What is Individualized Health?
Individualized health is a scientific approach to health promotion and disease management that acknowledges that people vary in their circumstances, preferences, and in their optimal path to full health. A century ago, William Osler, a founding father of modern medicine, said, “Variability is the law of life, and as no two faces are the same, so… no two individuals react alike and behave alike under the abnormal conditions which we know as disease.”* A primary goal of individualized health is that each person’s health decisions are fully informed by scientific evidence specific to their condition so that better outcomes are achieved at more affordable costs.
Bringing the best science to health decisions, requires: 1) improved acquisition, integration, and analysis of health information from existing data sources; 2) the development of novel ways to conceptualize and measure health and disease when key information is lacking; and 3) more effective tools to communicate scientific knowledge at the point of decision so that individuals and their clinicians make better choices. Better decisions demand science-based answers to questions like: what is my risk for a certain disease; how am I likely to respond to a particular treatment; and how beneficial is that clinical approach for a population of people with characteristics similar to mine.
Individualized Health is the Aspiration; Subsets are the Practice
There is a tendency to think individualized health means treating each patient as unique, basing decisions only upon his or her data. In practice, however, individualized health practitioners ground clinical decisions for an individual patient on data garnered from patients with similar characteristics. The idea is to reference each individual patient against a population of otherwise similar patients to answer clinical questions about that patient’s health state, disease trajectory, and likely response to treatment. The goal of “subsetting” is to create increasingly homogenous groups of “otherwise similar patients” against whom to reference the individual patient.
In prostate cancer evaluation, for example, a new patient’s risk of having an aggressive tumor can be predicted by comparing him to a subset of patients with similar age, PSA trajectory, prostate density, and previous biopsy results for whom prostatectomy revealed whether the tumor was aggressive or not. In the future, genomic and other biomarkers will be included to make the comparison subset of patients more homogeneous, and therefore, more similar to the individual patient.
*Source: Silverman, S., Murray T., and Bryan C. (eds.). (2008). The Quotable Osler. Philadelphia, PA: The American College of Physicians.
Does individualized health differ from precision medicine?
“A rose by any other name would smell as sweet”
Individualized health is a term used at Johns Hopkins since 2009 to describe a scientific initiative to promote health-related decision-making that is responsive to the circumstances and preferences of individuals. At the time “personalized medicine” or “genetic medicine” were in use, but faculty decided that all medicine is personal and that the Johns Hopkins initiative would be grounded in public health, nursing, and engineering, in addition to medicine. Hence, our choice was “individualized health.” “Precision medicine” is the name for an overlapping agenda popularized by the U.S. government.
What are the key components to achieving individualized health?
1) Acquisition, Integration, and Analysis of Existing Sources of Data
One approach to understanding how individuals’ vary in their disease experiences is to take advantage of the information contained in existing data sources. This involves acquiring and integrating a variety of data sources to gain a more comprehensive understanding of disease. For example, to reliably and accurately predict if a certain patient is likely to be diagnosed with an aggressive form of breast cancer, a woman’s genetics, proteomics profile, family history, lifestyle choices, and demographic characteristics should be jointly considered. However, when creating risk prediction tools – such as the hypothetical aggressive breast cancer prediction tool – it is difficult for researchers to account for all of these components affecting an individual’s risk of disease simultaneously. This is partially because it is burdensome and costly to collect all of the necessary information on study participants and partially because it requires sophisticated statistical models that can incorporate diverse information and produce accurate, consistent, and interpretable results.
To foster the integration of different types of data, large studies designed to collect a variety of information on participants, such as the one announced by the National Institute of Health’s Precision Medicine Initiative, hold a lot of promise. So does the development of learning health systems, which are designed to continually integrate and analyze data generated from patients’ health care visits. The successful implementation of learning health systems requires the extraction of data from clinical notes, the retrieval of research quality data from electronic health records, the acquisition of patient consent, and the protection of patient privacy, all of which require technical and ethical solutions.
Individualized health is also driven by the development of sophisticated statistical and computational methods to properly analyze integrated data. These methods form the basis of the clinical and public health tools created to individualize health care delivery and promotion. These tools can come in many forms, including apps, wearable devices, electronic medical record dashboards, and statistical software packages that can be used by both clinicians and researchers.
2) Improved Health Measurements
A second individualized health component involves obtaining better measures of individuals’ health and disease status. For many conditions, individuals must make health decisions without knowing the true nature of their disease or how it might progress. By creating better ways to measure health and disease, researchers aim to gain a more insight into how people experience disease, leading to the development of more effective health interventions.
