University of Virginia
EVA K. LEE
Georgia Institute of Technology
U.S. health care expenditures, $2 trillion in 2005 and 16.2 percent of the U.S. gross domestic product (GDP), are projected to reach $4 trillion by 2015 and 20 percent of GDP. Approximately 31 percent of these costs are administrative, 35 percent are for care of the elderly, 80 percent are related to management of chronic diseases, and 25 percent are related to treating people who engage in risky behaviors. Overall, these expenditures are almost evenly split between public and private funding, and this is expected to continue. Thus, health care expenditures have, and will continue to have, a substantial impact on public spending, private funding, and U.S. competitiveness in the international economy.
The medical and health care industries are fragmented and complex, have multiple stakeholders, and must accommodate dynamic, rapidly changing processes. When compared to other industries, improving health care presents unique challenges. Consider for instance, that one out of 100,000 parcels is misplaced by couriers, but 5 to 10 percent of medical records are reportedly misplaced. Whereas the banking industry has a transaction error rate of 1 in ten million, the error rate in hospital transactions is more than 2 in one hundred (2 percent). The accident rate for airplane landings and takeoffs is on the order of 1 in one million, whereas about 7 in one hundred (7 percent) adverse events are related to the administration of medication.
Because of the enormous cost of care, pressure for optimal decision making on both providers and consumers has grown astronomically, and a variety of
engineering tools have been helpful in creating optimal policies for the design and operation of health care delivery systems. As the use of electronic medical records and the availability of data and information increase, we are becoming more aware of how that can be used to help providers and patients design and evaluate individual choices of care. However, because of the nascent use of standards for data interchange, privacy and security concerns, and the special interests of insurance, medical, and consumer advocacy groups, a multitude of challenges must be overcome before these tools can be used to their best effect.
The four presentations in this session are focused on health information technology, advances in diagnosis and treatment, patient safety and the detection of adverse events, and effective management of chronic disease. In the first presentation, Elmer Bernstam highlights the status of health information technology (HIT) and describes promising research in biomedical informatics that could potentially improve HIT. Lucila Ohno-Machado, the second speaker, focuses on the technical aspects of calibrating measurements in medical decision support models and the implications of using un-calibrated models to make health care-related predictions.
The third speaker, Genevieve Melton, reviews classes of detection systems for adverse effects, describes some recent advances, and highlights technical challenges. In the fourth presentation, David Dorr describes a care-management model for providing reliable, effective care for older adults with multiple chronic illnesses and preventing unnecessary decline, expensive hospitalizations, and even death.