Improving inpatient and daycare admission estimates with gravity models
- Author
- Timo Latruwe (UGent) , Marlies Van der Wee (UGent) , Pieter Vanleenhove (UGent) , Kwinten Michielsen, Sofie Verbrugge (UGent) and Didier Colle (UGent)
- Organization
- Abstract
- Growing healthcare costs have been accompanied by increased policymakers' interest in the efficiency of healthcare systems. Network formation by hospitals as a vehicle for consolidation and achieving economies of scale has emerged as an important topic of conversation among academics and practitioners. Within networks, consolidation of particular specialties or entire campuses is expected and encouraged to take place. This paper describes the main findings of an effort to build gravity-type models to describe patient choices in inpatient and daycare hospital facilities. It analyzes the distance decay effects as a function of car travel times and great-circle distance, and it offers a method for inclusion of university hospitals. Additionally, it reviews the impact of driving and transit accessibility on hospital attraction and reviews the differences in distance decay for patient age groups and hospitalization types. In the described application, the best models achieve a Mean Absolute Percentage Error of around 10% in non-metropolitan areas, and 14.5% across different region types. Results in metropolitan areas suggest that latent factors unrelated to proximity and size have a significant role in determining hospital choices. Furthermore, the effects of relative driving and transit accessibility are found to be small or non-existent.
- Keywords
- HEALTH-CARE, CHOICE, ACCESSIBILITY, POPULATIONS, Hospital admissions estimation, Gravity model, Healthcare planning, Huff, Model
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01GPAYX7K11M993R01HP8DGCFR
- MLA
- Latruwe, Timo, et al. “Improving Inpatient and Daycare Admission Estimates with Gravity Models.” HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY, vol. 23, no. 4, Springer, 2023, pp. 452–67, doi:10.1007/s10742-022-00298-4.
- APA
- Latruwe, T., Van der Wee, M., Vanleenhove, P., Michielsen, K., Verbrugge, S., & Colle, D. (2023). Improving inpatient and daycare admission estimates with gravity models. HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY, 23(4), 452–467. https://doi.org/10.1007/s10742-022-00298-4
- Chicago author-date
- Latruwe, Timo, Marlies Van der Wee, Pieter Vanleenhove, Kwinten Michielsen, Sofie Verbrugge, and Didier Colle. 2023. “Improving Inpatient and Daycare Admission Estimates with Gravity Models.” HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY 23 (4): 452–67. https://doi.org/10.1007/s10742-022-00298-4.
- Chicago author-date (all authors)
- Latruwe, Timo, Marlies Van der Wee, Pieter Vanleenhove, Kwinten Michielsen, Sofie Verbrugge, and Didier Colle. 2023. “Improving Inpatient and Daycare Admission Estimates with Gravity Models.” HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY 23 (4): 452–467. doi:10.1007/s10742-022-00298-4.
- Vancouver
- 1.Latruwe T, Van der Wee M, Vanleenhove P, Michielsen K, Verbrugge S, Colle D. Improving inpatient and daycare admission estimates with gravity models. HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY. 2023;23(4):452–67.
- IEEE
- [1]T. Latruwe, M. Van der Wee, P. Vanleenhove, K. Michielsen, S. Verbrugge, and D. Colle, “Improving inpatient and daycare admission estimates with gravity models,” HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY, vol. 23, no. 4, pp. 452–467, 2023.
@article{01GPAYX7K11M993R01HP8DGCFR,
abstract = {{Growing healthcare costs have been accompanied by increased policymakers' interest in the efficiency of healthcare systems. Network formation by hospitals as a vehicle for consolidation and achieving economies of scale has emerged as an important topic of conversation among academics and practitioners. Within networks, consolidation of particular specialties or entire campuses is expected and encouraged to take place. This paper describes the main findings of an effort to build gravity-type models to describe patient choices in inpatient and daycare hospital facilities. It analyzes the distance decay effects as a function of car travel times and great-circle distance, and it offers a method for inclusion of university hospitals. Additionally, it reviews the impact of driving and transit accessibility on hospital attraction and reviews the differences in distance decay for patient age groups and hospitalization types. In the described application, the best models achieve a Mean Absolute Percentage Error of around 10% in non-metropolitan areas, and 14.5% across different region types. Results in metropolitan areas suggest that latent factors unrelated to proximity and size have a significant role in determining hospital choices. Furthermore, the effects of relative driving and transit accessibility are found to be small or non-existent.}},
author = {{Latruwe, Timo and Van der Wee, Marlies and Vanleenhove, Pieter and Michielsen, Kwinten and Verbrugge, Sofie and Colle, Didier}},
issn = {{1387-3741}},
journal = {{HEALTH SERVICES AND OUTCOMES RESEARCH METHODOLOGY}},
keywords = {{HEALTH-CARE,CHOICE,ACCESSIBILITY,POPULATIONS,Hospital admissions estimation,Gravity model,Healthcare planning,Huff,Model}},
language = {{eng}},
number = {{4}},
pages = {{452--467}},
publisher = {{Springer}},
title = {{Improving inpatient and daycare admission estimates with gravity models}},
url = {{http://doi.org/10.1007/s10742-022-00298-4}},
volume = {{23}},
year = {{2023}},
}
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