Unbiased Analysis of Today's Healthcare Issues
Randomized controlled trials are the gold standard for evaluating treatment efficacy, but effectiveness in the real-world may vary. One reason for this is that clinical trials often have stricter inclusion criteria than is the case for the target treated population. Policymakers, payers, and clinicians may wonder how well the results from the narrower clinical trial…
TL;DR A paper by Ress and Wild (2024) provide the following recommendations in answering this question. When aiming to control for a large covariate set, consider using the superlearner to estimate nuisance parameters. When employing the superlearner to estimate nuisance parameters, consider using doubly robust estimation approaches, such as AIPW and TMLE. When faced with…
What are the key elements for reporting your objective, attributes, experimental design, survey design, data collection process, econometric analysis, and results? A paper by Ride et al. (2024) conducted a Delphi Panel expert elicitation survey to create the DIRECT checklist for discrete choice experiment (DCE) studies in health. The checklist is pasted below. If you…
Should payers cover a new oncology treatment targeting specific biomarkers across multiple tumor types? One the one hand, one could require a separate trial for each tumor type. While this would be convincing evidence, it also is very expensive to conduct clinical trials for every tumor type, particularly if treatment efficacy is homogenous across tumor…
Contingent valuation is a survey-based economic method used to estimate the value of goods or services (often non-market goods) such as environmental benefits or public goods. The approach works by asking individuals to state their willingness to pay (WTP) for specific services or their willingness to accept (WTA) compensation for their loss. This method is…
Clinical trials are short, but the benefits of many drugs lasts months or even years beyond the duration of these trials. To quantify the full costs and benefits of a treatment over time (for instance as used for HTA purposes), one must extrapolate this clinical benefits. Commonly, this extrapolation is done using a parametric function…
While robust data is preferred when parameterizing economic models, this information is not always available. For instance, it may be unclear the degree to which clinical trial results would translate to the real world. Or, clinical trial results may need to be extrapolated beyond the time period of the trial. Or, there may simply be…
Many researchers are interested in how cost sharing impacts health care utilization, cost and patient outcomes. This is especially true as high-deductible health plans (HDHP) have become more common in the US. In 2023, 29% of covered workers in the US had a HDHP. One helpful type of data for analyzing HDHPs is claims data.…
Modelling health care cost is often problematic because are distributed in a non-normal manner. Typically, there are a large number of $0 observations (i.e., individuals who do not use any health care) and cost distribution that is strongly right skewed among health care users due a disproportionate number of individuals with very high health care…
Patient preferences should be the most important part of health care decisionmaking. However, third parties often make decisions for patients. Physicians make decisions for patients due to asymmetric information (i.e., physicians are experts; patients typically are not). Payers make decisions for patients since–in most developed countries–third-party payment cover most of the cost. Moreover, in some…