The Challenge of Accessing Specialty Drugs
Many patients struggle to access specialty medications, with one in three never beginning treatment. This issue arises not because the medications aren’t available, but due to slow and complicated systems that hinder proper access. Data architect Sujit Murumkar has dedicated nearly 20 years to addressing this problem, which lies at the crossroads of technology and healthcare.
A Focus on Patient Care
Murumkar has worked with major pharmaceutical companies and top financial institutions throughout his career. His goal has always been to ensure that patients diagnosed with chronic conditions receive their medications promptly. He emphasizes the need for doctors to have accurate, real-time information so they can make the best treatment decisions possible.
Bridging the Data Gaps
The systems supporting medication distribution are often more complex than many realize. Before a patient gets their medication, it must navigate through various systems that handle everything from identifying physicians to coordinating patient support. When these systems rely on outdated or fragmented data, patients face unnecessary delays.
As Murumkar points out, “If a field representative discovers an access issue weeks after it happens, they can’t assist that patient.” To make a real impact, data needs to be timely and trustworthy.
Research shows that using real-time data in healthcare leads to better outcomes, as it allows for quicker interventions and more effective care. Organizations that embrace real-time data see significant benefits, including increased patient engagement and adherence to treatment.
Murumkar helped create data platforms at a top pharmaceutical company that streamlined operations and reduced reporting time from several days to just hours, allowing teams to act more swiftly.
Uniting Disparate Systems
One major hurdle in patient support is that relevant data is spread across various systems—each with its own focus. Without a unified system that connects these different types of information, organizations lack a full view of a patient’s treatment journey.
Murumkar tackled this by designing comprehensive data management models that standardize how patient information is collected and maintained. This integration allows for a clearer understanding of each patient’s experience from prescription to adherence.
“When you can follow a patient’s journey at every step, from the doctor’s prescription to their refills, you can identify where the system is falling short,” he explains.
Harnessing AI for Proactive Support
Predictive analytics is changing how pharmaceutical companies assist patients. Instead of waiting for adherence problems to arise, advanced data systems can flag potential issues early. For example, if a patient fills a prescription but is slow to refill it, that may indicate a need for support.
Murumkar’s initiatives in AI have laid the groundwork for this proactive approach. By streamlining the data needed for predictive models, his teams have drastically cut the time it takes to implement them, which is crucial in a fast-paced industry where patient support must quickly expand as needed.
Connecting Technology with Human Impact
What sets Murumkar’s strategy apart from typical tech upgrades is his focus on how these decisions directly influence patient health. Every technical choice—whether related to data governance or cloud strategies—has implications for the people relying on these systems.
His experiences encompass a range of organizations managing vast resources. A common challenge remains: while organizations gather enormous amounts of data, they often lack the infrastructure to effectively use it for patient care. Closing this gap between data collection and actionable insights is vital.
In an industry where timely access to data can literally save lives, the argument for smart data architecture goes beyond money. It is about ensuring the systems in place live up to the mission of improving patient health.
