Medical intervention choices have been determined by very standardized by guidelines. These guidelines are generally safe and are always based on scientific research. But the same "one size fits all" guideline does not work universally for everybody - our individual health and wellbeing is unique.
The shift from “one size fits all” to “personalized care” refers to the change from general care guidelines for all to specific care for individual patients. Let’s take a look at two aspects to this shift in care guidelines:
- the change to how care is planned
- the change to the process of selecting treatment options
Shift to Personalized Care Planning
The shift to personalized care planning is most widely adopted for older patient populations. Common among this population are comorbidity and complex social issues which play a bigger role in determining the overall health of this population.
Under the conventional “one size fits all” care, older patients are often considered to be “fallen through the gaps” due to many unmet unique needs – A fact that is painfully apparent when we look at the associated immense costs of this population in our healthcare.
In some ways, the burden of this population on our healthcare is unsurprising. Scholars have repeatedly called for more personalized care toward the older population - but achieving that is difficult. Personalization of care require meticulously coordinated multidisciplinary care teams to provide a greater library of services.
One of the most vulnerable portion of care is transition in care where administrative silos between care programs often create communication gaps – leading to confused patients, poor outcomes, and repeated unplanned visits to hospital. Healthcare administrators know about these challenges and realize that the first step to personalized care planning is to push for better integrated care.
In Ontario, the formation of Family Health Teams provide a more integrated experience for patients. Patients no longer confuse between silos of care and providers coordinate personalized care plans between multidisciplinary team of care providers which can span multiple physical care settings.
This shift has created an unprecedented demand for ehealth tools that support a more integrated and coordinated care system. Integrated electronic health records to share patient information, personalized care plans, and lab results across care settings, electronic prescription service to share prescription orders with pharmacies, computerized physician order entry systems to disseminate doctor’s orders, health analytics tools to ensure patients don’t fall through the cracks, and much more.
Shift to Personalized Treatments
The other aspect to the shift to more personalized care is more personalized choice of treatment option for patients.
Traditionally, if a patient is diagnosed with disease A, then drug A will be used in treatment. While this strategy works for some diseases, it does not work well for most health problems. For one, diseases are often heterogenous. The same disease can manifest differently in different people and the root cause of the same disease can be different in different people. Moreover, treatments aren't equally effective for everybody – some may respond well to treatment, some may respond somewhat, some may not respond at all, while others may even experience an adverse reaction to treatment.
Take the diversity of breast cancer for example – there are 5 subtypes of breast cancer and each subtype can be caused by dozens of different possible genetic mutations. Moreover, variation in the patient also create unique drug response profiles.
These disease differences along with patient differences create differences in response to treatment. So having only one general guideline to treat these diseases can lead to undertreatment or overtreatment.
As we learn more and more about diseases, we realize that many diseases are heterogenous like breast cancer and we in turn develop targeted therapies that will work well in individual patients.
Personalized medicine’s fundamental goal is to deliver the right care at the right time to the right person. ehealth technologies play a crucial role to help achieving this goal.
The shift to personalized medicine has driven a wave of ehealth technologies focused on “analysis.”
Genetic sequencing technology for example helps to identify the genetic signature of a disease in a patient for personalized treatment. Its adoption has exponentially increased especially when its costs have also drastically reduced in recent years.
Adoption of data analytics software driven by the shift to personalized medicine is also on the rise. Technology makes it possible to compute efficiently and accurately the overwhelming combination of possibilities for disease and treatment options.
Biosensors and point of care devices are also critical to support personalized medicine. These technologies are necessary to reveal the complexities of many diseases and their underlying causes to guide treatment.
In some ways, the shift to personalized therapies is only made possible due to advancements in ehealth – nonetheless this shift has created landmark of opportunities for the adoption of ehealth technologies.
