Will Algorithms Drive Future Healthcare Optimization?

There is an overwhelming amount of data available to healthcare systems developers to create efficiencies in the system. Will there be future investment in the creation of customized algorithm “signals” to further guide and enhance human behavior, healthcare services and insurance?

What is an algorithm’s “signal”? Generally, it is considered a set of data, theory or plan of quantifiable factors that create measurable and optimized results within a coded computer program. As an example, for someone who is preparing for a periodic physical examination, they typically go to a lab to have blood drawn. The lab results are then provided to a physician for analysis and review with the patient at the exam. These factors, or “signals”, could be developed in an algorithm for an individualized healthcare plan. Thereafter, the plan could be monitored by the provider team for the patient’s optimized healthcare results. Ideally, chronic conditions could be flagged as soon as possible, with an objective of eliminating more costly treatments and medication.

The investment in signal and algorithm development could significantly advance the concept of personalized health, which focuses on prediction and prevention of healthcare issues for each individual. The ultimate goal of healthcare providers is to predict the condition or disease, prevent any further worsening, and to prescribe precise cures for the patient to alleviate or mitigate their conditions. The faster this purpose can be met, the more optimal the results will be. Presumably, the costs would be reduced as normalization occurs with each person’s plan.

Similarly to the Human Genome Project, signals could be developed and mapped to optimal outcomes for all conditions and diseases, thereby allowing healthcare professionals to focus on early intervention and treatments at each stage of an individual’s treatment plan.

As an example, the Mayo Clinic’s Personalized Medicine programs offer “Better diagnoses, earlier interventions, more-efficient drug therapies, customized treatment plans.” Investments in technology, including algorithm signals, would speed success toward these goals.

According to the most recent National Health Expenditure (NHE) data, the NHE grew 5.8% to $3.2 trillion in 2015, or $9,990 per person, and accounted for 17.8% of Gross Domestic Product (GDP). With the healthcare system such an important part of the economy, it is an imperative national priority to create healthcare system savings. Could signal development for individualized medicine algorithms be an important way to control future healthcare costs and insurance?