Seeing the Forest Through the Trees
Frequently the topic of keynote speeches at conventions, harvesting the benefits of big data is a collective area
of discussion and debate among healthcare and technology visionaries. Most agree, data itself will not contribute
to productivity unless it’s in a useful format that enables enterprise-wide decision support to ultimately
improve productivity. It’s at this point where data becomes BIG data.
The healthcare industry has some work to do when it comes to improving productivity, which is why big data
is such a game-changing opportunity for the industry. According to research done by McKinsey and Company,
during a 10-year period from 1990-2010, the computer and semiconductor industry improved productivity by
7.6 percent and manufacturing by 2.5 percent whereas the healthcare industry decreased by nearly 1 percent
in the same timeframe1. There’s much to gain by understand the journey other industries have taken in
using data to drive productivity.
Industry Productivity Improvement Percent, 1990-2010
Source: McKinsey & Company, “How US healthcare companies can thrive amid disruption”, June 2014
First, simplify the complexity of big data
Until recently, the ability to tap into all of the information available in a hospital was beyond the industry’s collective
technological capabilities. In this highly-fragmented industry, providers are grappling with how to tap
into healthcare IT systems to meaningfully harvest their data now available to combat two critical issues:
massive inefficiencies and rising costs. While there’s great potential for data to help improve patient outcomes
in tandem with cost-reduction, the path to achieve progress remains undefined. The lack of system integration
and complexity of the data across operational and clinical workflows is, arguably, why the challenge of harvesting
big data is so immense for healthcare.
“Even in 2010, a clinic in the U.S. would have
had one-billion terabytes of data. To put that
into context, that’s the same as having
two-trillion filing cabinets of information. So,
we are already there. We are in the era of big
data. The challenge is: how do you make sense
of two-trillion filing cabinets of information.”
– Dr. David Dembo, General Manager for Healthcare Solutions, Healthcare IT, Australia & New Zealand2
By taking a step back and recognizing the investment (time, money and people) required to truly achieve transformational
capabilities with data we can recognize where we are in the journey and outline the evolution that
must occur to reach our goals.
Take a data inventory
Healthcare faces a much larger challenge than other industries as it relates to achieving productivity gains.
Every industry has faced the productivity curve, but the challenge is multiplied in healthcare as data digitization
includes both operational and clinical information, and because of the interdependencies that exist across
the system of care that exponentially increases the complexity of achieving efficiency. Given the various data
inputs, it is appropriate that there would be tens and even hundreds of different processes that all must align to
drive operational efficiency within a service line, not to mention an entire system.
To compare to manufacturing (an industry which, according to the same McKinsey study mentioned above,
achieved a 2.5% productivity gain between 1990 and 2010), imagine a plant that manufactures hundreds of
variations of their product using the same line and people with little or no advance warning of which part they
must manufacture, and the potential for the identified pathway to change at any time based on the ‘response’
of the part. The variability of information would be worrisome at best.
Today, providers have too much data, but not enough information. There’s a roadblock, both mental and technological,
that makes it extremely difficult for organizations to envision how big data can lead to enhanced decision
support and its promised cost-reductions. The first step to overcome those roadblocks is to identify where
you are on the productivity journey.
Every organization should be looking not only at how to first digitize their data but how then to ensure the
digitized data will be able to be consolidated to connect meaningfully to the rest of their hospitals and entire
networks’ systems. Many organizations have focused on building clinical data systems, but there is an equal
need to digitize the operational data (ie. bed request and placement, patient transport, environmental services,
laundry, food services, etc.), for an organization to truly unlock productivity. It all starts with having the data
digitally. This will enable the analytics needed to get to the next steps. Once you get the information digital;
however, don’t stop. Digitizing in the first step in seeing your investment through to realize what’s ultimately
possible–clinically, operationally and financially.
Take, for example, the need to replace broken or old equipment. Customarily, budget requests drive the
process rather than data-driven decisions. Few providers have the capacity to analyze utilization data–how
equipment is used, and whether devices sit idle or are used at capacity.
“When organizations take a different approach to examine data, they often purchase fewer replacements
than anticipated,” explains John McCarthy, general manager of GE Healthcare’s Asset Management Professional
Services. “Ensuring that all equipment is at capacity is a task that few providers master, given that
compiling the data is a formidable undertaking. It takes effort and expertise to go into databases, but the
return is phenomenal. When you improve utilization rates, you can reduce operating expenses. In some
cases, we’ve seen providers purchase 30 to 40 percent less equipment than they anticipated following a
careful analysis of the data.”
