable research. We build ETL, vocabulary mapping, data quality assessment, and OHDSI tooling setup, and connect the CDM to broader data solutions and to research-ready infrastructure like a data lake.

01

Source Data Assessment

We assess source data, EHR, claims, and registries, and your research goals, defining what must be mapped into the OMOP CDM and how.

02

ETL Development

We build ETL transforming source data into the OMOP CDM, the core technical work, handling the structural and semantic conversion accurately.

03

Vocabulary Mapping

We build vocabulary mapping to SNOMED, RxNorm, LOINC, and other standards, so local codes become standardized concepts consistent across studies.

04

Data Quality Assessment

We run data quality assessment on the CDM using OHDSI quality tooling, so the OMOP database is validated and trustworthy for research.

05

OHDSI Tooling Setup

We set up OHDSI analytics tooling for cohort building, characterization, and analysis, so researchers can work with the CDM effectively.

06

Network Research Enablement

We enable research network participation, so standardized data can contribute to federated, multi-site observational studies and RWE.

Benefits of OMOP Implementation

A well-executed OMOP implementation delivers value that ad hoc research data cannot, because standardization makes analysis reproducible, portable, and tool-supported. Data in the CDM works with the mature OHDSI tool ecosystem, so researchers build cohorts and run analyses with proven tools rather than bespoke code. Standardized vocabularies make concepts consistent, so studies mean the same thing across sources. Reproducibility and portability let studies be validated and shared, and enable network research across institutions. Quality assessment ensures the CDM is trustworthy. OMOP also strongly supports real-world evidence generation. Together, these turn source data into a standardized, research-ready asset that produces reproducible, shareable, tool-supported observational research and real-world evidence.

Tool-Supported Research

The CDM works with the mature OHDSI ecosystem, so researchers use proven tools for cohorts and analysis instead of bespoke, unvalidated code.

Consistent Concepts

Standardized vocabularies make clinical concepts consistent across sources, so studies mean the same thing regardless of the originating system.

Reproducible Studies

The CDM makes studies reproducible and portable, so analyses can be validated, shared, and rerun consistently across institutions.

Network Participation

OMOP enables research network and federated study participation, so an organization’s data contributes to large, multi-site observational research.

Trustworthy Data

Data quality assessment validates the CDM, so research builds on a trustworthy standardized database rather than unverified mapped data.

Real-World Evidence

OMOP strongly supports real-world evidence generation, turning observational data into standardized evidence for research and regulatory use.

Our OMOP Implementation Process

Taction Software follows a quality-focused process refined across more than a decade of healthcare delivery. We begin by assessing your source data and research goals, and planning the ETL and vocabulary mapping. We then build ETL to the CDM and vocabulary mapping to standardized terminologies, the core and most demanding work. Development runs in iterative phases, and we run data quality assessment using OHDSI quality tooling to validate the CDM, because an unvalidated OMOP database produces unreliable research. We set up OHDSI analytics tooling and support researchers in using it. We validate mapping and quality against standards, then support ongoing refresh as source data updates. Throughout, we treat quality validation as essential, because the value of OMOP rests entirely on the CDM being accurate and trustworthy.

Assessment and Planning

We assess source data and research goals and plan ETL and vocabulary mapping, defining the path from source systems to the OMOP CDM.

ETL and Mapping Build

We build ETL to the CDM and vocabulary mapping to standardized terminologies, the core technical work, handling structure and semantics accurately.

Iterative Development

We build the implementation in phases, validating structure and mapping incrementally rather than attempting the full CDM conversion at once.

Quality Assessment

We run data quality assessment with OHDSI quality tooling, validating the CDM so research builds on trustworthy standardized data.

Tooling and Enablement

We set up OHDSI analytics tooling and support researchers, so the CDM is genuinely usable for cohorts, characterization, and analysis.

Refresh and Support

We support ongoing CDM refresh as source data updates and vocabularies change, keeping the OMOP database current and trustworthy.

Technology and Compliance

OMOP implementation handles sensitive observational data for research, so security, standards, and quality are foundational. Taction Software builds on a HIPAA-aligned foundation, with encryption, access controls, audit logging, and Business Associate Agreements where applicable, and supports de-identification and governance for research use. Our architecture builds ETL from EHR, claims, and other sources into the OMOP CDM, maps to standardized vocabularies via OHDSI vocabulary resources, and runs on healthcare-grade cloud. We validate the CDM with OHDSI data quality tooling, because an unvalidated OMOP database produces unreliable research. We set up the OHDSI analytics ecosystem for cohort building and analysis. We treat quality validation as essential and support ongoing refresh, so the standardized data stays accurate and trustworthy for reproducible research and real-world evidence.

HIPAA-Aligned Security

Encryption, access controls, BAAs, and de-identification protect the sensitive observational data converted into the OMOP CDM for research.

Standards-Based ETL

We build ETL from EHR, claims, and other sources into the OMOP CDM using OHDSI standards and vocabulary resources accurately.

Vocabulary Standardization

We map to SNOMED, RxNorm, LOINC, and other standards, so clinical concepts are consistent and comparable across sources and studies.

