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Operational Optimization

Big Data

Seeing the Forest Through the Trees

By Helen Stewart, GE Healthcare Partners

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

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.

Productivity Timeline

Productivity Timeline

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 patients.

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: Up?page=1&taxonomyId=3147

Helen Stewart

Helen Stewart, GE Healthcare Partners, Managing Principal, GE Healthcare Partners

Helen Stewart is Managing Principal, GE Healthcare Partners. In this role she leads strategy, day-to-day processes, commercial operations and delivery regionally for the business.

Helen began her GE career in 1995, where she held various field service sales and operational roles which expanded her knowledge of healthcare and created multiple strategic relationships with clients. In 1999 she became the Regional Manager for New York City and the surrounding boroughs where she led a region team in sales and strategic relationships for 11 key clients involving services, research, imaging solutions, and broad GE relationship management.

In 2002, Helen moved to a position helping key clients solve operational issues, and customizing GE’s approach to supporting those organizations to improve communications and ultimately client satisfaction.

In August 2007 she moved to a General Management position in which she was responsible for the Western 14 states delivery of quality services. She led the strategy and execution for delivery of imaging and biomedical service with focus on quality of care, compliance, alignment to healthcare needs, and development of people. She moved into her current role in January, 2012.

Helen graduated from Miami University with a B.S. in Manufacturing Engineering and a minor in Business Management.