What if you knew that you were at high risk of developing heart disease? Chances are you would start making some changes in your life. You might eat better, start exercising, maybe see your cardiologist more often. You would work to spare yourself the high physical and financial costs of heart disease.
Now picture that heart disease prediction spread across an entire patient population. Whole groups of at-risk patients could be identified and given the opportunity for preventive care. That’s the principle behind predictive medicine. Practitioners of predictive medicine use imaging systems, genetic testing, and other methods to assess a patient’s risk of developing specific health problems. Its cousin, predictive modeling, relies on data mining techniques to identify at-risk patients. Predictive medicine is being hailed as a potential weapon in the fight to control healthcare costs. Money can be saved if a patient doesn’t get sick in the first place, or receives intervention in the early, more treatable stages of a disease. Knowing a patient’s risk can also allow physicians to make more informed treatment decisions.
“Effective risk assessment is the key to appropriately managing not only the clinical conditions but the costs associated with certain disease states,” says Gary Gregory, president of Eye Tel Imaging. The company uses a retinal imaging device, developed out of Johns Hopkins University, to assess a diabetes patient’s risk of vision loss from diabetic retinopathy. Most cases of blindness related to diabetic retinopathy are preventable, and early detection and treatment may reduce vision loss. Although clinical guidelines suggest that diabetes patients undergo an annual eye exam, only half of patients have it done, says Gregory. “If all patients have it done, you not only prevent blindness and other complications, but it clearly improves the healthcare economics and outcomes.”
Hologic has developed a premature-birth risk assessment for pregnant women. The test analyzes the level of fFN, a protein that holds the baby in the womb. The protein is detectable in the vaginal secretions of women who are about to give birth. Women who test positive can work with their doctors to prepare for a possible preterm birth.
CompuMed‘s Osteogram is a software program analyzes x-rays to determine a patient’s bone density. The information can be used to assess the patient’s hip fracture risk.
The Center for Toxicology and Environmental Health offers risk assessment services in a variety of areas, including epidemiology, drug safety and dose response. The company helps clients develop a risk management plan based on the findings.
MEDai uses forecasting analytics and data mining to identify and rank high-risk patients. The predictive modeling company works primarily with insurance providers and disease management companies. MEDai’s Risk Navigator solution is designed to predict total patient cost, ER and pharmacy costs. The system also uses evidence-based guidelines to identify compliance issues and opportunities for improvement. “We look at a patient holistically,” says Swati Abbott, president of MEDai. Abbott explains that they’re familiar with the patient’s history, what laboratory tests they’ve had, what medications they’re on, how much the patient is going to cost, and whether they’re actionable.
Abbott views predictive modeling as critical to the future of healthcare, due in part to the large number of new patients who will be entering the system as a result of healthcare reform. “You can’t touch everybody in the healthcare system,” says Abbott. “How do you focus on the right people so that you can have a huge impact?” She predicts that the medical system will move toward a payment model where physicians are reimbursed based on how they provide care. She also sees physicians becoming more and more engaged in improving patient care—and those physicians will need the data provided by predictive modeling. “I think that the role of risk assessment will just continue to grow,” says Abbott.
Our recent posts have focused on potentially cost-saving trends such as predictive modeling, preventive medicine, mobile healthcare and remote monitoring devices. Which healthcare trends do you think will have the biggest money-saving impact?