Computer assisted clinical decision support tool for management of statins

DESCRIPTION provided by applicant Hypercholesterolemia particularly low density lipoprotein cholesterol LDL c is a major modifiable risk factor for atherosclerotic cardiovascular disease ASCVD the primary cause of death in the US Today an estimated million people in the US are hypercholesterolemic with ASCVD and of these million people take one of seven statin drugs that are remarkably effective in reducing elevated LDL c and cardiovascular morbidity However nearly of statin treated patients do not achieve target LDL c levels during the first year of treatment resulting in preventable mortality and unnecessary health care costs The most important barrier to achieving target LDL c levels is the lack of real time statin treatment recommendations synthesized from large evidence based datasets Since clinicians have little guidance in statin selection they instead typically select statins based on imprecise past experience start at the lowest dosage and titrate over a prolonged period generating otherwise preventable costs Preliminary research in a VA hospital setting indicates that Statin Managerandquot SM a patent pending computerized electronic medical record EMR based algorithm can predict with high accuracy the probability of achieving target LDL c levels These preliminary results have been confirmed using a national VA Hospital sample of million patients Using multivariate logistic regression models based on individual patient characteristics including concomitant clinical conditions and medications SM predicts the probability that target LDL c levels will be achieved by specific statins at specifc doses SM ensures that the right statin in the right dosage is prescribed for each patient at the beginning of the treatment regimen Further development extension and commercialization of the statin management algorithm will reduce the high cost extended time and frequent frustration of experimentation to achieve target LDL c levels potentially reduce side effects improve treatment adherence and ultimately reduce the resultant risk of ASCVD associated with elevated LDL c The economic savings associated with improved healthcare for ASCVD outcomes is estimated in the billions of dollars annually in the US alone The overarching goal of Phase II is to complete the research and development necessary to begin roll out and commercialization of SM There are five Aims in Phase II SM external validation and refinement in a retrospective cohort study using a representative heterogeneous non VA national patient database develop a robust SM prototype based on phase I study results and SM algorithm enhancements from Phase II Aim evaluate SM in a Clinical Utility Demonstration Project health economics research to confirm direct health cost savings and lower LDL c values for those treated with SMandapos s recommended statin and dose and Data Mining using existing software and biomedical literature to identify clinical variables and genomic markers linked to statin efficacy to improve SMandapos s model performance and predictive validity PUBLIC HEALTH RELEVANCE This research will further develop Statin Managerandquot SM a real time computer assisted clinical decision support system based on an individual patientandapos s Electronic Medical Record to accurately identify the best statin and starting dose for personalized treatment of high cholesterol SM will benefit millions of patients more than half of who do not achieve target levels of LDL C in the first year of treatment