OHDSI Quality Tooling

We validate the CDM with OHDSI data quality tooling, so the standardized database is trustworthy for reproducible research.

Analytics Ecosystem

We set up the OHDSI analytics ecosystem for cohort building, characterization, and analysis, so researchers can use the CDM effectively.

Ongoing Refresh

We support ongoing CDM refresh as source data and vocabularies update, keeping the OMOP database current and trustworthy over time.

Why Choose Taction Software

Taction Software is a US-based healthcare software company founded in 2013, with offices in Chicago, Cheyenne, Austin, and Sacramento. We build healthcare software exclusively, so data engineering, standards, and compliance are part of our default process rather than afterthoughts. We have delivered more than 200 healthcare projects, including EHR and EMR platforms such as Voyant Health, FDA-registered mobile applications, and behavioral health tools. That data engineering depth matters in OMOP implementation, where accurate ETL, careful vocabulary mapping, and rigorous quality validation determine whether the CDM produces trustworthy research. We work as a quality-focused partner, validating the CDM rigorously rather than delivering an unverified mapping.

01

Healthcare Specialization

We build healthcare software only, so data standards and compliance are built into our OMOP implementation from the start.

02

Data Engineering Depth

We build accurate ETL and vocabulary mapping from complex source data into the OMOP CDM.

03

Standards Knowledge

We work with OHDSI standards, vocabularies, and tooling, so the CDM is correct, comparable, and research-ready.

04

Quality Rigor

We validate the CDM with OHDSI data quality tooling, because unverified mapping produces unreliable research.

05

US-Based Team

US offices and US-based delivery support close collaboration and clear accountability on research-critical data work.

06

Long-Term Partnership

We support ongoing CDM refresh as source data and vocabularies evolve, keeping the OMOP database trustworthy.

Pricing

OMOP implementation pricing depends on scope, source complexity, and mapping effort. Taction Software scopes each engagement to your data, and typical ranges are as follows. A focused implementation, such as ETL and mapping for a defined source with quality assessment, generally falls between $40,000 and $80,000. A full OMOP implementation with multiple sources, comprehensive vocabulary mapping, quality validation, and tooling setup typically ranges from $80,000 to $200,000. Enterprise implementations across extensive sources and ongoing refresh start at $200,000 and up. Because quality validation is essential, it is always in scope. Final pricing follows a discovery phase that assesses source data. We provide clear, itemized estimates so you can build a validated CDM in stages.

Focused Implementation

ETL and mapping for a defined source with quality assessment typically ranges from $40,000 to $80,000, delivering a validated initial CDM.

Full Implementation

A complete OMOP implementation with multiple sources and tooling typically ranges from $80,000 to $200,000, covering research-ready standardized data.

Enterprise

Extensive implementations with ongoing refresh start at $200,000 and up, standardizing many sources for large-scale research.

What Drives Cost

Source complexity, mapping effort, number of sources, and refresh needs drive OMOP implementation cost more than data volume alone.

Quality Validation Included

Data quality validation is always in scope, because an unverified CDM produces unreliable research.

Estimate Process

A short discovery phase assessing source data produces an itemized, fixed-scope estimate before development begins.

Get Started

Ready to standardize your data for reproducible research and real-world evidence? Taction Software will assess your source data, scope the right build, and deliver a HIPAA-compliant OMOP implementation with validated data quality on a realistic timeline. Contact us to schedule a discovery call and receive an itemized estimate.

FAQs

Frequently Asked Questions

OMOP implementation converts observational health data into the OMOP Common Data Model (CDM), the OHDSI open standard. It builds ETL from EHR, claims, and other sources into the CDM, maps local codes to standardized vocabularies like SNOMED and RxNorm, and validates data quality, so data becomes standardized and research-ready for reproducible studies and real-world evidence.

The OMOP CDM standardizes observational data so it can be analyzed with the mature OHDSI tool ecosystem and shared across institutions. This makes studies reproducible and portable, enables participation in research networks and federated studies, and supports real-world evidence, none of which ad hoc, non-standardized research data can offer.

The core work is ETL transforming source data into the CDM and vocabulary mapping to standardized terminologies, followed by data quality validation using OHDSI tooling and setup of OHDSI analytics tools. Quality validation is essential, because an unvalidated OMOP database produces unreliable research.

Taction Software validates the CDM using OHDSI data quality tooling, checking that ETL and vocabulary mapping produced accurate, complete standardized data. Because the entire value of OMOP rests on the CDM being correct, we treat quality validation as essential rather than optional.

Yes. Taction Software builds on a HIPAA-aligned foundation with encryption, access controls, audit logging, Business Associate Agreements, and de-identification for research use, and validates security before launch. Because OMOP handles sensitive observational data, compliance is engineered into the implementation.

Cost depends on scope. ETL and mapping for a defined source with quality assessment typically ranges from $40,000 to $80,000, a full implementation with multiple sources and tooling from $80,000 to $200,000, and extensive enterprise implementations start at $200,000 and up. Quality validation is always included. A discovery phase produces an itemized estimate.

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