Pushing the frontier in behavioral health, we continue our efforts to align the Common Data Model (CDM) in NeuroBlu with the Observational Medical Outcomes Partnership (OMOP) standards provided by OHDSI. As our data partnerships continue to grow, we strive to close gaps and increase granularity of the data, providing means to access greater depths in encounter and prescription data.
The enhanced CDM accentuates NeuroBlu as the most robust behavioral health database of its kind, powering the creation of scientifically validated and clinically meaningful insights in behavioral health.
Key enhancements include:
1. visit_detail table
Define cohorts more accurately with granular information recorded, such as the movement of patients between hospital units during an inpatient stay. Furthermore, the sequential or hierarchical nature of the visits can be linked to diagnosis and medical procedures, hence accelerating the identification of patient’s journey.
For outpatient visits, this table provides information on where the individual services were performed, for example in assisted living facilities, home care, hospitals etc.
Adhering to OMOP standards, this table is now a distinct table from the procedure_occurrence table. It contains details on individual services provided during a visit and contains provider_idon each record.
By enhancing our data model to include mappings to both Current Procedural Terminology (CPT-4) and Healthcare Common procedure Coding System (HCPCS) terminologies, we have increased our coverage of patients’ procedure data by over 60%. This allows you to perform in-depth analysis on types of procedures that benefit specific patient segments.
Specifically, we have increased psychotherapy data by 6 times compared to the previous data version. This powers analysis on comparison of treatment modalities, such as comparing effects of psychotherapy and pharmacotherapy for patients diagnosed with PTSD.
This table provides greater details on individual procedures conducted during a visit and contains provider_id on each record.
procedure_concept_id is based on HCPCS or CPT-4 associated with the procedure. To enhance analyses, concept_class_id is populated to differentiate between HCPCS and CPT-4.
3. drug_era table
A drug era is defined as a span of time when a person is assumed to be exposed to a particular active ingredient. By aggregating information at the lowest possible complexity, the drug_era table empowers faster analyses on effectiveness of active ingredients regardless of the branded form of a drug.
This table contains eras of continuous exposures for the same ingredient into a single record, with the assumption that there are no gaps over 30 days. For example, you can search for information on buprenorphine, and this will automatically show all exposures to drugs containing buprenorphine.
4. drug_exposure table
Containing over 1,500 behavioral health specific drug concepts mapped to standard identifiers, you can now conduct deeper analyses on the effects of drug exposure on associated diagnosis. You can even analyze the impact of a drug’s dosage and strength on its effectiveness.
Besides providing information on the number of days of drug exposure under the days_supply key, this table also shows the route_concept_id, such as oral and intravenous therapy. Searches can be performed at the clinical drug level (including ingredient and strength), while also providing the option to aggregate them at an ingredient level.
5. persons table
Using the education_concept_id, we have mapped patients’ education information to 11 concepts adhering to OMOP standards. By mapping to standard concepts, we provide an unbiased manner to analyze the role of education as a social determinant of health in influencing health outcomes.
We are continuously improving our CDM to enhance the capabilities of NeuroBlu. This includes working toward having a standardized rating scale across RWE data partners, to allow for uniform longitudinal measurement. Along with uniform measurement, we work directly with each of our partners to ensure that mental status examination details are reviewed and mapped to OMOP standards.
1. Improved Code Studio with the ability to import and export source code files
Accelerate your research by directly importing R or Python source code into Code Studio. With this, you can easily import source files that your team members have shared with you, skipping the laborious process of manually transferring lines of code.
Export source files from Code Studio to save your coding work externally and share project inputs with others. When source files are exported, all files will be exported simultaneously to maintain their collective save state.
2. Enhanced Category Mapper with templates of DSM-5 Level 1 and Level 2 Groupings
Besides being able to select category values based on ICD-9 and ICD-10 codes, you can now align your studies and creation of real-world evidence to the American Psychiatric Association standards by starting from pre-built templates of DSM-5 Level 1 and Level 2 Groupings.