Healthcare Data Management In A Data Economy

By Karen Way, global practice lead for data and intelligence, NTT DATA Services.

Karen Way

A recent study conducted by NTT DATA Services and Oxford Economics highlighted the top three challenges identified by healthcare executives and consumers: standardizing and sharing of data across the healthcare spectrum, preparing for and adapting to regulatory changes and recruiting or retaining the right resources. It’s understandable that these challenges rise to the top of the list, as trying to meet rising consumer demands for access to their healthcare data while maintaining regulatory compliance with limited resources is a bit like juggling raw eggs. If your timing or skills are just a bit off, you end up with egg on your face.

How can a healthcare organization address these challenges? First, it’s important to understand exactly which challenges are present within your own organization, and how they are impacting the patient experience.

Data Sharing

Study results showed that only 24 percent of healthcare organizations share data across the business. Why?  There are several reasons:

  1. Interoperability – Even though this concern has been expressed since the inception of the EHR/EMRs, there are still barriers to being able to communicate data between different systems in a consumable, usable format. For example, several years ago, I had a CT scan due to the sudden onset of a continuous migraine headache. After the scan, I was referred to a neurologist that practiced out of another hospital system. I took a copy of the scan (on a DVD) to my specialist appointment, but the doctor was unable to view it on her system. As a result, I had to have another CT scan for the neurologist to see what may have been happening. Data already collected could not be used due to lack of standardization across systems. As noted in Dr. Eric Topol’s book Deep Medicine, “Your ATM card works in Outer Mongolia, but your electronic health record can’t be used in a different hospital across the street.”[1]
  2. Data Volume – The volume of data being generated daily in the healthcare industry has been estimated to be approximately 30 percent of the world-wide total. With the estimates of data generation rates of at approximately 2.5 quintillion (that’s 1, followed by 30 zeros) bytes/day, that’s a lot of healthcare related data. Healthcare organizations aren’t even beginning to tap the depths of this data, simply due to the data volume.
  3. Disparate Data – Like patients, healthcare data comes in many different shapes, sizes and languages. Even if interoperability issues didn’t exist, sharing of data across the healthcare business is hard because of these differences. Data can be an image, a PDF, a written note, a prescription label, etc. Historically, each type of data requires different mechanisms for managing it, often using different tools or systems.

These three factors combined can be overwhelming for healthcare organizations whose main goal is to provide the best healthcare possible.

Resource Management

Another leading challenge identified in the study is that of recruiting and retaining skilled resources.  Of the healthcare executives surveyed, only 51 percent stated that they were able to recruit and retain resources with the required skills and knowledge. There are two components to this issue:

  1. Upskilling resources – With the continual advancements in technology, it is important to ensure that resources can take advantage of training opportunities and professional growth. This is often a delicate balance for organizations; time spent in training is often seen as time away from projects with deadlines.
  2. Healthcare experience – While there may be a pool of qualified resources with the required technical skills, it can be hard to find resources with knowledge and/or experience in the healthcare sector. For example, several years ago, a client brought in resources to support their enterprise data warehouse that had extensive experience in data warehousing. There were high expectations of new and improved functionality due to the technical depth of these resources. Unfortunately, the project did not deliver as expected. Why?  None of the resources had knowledge of healthcare data or business processes. One resource posed the question to the client: “what is a healthcare claim?”

Just as important as reviewing the patient experience for ways technology can solve the problem, it helps to treat your workforce like your customer and improve the experience of transforming the organization into a digital-first enterprise. A recent article in the Wall Street Journal highlights the difficulty in recruiting resources and approaches to solving this challenge.  The article also reinforces that in today’s data economy, it is no longer enough that a resource be technically skilled, they must also have knowledge of the business environment in which they are applying the technology.

Regulatory Complexity

Here is where the biggest barrier lies: only five percent of the study’s respondents felt prepared for upcoming changes in the healthcare industry. This is not surprising, given that the healthcare industry has been undergoing rapid change over the past decade. Reasons for the changes include:

  1. Multiple regulatory changes – Starting with the HITECH Act of 2009, healthcare saw the introduction and adoption of Meaningful Use, value-based care, the Affordable Care Act, a shift from Physician Quality Reporting (PQRS) to Merit-based Incentive Payments (MIPS) and more. In February 2019, CMS released a notice of proposed rulemaking for improvement of interoperability of health information.
  2. Increase in security concerns – As noted in the survey results, consumers see healthcare as a leading industry to provide personalized experiences all while ensuring the data is secure. This is a very fine line for healthcare organizations to walk, especially given the increased number of data breaches occurring worldwide.

Overcoming Challenges

There has been a significant uptick in the desire of healthcare organizations to adopt AI technologies, and this is expected to continue for the next few years. There are new and amazing ways that AI can help to impact care. However, taking advantage of these capabilities requires a strong foundation; one that can only be achieved by addressing the challenges discussed here.

How can this be accomplished?  It is not something that can be done “automagically,” but there are steps that can be taken to ease the transition.

  1. Revisit and refine the enterprise data strategy and ensure that it is actionable. Too often, strategies are developed with no plan to execute.
    1. Focus the data strategy on the consumers; produce the holistic view for key stakeholders.
  2. Invest in personnel resources. Take into consideration the time it takes to develop the right combination of technical and business knowledge in your resource pool. Ensure that your people can grow into this specialized skill set.
  3. Foster a culture of innovation. When an organization allows for creativity and independent thinking, it is often found that people are less fearful of change. As healthcare continues to be an industry of rapid change and advancement, this is a critical step in the process.

Becoming a data-driven organization requires addressing and overcoming these challenges to stay competitive in today’s data economy. At the end of the day, we are here to help our consumers get the best care, and data is key in making this goal a reality.

 

[1] Topol, Dr, Eric, Deep Medicine, Hachette Book Group, Inc., 2019, p.30

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