**5. Conclusions**

We created a formula for the nursing times provided on the basis of time study data ob‐ tained through a short-term survey and patient condition information, and quantified fac‐ tors governing tasks.

2) We constructed simulation algorithms combining the results under 1) with information accumulated over an extended period on the length of hospitalization and patient condition (nursing intensity).

and cannot be used as population means with any confidence. But when long-term changes in numbers of patients on the ward are used, it has to be borne in mind that numbers of pa‐ tients on the ward fluctuate markedly during holiday periods such as New Year and the summer O-bon Festival, on weekends, and at times when conferences attended by large

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As mentioned in 3.3.2, data relating to anomalous tasks deviated from normal distribution and was therefore excluded from the present analysis. However, it is a fact that nurses may carry out duties on the ward in the morning and undertake anomalous tasks such as attend‐ ing meetings in the afternoon. Such anomalous tasks occur in a certain proportion through‐ out the year and a special distribution, different from those of ordinary tasks, must be assumed for them. We believe that we need to improve the accuracy of our simulation by

In this study, as we explained under 'Method,' only simulations of day-shifts on weekdays were carried out and we were unable to accommodate the special systems in force on week‐ ends and at the holiday times mentioned above. Under these special systems, the numbers of nurses on duty and of patients on the ward fluctuate considerably. Because this greatly

We have not incorporated into our simulation the difference in function of nurses such as team leaders, who head and support a team rather than taking responsibility for patients, or nurses that have responsibility for a small number of patients and carry out management tasks along‐ side these duties, as is very often the case with ward supervisors. We assumed for the purpose of the present simulation that all nurses were nurses whose actual work involved being re‐ sponsible for patients, but in fact there are nurses who perform their roles in different ways. In addition, each year there are new recruits who need constant guidance from experienced nurses. They may, after some months, be able to cope with basic tasks, but they still have limi‐ tations, such as not being able to take responsibility for patients whose condition is severe. Fur‐

It is not possible at this stage, but an evaluation that compared simulation results with reali‐ ty would be the most reliable form of evaluation. In recent years, computer systems such as ordering systems, distribution systems, and electronic patient charts have been actively adopted as hospital information systems, and even more widespread use of IT→it can be ex‐ pected in the future. We believe that if it becomes possible to collect task time data without

actively seeking to include data concerning unusual phenomena as variables.

affects task times, we believe that there is room here for future investigation.

ther investigation of a methodology that will reflect this state of affairs is needed.

**6.6. On the roles and level of experience of nurses**

**6.7. Comparison with the real world**

numbers of doctors are held.

**6.4. Handling skewed values**

**6.5. Seasonality**
