Big data may be about to overwhelm the healthcare system. A little healthcare business intelligence tip: Data by itself won’t drive value and outcomes. Smart healthcare analytics will. In Deloitte’s DBrief, “Big Data Revolution: Unlocking Healthcare Analytics,” healthcare industry experts talked about the opportunities and barriers for industries across the care continuum to harness data, contextualize it and use it to move from hindsight to insight (and eventually, with the help of predictive analytics, foresight).
“The future is already here,” Brett Davis, a principal at Deloitte, said. “It just hasn’t been evenly distributed yet.” Here are the six key trends in healthcare shaping how data will be used.
- Expanding definitions of health: Diagnostics, expense management and straight-to-consumer tools all are adding scope to the doctor’s visits and emergency care runs of yore.
Deloitte’s National Technology Principal for Life Sciences and Healthcare Dave Biel said that redefinition even begs the question, “What is medicine?” Questions arise about whether patients need to ask their doctors about certain things, or whether talking amongst themselves is sufficient. - Demanding demographics: With individualized risk assessments, personal health records and genetic screening (plus remote monitoring and other mhealth services), Dan Housman, the CTO of Recombinant by Deloitte, said it’s a “game-changer” to patient access in real time. But it also puts an enormous amount of pressure (and a big potential for opportunity) with the data.
And yet, those demographics also have “overarching demands” about the security and privacy of their data, Biel said. They want to know who owns it, who stores it and if it’s secure. This actually can add cost into the system initially, especially as data is added to the cloud, he said. - Rising pressure in policy, politics and economics: Grab a durable umbrella. Most simply put, as Biel said, “It’s a storm.” Not just Obamacare or regulation of high-tech — the Sunshine Act, ICD-10 and global regulatory trends also affect analytics.
If harnessed properly and well, of course, big data analytics could prove to be an answer to meeting many value- and outcomes-based healthcare goals, such as reducing readmissions and identifying high-risk patients, procedures and populations.
But it’s easier said than done.
“The basic goal in terms of medicine is to not do harm to your patients,” Housman said. That carries over to analytics. The research must be ethical, and patients will ask (and should) who’s viewed their records. But it gets tricky — for instance, does it count if the record was “viewed” as a faceless, nameless part of a statistic? - Converging relationships: Payers and providers are beginning to converge; pharma and device companies are too, Biel said. Outsiders are connected to projects within previously insular entities. Analytics work best when the data comes from the widest range possible: the hospital, the primary care physician, the home, when it considers environmental factors.
“It’s still a little bit the early days” for payers and providers, Housman said, with the two groups just trying to suss through all this information they didn’t have before. - Expanding connectivity any time, anywhere: Mhealth trends, yes, but also sensing technologies, connecting and contextualizing biometric data — all those smart watches and remote home monitoring systems, their data needs to be contextualized. In other words, the signal needs to be sorted from the noise, Davis said.
- Increasing transparency: Simulations can help with self management and with public health preparedness. The important takeaway is that in a transparent system, “technology shapes behavior,” whether it’s through real-time feedback from diagnostics or a system that slices the data.
Physicians sometimes complain about patients Googling or WebMD-ing symptoms and the health information available to anyone with a keyboard and a WiFi connection comes in a variety of qualities. “But the broader trend of transparency is here to say,” Davis said.
Harry Greenspun, Senior Advisor for Healthcare Transformation and Technology for the Deloitte Center for Health Solutions, noted a “reluctance in (healthcare companies) to actually collect this data and make it public.” Housman countered, saying companies don’t have a problem collecting the data. Instead, he said, there’s still a “firewall between providers and payers” on who owns what data.
Another interesting note is patients tend not to use those (few) electronic and statistical tools that are available to them now. They prefer guidance from “trust networks,” Housman said — those friends or long-time doctors. Will they some day behave as they do when using travel or restaurant websites, searching for the doctor with the most stars to perform their hip or gall bladder surgery? Who knows?
As the healthcare industry begins to implement big data analysis, it’s important to note they can’t move from the foundational (finally implementing EMRs) to the highest levels of innovation. It also isn’t the same as other technological jumps healthcare makes, such as transactional ones. It’s not a “We implemented it! It’s done!” Davis joked that healthcare analytics are Zen because they’re “in a constant state of becoming.”
For an example of predictive analytics being used broadly across a healthcare system in Indiana, click here.
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