@article {10.34196/ijm.00337,
article_type = {journal},
title = {SNFsim: A Discrete Event Simulator for Decision Support in Skilled Nursing Facilities},
author = {Strickland, Caroline and Wagner, Brittin and Wang, Stanley and Lizotte, Daniel J},
volume = 19,
number = 1,
year = 2026,
month = {jun},
pub_date = {2026-06-03},
pages = {79-112},
citation = {IJM 2026;19(1):79-112},
doi = {10.34196/ijm.00337},
url = {https://doi.org/10.34196/ijm.00337},
abstract = {We introduce SNFsim, an open-source discrete-event simulator for developing and evaluating reinforcement learning (RL) methods for multi-dimensional sequential decision support in Skilled Nursing Facilities (SNFs). SNFs play a vital role in the United States healthcare system, delivering specialized care to individuals with ongoing medical needs. Decision-making within SNFs is often complex due to their fast-paced and stochastic nature. SNFsim provides a modular and extendable simulation of major decision-making processes within SNFs, capturing many of the complexities and uncertainties existing in healthcare environments while still being flexible enough to allow for easy customization. Its potential uses are two-fold: First, as a test bed for the development and comparison of RL algorithms, and second, as the basis of a decision-support system that can be tailored to individual SNFs.},
keywords = {healthcare operations, reinforcement learning, simulation, sequential decision support},
journal = {IJM},
issn = {1747-5864},
publisher = {International Journal of Microsimulation},
}