Webinar: Maximizing HCP Engagement for Rare Disease Launches
For patients living with a rare disease, the journey to the correct diagnosis can be time consuming, frustrating — even dangerous. Finding the right treatment for the right condition at the right time can take years. Consider the sobering statistics:
- An average of 4.8 years can elapse between first symptom and accurate diagnosis.
- During those years, patients see on average 7.3 different physicians in search of information and relief.
- A whopping 40% of patients receive an incorrect initial diagnosis
- Financially, more than $100 billion is wasted in inaccurate diagnoses and treatment.
These statistics underscore the need to better align with the triple aim of healthcare: to reduce costs, boost outcomes and improve both the patient and the HCP’s experience.
What if you could change these statistics? What if you could engage HCPs managing relevant patients at actionable moments? What if, as a result, those HCPs could identify a rare condition sooner, alleviating pain, putting patients on a faster road to recovery, and driving better healthcare outcomes?
On Monday, December 16, Vice President of Solution Strategy, Dave Bitner, will present a webinar engaging life science companies specifically focused on rare disease.
These companies know it can be difficult for healthcare providers to identify and diagnose rare diseases. But patients would benefit from earlier interventions and therapies to treat these challenging illnesses. The webinar will explore how the Pulse alerting system can help identify undetected disease, and facilitate engagement with HCPs managing specific patients with rare disease at relevant points in the patient journey. For instance, when a patient has been diagnosed with a condition, taken a lab test, or has clinical cues that resemble other patients, all of these points may help lead to the accurate diagnosis.
Powered by Komodo’s Healthcare Map – the largest, most comprehensive and timeliest clinical encounter dataset of the US — Pulse uses our AI/Machine learning algorithms to create patient models that help us send predictive alerts based on clinical cues of interest. For example, Pulse can flag suspected instances of an undiagnosed disease, or patients who might benefit from a specific therapy.
The goal? To find the right patient. At the right time. And empower health teams to save lives.