Physician Data Analytics – Key to a New Payment Model

Physician data analytics is thought of by many physicians as something that I may do “sometime” in the future. We hear comments like “it is too hard,” “too complex,” or “this will take away time from my patients.” Even though these thoughts are valid, it is easier than one may expect to get into data analytics.



The current volume-based payment model is rapidly changing to a quality base/total cost of care model where, as a provider, you will get paid for improving the quality of patient care while reducing volume-based activities/payments. In this new model, the patient “wins” via improved care and outcomes, the insurance company “wins” in less claims/costs, and the physician “wins” by sharing in that cost savings with the payers. This creates a win-win scenario.

So, let me describe a potential patient care situation that will give you an idea of how easy it might be to get into physician data analytics. A sample scenario could be:

• Determine the highest frequency of patient diagnosis seen in your office;
• Determine which of these diagnoses is related to more “chronic” conditions, i.e. do not pick the “one time” visit for a sore throat in a group of patients that you may see only once;
• Then sort the diagnosis by age, body weight, sex, a lab value or some other key factor related to this chronic condition;
• Determine any common contributing factor(s), such as a lifestyle behavior, related to this chronic condition;
• Determine what would be the most obvious change in behavioral lifestyle of that patient group that could most significantly improve (i.e. reduce) the chronic condition;
• Have a member of the patient care team contact each patient in this group to schedule a “preventive medicine” call or appointment (It is important to note that the physician does not have to be the person doing this and the steps described below);
• Talk/meet with each patient to discuss and get agreement on the life style change.
• Follow up on a monthly time basis to “measure,” i.e. document and record, the life change factor(s);
• Use the physician data analytics to analyze the same patient group on a regular basis and document the results – both from an individual patient and a group point of view – and repeat the cycle as noted above.

You have now used physician data analytics to move from a volume-based model into a new preventive care-based model.

The benefits of using data analytics in practice include:
• Improved health and outcomes for your patients;
• Lower overall costs of treating these patients;
• Ability to move into a “cost sharing” arrangement with your payers (PCMH-like model);
• Having more personal time to spend with your family and friends.

All of these benefits come from taking a relatively simple data analytics approach to your current patients!