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The Realities of the Real-Time Enterprise

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By JENNIFER SCHWARTZ and MARIE MURPHY

As if healthcare leaders, especially those in health IT, didn't already have enough on their plates, something new is on the horizon that could have a profound effect on every area, from clinical to financial to operations and beyond: the impending real-time enterprise.

The proliferation of transformative computing trends such as the internet of things, machine learning, artificial intelligence, and virtualization is changing the way we view data - and the way we consume it. As a result, both our traditional hub-and-spoke networks and the devices that increasingly tie into them, such as sensors and mobile devices, are now able to share a virtually unlimited barrage of streaming data.

This capability opens up all sorts of new possibilities. Because streaming data is continual and immediate (as opposed to batch data, which comes in at set intervals), it gives enterprise-level healthcare organizations the ability to make decisions and take actions as the data is delivered. In fact, with the right infrastructure in place, all of this streaming data can be routed to a data lake, making a much broader range of data from disparate sources available to business intelligence solutions, enabling healthcare organizations and their many business functions to create actionable insights.

Of course, all this massive, real-time computing and decision-making power comes at a cost that is both technical and financial. That's why, before jumping in to become a real-time enterprise, healthcare organizations must first ask themselves whether these real-time capabilities are necessary. They may find that near real-time data is perfectly suited to many needs, and even that batch operations are still useful in many settings.

The key is to understand what the organization needs to best manage its flow of data regardless of where or when it is created. It can then use these five steps to develop the appropriate enterprise information management strategy.

Start with the business objectives to determine if real-time data is even needed

The time for adopting technologies simply for their own sake is long past. Key executives within the organization must collaborate to determine whether there is an actual business need that calls for immediate access to, or use of, information as it is created. This need must also be balanced by practical considerations.

Real-time data requires a much higher level of network resources than data that is sent every hour, or once a day, as batch processes often are. Does the organization already have those resources at its disposal, or will it need to make a significant investment? More important is the nature of the data itself.

Take telemonitoring for example. For some patients, receiving a daily or even hourly update of vital signs is sufficient to monitor trends and alert clinicians to potential issues before they occur. For other high-risk patients it may be necessary to monitor them continuously, as sudden changes can quickly trigger an adverse event that results in an emergency department visit or an inpatient admission. Once organizations understand their information needs they can set the proper data flow strategy.

Have a plan for mobile and outside devices

Healthcare was traditionally slow to adopt the use of outside devices as a result of concerns about security and maintaining the privacy of patient protected health information (PHI). That is rapidly changing, however, with tablets and mobile phones rapidly replacing computers on wheels (COWs) and pagers. Not to mention the widespread use of Wi-Fi-enabled medical devices. Essentially, the once-hardened edge of a hospital's or health systems' network has become far softer, particularly in the era of value-based care where patient information must be shared quickly with partners across the care continuum.

To be effective in this new reality, healthcare organizations must have a data and device strategy that ensures they can access the data they want, when and how they want. They must also develop asset management strategies for those devices to ensure the information on them, especially PHI, is properly controlled, secured, and maintained. Not just while on-premise, but also off-premise, including what to do if a device is lost or stolen. It's a complex issue that requires tremendous thought and expertise.

Make data available to the enterprise at large

Healthcare organizations gather a massive amount of disparate data due to the digitization of administrative, clinical and financial information in electronic health records, bill and other IT systems - clinical, claims, financial, supply chain/inventory, personnel, operational, individual departmental, the list goes on. Traditionally analytics to make use of that data has focused in one specific area.

Today, those siloes are breaking down, with new business objectives creating a need for users to access data from multiple sources in order to drive real business improvement. This change often requires the creation of a data lake to consolidate all of the data in one place and normalize it for use by business users. Whether planning for real-time, near real-time, or batch use, a strategy must be in place to store, govern access, protect, and back it up as-needed.

Think of how users will consume the data

While it's important to make information available in the digital age, thought must be given to how users will consume it. Otherwise it just becomes more noise - which no one needs.

Consider data dedicated to monitoring the status of systems in a hospital. A sensor that monitors the condition of emergency lighting fixtures may only need to report once a day via an email or other non-urgent format. One that monitors the temperature of a refrigerator where temperature-sensitive medications are stored will need to trigger an immediate alarm, text, etc. if the reading goes above a pre-determined level in order to avoid spoilage. The goal should be to provide the information when it's most needed, whether that's immediately, in a color-coded dashboard, or in some other form, to minimize alarm fatigue and ensure the most important needs are acted on first.

Ensure the data can be used for multiple analytics

Different users will need to apply the data to their analytics in different ways. Any enterprise information management strategies should be able to accommodate all of them.

Some will want to use it to understand and diagnose what has already happened (descriptive). Others will seek to understand the variables that could occur, such as using predictive analytics to forecast staffing needs at certain times of the week, month, or year. Then there are prescriptive analytics that help organizations look at alternative possibilities to help inform decisions about what they should do.

Data that can't be incorporated into analytics is of little use. A proper data strategy that facilitates analytics is the key to driving value.

Planning for the long-term

What makes all of this challenging, especially in healthcare, is the never-ending battle between solving what's urgent today and what's going to take the organization where it needs to go in the long-term.

That's why having a strategy is so critical. By following the five steps above, organizations can ensure they are managing today's challenges while preparing themselves to become the real-time enterprise the will one day need to be.

I think long term enterprise analytics capabilities are so crucial - by funneling information into BI solutions that analyze and report on the date, healthcare providers can make better administrative, client and financial decisions that improve patient care and create a positive impact on reimbursement.

Jennifer Schwartz is an accomplished professional with special expertise in enterprise information programs, consulting, strategic planning, and mobile solution architecture. As the Enterprise Information Management solution lead for CTG, Ms. Schwartz focuses on business process management and automation, providing best practice guidance, and executing special projects that help transform data into action. Jennifer works across industries, advising clients on the execution of projects to realize efficiencies.

Marie Murphy is the Managing Director, Delivery and Operations, for CTG's Health Solutions practice. She is a Registered Nurse and a professional healthcare executive with more than 30 years of healthcare consulting, informatics, and professional services leadership. Her experience spans provider, ambulatory, inpatient, vendor, and regulatory. She has helped multiple healthcare organizations ensure that their EHR becomes a vehicle for improved clinical and financial outcomes.



 
 
 
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