Over the past year and a half, the pandemic’s disruption on the healthcare supply chain has only heightened the need for data based decision-making within the healthcare ecosystem. While healthcare leaders used data to understand the clinical nature of the novel virus, data was also the backbone of the supply chain to inform decision-making like never before. With lives at stake, the need for accurate, comprehensive data was highlighted, not as a fleeting trend, but as a vital part of the future of healthcare, where achieving a clinically integrated supply chain is paramount.
Rather than relying solely on intuition or observation, Data-driven decision making (DDDM) leverages multifaceted analytics to achieve high-functioning results within the healthcare supply chain. For DDDM to be successful, data must not only be easily accessible to stakeholders, it must also be strategically integrated throughout the system rather than exclusively at the facility level in order to realize the largest impact. Throughout the pandemic, integrated data proved vital for strategic decision making ranging from EHR integrations to discovering alternative products under a strained supply chain. While there are a wealth of resources available to support product decision making from clinical evidence to regulatory and safety information, utilizing comprehensive data systems provides amplified information power for decision-makers.
As the reality goes, what’s possible is not always what’s practical. It may be possible to source ad-hoc insights, but the time invested to do so and the ability to aggregate information for advanced comparative ability may not be practical. Rather than relying on individual, manual information gathering, leveraging integrated data through APIs and technology partners allows for systemwide improvements, making congruent data available and accessible across the entire system.
It is evident that virtually all industries are pushing towards data-driven models as more forward-thinking leaders wish to avoid bias, assumptions, and wasted time when it comes to making decisions. While DDDM is not necessarily unique for the healthcare industry, it is arguably the most important setting due to high levels of risk and numerous overlapping data channels. During the early months of the pandemic, the supply chain was severely crippled in light of increased demand for products such as respirators and PPE; during these times, it was vital that hospitals could make informed decisions with integrated data surrounding sourcing equivalent products when the desired product was simply unavailable.
While the value of DDDM was certainly accentuated during the pandemic, it will continue to be an important part of the healthcare ecosystem long after the storm dissipates. Without data-driven decision making, incomplete information wastes valuable time, resources, and expertise that could be put to better use if high-quality, integrated data was utilized to inform vital product decisions. Ultimately, enhancing data-driven decisions in healthcare supply chain and value analysis management has the ability to impact frontline care by making effective, clinically-backed product decisions that improve patient care.
Learn how GreenLight supports data-driven decision making though their Clinical Evidence database, which includes aggregated clinical evidence and summaries on thousands of products, alongside powerful analytics on safety and financial impact.
 A Guide To Data Driven Decision Making: What It Is, Its Importance, & How To Implement It. Tableau. (n.d.). https://www.tableau.com/learn/articles/data-driven-decision-making.
 Healthcare Data Integration: 2 Success Strategies. Health Catalyst. (2021, April 6). https://www.healthcatalyst.com/insights/healthcare-data-integration-2-success-strategies.
 Miller, K. (2021, April 23). Data-Driven Decision Making: A Primer for Beginners. Northeastern University Graduate Programs. https://www.northeastern.edu/graduate/blog/data-driven-decision-making/.