This study proposes a new method of evaluating nursing care service processes in order to address the critical shortage of caregivers in Japan. Traditional evaluation methods, which often rely on a single metric such as the 'direct work ratio', fail to capture the inherent complexity of care work, including its parallelism, irregularity and diversity. To overcome this limitation, the study employs Data Envelopment Analysis (DEA), a method capable of handling multiple inputs and outputs simultaneously. This study is the first to apply DEA using dynamic time-study data as variables, establishing three types of decision-making unit (DMU) for analysis: employee, task and workplace. The results demonstrate that this approach can effectively quantify process inefficiencies and generate specific, actionable improvement proposals. For example, analysing tasks such as 'Excretion' and 'Meals' revealed inefficiencies in their indirect work ratios. Applying the suggested improvements successfully increased their efficiency scores in the validation data. This methodology provides a multifaceted, quantitative foundation for improving the efficiency and quality of care services.
KUGA et al. (Wed,) studied this question.