The world is awash in data. It is estimated that the amount of digital information increases ten-fold every few years, with data growing at a compound annual rate of 60 percent. The big technology company Cisco has forecast that by 2013, the amount of traffic flowing over the internet annually will reach 667 exabytes. Just to put that in perspective, one exabyte of data is the equivalent of more than 4,000 times the information stored in the US Library of Congress.
This data explosion – now rather imprecisely dubbed “big data” – is both an opportunity and a curse. Having all of that information makes it possible to do things that were previously never even imaginable. Last year, the McKinsey Global Institute (MGI) conducted a major research study on big data, calling it “the next frontier for innovation, competition, and productivity.” The MGI study noted that big data is becoming even more valuable as our analytical and computing abilities continue to expand.
On the “curse” side of the big data phenomenon, the growing mountains of information also pose massive challenges to those who need to manage it. Having ever greater volumes of data to sift through to find critical insights (the proverbial needle in the digital haystack), is a growing problem for companies, organizations, and governments the world over. Sometimes, there really is such a thing as too much information.
The data deluge is especially urgent for hospitals, which are factories of data. In the typical hospital, data flows from every department and function – from emergency department admission records and HR systems, to purchasing and billing information. But, hospitals are not exactly known for effectively managing data. The healthcare provider sector is probably 20 years behind other major industry domains in terms of how its uses data. Many hospitals fail to realize the value of the data they do have – or they are overly focused on EMRs.
Here’s the real problem: The failure to “connect the dots” of these treasure troves of data is having a profoundly negative impact on the ability of hospitals and health systems to make the right and timely decisions that are essential to produce better outcomes and results.
But there’s good news, too. Effectively mining and managing these assets presents a huge opportunity for the healthcare sector as a whole. The following quote from McKinsey’s big data study vividly captures the potential scope of that opportunity: “If US health care could use big data creatively and effectively to drive efficiency and quality, we estimate that the potential value from data in the sector could be more than $300 billion in value every year, two-thirds of which would be in the form of reducing national health care expenditures by about 8 percent (at 2010 levels).” Regardless of where you sit within healthcare, numbers like that tend to focus the mind!
All of that said, healthcare providers still have a long way to go before they can come even close to realizing the value creation, efficiency improvements, and cost savings described above. In the typical hospital setting, for example, each department controls its own information silos. This highly fragmented data environment begets disconnected strategies and uncoordinated decision making. The result is that both hospital issues and opportunities are dealt with on a one-by-one basis, rather than as a holistic strategy. It certainly is not a recipe for the kind of well founded strategic planning that is so critical to hospitals’ success in today’s intensely challenging healthcare environment.
Streamlining – Time-stamp data that is critical for streamlining patient throughput is – almost never – connected to quality data that measures the value of a hospital’s services. These data silos are never connected to workforce data that measures nurse productivity. That is a difficult way to approach operational improvement initiatives.
“Connecting the dots” by mining siloed data to create actionable insights still stands as the management “Holy Grail” for hospital executives. I argue that it is an absolute imperative for hospitals today. Emerging technologies such as cloud computing, open-source software, and advanced analytical tools have all provided powerful new capabilities to solve this big data challenge for hospitals. And while there is still plenty of work to do to attain the true state of data analytics “nirvana” in healthcare, the journey is a necessary one.
By “connecting the dots” and leveraging the power and promise of data assets, hospitals can improve the practice, delivery, and economics of healthcare. But, to accomplish these ambitious goals, hospitals need to first make some significant changes in how they handle big data.
Still Struggling to Get the Right Data Into the Right Format? – If the answer is “yes” for your hospital, you are not alone. Each hospital system has a profusion of datasets – workplace/labor, financial, EMRs, purchasing, etc. – and a multiplicity of vendors offering their services to manage those data. There typically is not one dedicated person or entity looking at the vast amounts of data being produced every day in a given hospital. The data “management” is all over the map. You could thus say that attempting to manage a hospital’s data is like trying to weave a basket without actually connecting any of the strands. There’s even a more fundamental issue – the majority of hospital data is not even kept. According to the McKinsey Global Institute big data study, healthcare providers discard 90 percent of the data they generate!
