The healthcare industry is a rapidly changing landscape where, at first glance, players appear to have competing interests. This is likely because the cost of care is approached from a different perspective when being measured by patients, healthcare providers, hospitals or payers.
However, when we take a closer look, it is clear we all are trying to accomplish the same goal: deliver better health outcomes while reducing costs and improving patient satisfaction. We also agree there is an urgent need to eliminate wasteful spending, which by some estimates accounts for over one-fourth of total health care spending in the U.S. How we eliminate wasteful spending is still a matter of ample discussion.
To that effect, and according to the Harvard Business Review, only 40% of the estimated $1 trillion in wasteful spending would be addressed through the implementation of currently recommended approaches. This represents a significant opportunity for innovation in all areas of health care.
Those of us with decades of experience in the healthcare industry have experienced first-hand how technology is constantly opening new paths that lead us to the improved outcomes and cost reduction we are striving to achieve. Technology is also transforming business models to make them more responsive to the needs of the changing market and the customers.
This transformation is evident in the adoption of artificial intelligence (AI) and machine learning technology by healthcare industry players who are embracing the next chapter in patient care. The technology has developed to the point where it allows us to design a better, more efficient individualized care plan that matches a patient with a local facility with proven high-quality outcomes in the medical specialty that specifically fits the patient needs.
Using data from millions of patient experiences, we can analyze past results to recommend future paths for better care. For example, we can now match the characteristics of an individual patient in need of a knee replacement surgery with a provider with measurable success in caring for other patients sharing similar clinical and social characteristics. Matching the patient with the right provider at the start of care improves outcomes, increases patient satisfaction and provides cost-saving solutions that avoid hospital readmission in the long run.
AI and machine learning are making it possible to create smart networks that match patients with the best possible providers using the patient’s individual needs and the provider’s track record. Avoiding a trial-and-error care approach reduces the risk of unwanted healthcare outcomes and costs, replacing it with a direct path of care for patients to heal.
Likewise, for the provider who is successfully and consistently delivering results for patients with a particular clinical need, the pattern identification that the new technology provides can easily connect them with new patients who would otherwise not have learned about their outstanding track record.
By tapping into the latest technology, we are finally able to place patient at the center of their care team – whether they are in the hospital or on their way to healing at home. Everybody wins.