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| home > epc > autumn 2002 > novel use of interactive voice response systems in the measurement of clinical endpoint data in cns studies |
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 PUBLICATIONS |
European Pharmaceutical Contractor
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In clinical trials, interactive voice response (IVR) systems are commonly used to perform randomisation and twenty-four hour emergency code break, and to provide a sophisticated method of optimising and managing the clinical drug supply chain (1,2,3). Because of the drive to improve the quality and integrity of patient-recorded data, IVR has been employed more recently to collect clinical data directly from patients, such as patient diary data (4). This has included data that are increasingly important to regulatory submissions, pricing and launch activities, such as health, economic and quality of life data. Interestingly, IVR has also been used to deliver very novel applications to make measurements from the patient. These include computerised structured interviews to perform psychiatric assessments, such as the Hamilton Depression Rating Scale (HAM-D) and cognitive function test batteries to measure, for example, patient reaction times and aspects of memory. This article describes these more novel uses of IVR when measuring clinical endpoint data, and also the extension of this methodology as a pre-screening patient qualification tool to improve patient recruitment and reduce screening failure costs.
Interactive Voice Response (IVR) Systems
An IVR system uses the telephone as a means of inputting data. Pre-recorded prompts list the various options available to the user or request responses to particular questions. Data are entered using the telephone touch-tone keypad and are written to the underlying databases. For example, a simple smoking cessation diary may ask the patient to rate the intensity of his or her desire to smoke for that day on a 0 to 7 scale (where 0 represents no desire and 7 represents extreme desire), or to indicate the number of cigarettes smoked during the day.
Sophisticated IVR systems are able to deal with the language requirements of individual users by relaying messages in the language appropriate to that individual. Commonly, the country of origin of the caller is known by the toll-free number they have dialled in order to access the IVR system. In this way, callers will initially be greeted in the default language of their country. On entering their unique user codes, individual language requirements can be implemented. As with other electronic data collection devices, using an IVR system brings many advantages to the collection of patient-recorded data, as discussed below.
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By Dr Bill Byrom, Product Development Manager at ClinPhone Group Ltd, and Dr John Greist, CEO of Healthcare Technology Systems and Clinical Professor of Psychiatry at the University of Wisconin, US
Bill Byrom joined the pharmaceutical industry in 1991 after completing a PhD in Disease Modelling related to animal health at Strathclyde University. He has worked for a number of pharmaceutical companies in a variety of roles, as a Statistician, Clinical Study Director, Medical Marketing Representative and Health Economist. His therapeutic experience includes diabetes, asthma, heart failure and schizophrenia.
Bill joined ClinPhone in July 2000 as a Business Manager responsible for product development and management of a number of accounts. Bill's background in clinical trials, from both a clinical and statistics/data management perspective, enables his input into the development of new ClinPhone services and areas of technology application.
John Greist MD is CEO of Healthcare Technology Systems Inc. He received his bachelor's degree from Princeton University and his MD from Indiana University. He is a fellow of the American Psychiatric Association and in 1998 became a distinguished senior scientist at the Madison Institute of Medicine Inc.
John is also a Clinical Professor of Psychiatry at the University of Wisconsin Medical School. His major clinical and research interests are anxiety and mood disorders, psychopharmacology, behaviour therapy and clinical applications of computing, all of which John has written and lectured on extensively.
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