Our Platform
The Loopback platform assembles clinical, pharmacy, enterprise and social data for insight and action across the specialty pharmacy and life sciences value chain.
Understand the patient journey, compare how drugs and devices are used within and across populations, and assess patient outcomes across a wide range of endpoints – all from anonymized real world patient data from across the United States.
Estimated portion of time data researchers spend collecting and cleaning data
Clinical researchers are frequently faced with grooming vast quantities of electronic health record (EHR) data
All too often, they face ingesting, mapping & cleaning inconsistently implemented identities, locations, and naming conventions, procedures, labs, and medications
Loopback addresses data pipeline and preparation needs of the clinical data researcher, serving as a ‘project-ready’ real-world data (RWD) resource for electronic health record (EHR) data. De-duplicated, normalized to a common data model, and enriched with an expanding range of researcher-friendly attributes
>30M
Patients
> 500
Hospitals
> 3500
Facilities
~50%
Academic
Affiliated
All elements linked to an anonymized patient identity
Loopback Clinical Intelligence proudly extends from the PCORnet common data model used across health systems and clinical research consortia.
The Loopback platform assembles clinical, pharmacy, enterprise and social data for insight and action across the specialty pharmacy and life sciences value chain.
When importing data from an EHR, pharmacy dispense system, etc. there will inevitably be multiple patient records for the actual real patient. Loopback’s Master Patient Index uses a combination of probabilistic and deterministic processes to deduplicate and connect patient records across the health system or geographic region.
All data ingested by Loopback is standardized into a common data model, but that isn’t enough. A common understanding requires normalizing the definition of critical events and establishing data relationships that do not always exist in every health system.
Every EHR implementation is obviously tailored to the needs of the health system. To get to a common understanding, the Loopback platform must normalize those customizations. This could be as simple as mapping data elements to common terminologies but also as complex as standardizing the definition of an encounter.
All elements linked to an anonymized patient identity
An analyst from the Loopback Data Science team will walk you through the Loopback Clinical Insights population builder to design your inclusion and exclusion criteria, time scale, required data elements and levels to increase the fit with your study objectives.
Population summary demographics, intersections of key sub-populations, and key terms & data domains to help researchers understand data will support the desired research objective. Iterate on population until satisfied.
Population license terms dictate allowed uses for study data. Row-level data sample provided upon request. Annual licenses for the defined dataset with opportunity to receive weekly, monthly or quarterly refreshes.
Upon defining your study population, we will provide access to your study dataset. You can access the file via our cloud environment, receive structured .csv files via a secure delivery, or ingest into the analytics platform of your choosing.
