Unbiased Analysis of Today's Healthcare Issues
What should you do when you want to conduct a cost-effectiveness analysis based on efficacy estimates from clinical trials but the trial has missing data. One common approach—known as complete case analysis (CCA)—is to discard the participants with incomplete observations. This approach is problematic as not only is there a loss in efficiency of the…
If you are doing a cost-effectiveness analysis (CEA) that relies on clinical trial data, what should you do if there is missing data in the trial? A paper by Faria et al. (2014) helps to provide the answer. The first question is, how are the data missing. There are a few options for defining this…
Let’s say we are interested in determining whether a particular treatment improves quality of life. Common measures of quality of life include EQ-5D, SF-12, and SF-36, among others. However, a systematic review of 237 randomized controlled trials found that only 43% collected SF-12 or SF-36 measures. If you are measuring a treatment’s effect on quality…
What happens when you have missing data? Many people recommend using multiple imputation (see Briggs et al. 2003; Faria et al. 2014; Gomes et al. 2013; Hunter et al., 2015; Hughes et al., 2016). This approach, however, generally assumes that data are missing at random. Missing at random could be interpreted as the probability that health…
Pay-for-performance programs often offer bonuses (or penalties) for physicians, hospitals and other providers based on the quality of care patients receive. Measuring quality of care, however, is often difficult. For chronic conditions, for instance, many patients eligible for outcome measures may be lost to follow-up. This issue can potentially affect provider evaluations and bonus payments.…