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Title: Token Economy–Based Hospital Bed Allocation to Mitigate Information Asymmetry: Proof-of-Concept Study Through Simulation Implementation
Authors: Hiragi, Shusuke
Hatanaka, Jun
Sugiyama, Osamu
Saito, Kenichi  kyouindb  KAKEN_id
Nambu, Masayuki
Kuroda, Tomohiro  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-1472-7203 (unconfirmed)
Author's alias: 平木, 秀輔
畠中, 純
杉山, 治
齊藤, 健一
南部, 雅幸
黒田, 知宏
Keywords: hospital administration
resource allocation
token economy
bed occupancy
hospital management
simulation
decision-making
organization
Issue Date: Mar-2022
Publisher: JMIR Publications Inc.
Journal title: JMIR Formative Research
Volume: 6
Issue: 3
Thesis number: e28877
Abstract: [Background:] Hospital bed management is an important resource allocation task in hospital management, but currently, it is a challenging task. However, acquiring an optimal solution is also difficult because intraorganizational information asymmetry exists. Signaling, as defined in the fields of economics, can be used to mitigate this problem. [Objective:] We aimed to develop an assignment process that is based on a token economy as signaling intermediary. [Methods:] We implemented a game-like simulation, representing token economy–based bed assignments, in which 3 players act as ward managers of 3 inpatient wards (1 each). As a preliminary evaluation, we recruited 9 nurse managers to play and then participate in a survey about qualitative perceptions for current and proposed methods (7-point Likert scale). We also asked them about preferred rewards for collected tokens. In addition, we quantitatively recorded participant pricing behavior. [Results:] Participants scored the token economy–method positively in staff satisfaction (3.89 points vs 2.67 points) and patient safety (4.38 points vs 3.50 points) compared to the current method, but they scored the proposed method negatively for managerial rivalry, staff employee development, and benefit for patients. The majority of participants (7 out of 9) listed human resources as the preferred reward for tokens. There were slight associations between workload information and pricing. [Conclusions:] Survey results indicate that the proposed method can improve staff satisfaction and patient safety by increasing the decision-making autonomy of staff but may also increase managerial rivalry, as expected from existing criticism for decentralized decision-making. Participant behavior indicated that token-based pricing can act as a signaling intermediary. Given responses related to rewards, a token system that is designed to incorporate human resource allocation is a promising method. Based on aforementioned discussion, we concluded that a token economy–based bed allocation system has the potential to be an optimal method by mitigating information asymmetry.
Rights: ©Shusuke Hiragi, Jun Hatanaka, Osamu Sugiyama, Kenichi Saito, Masayuki Nambu, Tomohiro Kuroda. Originally published in JMIR Formative Research (https://formative.jmir.org), 04.03.2022.
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
URI: http://hdl.handle.net/2433/278466
DOI(Published Version): 10.2196/28877
PubMed ID: 35254264
Appears in Collections:Journal Articles

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