No matter the industry, it is often challenging for an organization to foster brand loyalty, and healthcare is no different. A 2021 study showed that over 33 percent of patients have no preference when it comes to a healthcare brand and over six in 10 respondents expected their preference to change after the pandemic.

Against that backdrop, it is incumbent upon healthcare organizations to find ways to set themselves apart from their competition and one of the ways of doing that is through personalized medicine. Issam Zinneh, Director of the Food and Drug Administration’s Office of Clinical Pharmacology, has said that such care has taken on many definitions, but that it is essentially “using genetic or other biomarker information to make treatment decisions about patients.” In other words, customized care. Zinneh stated: 

These could include decisions about who should get certain kinds of therapies or specific doses of a given therapy, or who should be monitored more carefully because they’re predisposed to a particular safety issue.

As is the case with customers in the retail space, the patient needs to be center stage. Their unique makeup needs to be considered by clinicians and their wants and needs must be taken into account.

Personalized care dates all the way back to the ancient Egyptians and Greeks, who in their rudimentary fashion tried to ascertain the factors affecting each individual’s well-being. It wasn’t until the 20th Century that a more uniform approach to care came about – population health – but now the pendulum has swung back in the other direction.

It began in 1990 with the Human Genome Project, which sought to identify each of the estimated 20,000 to 25,000 human genes. The 13-year project confirmed that a person’s DNA profile plays a role in determining those health issues to which someone might be predisposed and that certain treatments might be more effective than others.

Further progress toward personalized care continued from there. One of many examples was the launch in March 2022 by Cedars-Sinai Medical Center in Los Angeles of an artificial intelligence unit, the goal of which is to use AI and machine learning to scour hospital data and make disease prevention a greater possibility. The following month, the Mayo Clinic collaborated with Vuno, a South Korean AI firm, to develop precision oncology tools.

Indeed, AI can automate image analyses and thus hasten preliminary diagnoses, as was proven when that technology was able to identify COVID-19 on chest X-rays. It can also reduce dosage errors and play a role in robot-assisted surgery. Additionally, it can ease administrative burdens, a major cause of physician burnout.

All these examples point toward a larger trend in the direction of personalized medicine. Simply put, users want the best service, and the service that best addresses their individual needs. If they don’t find it, they are perfectly willing to go elsewhere. Therein lies the challenge for each healthcare organization: They must evolve and innovate in order to continue to build patient loyalty.