JMIR Publications

ABSTRACT

Background:

Hospital bed management is important resource allocation task in hospital management but current hospital bed allocation is problematic. However, acquiring an optimal solution is difficult because intra-organizational information asymmetry exists. Signaling, defined in the fields of economics, can be used to mitigate this problem.

Objective:

This study aimed to propose an assignment process based on a token economy as signaling intermediary and to perform a preliminary evaluation with nurse managers.

Methods:

We implemented a game-like simulation representing token-economy-based bed assignments which asks three players each to behave as ward manages of inpatient wards. As a preliminary survey, we recruited nine nurse managers to play aforementioned simulation and to participate in a survey about qualitative perceptions for current and proposed methods (7-point Likert scale). We also asked them about preferable rewards for collected tokens. In addition, we quantitatively recorded participant “pricing” behavior.

Results:

Participants scored the proposed method positively in staff satisfaction (3.89 points vs. 2.67) and patient safety (4.38 vs. 3.50) compared to the current method, but they scored the proposed method negatively for managerial rivalry, staff personal development, and goodness for patients. As a reward for tokens, seven of nine participants listed human resources as the priority. Participant behavior showed slight associations between workload information and pricing.

Conclusions:

Survey results indicate that the proposed method can improve staff satisfaction and patient safety by increasing decision-making autonomy of staff. Conversely, the proposed method can increase managerial rivalry, as the previous decentralized decision-making method has been criticized. Participant behavior indicated that token-based pricing can act as a signaling intermediary. Considering responses related to rewards, a token system designed to incorporate human resource allocation is a promising method. Based on aforementioned discussion, we concluded that token-economy-based bed allocation system has a potential to be an optimal method by mitigating information asymmetry.