Big data, technology and the new health economy

2015 was a year of upheaval for the healthcare market. It was dominated by two main story lines – out-of-control drug pricing, and an influx of new investment into digital health and healthcare IT.

On the surface, it would seem that those two waves would converge with technology helping to solve the current medical economic crises. Unfortunately, the greatest impediment to modernizing the notoriously conservative healthcare industry is the fear of challenging the status quo.

The status quo in medicine exists for good reason: how we treat patients may determine whether they live or die. Making wholesale changes to those treatment protocols without proper testing, vetting and study is eminently dangerous. But so is failing to challenge the status quo. Trepanation, lobotomies, and blood-letting used to be standards of care. It wasn't until those standards were challenged with improved technology and science that the status quo changed. The unfortunate reality is how long it took for those changes to come about.

It may seem a radical statement, but I believe we're facing a similarly dire situation in the healthcare system. Technology in healthcare is accelerating at a quantum rate, but the pace of adoption is incredibly slow. That dichotomy is a recipe for disaster if not rectified in 2016 and beyond.

2015 saw the most active new company creation and funding environment in the healthcare space ever. More than 800 new healthcare IT and digital health companies collectively received over $10 billion in investment capital in 2015. Even technology focused investors like Google Ventures have re-positioned their investment portfolios to focus on healthcare and life sciences. The innovation machine sees and understands how underserved healthcare is technologically and wants to apply its credible and significant force to help fix it.

What stands in the way? The healthcare market as a whole is not ready for this new rash of applications and solutions. Whether it's a top-level decision to not support a new effort or a basic problem like users still being stuck using outdated Internet browser technology, it doesn't seem that the healthcare system is quite ready for the wave of innovation about to crash on its shores.

But there are glimmers of hope. One of the areas where innovation has started to take hold is in the area of improved data analysis – or "big data." While many have come to recognize the value of improved data collection and dissemination in healthcare, the real advances are now being made in how best to analyze those disparate data and transform them into actionable intelligence.

Maybe the reason for the early uptake of data analytics in the current healthcare market is that science and medicine have relied on observation, data collection and curation, and outcomes analysis in various forms for the past few hundred years. The challenge today is that data availability has increased exponentially, so the tools to analyze those data have naturally had to grow in size and scope as well. But at least in this arena, we're re-inventing the wheel rather than chiseling the first wheel out of stone.

And that's a good thing, because data don't lie. Data tell stories that can't be ignored. Data is factual evidence. And when presented via analytics it becomes clear that this knowledge truly is power for all stakeholders – payers, physicians and patients. Broad datasets will enable MCOs to better monitor, control, and mitigate patient risks and system costs. And the advent of analytics that review and dissect data will enable proactive and not just reactive action to be taken. Undoubtedly, we will see data and technology-driven systems drive healthcare the same way data drives the financial markets. It will become the rule and not the exception for health organizations to mandate the use of big data because otherwise it would be negligent to ignore data that reveals potentially life-saving information.

For MCOs to do their jobs and fulfill their obligations to the public at large they need accurate, unbiased post-approval side effect data that can help them inform recommendations and decisions on new and existing drugs. One of the best ways to control safety risks and reduce the cost of developing and deploying new medications is through technology-based data collection, management and analysis. Any broad discussion on cost containment must include a focus on how better data analytics systems can help achieve those goals. There is a tremendous amount of data available – everything from the FDA Adverse Event Reporting System (FAERS) to claims, EHR, social media and patient forum data. Each system has the promise of adding a significant layer to identifying drug safety concerns, and all should be considered as potential data sources. The only way to know a drug's complete safety profile is once it is widely used on the open market, and then only after the usage data is collected and mined.

In case after case analytics are changing the way prescription costs are determined. The industry is starting to adopt technology platforms that give them broad insight into the total financial implications of taking one medication over another. Managed care health professionals are modifying the way they determine formularies and altering their daily workflow, which substantially reduces the decision making cycle. They are now able to obtain concrete evidence to justify prior drug authorizations. Those that still adhere to the status quo and are not willing to disrupt their traditional workflows are getting left behind to deal with smaller profits and poorer outcomes. The innovators are reaping the rewards that data brings to their processes.

For example, Memorial Hermann in Houston, TX reports: "The future of healthcare can benefit from the systematic use of advanced data analytics with regard to adverse drug events... As our experience indicates, hospitals and health networks can improve drug decision-making by incorporating a thorough analysis of the most current post-approval drug side effect data. The benefits will be realized in a reduction in adverse event costs, such as hospital readmissions or other serious consequences, as well as improved outcomes among patients."

Of the 800 or so healthcare IT companies that received venture funding in 2015, some will succeed but most will fail. But they will fail doing what the healthcare system itself is loath to do – disrupt the status quo. Maintaining the status quo is no longer a workable strategy. The promise of Big Data is here and the ability to extract actionable intelligence and meaningful conclusions from those data is what will propel the healthcare industry into the 21century.

About the Author
Brian Overstreet believes the more data (evidence) available, the better chance patients will have access to safer and more effective medications, and providers and payers will be able to lower costs. Brian can be reached at brian@adverahealth.com

The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker's Hospital Review/Becker's Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.​

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