3 Challenges and Trends Accompanying the Implementation of Digital Innovations in Healthcare Analytics

Recently, the healthcare community as a whole saw an explosion in the availability and accessibility of data. Whether you work at the C-level, in finance, IT, or as a clinician on the line, the prevalence of data has created plenty of opportunities, discussions, and challenges requiring attention.

In a recent webinar entitled The Modern Healthcare CMIO: Best Practices for Implementing Digital Innovations, I spoke with several experienced thought leaders about the challenges and trends that may accompany the growth of predictive analytics and healthcare analytics spurred on by the increase in the collection and accessibility of data.

The discussion was a high-level, top-down look at some of the challenges, trends, and themes that Chief Medical Information Officers (CMIOs) and other key personnel who work with clinical decision-making may be experiencing now or could see in the future.

The Sheer Volume of Data – Paralysis by Analysis

The biggest takeaway from the discussion has to do with the effects the quantity of data has on clinical decision-making. Many of the software solutions released on the market today may present dashboards full of numbers and aesthetically pleasing graphs. However, the real question is whether or not these numbers are all meaningful and accurately tell the real story of what’s going on?

Not everything that’s measurable is important, and not everything that’s important is measurable. The language of healthcare is already difficult, to begin with. Are data solutions and healthcare analytics ineffectively adding to the confusion, or are they helping to drive meaningful change and improvements?

The Evolving Role and Importance of the CMIO

An underlying theme of the discussion was the growth in the importance of the Chief Medical Information Officer (CMIO) role. More importantly, the panel expressed how that importance was born out of data-driven challenges helping to define the CMIO’s role and job description. To date, the role has been somewhat sporadic from organization to organization, unlike something like a CEO or CFO that you see in nearly all organizational structures.

But as things like predictive analytics and data-driven clinical decision-making grow in prevalence, you can expect the CMIO role to become more commonplace. The CMIO can be the person at the forefront of helping individual departments and interdepartmental relationships adapt to changes. The CMIO can be a project manager, the owner of quality control, and the lead in scoping lean methodology—operational processes that generally aren’t as pervasive in healthcare.

By fully grasping not only the data collection process but understanding how to manage that data and turn it into a useful and applicable resource, the CMIO may just become the most critical member of the C-level team.

The Debate on the Natural Interoperability Progression of EHR and Analytics Integration

There is a lot of attention on our industry from technology providers looking to solve problems and address the opportunities data brings to the table. Currently, many of the healthcare analytics products put forward operate as standalone solutions. However, many in the industry believe that the natural progression is for analytics to embrace interoperability by directly embedding into Electronic Health Record (EHR) systems.

But not everyone is sold on this. Some point to the possibility that too much technology could get in between the patient and the provider, much like the discussion in the early days of the stethoscope.

However, the ability to leverage predictive analytics, aggregate a vast amount of data quickly, and the ability to scan vertical health records can’t be discounted. The questions just become how far these tools can go and how long it takes to validate algorithms. Additionally, if we’re to see the synergistic benefits that come with interoperability, there needs to be buy-in from every system involved.

It also begs the question of whether or not providers will trust the recommendations because, for many complex algorithms, the machine may not be able to “show its work,” for a lack of better terms.

The Future of Healthcare Analytics

In most industries that have seen an influx in available data, two things are constant—the data helped to revolutionize processes, and people hesitant to change initially pushed back. But if the story for healthcare analytics follows the same path as other industries, there are great and exciting things on the horizon.

 If you’d like to hear more of this discussion, I’d invite you to listen to the complete webinar now.

The Modern Healthcare CMIO

Best Practices for Implementing Digital Innovations

Download the ebook