Use of Meta-analytic Results to Facilitate Shared Decision Making
- Affiliation of the authors: San Diego Veterans Administration Medical Center and the University of California-San Diego, San Diego, California (LAL): Exponent Health Group, Menlo Park, California(DJC)
- Corresdpondence and reprints: Leslie A. Lenert, MD, Health Services Research and Development 111N1, Veterans Affairs Health System, San Diego, 3350 La Jolla Village Drive, San Diego, CA 92161. e-mail: 〈llenert{at}ucsd.edu〉
- Received 22 December 1998
- Accepted 26 April 1999
Abstract
Objectives Describe and evaluate an Internet-based approach to patient decision support using mathematical models that predict the probability of successful treatment on the basis of meta-analytic summaries of the mean and standard deviation of symptom response.
Design An Internet-based decision support tool was developed to help patients with benign prostatic hypertrophy (BPH) determine whether they wanted to use alpha blockers. The Internet site incorporates a meta-analytic model of the results of randomized trials of the alpha blocker terazosin. The site describes alternative treatments for BPH and potential adverse effects of alpha blockers. The site then measures patients' current symptoms and desired level of symptom reduction. In response, the site computes and displays the probability of a patient's achieving his objective by means of terazosin or placebo treatment.
Setting Self-identified BPH patients accessing the site over the Internet.
Main Outcome Measures Patients' perceptions of the usefulness of information.
Results Over a three-month period, 191 patients who were over 50 years of age and who reported that they have BPH used the decision support tool. Respondents had a mean American Urological Association (AUA) score of 18.8 and a desired drop in symptoms of 10.1 AUA points. Patients had a 40 percent chance of achieving treatment goals with terazosin and a 20 percent chance with placebo. Patients found the information useful (93 percent), and most (71 percent) believed this type of information should be discussed before prescribing medications.
Conclusions Interactive meta-analytic summary models of the effects of pharmacologic treatments can help patients determine whether a treatment offers sufficient benefits to offset its risks.
Footnotes
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This work was supported by an Ambulatory Care Fellowship from the Department of Veterans Affairs and by grant AR46127 from the National Institutes of Health.
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This research was presented in part as a poster at the 1997 AMIA Annual Fall Symposium, October 1997, in Nashville, Tennessee, and at the AMIA Spring Symposium, May 1998, in Philadelphia, Pennsylvania.
