AI Medical Compendium Journal:
Health economics

Showing 1 to 5 of 5 articles

Integrating decision modeling and machine learning to inform treatment stratification.

Health economics
There is increasing interest in moving away from "one size fits all (OSFA)" approaches toward stratifying treatment decisions. Understanding how expected effectiveness and cost-effectiveness varies with patient covariates is a key aspect of stratifie...

The infant health effects of doulas: Leveraging big data and machine learning to inform cost-effective targeting.

Health economics
Doula services represent an underutilized maternal and child health intervention with the potential to improve outcomes through the provision of physical, emotional, and informational support. However, there is limited evidence of the infant health e...

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Health economics
Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a...

Does the rise of robotic technology make people healthier?

Health economics
Technological advancements bring changes to our life, altering our behaviors as well as our role in the economy. In this paper, we examine the potential effect of the rise of robotic technology on health. Using the variation in the initial distributi...

Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury.

Health economics
For a continuous treatment, the generalised propensity score (GPS) is defined as the conditional density of the treatment, given covariates. GPS adjustment may be implemented by including it as a covariate in an outcome regression. Here, the unbiased...