Lab data
What did the test show?
Results & biomarkersReference ranges
Clinical trends
Lab data vs. claims data
Claims help explain the care a patient received. Lab results add the clinical detail behind the journey. Choose the source or combination that answers your question.
Different sources. Different answers.
What did the test show?
Results & biomarkersWhat care was recorded?
Treatments & servicesConnect clinical meaning
with the broader patient journey.
A billing record can establish that testing occurred. The result itself can define a biomarker profile, quantify a clinical value, or reveal change over time.
Start with your question
Use the questions below to explore a useful starting point for a commercial, medical, or research program.
Start with lab data
Evaluate observed test findings, values, reference ranges, and available report detail to define the population your question requires.
Compare what each source contributes
The useful distinction is the information a source captures—not a universal ranking of every lab or claims dataset.
Swipe across the table to compare both sources.
| Your question | Direct-source lab data | Medical & pharmacy claims |
|---|---|---|
| What is happening clinically? | Observed test results, numeric values, biomarkers, and available pathology or genomic detail. | Recorded diagnoses, tests, procedures, and billed services. Exact results usually require an added clinical source. |
| Which therapies were used? | Clinical findings before, during, or after treatment, within the available lab history. | Recorded prescriptions, administrations, procedures, and other treatment activity, depending on the asset. |
| How has the patient changed? | Changes in measured values and test findings across participating sources. | Changes in recorded diagnoses, therapy, visits, and utilization within the captured history. |
| How fresh is the information? | Depends on source reporting, ingestion, processing, and delivery cadence. | Depends on submission, adjudication where applicable, aggregation, and delivery cadence. |
| Which HCPs are visible? | Providers on lab records; enrichment can add observed care-team context where linkage is available. | Billing or rendering providers and other recorded HCP fields; relevance to a specific disease may need further assessment. |
| What could be missing? | Care outside participating labs, unperformed tests, and clinical context absent from source records. | Unbilled care, uncaptured transactions, exact clinical results, or history outside the asset’s coverage. |
When lab data makes more sense
If your question depends on the actual test result, a diagnosis or procedure code may not provide enough specificity.
Lab data can help distinguish biomarker-defined populations, describe measured clinical status, or evaluate patterns that warrant further investigation. That detail can support patient finding, HCP engagement, and evidence-generation questions.
Start with lab data when a measured value or observed finding changes who belongs in the population—or what question to ask next.
Questions that need result detail
Which patients have a specific biomarker, variant, or test-defined clinical profile?
How are relevant clinical values changing across the observed history?
Which physicians are connected with patients showing relevant lab signals?
Explore the use cases
These examples show how clinical detail and recorded care contribute different information. Explore what each source can add to a more specific clinical or commercial question.
Lab contribution
Available eGFR and uACR results can add quantitative context to a kidney-related population.
Claims contribution
Prescription activity, visits, and procedures help describe the care captured in the claims asset.
Together
Link clinical measures with treatment activity to examine how observed care relates to the available lab profile.
When combining sources makes sense
Many questions span both what happened biologically and what happened in care. Linking lab and claims data can help teams evaluate those questions within a more connected patient journey.
For example, a lab-defined cohort can become the starting point for examining recorded therapies, utilization, and provider activity.
The Prognos difference
Prognos focuses on harmonizing and enriching lab data so clinical findings can support analysis and appropriate HCP engagement.
Interpret test names, results, units, and available report detail to help make source data consistent and usable.
Explore observed care-team connections beyond the provider listed on a lab record, subject to available source data and linkage.
Use compatible tokenization and agreed linkage arrangements to connect participating lab and other data sources.
Before choosing a dataset
A good source decision starts with the required clinical variables and the workflow the data needs to support.
Does the asset contain actual results, codes, inferred profiles, or a combination?
Are the tests, therapeutic areas, and patient populations relevant to your question?
What is the time from source event to usable delivery?
Which provider roles are observed, and which are enriched or inferred?
Can the data be linked to the other licensed sources your question requires?
What is missing, and how are completeness, provenance, and continuity assessed?
Common questions
The most useful approach balances clinical specificity, coverage, and the context required for the intended analysis.
Some questions can be answered primarily with lab results. Others require treatment or utilization information that claims can contribute. When the question spans both, a linked approach may be more useful.
No single lag applies to every asset. Compare source-event dates, receipt dates, processing time, and delivery cadence for the datasets you are evaluating. Direct lab feeds can support frequent refreshes, while claims availability varies by source and feed type.
A lab signal may help define a clinical profile or flag a patient for further evaluation. The interpretation depends on the test, available history, and the program’s clinical criteria.
Compatible patient tokenization can support linkage where the appropriate permissions, licensed access, and technical arrangements are in place. Evaluate matchability and overlap for the specific sources.
Further reading: FDA guidance on assessing electronic health records and medical claims data discusses data relevance, reliability, and linkage for research.
Bring your clinical population, use case, and current data sources to a conversation with Prognos.