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Orion™ is a sophisticated proprietary machine-learning–based algorithm that analyzes disparate sources of health care encounter data to quantify the probability that individual patients are likely to have a disease, adopt a specific product, and/or become nonadherent to a specific product. This output provides the specific physician practices where these patients are currently being managed and assigns a relative probability to each patient.


Shorten the diagnosis journey for patients

Oftentimes, it takes several years for patients with difficult-to-diagnose diseases, including rare diseases, to receive a proper diagnosis, forcing the patient and their caregivers on an arduous and expensive journey. However, there is a bright side:
At 81qd, we have developed Orion, a solution that uses predictive analytics to identify HCP practices with the highest probability of having yet-to-be-diagnosed patients with difficult-to-diagnose diseases in order to help facilitate earlier diagnosis and treatment.

Identify HCPs managing undiagnosed patients in difficult-to-diagnose diseases

Orion examines billions of data points to uncover hidden patterns within individual patient journeys.
Each Orion model is customized to a particular disease state and uses complex machine-learning–based algorithms to identify previously undiagnosed patients with a high probability of having a specific disease
Orion is not a diagnostic tool—rather, it serves to help increase the screening of patients with a high probability of having a specific disease through more efficient clinician outreach and education, which ultimately will lead to earlier diagnosis and proper treatment


Drive product adoption

Orion analytics go well beyond the historical approaches of assessing likely adoption based on broad segmentation and extrapolation based on research using analog products. Orion leverages machine learning to assess thousands of patient and HCP features to identify and weigh their roles in driving adoption.

These insights provide our clients with tools to optimize HCP targeting and engagement to drive product adoption.

Identify HCPs managing patients likely to adopt a therapy

To predict the practices with patients likely to adopt a specific product, 81qd leverages claims data and machine learning to assess thousands of patient and HCP features to identify and weigh their role in driving adoption. Orion identifies patients that are likely adopters of a specific product and the HCPs who are currently managing these patients.

Clients can leverage Orion analytics within marketing initiatives/campaigns to engage directly and across multiple digital channels.


Maximize therapy adherence

Nonadherence to a medication is a complex healthcare problem, driven by a myriad of both patient- and HCP-related factors, such as:

Patient-driven factors:
Ability to follow a medication regimen
Willingness to pay for a medication regimen

HCP-driven factors:
Prescribing patterns
Practice attributes
Historical adherence patterns

81qd offers clients the ability to be proactive in efforts to address nonadherence by leveraging machine learning to identify HCP practices with the highest probability of patients likely to be nonadherent to therapy and provide targeted interventions to improve adherence.

Identify HCPs managing patients likely to be nonadherent to therapy

To identify the practices likely to have nonadherent patients, machine learning structures and finds interrelations between patient and HCP features, then assesses which features are predictive of nonadherence for a specific product and disease. Our clients can then leverage these findings to proactively engage and educate clinicians and patients across channels.

These applications span our clients' core business needs...
Effectively target disease management interventions
Optimize resource allocation
Improve financial support program efficiency and effectiveness