Just last month I wrote about the many ways data analytics is being used to transform healthcare. From infection reduction to pill management to controlling labor costs to managing transfusion medicine and much more, analytics is helping providers deliver higher-quality healthcare while controlling costs.
But as with analytics initiatives in any industry, success is dependent in large part on buy-in from an organization’s decision makers. Paying lip service to the importance of data analytics without providing the resources necessary to implement an effective analytics initiative is a sure recipe for underperformance and even failure.
A survey conducted at the HIMSS16 conference in Las Vegas in early March shows that many healthcare providers feel they simply aren’t getting what they need to make their analytics programs pay off. The fourth annual Health IT Industry Outlook Survey by Stoltenberg Consulting polled healthcare CIOs, CMIOs, IT project managers, IT directors, and consultants.
Among the results:
- 37% of respondents said while their organizations’ data analytics programs are “well underway, they lack resources to complete requested initiatives”
- 36% said their programs are in the early stages, and they need assistance to further develop them
- 32% said “correlating data from diverse and dissimilar sources is the biggest hurdle to data analytics”
Combining the top two results, nearly three-quarters of respondents are saying they’re not getting enough resources to meet their data analytics goals. There could be several reasons for this, including that clinicians and healthcare IT directors aren’t making a strong business case to CFOs and other decision-makers. Or maybe the decision-makers are hedging on providing support because of budget limitations or competing priorities.
Whatever the source of the disparity between intentions and allocated resources, the end result will be disappointment and lower-quality customer service (healthcare) as long this inherent misalignment persists. One strategy providers can pursue if they want more commitment from decision makers is to focus on one analytics project that enables them to deliver a “quick win” in which positive results are clear and demonstrable. There’s nothing like real-world evidence to persuade reluctant decision makers to up their commitment.
Are your enterprise’s analytics initiatives getting buy-in or lip service?