A tool that predicts survival based on a patient's total burden of key chronic diseases also identifies which patients in the healthcare system will incur the highest future costs, according to new Weill Cornell Medical College research. Doctors can use this information to intervene early on in a patient's care, potentially reducing hospitalization and costs for the healthcare system and promoting improved health for patients.
Once these patients are identified, doctors can help set them on a healthier course, using a wide variety of techniques ranging from teaching disease-management skills, to meditative healing, to stress management, coaching and care coordination. The goal is to “teach patients the skills to manage their own diseases and to work directly in an empowered fashion with their physician,” said lead author Dr. Mary Charlson, chief of the Division of Clinical Epidemiology and Evaluative Sciences Research and executive director of the Center for Integrative Medicine.
The study, published Dec. 3 in PLOS ONE, tested her Charlson comorbidity index against the current approaches to identifying high-cost patients: prior-year costs, prior diagnoses (which is modeled by Diagnostic Cost Group, or DCG), and hospitalization. In the study of 187,000 people, the researchers found that as the comorbidity index increased, so did the patient's total yearly future cost, demonstrating that the tool works as well as prior cost and DCG and better than the prior hospitalization measure. Essentially, the patient's total burden of 23 chronic conditions can determine his or her costs to the healthcare system in the coming year.
The comorbidity index represents a significant departure from existing methods of projecting healthcare costs, which rely on statistically grouping patients together by cost and condition. "The statistical modeling using complicated risk algorithms can be hard to translate directly into clinical practice. So the million-dollar question in healthcare is how you identify people who are likely to be hospitalized and to be repeatedly hospitalized?" Dr. Charlson said.
Additionally, current methods rely on claims data, which often take between six and 18 months to obtain. By then, patients may have already been repeatedly hospitalized, resulting in a constant game of catch-up for a healthcare entity. The comorbidity index, however, is available through data from any electronic medical record or through short patient surveys, paper or web-based questionnaires, allowing healthcare providers to understand and intervene with patients in real time. This prospective, straightforward accessible approach can identify likely high-cost patients and support them on an individual basis – a true win-win for the healthcare system, Dr. Charlson said.