Next, manage and analyze your data to enable decision support
My conversations with healthcare executives reflect the growing need for new approaches to making use of
information to ultimately enable decision support. From an operational perspective, clinical needs still tend to
drive decision-making. In healthcare, integrated data across departments, as well as clinical and operational
workflows, will be critical to unlock the ability to prioritize work, activate decision support and enable technology
to support the advancement of patient care with significantly less non-value added human interaction
than is required today, thereby improving efficiency and productivity, while increasing the caretakers’ time with
Significant advancements are being made every day in shifting to analytics that can drive productivity–from
tools that can provide operational workflow across the patient stay, to predictive tools that can inform of
pending bed shortages hours and even days in advance. However, until integration across all aspects of the
patient’s journey–both clinical and operational–can interconnect for every patient in the system, we will fall
short of what is truly possible to automate.
The journey is painful but imagine the day a patient calls their physician and is seen immediately, with all historical
records available–via telemedicine–and is asked to go to the hospital. He/she then hops onto a website,
which already knows he/she is coming, and is asked to select a bed (much like seats on a plane). He/she shows
up in the room they will occupy and is greeted by a nurse who has the patient’s records on hand and who has
already scheduled the required procedures and can give the patient an itinerary including a projected date and
time of departure. This–and much more–is possible if we unlock the data that exists.
The challenge of moving from consolidating and analyzing data to technology that unites systems is critical in
the journey from volume to value. At the end of the day, the technology that will give providers integration will
be much more powerful than any other breakthrough development on the productivity journey.
Finally, unlock the value (moving from volume to value)
As healthcare reform drives organizations to shift from volume to value, healthcare systems are shifting their
thinking about care settings. As we strive to deliver more care outside of the acute care facility it will be imperative
to create flexibility in operations to flex resources, processes, and ultimately cost structures very efficiently.
Longitudinal workflows–across care pathways regardless of the location of care (hospital, ambulatory, outpatient,
physician office, lab, etc.) –will also be necessary. This will require integration of IT systems to allow connected,
patient-centric clinical and operational workflow. Technology has not yet arrived at the point of delivering
these decision support tools, but they are on the horizon. It is short sighted to shift care from the hospital to
an ambulatory or home health approach, for example, without having a way to quickly re-purpose or remove
the capacity that is left behind. This flexibility in operations is a major output of the productivity journey and
what automation can provide. Big Data, and the ability to integrate that data meaningfully, is critical to developing
flexibility for health systems. For example, we can use clinical and operational data sets to simulate and test
new approaches to care in a virtual environment before implementing in the real world. Testing and iterating
the complex care pathways will allow for designs that can minimize the number of steps needed to complete
tasks, optimize staffing to improve outcomes and patient experience while reducing cost, set schedules that
minimize variation and peaks and valleys in the flow of patients, and more. Designing the hospital and health
systems service line strategy and operational approaches using big data will help overcome speed and flexibility
issues that plague health systems today. The benefit of integrating data and moving toward predictive
analytics offers too great a potential to be ignored.
As big data allows us to move from design and testing virtually, to true automation, healthcare executives will
gain the ability to flex structure, change where care is delivered, increase or decrease acuity, and understand
the cost and staffing implications at a detailed level before making a single change to the care delivery system.
This capability will enable the transformation from volume to value.
According to a recent study titled The Big Data Cure (produced by MeriTalk and underwritten by EMC
Corporation), “Federal agencies focused on healthcare research and care delivery are testing the waters
today One in three say their agency has successfully launched at least one Big Data initiative–35 percent
use Big Data to improve patient care, 31 percent are reducing care costs, 28 percent are improving health
outcomes, and 22 percent are increasing early detection.”3
When we imagine breakthroughs in healthcare, we picture life-saving vaccines and disease prevention.
However, with the potential to curb costs through massive efficiency gains while simultaneously delivering a
higher standard of care, big data offers one of the biggest breakthroughs available in healthcare. Leadership
and vision at the C-level of each organization is absolutely critical to driving big data beyond just digitization
and focusing on how that digitized data connects the system and is used to redefine efficiency and flexibility.
It will take more time and investment to truly realize the potential that healthcare can achieve.
“Blogger Paul Roemer asks, What if Amazon ran population health management? Amazon collects lots of
data on shoppers’ purchasing behavior and makes recommendations for future purchases. Healthcare
organizations collect lots of data on patients’ (un)healthy behaviors–but they sit on it.
How much better would healthcare be, Roemer asks, if hospitals made recommendations based on the
terabytes of data they’ve collected about their patients? How many hospital readmissions would be avoided?
How many chronic patients would get better? How many accidental deaths would be prevented?”
– Brian Eastwood, senior editor, CIO Magazine4
1 McKinsey & Company, “How US healthcare companies can thrive amid disruption,” June 2014
2 See GE Reports, “Healthy data: How big data will transform the patient journey”
3 MeriTalk, a public-private partnership focused on improving the outcomes of government IT, released the
results of its new report, “The Big Data Cure” on March 24, 2014. The study, underwritten by EMC Corporation,
surveyed Federal executives focused on healthcare and healthcare research to examine the current state of Big
Data in Federal healthcare. Download the full report here.
4 See Eastwood, Brian, “Why Healthcare Needs Amazon (or Anyone) to Shake Things Up,” April 2014: