Variation shows how the continuous or interval variables are spread around the mean value. The low value of variability indicates that the results are concentrated around the mean value; it means that the variables have values close to the mean value. The big value of variability indicates that the results are significantly spread around the mean value.
The key processes for health-care organizations are the number of patients visits, serious disease diagnostics rate, or hospitalization rate.
The common causes of variation are random factor and seasonality.
The special causes of variation might be epidemic, political, economic, or demographic situation.
The health-care organization business is dynamic and it changes over time since there are always changes over time due to common or special causes. The variables change in time, increasing or decreasing due to political, economic, or demographic situation, the visits rates increase during the epidemic or in winter or autumn (Hart, 2001).
II. Basic Data Review for Construction Project Equipment Arrangement.
1. The value added work in the process are the following steps:
Step 1. Read basic data package;
Step 6. Hold meeting;
Step 7. Project leader and specialist develop missing information;
Step 8. Determine plant preferred vendors;
Step 9. Review notes from meeting;
Step 10. Resolve open issues.
2. The main opportunities to improve the cycle time of this process:
Step 2. Write, type, proof, sign, copy, and distribute cover letter
Step 4. Lead engineer calls key people to schedule meeting
Step 5. Write, type, proof, sign, copy, and distribute confirmation letter
Step 11. Write, type, proof, sign, copy, and distribute basic data acceptance letter.
The cycle improvement opportunities should be determined by the highest difference to actual time ratio (Difference column divided by Actual time), and the steps with the ratio greater than 0.5 should be chosen as the improvement step.
3. Since there is difference between the actual and potential cycle time, there are some opportunities for improvement. However, taking into account the other steps that are characterized with greater difference, the opportunities for improvement are not worthwhile.
4. The most difficult critical issue is queue since this process involves other projects that require processing and it is difficult to adjust the queue time independently of other projects.
The seasonality factor causes the increase in the waiting time to the physician at the local hospital. This is the common cause variation case. When the case is explored as a problem, and the daily number of visits is presented as variables, and the appropriate hypothesis are set, the waiting time can be reduced.
First, the manager has to study the seasonal trends in hospital activity. For example, obtain the daily quantity of visits and arrange them according to the months groups. Then, set hypothesis and apply ANOVA analysis to decide which mean values are different (Cook, Netuveli & Sheikh, 2004). The data for the number of physicians available every day are necessary. Then, for seasons with higher visits rate, the number of physicians available should be increased. Alternatively, the plot can be used for the problem. On the x-scale, the periods are presented, on the y-scale the bar chart with the number of visits should be plotted, and the number of physicians is displayed as the line (Figure 1). The graph helps to identify how many physicians the hospital needs to reduce the wait time.
Figure 1. Graphical approach to waiting time at the physician’s at the local hospital.
The red line on the graph (Fig. 1) represents the adjusted (increased) number of physicians at the hospital according to the patients number.
Cook, A., Netuveli, G., & Sheikh, A. (2004). Basic skills in statistics: A guide for healthcare professionals. London: Class Health.
Hart, A. (2001). Making sense of statistics in healthcare. Abingdon, Oxon: Radcliffe Medical Press.