Analytics4Medicine - A4M

The patient records their peak diurnal home blood pressure readings on a Tuesday, Thursday, Saturday, Tuesday, Thursday schedule. The computer calculates the percent control for each patient in your panel. You get a list every 10 days of uncontrolled patients that need medication adjustment. If they are controlled, they come off the list and are sent an email congratulating them reenforcing lifestyle changes and continuing their medications. Every 10-day monitoring improves both patient and provider compliance. If the patient stops their medication, the blood pressure will acutely rise alerting you to intervene. If they come off their meds and they are controlled, they do not need anti-hypertensives. Frequent adjustment has been shown to improve the rate of control.

We use a 9 box matrix to divide hypertension into nine categories based on renin and aldosterone levels from low renin - low aldosterone hypertension, to high renin high aldosterone hypertension. Clicking on the appropriate category provides an extensive differential diagnosis with peer reviewed therapy for each specific condition found under that category. Given that 20 to 30% of patients will have a secondary diagnosis, some form of systematic evaluation is required.

The application has a drug sequencing algorithm based on age, ethnicity, associated disease, and renin aldosterone levels. The attempt is to match the mechanism of hypertension to the mechanism of the anti -hypertensive drugs. For example, low renin - normal aldosterone hypertension is most often due to low renin primary hypertension and this should respond to a diuretic alone. High renin hypertension implies renal vascular disease where ACE inhibitors, ARBs and beta blockers would be better first choice medications.