Data, data, data: just saying the words makes you sound smart. It’s not that easy, however. Yes, data collection has been simplified–just think of how much storage we get for free on our Google or Microsoft accounts. Analyzing data is easier too, although there are certainly big differences between basic and advanced analytics. The last piece of the puzzle, applying analytics to inform active decision-making, has historically been the hardest part, and healthcare is no exception.
This is what makes Paddy Padmanabhan’s article in CIO about the use of big data in healthcare so interesting. Among the challenges to adoption he cites are inflated expectations, data management, interoperability, and lack of coordination among stakeholders. The last challenge on his list, operationalization of analytics, may be the most important, however.
Padmanabhan astutely writes that “Most analytics solutions are ‘offline,’ meaning they operate in a stand-alone fashion, and analytics are not integrated into day-to- day clinical workflows.” Well said. He goes on to note that “Providers have limited options today for obtaining actionable insights through the implementation of big data technologies.” Limited, but not zero.
Padmanabhan’s article does a great job of highlighting what he calls “one of the significant gaps today in big data analytics implementations where standalone analytics platforms are unable to deliver real-time insights at the point of care.” The key, as he points out in his overview of Data Diagnostics®, a suite of patient-specific analytical reports (or "diagnostics") that physicians order within their existing workflow at the point of care, is that data is linked to specific actions physicians can take to improve the patient’s care, actions that connect directly to highly complex quality, risk, utilization, and other metrics upon which value-based care reimbursement models depend.
Padmanabhan calls this the “The unlocking of value,” and it may be the most important takeway. Sure, having more data is important. And analytics are absolutely critical. But without affording access at the point of care to those who need it most–physicians–the value of the data is largely untapped. As Padmanabhan puts it, “having a mountain of data is one thing, and delivering real-time insights from the data at the point of care is a whole another thing.”
Padmanabhan’s final point is that the industry’s path forward toward value-based care isn’t just about disruption. It’s about taking an existing workflow and improving it for new demands and better outcomes. Data isn’t an end, but rather a means to an end. That end should be actions at the point of care that have upstream ripple effects related to quality, financial performance, and outcomes across health systems and health insurers, who both stand to gain from them. It would appear that Padmanabhan agrees.
*All databases are limited to the data input into them.
Paddy Padmanabhan "How Quest and Inovalon have unlocked value in healthcare analytics" - CIO From IDG - Mar 17,2016