Predictive Medicine & Health IT Systems

Predictive medicine is the emerging field of medicine that entails predicting the probability of disease and taking proactive steps to either prevent the disease altogether or significantly decrease its impact upon the patient. What follows is a short, high level overview of predictive medicine for managers and health IT specialists new to this area.

Predictive Health, Genomic Information, Nanotechnology, and Implantable Systems are just a few of the more interesting emerging solutions explicitly highlighted in Health Informatics 2040.


A major focus of the future of medicine will be the continued shift from contemporary medicine to integrative medicine, preventive medicine, predictive medicine, and regenerative medicine. Predictive medicine is the emerging field of medicine that entails predicting the probability of disease and taking proactive steps to either prevent the disease altogether or significantly decrease its impact upon the patient. What follows is a short, high level overview of predictive medicine for managers and health IT specialists new to this area.

Predictive Medicine

The Predictive Health Institute at Emory University is exploring the creation of a new and innovative model of healthcare that focuses on taking a proactive stance to maintain one's health rather than treating a disease or curing illness in a patient after the fact. This proactive approach uses new tools of bio-science to identify and measure risks and deviations from health, predicts potential consequences, and strives to develop health maintenance processes that address potential health problems or disease before they occur.

The following are examples of various types of predictive medical testing already in place that can be conducted by healthcare professionals include:

Preconception testing: Conducted on potential parents before a child is even conceived, allowing them to better understand physical traits and the risk of diseases in their offspring.
Prenatal testing: Used to look for diseases and conditions in a fetus or embryo before it is born. Generally offered to couples who have an increased risk of having a baby with a genetic or chromosomal disorder.
Newborn screening: Conducted just after birth to help identify genetic disorders that can be treated early in life.
Predictive Risk Testing: Often used to determine if an individual is at higher than average risk of developing a disease over a given period of time, e.g. breast cancer.
Diagnostic testing: Often used to confirm a particular diagnosis when a certain condition is suspected based on the subject's mutations and physical symptoms.
Carrier testing: Offered to individuals who have genetic disorder in their family history or to people in ethnic groups with increased risk of certain genetic diseases.
Health Risk Assessments: A systematic approach to collecting information from individuals that identifies risk factors, provides individualized feedback, and links the person with at least one intervention to promote health, sustain function and/or prevent disease.
Prognostic models: Used to predict best possible choices for patients in particular clinical scenarios with regards to providing treatment advice and  patient-centered consultation .

Predictive Health IT Systems

The health information technology (IT) industry is already in the process of developing the first generation of predictive health IT systems.  These new systems gather and analyze a range of information from EHR systems, health assessment instruments, genomic information systems, and other sources. A personalized predictive health profile is then generated to assist patients and their healthcare providers work together to improve an individual's health and help prevent the onset of certain diseases whenever possible. Many of these new, cutting edge predictive health IT tools are coming out of the collaborative, 'open source' health IT community.

The following are selected examples of just a few of the many health IT projects, open source tools, organizations, and activities associated with the field of predictive health:

Predictive Health Institute  - Focused on changing the future of healthcare by creating a model of healthcare using new tools of bioscience to identify and measure health risks, generating a predictive health profile for patients, and encouraging healthcare providers to intervene early to prevent or minimize illness.
Center for Health Discovery & Well Being – A joint Emory University-Georgia Tech initiative to develop an innovative model of care using predictive health processes, information technology, and tools.
MEDai has been doing predictive models for five years. Adding genetic data to that would not be hard.
Optimal Health & Prevention Research Foundation (OHPRF)  - Their Predictive Health Biomarker Assessment is used to collect data that is analyzed using an advanced translational algorithm and then converted into an interventional Personalized Integrative Self-care Plan.
Active Health Management – Their CareEngine system provides tailored and actionable clinical analytics and decision support to help improve patient health, reduce costs, and save lives.
NIH Genomic Information & Resources – There are numerous public domain or open source initiatives related to the creating of genomic information systems and software tools that will have a direct impact on the development of predictive health IT systems.
Predictive Health LLC – Uses award winning forecasting tools to identify patients who may be at high risk for hospitalization and high consumers of healthcare services. Once identified, they proactively contacts patients to initiate positive behavioral change to improve their health.
Allostatix – Next generation of health risk tools for use by employers, insurance companies, etc.  predicting the likelihood of disease in people, three to five years in advance, with up to a 90% accuracy. They can identify individuals with negatively trending health trajectories before any claims are incurred and before any medical events occur.
SimpleCare – They test for genetic components and provides a report about your chances of developing a particular disease or trait. These can then be used to develop quantitative estimates and definitive explanations of what they mean for you. 
Heritage Provider Network (HPN) – In 2011, they put up a purse of $3 million for the person or group who can come up with a predictive algorithm that accurately identifies people at risk for hospitalization in the next year, thus reducing unnecessary hospital stays and costs.
Electronic Health Records (EHR) – There are a number of commercial and open source EHR systems that are beginning to develop and integrate genomic information into their EHR solutions - see Open Source Electronic Health Record Agent (OSEHRA).

Information on other 'open source' EHR, PHR and Genomic information systems can be found on the COSI Open Health or the Open Health News (OHN) web sites.


Right now the health IT industry is focused on the acquisition, development, and deployment of Electronic Health Record (EHR) systems, Health Information Exchange (HIE) networks, and Personal Health Records (PHR). But coming rapidly down the pike are  next generation Genomic Information and Predictive Medicine modules that will be integrated into future EHR systems.

Here are some key management observations, conclusions, and recommendations on the subject of predictive medicine and predictive health IT solutions:

• Predictive medicine and associated predictive health IT solutions offer great potential to improve care, reduce costs, and prevent disease.
• Concerns related to companies trying to use predictive health information about employees to make hiring or firing decisions, insurance companies refusing to offer coverage, and other potential abuses will need to be addressed.
• Predictive medicine will require a fundamental realignment of many health care delivery processes. Individuals must be trained to take greater responsibility for their personal health.
• Collaboration and sharing of 'open' solutions will lead to continuous innovation  and rapid advancements in the field of predictive medicine in the coming decades.

Finally, according to a national survey recently conducted by researchers at Tufts Medical Center, consumers placed a high value on information to predict their future health and indicated they were willing to pay for it. Predictive healthcare is becoming a reality.


Other Selected Links on Predictive Medicine – Links to books on Predictive Medicine
Annual Predictive Health Symposium
Journal of the European Association for Predictive, Preventive & Personalized Medicine
National Predictive Health Modeling Summit
NAHDO Annual International Symposium on Forecasting
Predictive Health Today
University of Louisville Center for Predictive Medicine