Telehealth's importance in rural communities, per Dr. James Blum

James Blum, MD, serves as chief medical informatics officer and associate professor of anesthesia at Iowa City, Iowa-based University of Iowa Health Care.?

Dr. Blum will be on panel "Two Years into the Pandemic: What Tech is Worth Investing In? What's Not?" at Becker's 7th Annual Health IT + Revenue Cycle, which will take place in Chicago from Oct. 4-7.

To learn more about the conference and Dr. Blum's session, click?here .

Question: What are your top priorities today?

James Blum:?My top priorities are looking for what is coming next while continuing to optimize what we have. There are profound opportunities to improve patient outcomes with new technologies and enhance the quality of the provider experience with new modalities. Examples include the implementation of Epic's Cognitive Computing/Nebula platform and the Nuance DAX product.

However, optimization of our existing systems is also a distinct opportunity. At the University of Iowa, the latter is particularly true as we were an early adopter of Epic and many of our workflows are different from what you would see in a 2022 installation. Finding where we will derive maximal value from reworking something old or implementing something new is my top priority.

Q: How are you thinking about growth in the next two years?

JB:?Growth for us is primarily about access. Iowa's population is mostly rural and providing access to high-quality quaternary care at the University of Iowa is what we need to do for the welfare of the people of our state. Our greatest opportunity to increase access, in the next two years, is in the use of telemedicine and related technologies. How we help avoid long trips for in-person visits is key to our growth strategy. Additionally, keeping patients out of the hospital is also key for us to have beds to provide access to inpatient services for those who need them. I see remote patient monitoring in combination with telemedicine as the keys to achieving these goals. Thankfully, payers are starting to see benefits to all of this which will enable us to offer these programs widely.

Q: Where is the best opportunity to disrupt traditional healthcare today?

JB:?I think predictive modeling as a whole is the greatest opportunity today. Increasing our ability to forecast trouble with patients and assess overall risk quantitatively will enable us to implement better protocols with branch points that will personalize medicine. This is particularly true as we add social determinants of health data to those models.

However, it's how you implement and utilize the models that is most important. A solid workflow and standard approach to the integration of models today is necessary to improve outcomes. This is particularly true today as many models offer insights and can direct attention but are not accurate enough to make decisions on a model's results alone. The models today are new, powerful tools that clinicians need to learn to work with. If implemented wisely, the tools can dramatically change the way we deliver care.

Q: What are you most excited about for the future?

JB:?In the long term, it's 'omics': genomics, proteomics and metabolomics. As knowledge expands and whole genome processing becomes readily affordable, we're going to see the predictive models become much, much better, particularly in the development of chronic diseases and their impact on individual lives. That will just be the start.

Although in their infancy, proteomics and metabolomics will continue to add valuable data to those models over the coming decades. This will fundamentally help drive care and reduce clinician variability based on solid information which will unquestionably lead to better outcomes. This is where good decision support will be so important. The body of knowledge a clinician has access to today is already not navigable. Imagine that expanding by 1000 times. No longer can your decision support simply be best practice alerts. We'll need fundamental changes in workflow, human-computer interfaces, and data processing to take full advantage of each patient's data.