Equitable Allocation of Healthcare Resources with Fair Survival Models
| dc.contributor.author | Keya, Kamrun Naher | |
| dc.contributor.author | Islam, Rashidul | |
| dc.contributor.author | Pan, Shimei | |
| dc.contributor.author | Stockwell, Ian | |
| dc.contributor.author | Foulds, James | |
| dc.date.accessioned | 2020-12-09T17:01:13Z | |
| dc.date.available | 2020-12-09T17:01:13Z | |
| dc.date.issued | 2020-10-14 | |
| dc.description.abstract | Healthcare programs such as Medicaid provide crucial services to vulnerable populations, but due to limited resources, many of the individuals who need these services the most languish on waiting lists. Survival models, e.g. the Cox proportional hazards model, can potentially improve this situation by predicting individuals' levels of need, which can then be used to prioritize the waiting lists. Providing care to those in need can prevent institutionalization for those individuals, which both improves quality of life and reduces overall costs. While the benefits of such an approach are clear, care must be taken to ensure that the prioritization process is fair or independent of demographic information-based harmful stereotypes. In this work, we develop multiple fairness definitions for survival models and corresponding fair Cox proportional hazards models to ensure equitable allocation of healthcare resources. We demonstrate the utility of our methods in terms of fairness and predictive accuracy on two publicly available survival datasets. | en_US |
| dc.description.sponsorship | This material is based upon work supported by the National Science Foundation under Grant No.’s IIS1927486; IIS1850023. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This work was performed under the following financial assistance award: 60NANB18D227 from U.S. Department of Commerce, National Institute of Standards and Technology | en_US |
| dc.description.uri | https://epubs.siam.org/doi/10.1137/1.9781611976700.22 | en_US |
| dc.format.extent | 9 pages | en_US |
| dc.genre | conference papers and proceedings | en_US |
| dc.identifier | doi:10.13016/m2linh-rxcx | |
| dc.identifier.citation | Kamrun Naher Keya, Rashidul Islam, Shimei Pan, Ian Stockwell and James R. Foulds, Equitable Allocation of Healthcare Resources with Fair Cox Models,https://arxiv.org/abs/2010.06820 | en_US |
| dc.identifier.citation | Keya, Kamrun Naher, Rashidul Islam, Shimei Pan, Ian Stockwell, and James Foulds. “Equitable Allocation of Healthcare Resources with Fair Survival Models.” In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), 190–98. Proceedings. Society for Industrial and Applied Mathematics, 2021. https://doi.org/10.1137/1.9781611976700.22. | |
| dc.identifier.uri | http://hdl.handle.net/11603/20209 | |
| dc.identifier.uri | https://doi.org/10.1137/1.9781611976700.22 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | SIAM | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartof | UMBC Staff Collection | |
| dc.relation.ispartof | A. All Hilltop Institute (UMBC) Works | |
| dc.rights | Copyright © 2021 by SIAM | |
| dc.title | Equitable Allocation of Healthcare Resources with Fair Survival Models | en_US |
| dc.title.alternative | Equitable Allocation of Healthcare Resources with Fair Cox Models | |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0001-5276-5708 | |
| dcterms.creator | https://orcid.org/0000-0002-5989-8543 | |
| dcterms.creator | https://orcid.org/0000-0002-3995-339X | |
| dcterms.creator | https://orcid.org/0000-0003-0935-4182 |