Who will unlock the giant data bottleneck in healthcare?

A recent article in the Harvard Business Review discusses the findings of a survey of senior executives across sectors and confirms that two-thirds of them report having big data in production, with 70 percent indicating that big data is of critical importance to their firms. Consumer oriented industries such as financial services are heavily represented in the survey, as are life sciences firms.

As with most innovation and new technology programs, adoption rates and effectiveness will vary across sectors, and even within sectors. Typical factors influencing this dynamic are an industry sector’s historical approach to cutting edge technologies, focus (or lack thereof) on top-line oriented innovation vs cost reductions, and ROI considerations, just to name a few.

Even within Healthcare, the focus may be on R & D in pharma, claim expense control among payers, and clinical outcomes improvement in providers. Accordingly, stakeholders take widely varying approaches to investments in big data, and this consequently shapes their approaches towards the stewardship of enterprise-level data.

Why is healthcare suboptimal in the use of available data?

A paper by the IMS Institute for Health examines this issue in great detail and outlines the tradeoffs that regulators and patients have to make for data to be leveraged meaningfully. The paper argues that longitudinal data, even in a non-identifiable form, can be extremely useful in accelerating research and supporting connected health initiatives, involving big data from multiple sources, including new sources such as wearables. However, there are several bottlenecks in harnessing all this data – these include the willingness of participants to share data, regulatory and privacy restrictions, the suitability and reliability of new data sources, and information security considerations.

The challenges related to interoperability of data are well-known, as are the privacy restrictions on the use of data. However, several workarounds are emerging, as market participants (belatedly) coalesce around common standards to enable data exchange and analysis across the healthcare ecosystem. Cloud-based models that are HIPAA compliant and secure, are becoming more and more accepted as enterprises recognize that in many cases, cloud environments can be even more secure than their own legacy environments.

However, even with all of this, the ability to derive value depends on an individual institution’s access to large amounts of data within and across health systems that enable benchmarking and pattern analysis. This is where the fragmented healthcare system comes up short. The big EHR vendors, despite their access to vast amounts of data, have been slow to take the lead. Initiatives such as health information exchanges (HIE) remain regional, with their own set of restrictions governed by the individual members of the exchange.

The HBR article concludes that the vast majority of the problems in big data programs relate to people, not technology. Within organizations, effective use of data is stymied by management silos, and the disconnect between CIO’s and the lines of business hampers the collaboration required for improving patient outcomes. Governance models within healthcare are evolving slowly, with the role of Chief Data Officer still relatively rare. The absence of centralized governance and the lack of collaboration weakens the data even further as individual groups choose to work with the limited data available within their silos.

The result of all this is an industry that operates sub-optimally at a system and a firm level across all of healthcare.

So who bells the cat?

As technology continues to progress, the ability of healthcare to adopt and benefit from big data programs will continue to increase, and the focus has to inevitably turn to governance issues. As with sectors like retail and financial services, the solutions may emerge from disruptive forces outside the system. One obvious source of disruption is Silicon Valley, with its iconoclastic ways of approaching the status quo.  Notwithstanding some regulatory challenges, most recently with insurance broking startup Zenefits, some of these startups will successfully disrupt incumbent players and their deeply entrenched interests in maintaining the status quo.

A second, unexpected, source of disruption seems to be big employers, especially the large companies that underwrite the costs of medical expenses for their employees. A group of twenty large employers, including the likes of American Express and Verizon, are forming a coalition to pool the medical claims information on their 4 million collective employees to identify opportunities for group purchasing and contracting that will put pressure on health plans and providers to reduce costs. These employers are motivated by multiple factors – controlling costs, retaining employees, and managing financial risk being some of them.

Frustration with the current state of healthcare, especially the large premium increases we have seen this year, will lead to some radical new thinking – which many of us crave, including this blogger. Sure, there will be lots of hand-wringing about new players playing fast and loose with patient data.  At the same time, the fact is that the key to solving this bottleneck is in the hands of the incumbents in the healthcare system. If they choose not to use it, someone else will. Very soon.