Dear Healthcare Industry,

We are drowning in data, and despite the current challenge to stay afloat, we continue to demand more. Thankfully, life jackets are all around us — from the successes and failures of past healthcare initiatives, to best practices from other data-rich industries, we are surrounded by insights to help us ride the massive data wave of the coming decade.

Source: Statista report forecasts that global Big Data revenue will hit 103 billion by 2027.

Lessons From Our Past

I lived through the era of genomics — a time in which sequencing the human genome was akin to unleashing the “key of life.” In 2000, President Bill Clinton predicted the Human Genome Project’s findings would “revolutionize the diagnosis, prevention, and treatment of most, if not all, human diseases.” It was hailed as the most significant scientific discovery since Darwin’s theory of evolution.

While the genome continues to yield surprise after surprise for researchers and biologists, the primary goal of the $3 billion project — to identify genetic roots of common diseases and generate treatments — remains largely elusive. When it comes to knowing where to look for the roots of common disease, geneticists are back to square one. Genomics provided a profound understanding of science, but the DNA sequence alone was insufficient to transform medicine and must be aggregated with additional data streams.

Similarly, in healthcare, access to more data may provide a flood of digital information, but it takes rationally informed effort to guarantee improved care. How can healthcare organizations be confident that there is an effective use for the protected data? Further, how can these organizations conclude that such access would improve the quality of care? Before we can effectively handle higher quantities of data, we need higher quality digital information and established infrastructure.

Lessons From Our Neighbors

If data alone does not promise transformation for the healthcare system, how has it been so revolutionizing for other global industries? Consider the financial industry, where real-time big data fuels algorithmic trading and yields better-informed decisions on a second-to-second basis. If we reflect on data’s profound reformation of our shopping experience, we encounter big data at every step of the retail process — identifying popular trends, advertising, forecasting demand, optimizing prices, identifying target customers, securing payment, assisting delivery, suggesting related purchase options, and strategizing on what to offer next. The insurance industry is another case in point. From setting policy premiums to tracking fraudulent claims, big data has forged new business models and created enormous opportunities to increase revenue streams.

The financial, retail, and insurance industries are not alone — 80 percent of executives from media, entertainment, manufacturing, travel, and logistics companies report their investments in big data processing as “successful,” and more than one in five declare their big data initiatives have been “transformational.” If big data is revolutionizing old-school industries, birthing new systems, and radically improving business for many, why has its impact on healthcare been so different?

Key Takeaways To Optimize Big Data

First, industries that have implemented effective big data solutions had to first identify and understand their core pain points. In healthcare, this requires an inquisitive consideration of the factors that deter providers from achieving the higher purpose of healthcare — to effectively treat patients. Data solutions should help achieve this goal for clinical providers and for individuals who are attempting to improve their lives. This means designing for the challenges of today and implementing data solutions that enhance existing medical knowledge and practices. Rushing to adopt the latest data-driven technology for the sake of appearing innovative is costly and senseless. Let’s innovate for today’s users, the patient and physician, and stop investing in outdated infrastructure and future fantasies of magically disrupted clinical practices.

Second, industries that have successfully adopted big data practices have the infrastructure for data collection, storage, analysis, and output that is functional for companies and consumers alike. Without the proper technology platforms, tools, and training, it is impossible to effectively capture, analyze, and utilize digital information to serve customers. Establishing the infrastructure requires a difficult cultural shift: Interactions are redefined, rules are rewritten, and patience is necessary. Until healthcare organizations strategize on how to use data and analysis to support the existing model, the industry will not be able to reap the benefits of big data.

Lastly, in addition to introducing big data with infrastructure and intent, without interpretive human labor, data is but digital information and does nothing to improve the state of healthcare without identifying how people, patients, and providers will use it. This begins with data scrutinization: Who is this data for? What is its purpose? When and how did it come into existence? Why is it meaningful? The answers to these questions are infinite. People in the different segments of healthcare — insurers, clinical providers, lab analysts, and patients — all have varying perspectives on the value and capability of data. And even if value could be agreed upon, we would need the expertise to process it. With less than 3% of data scientists in the U.S. working in the healthcare field, we have to question ourselves: Even if we “get what we want,” will we know what to do with it? For big data to be as meaningful, innovative, and transformational in health as it has been for other industries, there must be intentional human labor and technological prowess behind it.

Innovation only goes so far as a roadmap. Let’s reevaluate the who, what, and why of data before we pour critical resources into attaining more of it. Without a rational, pragmatic, grounded and ruthless consideration of public health applications, R&D efforts, and tangible clinical results, big data will forever fail to cure the pain points of healthcare. I recommend that we take two steps back and reorient our innovative efforts around providing quality care.

Lawrence Cohen
Chief Executive Officer, Health2047