Map the clinical concept.
Interpret local order and result names so the same clinical test can be evaluated consistently across source conventions.
Direct-source vs. EHR-derived lab data
When your population is defined by biomarkers or measured clinical values, direct-source lab data is often the stronger starting point. Prognos harmonizes and enriches that detail so your team can put it to work.
Follow the data from source to use
Test identity, measured findings, units, reference ranges, and available report text.
Evaluate which fields survive extraction, aggregation, mapping, and standardization.
Harmonization + enrichment
make the detail more useful.
Result values become more useful when test identity, units, reference ranges, and relevant report detail are accessible and consistently structured.
What the sources contribute
For questions that depend on the test result, prioritize access to the original clinical detail. Prognos pairs direct lab-source relationships with the processing that makes that detail useful.
Swipe across the table to compare both approaches.
| Dimension | Direct-source lab data | EHR-derived lab data |
|---|---|---|
| Origin | Feeds from participating laboratories and their source systems. | Lab information extracted from participating EHR systems, networks, or related aggregations. |
| Clinical detail | Access to available result fields and source reports can support lab-focused interpretation. | Can include results and clinical reports; retention depends on the systems, extraction, and delivered fields. |
| Broader clinical context | Focused on testing and diagnostic findings. Other care information may require linkage. | May add diagnoses, medications, encounters, and clinician notes within participating settings. |
| Coverage & continuity | Reflects participating labs, available testing, history, and patient linkage. | Reflects participating care settings, data-sharing arrangements, available history, and patient linkage. |
| Freshness | Depends on source reporting, ingestion, processing, and delivery cadence. | Depends on source updates, extraction, aggregation, processing, and delivery cadence. |
| Standardization | Test mapping, unit handling, range parsing, and source interpretation remain important. | Field retention and mapping across EHR sources require evaluation, as do units, ranges, and test identity. |
| Provider context | The provider on a lab record may be an ordering clinician, pathologist, or other recorded provider. | Provider fields reflect the captured EHR workflow and may require attribution for the intended use. |
Inspect what matters
Choose a dimension to explore the questions that matter when evaluating a lab dataset.
Results & standards
Check whether the delivered fields preserve the test identity and the clinical context needed for the intended analysis.
The Prognos difference
Prognos goes beyond access to lab records. Direct lab-source relationships, harmonization, and enrichment give teams a stronger foundation for clinically specific analysis and HCP engagement.
That work includes interpreting local test names, separating numeric and qualitative results, standardizing available units, and structuring relevant source information for analysis.
The advantage comes from pairing direct access to lab results with the clinical expertise to make them usable for your population and workflow.
Harmonization & enrichment
Useful lab data requires more than placing records into a common table.
Interpret local order and result names so the same clinical test can be evaluated consistently across source conventions.
Handle numeric and qualitative findings, available units, reference ranges, abnormal flags, and relevant report text.
Apply appropriate patient linkage and deduplication across participating sources while retaining source context.
Enrich provider context beyond the name on the lab record where the source data and linkage support it.
Illustrative application · Rare renal disease
For a C3G or primary IC-MPGN program, cohort evaluation may require specific pathology findings, available complement results, and the surrounding clinical history.
Biopsy detail and available C3/C4 results add information for clinical profile evaluation. These signals need interpretation within a defined clinical profile; they do not establish a diagnosis on their own.
Evaluate available biopsy narratives and whether relevant findings are retained or extracted into structured fields.
Review available C3/C4 values with test identity, units, reference ranges, and longitudinal context.
Assess which recorded HCPs are connected to the patient and whether additional context supports nephrologist engagement.
Connect the broader journey
A direct-source lab asset can add diagnostic detail to an EHR-based view. EHR data can contribute clinical context beyond the test result.
Where compatible linkage and permissions are available, evaluate what each source adds, how much overlaps, and which gaps remain.
Evidence in practice
Explore concrete examples of harmonization and provider enrichment alongside the broader source comparison.
Common questions
Use the source pathway as a starting point, then evaluate the data against the needs of your program.
It can. The important questions are which results and report elements are captured, how they are transformed, and what is available in the delivered dataset. EHR-derived lab data should not be treated as diagnosis codes alone.
No. Direct feeds still need source interpretation, quality review, and harmonization. Available detail and completeness vary by source, test, field, and time period.
No dataset guarantees a complete journey. Evaluate the participating labs and care settings, source history, and linkage. Changing geography or care settings may affect what any individual asset captures.
The recorded provider may be an ordering clinician, pathologist, or another role. Additional provider context can help teams evaluate relevance, but observed activity alone does not confirm a disease-specific treating relationship.
Separate the date of the clinical event, source reporting, receipt, processing, and usable delivery. Daily or weekly delivery describes cadence, not necessarily the full elapsed time from the original event.
Further reading: FDA guidance on assessing EHR and medical claims data, including missing data, linkage, unstructured information, and data quality.
Bring your tests, clinical criteria, and current sources to a conversation with Prognos.