| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2022: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2021: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2020: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2019: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
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| Outline of Final Research Achievements |
We formulated the behaviors of patients and healthcare providers in clinical settings as decision-making problems under uncertainty. The probability of cancer incidence rates is known to some extent from past research. On the other hand, the evaluation of PCR tests for COVID-19 includes not only uncertainties, but also the evidence is scarce and probability calculations are inherently impossibles.
While such problems are typically formulated within the frameworks of probability theory and Bayesian statistics, in the case of COVID-19, the initial probabilities required for discussion are unknown (though several candidates exist, the true probability remains uncertain). Therefore, we attempted to solve the decision-making problem of selecting procedures and policies based on test results by applying recently developed decision-making theories that account for ambiguity, and aimed to translate these findings into policy recommendations.
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