The Primary Care Incorporates Collection And Analysis Of Genetic Data

The Primary Care; A pilot project tests a new model of primary care that incorporates collection and analysis of personal physiologic and genetic data into the electronic health record to inform personalize care plans with unique features of the whole patient. Megan R. Mahoney, MD, and Steven M. Asch, MD, MPH, from the Division of Primary Care and Population Health, Stanford University, Palo Alto, California, describe the pilot project in an article published online in the May/June issue of Annals of Family Medicine.

Amassing patient data

Another Stanford team, led by Michael Snyder, PhD, recently identify 67 clinically actionable findings among 109 participants in an 8-year longitudinal assessment that include clinical testing, multiomics big data, and input from wearable devices. That study provide a proof of concept of the value of amassing patient data. The participants were select for elevate type 2 diabetes risk.

As in Dr Snyder’s study, data were collect for each of 50 participants on a variety of factors known to influence health; but Human wide also include visits with a collaborative care team that include a physician, nutritionist, behavioral health specialist, and clinical pharmacist. Working with a certify health coach, that team partnered with the patient to create a detailed, personalize care plan.

Although 68% of the participants in Snyder’s study discuss findings with their physicians, that was not the primary goal, Mahoney said. “Both studies demonstrate the promise of using health data and other information to more precisely predict and prevent disease for individual patients,” she added.

The primary care

Data collected from wearable devices and home scales report directly to the electronic health record. These include data from pedometer readings; also blood pressure measurements, and glucose monitoring. The data were present in graphic form to clearly reveal the beginnings or progression of disease. The information enable the team to stay ahead of symptoms and lower the risk for complications.

Pharmacogenetic testing indicate optimal dosages and enable evaluation of drug combinations; so on the basis of the rate at which an individual metabolizes a drug. Findings for 1 in 4 patients led to changes in medication for treating chronic conditions. For example, one patient with leg cramps learn that the pain arose from the fact that the patient metabolize statins slowly. A lower dose prevent the problem.

Of 33 women screened for breast cancer risk, five had a high-risk mutation; also enhance surveillance was begun. Routine screenings would not have detect the risk, Mahoney said. Human wide was design to bring a precision health approach; so to a clinical setting. Our early experience demonstrate the feasibility of a more comprehensive patient centered; hence data-driven environment in primary care,” she concluded.