Wednesday, February 21, 2024

How do HEOR research deal with lacking information? – Healthcare Economist


That’s the wondered spoke back in a paper via Mukherjee et al. (2023). The authors outline an “HEOR find out about” for this paper as

…real-world proof research that carried out a secondary/post-hoc research the usage of randomized
managed trial (RCT) information, and a within-trial cost-utility research during which the result of passion was once prices or PROs together with preference-based utilities (e.g., EQ-5D).

Essentially the most suitable method for imputing lacking information will depend on the assumptions about how the information are lacking:

  • Lacking utterly at random (MCAR): the noticed or unobserved values of all variables in a find out about wouldn’t have any affect at the chance of an statement being lacking
  • Lacking at random (MAR). The chance of lacking information for a selected variable is related to the noticed values of variables (both noticed values of alternative variables within the dataset or noticed values for a similar variable at earlier timepoints) within the dataset, however no longer upon the lacking information. One can not take a look at for whether or not MAR holds in a dataset.
  • Lacking Now not at Random (MNAR). On this case, the chance of lacking information for a selected variable is expounded to the underlying price of that exact variable. MNAR can also be ignorable (when lacking values happen independently of the information assortment procedure) or non-ignorable (when there’s a structural purpose to the missingness mechanism that will depend on unobserved variables or the lacking price itself).

To deal with the lacking information, more than a few ways are obtainable together with: complete-case research (CCA), available-case (AC) research, a couple of imputation (MI), a couple of imputation via chained equation (MICE), and predictive imply matching.

To higher perceive which approaches are often utilized in well being economics and results analysis (HEOR), the authors carried out a scientific literature evaluate in PubMed and tested what form of statistical strategies had been used to deal with lacking charge, application or patient-reported end result measures.

The authors discovered that a couple of imputation, a couple of imputation via chained equation and complete-case analyses had been maximum often used:

From 1433 known data, 40 papers had been incorporated. 13 research had been financial critiques. Thirty research used a couple of imputation with 17 research the usage of a couple of imputation via chained equation, whilst 15 research used a complete-case research. Seventeen research addressed lacking charge information and 23 research handled lacking end result information. 11 research reported a unmarried means whilst 20 research used a couple of the right way to cope with lacking information.

The authors observe that whilst they discovered a considerable amount of HEOR methodological literature on find out how to deal with lacking information in a RCT context; on the other hand, there have been only a few research that experience tried to in fact enforce those suggestions and impute the lacking information. You’ll learn the overall article right here.


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