Using EMR Data to Support Budget Impact Modeling
A large pharmaceutical company needed to
demonstrate the potential cost savings of placing a new drug on payer formularies.
A large pharmaceutical company needed to
demonstrate the potential cost savings of placing a new drug on payer formularies.
A small-size pharmaceutical company was interested in using real-world evidence to compare adherence between two formulations of an oral oncology treatment for Multiple Myeloma (MM).
A mid-size pharmaceutical
company was interested in
obtaining real-world evidence
demonstrating the safety and
effectiveness of higher dosage
chemotherapy for a labeled
oncology indication.
A mid-size pharmaceutical company was interested in obtaining real-world evidence demonstrating the safety and effectiveness of higher dosage chemotherapy for a labeled oncology indication.
Magnolia was asked to assess which type of cell therapies and disease states offered the greatest potential for development, and also wanted to further understand the benefits of creating an autologous or allogeneic product.
A new, oral formulation of an existing infused product offered better adherence and less waste, but it was uncertain if these benefits would change payer, provider, and patient pain points or critical success factors for the product’s pricing strategy.
A company wanted to understand if user perceptions of the hub had improved after implementing changes. Patients and providers previously expressed dissatisfaction with services offered by company’s hub (confusing process, eligibility criteria, who to communicate with), and they recently relaunched the program with enhanced services, a customer portal, and redefined roles for client facing teams.
Magnolia was engaged as a payer agency of record for a mental health digital therapeutic. Although the company had experience launching drugs in the U.S. market, the novelty of the digital therapeutic space was challenging, and the company did not have experience in mental health, nor a comprehensive launch plan in place across channels.
Magnolia to evaluated the likelihood that a drug compendia would support an off-label dose for a drug with an FDA-approved maximum dose, and helped the client obtain stronger payer coverage with a compendia submission.
A client needed to develop an algorithm to identify patients at risk for chronic obstructive pulmonary disease (COPD) exacerbations via structured and unstructured EHR data to help clinicians optimize treatments. Magnolia was able to identify patients more precisely through Deep6 AI data than existing algorithms that use claims data alone.