Clinical deployment of a medical expert system to increase accruals for clinical trials: Challenges
ABSTRACT Before new medical treatments become available to the public, clinicians must conduct extensive trials to determine the efficacy of the novel therapy. In order for the clinical trial to be successful, a significant number of patients with an appropriate set of medical conditions must be accrued. We have implemented a web-based expert system at the H. Lee Moffitt Cancer Center & Research Institute in the Gastrointestinal Tumor Clinic (GITC) to help physicians screen patients for phase II trials. Our system allows physicians to screen a patient for multiple trials simultaneously. Our experiments have shown that adaptation of the system into a clinical environment and the success of the system are related to the amount of time physicians are willing to spend entering data. We also found significant regulatory issues (HIPAA) that make implementation challenging.
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ABSTRACT: A clinical trial is a study conducted on a group of patients to evaluate a new treatment procedure. Usually, clinicians manually select patients for a clinical trial; the choice of eligible patients is a labor-intensive process, and clinicians are often unable to identify sufficient number of patients, which delays the evaluation of new treatments. We have developed a Web-based system that helps clinicians to determine the eligibility of patients for multiple clinical trials. It uses probabilistic techniques that minimize the amount of manual data entry, by ordering the related data-entry steps. We describe the developed system and give the results of applying it to retrospective data of breast cancer patients at the Moffitt Cancer Center.Computer-Based Medical Systems, 2004. CBMS 2004. Proceedings. 17th IEEE Symposium on; 07/2004
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ABSTRACT: The task of determining patients' eligibility for clinical trials is knowledge and data intensive. In this paper, we present a model for the task of eligibility determination, and describe how a computer system can assist clinical researchers in performing that task. Qualitative and probabilistic approaches to computing and summarizing the eligibility status of potentially eligible patients are described. The two approaches are compared, and a synthesis that draws on the strengths of each approach is proposed. The result of applying these techniques to a database of HIV-positive patient cases suggests that computer programs such as the one described can increase the accrual rate of eligible patients into clinical trials. These methods may also be applied to the task of determining from electronic patient records whether practice guidelines apply in particular clinical situations.Methods of Information in Medicine 09/1993; 32(4):317-25. · 2.25 Impact Factor
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ABSTRACT: We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel estimation and pruning techniques. We also present results of applying this algorithm to sales data obtained from a large retailing company, which shows the effectiveness of the algorithm.Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Edited by Peter Buneman, Sushil Jajodia, 06/1993: pages 207--216; ACM Press.