Recently, Global Healthcare Exchange (GHX) released its top priorities for healthcare supply chains in 2017. The priorities were the result of a survey of 50 leading supply chain provider organizations. At the top of the list was predictive analytics, with improved price accuracy between supplier and provider partners and standardized business processes/data across the organization also being identified as top priorities.
It’s no surprise that predictive analytics came out on top in the survey, as hospitals have focused on improving data analytics to drive healthier financials. Per the press release from GHX:
“Quality data is the foundation for all analytics activities. The supply chain is a valuable source of data on healthcare supply chain spend necessary for evaluation of outcomes and for decision making for savings initiatives. Supply chain leaders anticipate the use of this information becoming an important contributor to value (cost and quality) measurement as an important metric for assessing overall financial performance.
As the strategic importance of the supply chain grows, so does the role of the supply chain executive. According to the survey, supply chain leaders will increasingly work hand in hand with clinical peers to help lower costs and improve patient care. In addition, the supply chain team plays a more strategic role in provider organizations, tackling a variety of critical healthcare issues (e.g., value based care, improving clinical performance, reducing risk, EHRs, etc.).”
Read the results of the survey here: GHX Survey Reveals Predictive Analytics as Top 2017 Priority for Healthcare Supply Chain Leaders
For hospitals looking to take advantage of predictive analytics in the supply chain, the most important factor is having access to the right data. The “garbage in-garbage out” mentality is especially important when it comes to predictive analytics, as having inaccurate or incorrect data can lead to poor decision-making. Using a tool such as iRISupply from Mobile Aspects can help hospitals ensure their data is as highly accurate as possible as they go down the journey of using predictive analytics in the supply chain. Without a system to ensure high fidelity data, hospitals may be stuck with “garbage” in their supply chain.