Anywhere you look, the demand on health care systems and the brick-and-mortar buildings where patients are treated is vast. When you mix acute problems with chronic diseases and an aging population, there is a perfect storm settling over cash-strapped hospitals, packed waiting rooms, and busy clinicians.
This is felt to the greatest degree when you consider the most burdensome diseases out there: chronic heart failure (CHF) and chronic obstructive pulmonary disease (COPD). When these patients visit their local emergency department (ED) and/or are admitted to hospital, it not only strains the health care system, it ultimately hinders their well-being.
Being in hospital for days on end for what may be unnecessary reasons inflicts a major burden on patients’ quality of life, their actual prognosis, and on the health care system. Simply put, patients are more likely to return to hospital and when they do, they stay for a long time. In fact, in 2012, the direct costs associated with chronic conditions was estimated to be at over $50 billion in the U.S. alone.
The situation will only become increasingly dire. In Canada, for instance, it is estimated that by 2036, one in four Canadians will be over the age of 65, and 85 percent of that group will develop chronic conditions. Heart failure alone is already a multi-billion dollar annual problem here.
The consequences of this rising demand are enormous. Finding a solution to manage it: imperative.
We wanted to know: what if remote patient monitoring (RPM) data collection and analysis could illuminate the factors that precede a patient going to hospital? And then prevent them from having to do so?