Accounting for the sedative and analgesic effects of medication changes during patient participation in clinical research studies: Measurement development and application to a sample of institutionalized geriatric patients

Abstract

Background To date, no system has been published that allows investigators to adjust for the overall sedative and/or analgesic effects of medications, or changes in medications, in clinical trial participants for whom medication use cannot be controlled. This is common in clinical trials of behavioral and complementary/alternative therapies, and in research involving elderly or chronically ill patients for whom ongoing medical care continues during the trial. This paper describes the development, and illustrates the use, of a method we developed to address this issue, in which we generate single continuous variables to represent the daily sedative and analgesic loads of multiple medications. Methods Medications for 90 study participants in a clinical trial of a nonpharmacological intervention were abstracted from medication administration records across multiple treatment periods. An expert panel of three academic clinical pharmacists and a geriatrician met to develop a system by which each study medication could be assigned a sedative and analgesic effect rating. Results The two measures, when applied to data on 90 institutionalized persons with Alzheimer's disease, resulted in variables with moderately skewed distributions that are consistent with the clinical profile of analgesia and sedation use in long-term care populations. The average study participant received 1.89 analgesic medications per day and had a daily analgesic load of 2.96; the corresponding figures for sedation were 2.07 daily medications and an average daily load of 11.41. Conclusions A system of classifying the sedative and analgesic effects of non-study medications was created that divides drugs into categories based on the strength of their effects and assigns a rating to express overall sedative and analgesic effects. These variables may be useful in comparing patients and populations, and to control for drug effects in future studies.