As a statistician and outcomes researcher, I have supported healthcare providers and administrators in the collection and analysis of real-world data for over 15 years with the aim of understanding the association of patient characteristics and treatments associated with improved outcomes. Often these analyses were the starting point for quality or process improvement initiatives. HEOR data supports my work with healthcare organizations to learn how to better care for patients, while providing greater value through improved quality and smarter spending.
Drugs and interventions may be efficacious in clinical trials, but healthcare organizations really need to know what drugs and interventions improve the value of the care they deliver, as well as how they can use new drugs or interventions to achieve the best outcomes at the most cost-effective price point. A successful clinical trial does not guarantee that a clinician will see the same value on the frontlines. HEOR data can help close this gap, identifying best practices for both implementation and speed to adoption.
Today, there’s little to inform healthcare providers about the best approaches to capitalizing on the potential value that each new intervention poses. HEOR data can be used to understand this value, as well as the patient outcomes that are not usually studied in the clinical trial setting. These can include things such as days at home or number of admissions. In addition, it can identify facilitators and barriers to adoption of new drugs and interventions.
As a learning organization, we seek to identify who is improving most efficiently so that those best practices can be shared among our hospital and health system members. This shared knowledge allows for accelerated learning around the care transformations and new interventions that are most effective. This also enables providers to quantify the resources needed for change and the time it takes for initial investments to bear returns.
Bringing Life Sciences Companies in the Fold
Given the new value paradigm in healthcare, life sciences companies will need to support learning in this area as new products are launched. For example, a new oncology agent may require testing prior to initiation and have a risk of specific adverse events. A health system will want to understand how to best incorporate the new testing and prescribing into their protocols. For the life sciences company, that means the ability to answer questions such as:
- When and how should those changes happen?
- With what education?
- Should it be a nurse-driven protocol or a physician order set?
- How should the new adoption be monitored?
- Once a patient starts the agent, how should the practice monitor the patient to mitigate any adverse events?
- What types of accompanying symptom management promotes the best therapeutic care and avoids any unnecessary burden to the patient?
It is imperative for life sciences companies to partner with provider organizations and use HEOR data to understand the key questions for their new therapies and arrive at answers together. An untapped opportunity, HEOR data and analysis helps to support this work, creating new knowledge around healthcare transformation.