To improve health and disease measurements, many researchers work to discover new biomarkers (markers of disease that indicate whether or what kind of disease is present). Biomarkers can not only be used to detect or categorize diseases, but they can also serve as targets for treatment. Clinicians, for example, test for the presence of estrogen receptors to determine the type of breast cancer a women has and to guide what treatments she will receive.
Improving health measurements is also bolstered by the development of devices that can measure and track biomarkers and other components related to health and disease. Researchers and engineers are building on technological advances to develop wearable devices that can link health-related measurements to patients’ disease experiences and transmit the data to research databases and clinics, ultimately enabling clinicians to oversee patients’ compliance to their treatment regimen, track patients’ response to therapy, and monitor triggers for adverse events. This data can be used to tailor patients’ treatments and send warnings to patients and clinicians when there is high risk for adverse events.
3) Communication to Patients and Clinicians
The third component to achieving individualized health involves communicating scientific knowledge to patients and clinicians so that they can make optimal decisions. This requires embedding new scientific evidence into clinicians’ workflow so they can access information during clinic visits. It also entails developing effective strategies for communicating risk with patients.
How does individualized health improve decision-making?
Through enhanced integration and analysis of data and the development of better measurements, individualized health researchers are creating a foundation on which to develop tools that will ultimately improve health-related decision-making. The tools created by researchers are diverse, ranging from risk prediction scores and statistical software to apps, wearable devices, and electronic medical record dashboards. These tools will allow individuals, clinicians, and public health practitioners a deeper understanding of individuals’ and populations’ health statuses, disease risks and prognoses, and the impact of different interventions. Initially, the tools will target groups of people with similar health outlooks, but as data and methods improve, the tools will enable increasingly individualized care.
What are some of the barriers to achieving individualized health?
Access to Personal Information and Protection of Privacy
The success of individualized health depends in large part on the ability to analyze patient data. This requires access to data not routinely collected for research purposes, including data contained in electronic health records, apps, and wearable devices. Research ethicists are determining the best way to obtain patients’ permission for use of their health information, while ensuring patient privacy is maintained and their data is protected from security threats.
Fully utilizing the many forms of data collected on patients requires access to information in formats commensurate with research needs. This involves translating the text and results found in electronic health records into useful data points for researchers. It also requires the physical integration of data from different sources. Creating and using software that enables interoperability and integration among the various electronic health record systems is an important step in providing researchers a more comprehensive view of patients’ health care experiences.
Many of the methods driving individualized health research involve observational data, the analysis of which can be prone to certain types of errors. To ensure that the decision-making tools generated from individualized health research are of the highest standards, it is critical that all tools are properly validated.
Application of Information
A major challenge facing individualized health is ensuring that the vast array of tools being developed to improve health are accessible to clinicians, patients, and public health professionals in a timely and effective manner. Overcoming this challenge will require systems that can integrate up-to-date scientific knowledge into medical practice and studies that test individualized health tools in real-world settings.
How to Get Involved
The analysis of high-quality data is necessary for achieving individualized health. Individuals can help by participating in studies and allowing researchers access to the data contained in their health records. Patients can work with research ethicists to ensure concerns regarding data security and privacy are addressed.
Individualized health also aims to be responsive to the needs of patients; therefore, knowing patients’ priorities is critical. To facilitate this, individuals can serve on research boards to help shape the research agenda.
The success of many individualized health tools depends on their seamless incorporation into clinical practice. Clinicians are important partners in ensuring the decision-making tools being created by researchers are useful and acceptable to both clinicians and their patients. To facilitate this, clinicians can collaborate with researchers to identify pressing medical needs, aid in the design of tool interfaces, and consult on the integration of tools into the clinical workflow.
Clinicians can also promote the availability of high-quality data by working with researchers to optimize electronic health records for research purposes and by encouraging their patients to participate in research studies.
Public health practitioners
Public health practitioners can collaborate with communities and individuals to prioritize public health needs and determine which of these priorities are amenable to a tailored, individualized health approach. They can also design studies that collect a spectrum of variables on individuals, ranging from the molecular to the societal level.
Researchers can continue to focus on developing solutions to the methodological and technical challenges facing the individualized health approach. Researchers should also collaborate extensively with clinicians, public health practitioners, and patients to identify the most important needs that can be addressed by individualized health and ensure that the tools they create are relevant and practical.