Version 1
: Received: 4 January 2023 / Approved: 10 January 2023 / Online: 10 January 2023 (03:01:49 CET)
How to cite:
Wu, S.; Galteland, Y. J.; Hasselgren, A. Cryptographic Tokens as an Incentive Mechanism for Patient-Reported Outcome Measures Surveys. Preprints2023, 2023010169. https://doi.org/10.20944/preprints202301.0169.v1
Wu, S.; Galteland, Y. J.; Hasselgren, A. Cryptographic Tokens as an Incentive Mechanism for Patient-Reported Outcome Measures Surveys. Preprints 2023, 2023010169. https://doi.org/10.20944/preprints202301.0169.v1
Wu, S.; Galteland, Y. J.; Hasselgren, A. Cryptographic Tokens as an Incentive Mechanism for Patient-Reported Outcome Measures Surveys. Preprints2023, 2023010169. https://doi.org/10.20944/preprints202301.0169.v1
APA Style
Wu, S., Galteland, Y. J., & Hasselgren, A. (2023). Cryptographic Tokens as an Incentive Mechanism for Patient-Reported Outcome Measures Surveys. Preprints. https://doi.org/10.20944/preprints202301.0169.v1
Chicago/Turabian Style
Wu, S., Yao Jiang Galteland and Anton Hasselgren. 2023 "Cryptographic Tokens as an Incentive Mechanism for Patient-Reported Outcome Measures Surveys" Preprints. https://doi.org/10.20944/preprints202301.0169.v1
Abstract
(1) Background: As Patient-reported outcome measures face challenges with low response rate on surveys, different incentive mechanism have been proposed to achieve a higher response rate. However, it seems that monetary incentives are the only mechanism with proven effect. Nevertheless, it is less likely to be used than other mechanisms due to the monetary cost. (2) Methods: In this research work, a cryptographic scheme for rewarding patients with cryptographic tokens is developed and implemented on the Ethereum test network. (3) Results: The model is able to distribute decentralised tokens to patients who complete the PROMs in a fair, private, decentralised approach. The token can be further used by patients to exchange more healthcare services, encouraging more patients to participate in PROMs. At the same time, an IER detection method is built to improve the quality of PROMs, avoiding the healthcare provider paying for meaningless PROMs from patients who barely participate for incentives. (4) Conclusions: This work provides an privacy-preserving incentive model to increase the response rate for PROMs surveys. Our model prevents patients providing invalid responses to gain rewards.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
