How Leveraging Data Promotes Intelligent Healthcare
The healthcare industry is undergoing a fundamental transformation.
Value-based healthcare, patient-centricity, connectivity, and home care are key drivers of change in the pharmaceutical sector. With this in mind, supply chains have to adapt to this new environment which demands higher visibility and agility in order to increase revenue and ensure consumer safety. Altogether, the prevailing strategy boils down to intelligent healthcare with data insights and analytics as the main components to determine whether or not your operations are a success.
To help you manage your end-to-end cold chain and explore how to develop the key building blocks for forward-thinking, here's how you can leverage data to make an impact:
Automate Data Collection and Analytics
Research from the McKinsey Global Institute shows that improving decision-making with big-data strategies could potentially generate a staggering $100 billion annually within the US healthcare system. However, accessing data and making it useful has proven to be a real challenge for pharma and biotech companies of all sizes.
Here are the main business benefits that data automation includes:
- Real-time tracking of patient trials to ensure safety and eliminate the risk of potential delays and extra costs
- Consistency throughout the supply chain and cold chain to ensure product integrity and on-time deliveries
- Metric visibility to provide insights across multiple departments, such as accounting, sales, marketing, and logistics; allowing teams to optimize workflow and better execute tasks
- Complete digital transformation to streamline data between entities, such as patient profiles to physicians, physicians to contract research organizations (CROs), and CROs to clinical trials; all of which speed up approval processes
"Making data and insights available instantly takes the pain out of data collection, curation, and analysis, which means companies can make more informed decisions faster, " says Tripathi.
For a list of analytic solutions leading the pack, check out these top 10 providers.
Data and Supply Chain Segmentation
It's estimated that 38% of manufacturers use static segmentation to execute their supply chains, whereas 28% operate without any kind of data-driven approach whatsoever.
As global demands continue to rise, performing from an invariable standpoint no longer allows for scalability. Not to mention, opting to refrain from supply chain segmentation driven by data only leads to more errors and greater costs along the way.
For example, pharma companies typically manage their supply chains based on customer demand. This develops a standard approach over time and generates the same issues across multiple channels. On the other hand, segmentation strategies allow for multiple supply chains according to...
- Customer type
- Geographic location
These parameters all center around data from one end of the supply chain to the other, so with the right resources, you can access this information in real-time to prepare for any issues and enhance productivity.
This is especially true for cold chain management on a global scale. Research shows that 10% of all pharmaceutical inventory relies on controlled temperatures to remain stable. Even the slightest drop in temperature may cause wasted inventory, high logistical costs, and potential lawsuits.
Thankfully, data-driven approaches are solving these issues and relieving cold chain operations of painstaking procedures. Here are some of the solutions that you can apply to your cold-chain management:
- Inventory pre-cooling to increase the longevity of refrigeration equipment and maintain product temperatures during global shipment
- Install trailer cooling systems to regulate temperatures and receive alerts in real-time to mitigate issues throughout transport
- Optimize packaging to enhance inventory conditions and prolong product shelf life
The Future of Pharma and Intelligent Healthcare
Global healthcare data analytics are poised to top $34.3 billion by 2022. With that in mind, the horizon is replete with data initiatives that will reshape the future of pharma and define intelligent healthcare for years to come.
Primarily, these efforts focus on research and development in technology sectors, patient populations to determine value-based pricing, open collaborations with internal and external partners to streamline development, and most of all, data organization to extract siloed information and use it toward driving long-term change.