Leveling the playing field The average time to correctly diagnose a patient with a rare disease is 7 years, largely due to data sparsity, misdiagnoses, incorrect prescriptions, etc. Now, through the application of artificial intelligence and machine learning algorithms, we are able to shorten the time to diagnoses of rare diseases and even discover undiagnosed […]
In his latest white paper, Oodaye Shukla, EVERSANA’s Chief Data and Analytics Officer, outlines the revolutionary impact that artificial intelligence and machine learning can have on improving patient outcomes and access to therapy. Rare disease statistics: The average time to get an accurate rare diagnosis is 6-8 years. There are 7,000 distinct types of rare […]
The First & Only Go-To Complete Commercialization Expert Manufacturers spend >$125MM over three years leading up to launch, yet 66% of drugs don’t meet launch expectations. An unpredictable landscape, coupled with inevitable industry pressures, is forcing manufacturers to seek a more complete commercialization approach with less risk and more value. In 2018, EVERSANA, a leading […]
Patient Services Programs Are Falling Short To give credit where credit is due, pharmaceutical manufacturers make a tremendous – and well-intended – effort to alleviate the product access obstacles and burdens patients and providers often endure when a new medication is prescribed. While interactive wellness apps, generous co-pay card offerings and essential patient assistance programs […]
Patient and hub services represent a significant and often ineffective spend surrounding overall patient support. How can we use data and analytics to build better patient services programs that predict next best actions and achieve improved patient engagement and outcomes across the treatment journey? As the industry continues its shift to value-based care, this challenge […]
The following is a exchange between Brigham Hyde and Ed Cox, two health tech experts and coworkers on a quest to educate each other and their teams. Note: An inquiry from a colleague who interchanged terminology initiated this exchange. Download the PDF Version
Delivering value in the era of empowered patients renders the one-size-fit-all patient services program obsolete. Not every treatment journey is consistently linear within a disease state because patients take different paths to medication adherence. For example, one patient may be compliant when prompted by a smartphone notification while another relies on a caregiver for their […]
Patient Switching Behaviors Impact on Adherence and Engagement: A Predictive Analytics and Machine Learning Approach to Improving Hub Performance and Patient Outcomes Today we have access to more data, from more sources than we could ever dream possible. Living in a digital world, we increasingly need the ability to efficiently and effectively process this data […]
IF I COULD ONLY ASK TWO QUESTIONS, THE FIRST WOULD BE: What is your data integration and analytics platform strategy? As the industry continues its shift to a patient-centric, value-based model of care, it is critical that the next generation of patient services programs integrate data and analytics into their care models to track the […]
“The complete product lifecycle requires the use of real world evidence to achieve launch success and optimal market access.” As manufacturers develop new innovative medicines and healthcare interventions that disrupt traditional treatment paradigms, it’s critical they demonstrate product value from a real-world standpoint through rigorous scientific evidence on reduction in burden of disease, limitations of […]
