Two data trends will impact practice patterns for clinicians
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Because practice management systems and electronic health records originally were designed to support accurate billing for subsequent reimbursement, fundamental changes to practice patterns are slow to enter clinical practices.
The industry is trained to identify diagnoses and procedures using accurate coding.
This creates the trail of description of a person’s health history, along with related diagnostic results from labs and imaging.
Add the pharmaceutical and therapeutic treatment data, and you have a complete picture of the patient.
Or do you?
Two types of data that are vital to understanding the whole person are generally missing for today’s medical practitioners.
These are data related social determinants of health (SDOH) and multi-omics (OMICS).
Until about a decade or so ago, these data were difficult to come by, as the basic taxonomies of the underlying data were not at all standardized.
Slowly and steadily, efforts around SDOH, OMICS and mental health have been gaining strength, and commercial solutions are increasingly available.
Although I have never met a physician who does not believe these issues are important, allow me to reference a version of the unifying equation in health care I set forth in my book, Not Just In Sickness But Also In Health: Moving Beyond Sickcare To Health Optimization For All.
This equation says that health care value is defined by achieving a better health status to a person or population as a function of the inputs of clinical care and daily living support resources. The lower the costs in the denominator relative to the numerator, the better the value.
It also says that clinical care is significantly impacted by OMICS, and daily living support is significantly impacted by social determinants.
Let’s explore these briefly.
OMICS
As familiarity with the human genome increases, most clinicians consider the importance of DNA and genetic mutations for the likelihood of predicting and the adjustment of treatment for certain diseases.
RNA recently has entered the mainstream of clinical consciousness with vaccine delivery methods. For the most part, it is a subset of the universe of clinicians that tend to cluster around certain disease types (eg, cancer) who currently utilize partial or full genetic testing in daily practice.
If you think about other types of OMICS, such as proteomics and microbiomics, these are largely at research stage. Neither isolated single-type OMICS nor multivariate OMICS has yet hit the mainstream in the form of personalized medicine — although everybody knows it’s coming.
Clinicians should assume that — in addition to the ability to see and apply traditional diagnostic results and medical records — OMICS data must and will become increasingly accessible.
Primary OMICS data with secondary analysis will not just be in the domain of research, but rather part of determining the best clinical treatments in practice across a broader range of diseases, as well as prevention activities.
OMICS data sets that are many times larger than the most of today's clinical and diagnostic data sets will become part of mainstream medicine, and analytic tools to find patterns and utilize artificial intelligence for treatment recommendations will proliferate.
These will find their way to physician practice tools as commonly as medical records do today.
SDOH
SDOH data is becoming increasingly organized and accessible.
Knowing a person’s living arrangements, work situation, micro-geography (ie, neighborhood) and basic economics certainly would go a long way toward creating a productive dialogue between patient and physician, as well as adding thoughtfulness to health recommendations.
My book defines total health and well-being as a combination of physical health, mental health, social health, financial health and purpose.
I have little doubt that clinicians both understand and would welcome information about a patient along these dimensions if presented in a manner that could be usefully referenced before and during a clinical interaction with a patient.
SDOH data increases the humanness of clinical interactions, and having data available during both physical and virtual encounters will make any visit more contextual and personalized.
Although physicians and their teams certainly do not need additional burnout-inducing activities, SDOH data that are teed up at the right time in a digestible way seem likely to improve productivity for both providers and patients as the barriers of a clinical-only data world are broken down.
As clinicians consider decisions regarding software and technology that support their practices, an eye toward the mainstream use of OMICS and SDOH data should help them get a jump on the future. It will be here soon!
For more information:
Jeffrey H. Margolis is the Forbes Books author of Not Just in Sickness But Also in Health: Moving Beyond Sickcare to Health Optimization for All. He is former CEO and chairman of Welltok (A Virgin Pulse Company) and TriZetto (A Cognizant Company). He currently is a Blackstone senior adviser and serves as a director on a number of public and private company boards of directors. Margolis is a health care IT entrepreneur and innovator based on his 35-year track record of successfully applying technologies to address the complex problems facing the health care industry. He can be reached at jeff@margolisenterprises.com.
Reference:
- Margolis J. Not Just In Sickness But Also In Health: Moving Beyond Sickcare To Health Optimization For All. Forbes Books. 2021.
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