“Data in Motion” Will Promote Patient-Centric Care Models

Wayne Kuznar

June 2015, Vol 6, No 5 - AVBCC 2015 5th Annual Conference


Washington, DC—Personalized medicine will become even more critical ­­as care transitions to patient-centric, outcomes-based care models. The use of real-time data, along with an increasingly advanced understanding of cancer biology, will exponentially increase the number of treatment options for patients, making personalized treatment more effective and ultimately leading to better clinical and financial outcomes.

These were the themes sounded by Sanjeev Wadhwa, Chief Executive ­Officer at Digital Health Venture, and Alex Jung, Principal in the Global Strategic Advisory Services practice of Ernst & Young, at the Fifth Annual Conference of the Association for Value-Based Cancer Care.

Real-World Data May Shift Focus to Prevention

Mr Wadhwa began by questioning what really matters to health. “Are we approaching this whole equation of health the right way?” he asked. “What is the context in which we are treating diseases?” Mr Wadhwa argued that before the focus turns to personalized medicine, perhaps we should be concerned with personalized health (Figure 1).

Table

We need to go beyond the data at rest that are collected during visits to physicians, clinics, and hospitals, and we need to measure the context of an individual’s health. This means measuring components such as physical and mental health; lifestyle factors; community conditions; and general socioeconomic, cultural, and environmental conditions.

The United States currently spends almost $3 trillion annually on healthcare. Only 3% of this amount goes toward preventive health measures, whereas 90% is spent on healthcare after events have occurred. Yet, Mr Wadhwa pointed out, health is determined largely (90%) by an individual’s health context and behaviors and only 10% by healthcare measures.

He believes that the emphasis on healthcare intervention after an event is a result of the idea that this approach is measurable. Because measuring health context and behaviors is difficult at this point, the overall holistic health of an individual is not addressed, nor is the focus on preventive healthcare.

“We always intervene at a late stage or after the event has been discovered, hence the entire discussion about how to fix quality in care and outcomes. Could we have captured some of these [data] earlier in the patient’s journey?” Mr Wadhwa asked.

He proposed that with the use of ­real-world data and “data in motion,” prevention could be the focus in healthcare, which would lead to better outcomes.

“Big data is about to change how we measure health,” Mr Wadhwa claimed. He acknowledged that an already overwhelming amount of data will become even larger with the use of biosensors and wearables on patients to capture real-world data.

An Expanding Number of Patient Profiles

Ms Jung predicted that this huge increase in data will be difficult for physicians to manage using traditional statistical methodology and actuarial models that were created 30 to 40 years ago to establish standards and ranges for treatment. The traditional approach has led to treatments that are not effective for 40% to 70% of patients.

She believes that, in the future, proxies will become important to the development of standards of care for various patient profiles. By applying logic, archetypes can then be determined and used to match the appropriate therapy to the appropriate patient archetype. The result will be more effective treatment.

In oncology, an increasingly sophisticated knowledge of cancers is giving rise to more targeted diagnostics and treatments. This knowledge leads to growing numbers of patient profiles for each type of cancer. For example, the number of patient profiles for breast cancer will increase from 4 that are based on the progression or stage of the tumor to dozens with the existence of an array of biomarkers.

Ms Jung speculated that factoring in 1 or more other chronic diseases in a patient with cancer will probably produce hundreds of patient profiles, all with very unique characteristics in terms of their response to treatment.

It will be untenable for an oncologist to determine treatment for hundreds of different profiles of patients, she pointed out. “There has to be a way to correlate the profile of the patient and the profile of the therapy,” Ms Jung said. “We have to rely on some of these larger data sets to make that link for us to simplify the decision-making process for the doctor.”

She explained that deciding which treatment will be most effective is much like an algebraic equation, but when there are so many options (variables) available and so much dynamic input, a multivariate analysis must be used.

“It completely changes the way decisions are going to be made and it exponentially increases the number of treatment choices,” Ms Jung noted. She insisted that this high-speed, high-intensity data analysis will make it possible for physicians to personalize treatment paths.

According to Mr Wadhwa, healthcare ecosystems will be necessary to make the transition to patient-centric, outcomes-based care. They are essential to bring all of the stakeholders to the table to collaborate and to create standard protocols, he said. By bringing together all of the entities involved in healthcare, the opportunity for creativity increases, as do new ideas to improve healthcare.

Mr Wadhwa foresees that real–world evidence will mean a dynamic measurement of health. Technology; the use of biosensors, such as Garmin, Fitbit, and iHealth; and smart cities will provide these real-world data (Figure 2).

Figure 2

If data at rest and data in motion are brought together, the information can be used to define what our health may be, he suggested.