Simulation analysis of an adjusted gravity model for hospital admissions robust to incomplete data.

ABSTRACT:

Background

Gravity models are often hard to apply in practice due to their data-hungry nature. Standard implementations of gravity models require that data on each variable is available for each supply node. Since these model types are often applied in a competitive context, data availability of specific variables is commonly limited to a subset of supply nodes.

Methods

This paper introduces a methodology that accommodates the use of variables for which data availability is incomplete, developed for a health care context, but more broadly applicable. The study uses simulated data to evaluate the performance of the proposed methodology in comparison with a conventional approach of dropping variables from the model.

Results

It is shown that the proposed methodology is a

SUBMITTER: Latruwe T 

PROVIDER: S-EPMC10540423 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature