TY - GEN
T1 - Dynamic Physician-patient Matching in the Healthcare System
AU - Chen, Ruimin
AU - Chen, Mutong
AU - Yang, Hui
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - Long waiting time has attracted public attention significantly due to the negative effects on patients' satisfaction with health systems. In the United States, waiting time of a patient to see a physician for the first time has been increased by 30% since 2014. This is in part due to the ineffective allocation between physicians and patients, and in part due to growing population needing healthcare and the restriction introduced by insurance policies. There is an urgent need to develop matching mechanisms with the consideration of preferences from both patients and physicians to improve matching results. This paper presents a new allocation framework between physicians and patients to shorten the patient waiting time as well as improve the allocation effectiveness. We leverage the matching theory and extend the conventional deferred acceptance algorithm to a discrete-time stable marriage framework (i.e., discrete deferred acceptance algorithm, DDA) with the consideration of uncertainty constraints introduced by insurance types. We benchmark our proposed algorithm with the current practice (i.e., continuous deferred acceptance scheme, CDA) under different scenarios when the demand-supply ratio (DSR) varies. Experimental results show that when the DSR is more than 1.25, DDA outperforms traditional CDA practices in terms of waiting time and matching regret. The proposed framework shows strong potential to tackle the problem of long waiting time in the healthcare system.
AB - Long waiting time has attracted public attention significantly due to the negative effects on patients' satisfaction with health systems. In the United States, waiting time of a patient to see a physician for the first time has been increased by 30% since 2014. This is in part due to the ineffective allocation between physicians and patients, and in part due to growing population needing healthcare and the restriction introduced by insurance policies. There is an urgent need to develop matching mechanisms with the consideration of preferences from both patients and physicians to improve matching results. This paper presents a new allocation framework between physicians and patients to shorten the patient waiting time as well as improve the allocation effectiveness. We leverage the matching theory and extend the conventional deferred acceptance algorithm to a discrete-time stable marriage framework (i.e., discrete deferred acceptance algorithm, DDA) with the consideration of uncertainty constraints introduced by insurance types. We benchmark our proposed algorithm with the current practice (i.e., continuous deferred acceptance scheme, CDA) under different scenarios when the demand-supply ratio (DSR) varies. Experimental results show that when the DSR is more than 1.25, DDA outperforms traditional CDA practices in terms of waiting time and matching regret. The proposed framework shows strong potential to tackle the problem of long waiting time in the healthcare system.
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U2 - 10.1109/EMBC44109.2020.9176324
DO - 10.1109/EMBC44109.2020.9176324
M3 - Conference contribution
C2 - 33019309
AN - SCOPUS:85091018360
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5868
EP - 5871
BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Y2 - 20 July 2020 through 24 July 2020
ER -