Addressing gaps in care and insights
Rheumatologic diseases affect an estimated 54 million patients in the U.S alone and represent a leading cause of disability. The introduction of innovative medicines continues to reduce patient burden of disease. Recognizing the mechanisms of action across these treatments is diverse, delivering the benefits to patients requires high quality research-driven insights on treatment effectiveness, gaps in care, and disease progression.
Rheumatology conditions are complex. Accessing data shouldn’t be.
Understanding the complexities of these systemic inflammatory diseases, and the factors that affect response to treatments, drives our focus on bringing a dynamic new approach to real world evidence generation to healthcare stakeholders.
Meet the largest Rheumatology data network in the U.S.
A comprehensive view of the patient journey from clinical development to the clinic
Bringing new treatments to market and delivering personalized care is challenging. Insights from real world data can expedite development and inform commercialization. OM1 purposefully built the largest rheumatology network in the U.S to deliver the longitudinal clinical data necessary to answer your most urgent questions.
• Axial Spondyloarthritis
Every condition presents its own unique challenges and opportunities. Select one of our sample datasets above to explore some of the features.
RA patients with deep clinical data
SLE patients with deep clinical data
AxSpa patients with deep clinical data
PsA patients with deep clinical data
*Data counts as of Q1 2022 ©OM1 Rheumatology Specialty Area
Understanding the drivers of treatment choice in the real world to see if certain patient subtypes see greater use of specific, competitive treatments and which are favored for lines of therapy.
Understanding the effectiveness of hydroxychloroquine in the real world across specific racial subtypes with Systemic Lupus Erythematosus (SLE).
How we can help
Our specialized real world data, deep research teams, and physician experts offer you the longitudinal patient journeys and critical outcomes to enable your teams with the rapid and in-depth analyses necessary to drive your critical business objectives.
Fully utilize deep, clinical RWD to more efficiently design and conduct clinical trials such as seeing where unmet needs are greatest or determining which groups the protocol should be designed to enroll.
Measure key safety outcomes of interest and support regulatory requirements, such as monitoring and comparing the real-world safety profiles for patients.
Align with real world-based patient behaviors to measure adherence to novel treatment approaches.
Develop sound evidence for payers through deep clinical and linked claims data for a more complete view of clinical outcomes and utilization. For example, to assess the cost effectiveness of early treatment interventions.
RWD can help guide planning, forecasting, and improving brand performance, such as understanding the size of the market by segment in specific patient subtypes that are best aligned with a brand’s positioning.
Meet our rheumatology expert
Kazuki Yoshida, MD, MPH, ScD is the Director of Rheumatology & Principal Epidemiologist at OM1. As a rheumatologist and pharmacoepidemiologist with more than a decade of experience, he provides expertise in clinical areas around immunology as well as the design, conduct, and reporting of observational drug studies.
Prior to joining OM1, Dr. Yoshida was an Assistant Professor of Medicine at Brigham and Women’s Hospital and Harvard Medical School. At BWH/HMS, he led NIH-funded research on rheumatic disease epidemiology and research in real-world data causal inference approaches. His prior research topics include rheumatoid arthritis, psoriatic arthritis, gout, systemic lupus erythematosus, axial spondyloarthritis, osteoporosis, heart failure, infectious diseases, propensity score methods, and causal mediation analysis. Dr. Yoshida received his medical degree in Japan, his Master of Public Health and Doctor of Science degree (jointly in Pharmacoepidemiology & Biostatistics) from Harvard T.H. Chan School of Public Health.