Now is the time to rethink our strategies for healthcare budget allocation and invest in the development and implementation of advanced information analytics.

The picture is grim

Healthcare systems all over the world are collapsing and cannot shoulder the amount of care and treatment requests, which are growing at exponential rates. COVID-19 only exacerbated the load, and amplified the pre-existing reality, while exposing that health systems' resources were already close to being maxed out even during routine times. It is clear that they are ill-prepared for a crisis of any magnitude.

Older and sicker populations will burden doctors at even higher levels. At the same time, increasing data overload will create new levels of stress and care delivery shortfalls.

Often the wrong solutions are proposed

Understandably, the reaction to this has been an increased public demand for more investments in healthcare budgets; in the building of new facilities; and in the purchase of equipment and beds.

While this distribution of funds might be helpful in some scenarios, it doesn’t solve the fundamental problems of our global healthcare systems. The long-term solution is in creating dedicated budgets that can be used to fund technologies such as sophisticated data analytics, in order to turn the tsunami of data that is being produced at unprecedented rates, from barriers into strategic assets.

Let's look beyond the simplistic solution of buying new beds, and instead invest in leading-edge AI-based data technology that will shift medicine from reactive to proactive, save many hospitalizations, and reduce, if not eliminate, the need for additional capacity.

We are at a generational tipping point

Over the last 15 years, the United States invested about $19 billion in the digitalization of its health system, during which billions of medical documents were scanned. But there is a massive chasm between availability and usability.

To wit: family physicians, who are the linchpin of any health system, have access to these documents but they are so massively overwhelmed, and are so time-starved, that while they have access to these documents, it’s simply too much data to cover before the patient walks into the clinic, and as a result, crucial information is often missed.

Moreover, the healthcare technology ecosystem is all about creating more data–from the data generated by various tests to technologies that monitor patients from home. However, the problem of how all this information can be processed by physicians, especially at the point of care, still hasn’t been solved.

Due to these huge quantities of data, doctors, ironically, don’t actually know their own patients. Misdiagnoses are happening every day; in the United States, for example, a recent study shows that one in seven diagnoses is mistaken.

Furthermore, doctors are missing preventive care opportunities, illnesses are developing and becoming chronic when there are interventions which can stop them, and the general overload on the healthcare system increases.

The recognition moment is here

Slowly, there is a growing acknowledgment that artificial intelligence and NLP (Natural Language Processing) can make a profound difference in our healthcare systems, and dramatically improve the status of patients and the emotional conditions of physicians while requiring a relatively small investment. It’s a recognition that not just putting information, but rather putting the right information, in front of physicians can help make healthcare proactive rather than reactive. But even with this knowledge and recognition, there still remains the question of how we get there.

One solution is to use healthcare budgets more wisely—by leveraging technology that ensures a larger percentage of the elderly population receives a flu vaccine or gets screened for colon cancer, in turn reducing the need for more hospital beds—rather than obsessively working to increase these budgets. When you look at the U.S. healthcare system’s transition from a fee-for-service model to a value-based care approach—an approach that has been growing all over the world—you can see that we’re already on the right path. Our role now is to ensure that physicians have access to the data technology they need to reduce burnout, misdiagnoses, and the human error that costs people’s lives, ultimately reducing the burden on the entire healthcare system.

Written by Ronen Lavi, co-founder and CEO of Navina