These days there is more attention being paid to EMRs (mostly due to healthcare reform’s “meaningful use” incentive), but other hospital data streams are equally important. The fact remains that the technology “plumbing” that formats and stores these datasets can be strikingly different, and very difficult to integrate and manage cohesively. And that’s not the end of the data integration roadblocks for hospitals. The dominant technology vendors serving the healthcare provider sector have their own proprietary systems, which seldom operate effectively with others. The result is that the hospital’s internal silos get integrated into even bigger proprietary technology silos, further exacerbating the fragmentation problem.
For hospital management, the starting point for capitalizing on the opportunity is to get the data they need, in the right formats. This daunting task requires skilled data “plumbers” who can architect systems that effectively collect and manage the huge volumes of data that constantly flow through hospitals. However, because of the fragmentation and complexity of the data plumbing in the healthcare provider sector, there are not a lot of entrepreneurs working on reinventing big data for hospitals. The effect has been an unfortunate stifling of innovation in the space. By contrast, the datasets are relatively consistent on the payer side of healthcare. Because of this comparative technology alignment, payers and their technology partners have been much more successful at mining their big data, delivering real competitive advantages to this healthcare sector.
Run ‘Meaningful’ Analytics on Those Datasets – Once digitized, collected, and formatted, those massive streams of hospital data are still not useful unless they are analyzed effectively. Advanced analytics now exist to make sense of big data, but that does not mean that these sophisticated software tools are being used widely or effectively among healthcare providers. Many hospitals are already deploying “business intelligence” tools that feature “dashboards,” which purport to give senior management a real-time (or close to real-time) view of key metrics for operations, finance, productivity, etc. When you dig a little deeper, however, you find that most of these tools are barely used, if ever, by hospital management. The tools are good at generating a lot of reports, but much less effective at giving hospital executives the information and insights they need to make decisions that create real impact and effect positive change. We know of one hospital that uses its business intelligence system to generate a 500-page report every month. The problem is, no one ever looks at it.
The overriding goal must be to produce “meaningful” information and “actionable” insights that actually answer real-world questions for hospital management. To be sure, this requires deep data analysis, using advanced analytics software that sits on top of the big data streams created within the hospital. Equally important in this analytical process is having valid, external benchmarks that enable management to determine what “good” actually looks like. Without these benchmarks, hospital directors are just making decisions in a vacuum. As one hospital CEO said recently, “The real problem is that I don’t necessarily trust the data I am seeing, so how can I make effective decisions based on this information?”
Get the ‘Actionable’ Insights into the Hands of the Right People – In your journey to capitalize on the data opportunity, you can nail steps 1 and 2 and still not drive meaningful change in your hospital. To do that, you’ve got to bridge the “last mile” of connecting the dots and get the actionable insights into the right hands, at the right time. This is a challenge of both technology and management. We are still seeing hospitals continue to over-emphasize the collecting of information rather than carefully analyzing those data to create insights that truly matter. Many hospitals also lack effective ways to deliver the right information to the people who need it most – especially at the critical point in time when that information will have the greatest impact. For example, “hotspot” alerts need to be delivered to the Chief Nursing Officer when she urgently needs them. The CEO, on the other hand, needs to receive timely metrics on financial and productively trends that are vital in making go-forward plans and decisions. Too often, neither of these hospitals leaders have the critical information in their hands, when they most need it.
Every single day, the healthcare industry is producing ever increasing volumes of data and information – whether it’s managerial, operational, or at the patient level. For hospitals and their management teams, the biggest challenge – and greatest opportunity – is connecting the dots by effectively analyzing those big data streams to drive better decisions, and a higher level of quality patient care.
We call this problem “the last mile” problem. For many hospitals it can be the thorniest challenge. Analytic results must be effectively delivered to the point of decision-making, they must be integrated into managerial hygiene, and sometimes presented into workflow. Each hospital will make decisions in a slightly different way, so it is important to have flexible, configurable systems that can become part of an organization’s usage and culture.
Russ Richmond is the CEO of Objective Health, part of the global McKinsey Healthcare practice, which serves hundreds of public- and private-sector organizations worldwide. He is passionate about the use of data to manage health and to improve healthcare performance. Russ served over 50 hospitals as a McKinsey consultant, across the USA, Europe, and Asia.