The EMR is the backbone of how we deliver care. It doesn’t matter if you’re handling hundreds, tens of thousands, hundreds of thousands, or even millions of visits each year, a great EMR solution does a masterful job of keeping the ducks in a row and marching forward towards the goal of better patient care.
But a question that has to be asked of any technological solution in a rapidly growing industry like healthcare analytics is whether or not it’s prepared to continue fostering growth or if it may turn into a roadblock to future innovation.
What Are the Digital Opportunities?
The growth of technology to support healthcare providers continues to be explosive and exponential. To stay relevant, CIOs of the future will need to aggregate a collection of tools and technological solutions to drive higher levels of care for patients, better overall efficiencies, and stronger bottom lines. The emerging opportunities to meet these demands are likely to include the use of artificial intelligence (AI), machine learning, and data-driven clinical decision-making.
Through these tools, healthcare organizations may be able to:
- Better manage the supply of their resources
- Meet the demands of patients when and where they need it most
- Guide patients to easier access to clinical care and the most efficient path to getting well
- Select more effective treatment interventions through predictive analytics
- Use the digital experience to alter the way a patient’s behaviors influences overall outcomes
Challenges Lie Ahead
As with any new solution, though, there are challenges that must be addressed. Specifically, strong interoperability between these systems and the EMR is a must, or else gains in one area could result in losses elsewhere. Let’s look at a few of the biggest areas that must be addressed to preserve gains.
Access to Information
The success of these digital solutions relies heavily on an EMR robust enough to not only collect meaningful data, but also one that’s able to connect to and point to other sources of data that may be rich in usefulness. Can your EMR identify and collect the data needed, but also can it support the interoperability needed to do something with that data? Is the information readily available inter-departmentally? Furthermore, can this be completed in an efficient manner that doesn’t rob efficiencies from other areas of your organization?
While many of the AI solutions that drive the digital opportunities outlined above are exciting, they’re also data-hungry. Many models look at potentially thousands or tens of thousands of different dimensions of information when producing solutions. If the model requires these processor-intensive processes every time and for every single patient, scalability becomes a big concern.
The bottom-line question is, what’s the future going to look like when we have not just one model running, but potentially hundreds of models? If we’re doing things like creating a digital twin of the patient through hundreds of processes, how do we scale?
Learn More About the Future of Healthcare Analytics
Ultimately, the potential benefits that come with AI, machine learning, and data-driven clinical decision-making are so promising that the potential limitations of existing EMR systems would never be a deal-breaker. Systems providers will need to find solutions or new solutions will take their place. Learn about Net Health® Analytics.
Want to learn more about how your organization can be at the forefront and the cutting edge of digital transformation? If so, we’d encourage you to check our webinar The Modern Healthcare CIO.
The Modern Healthcare CIO
Digital Transformation in a Post-COVID World