doi:10.1016/j.csda.2006.09.029 
Copyright © 2006 Elsevier B.V. All rights reserved.
New classification of medical staff clinical services for optimal reconstruction of job workflow in a surgical ward: Application of spectrum analysis and sequence relational analysis
Hodaka Numasakia, 
, 
, Hajime Harauchib, Yuko Ohnoc, Kiyonari Inamurad, Satoko Kasaharac, Morito Mondene and Masato Sakonf
aDepartment of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Japan
bDepartment of Radiological Technology, Kawasaki College of Allied Health Professions, Japan
cDepartment of Health Promotion Science, Osaka University Graduate School of Medicine, Japan
dDepartment of Business Management, Kansai University of International Studies, Japan
eDepartment of Surgery and Clinical Oncology, Osaka University Graduate School of Medicine, Japan
fNishinomiya Municipal Center Hospital, Japan
Received 28 September 2004;
revised 31 May 2006;
accepted 25 September 2006.
Available online 19 October 2006.
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Abstract
In order to optimize the job workflow of medical staff, clinical job workflow was investigated from the viewpoint of its periodicity and the strength of causal association among jobs. Time-motion study for the staff at a surgical ward was carried out. To detect the periodicity of the occurrence of each job element, its frequency histogram was determined, and the discrete Fourier transformation was applied. For the analysis on the strength of the relationship among the job-sequence, the sequence relational analysis was developed, which was the expansion of the relation analysis to the sequence process. The job elements were classified into five incident patterns based on the periodicity of each element and into three patterns based on the association with other job elements. Based on time-motion study data, job workflow patterns of medical staff’ were clarified based on the incident pattern of the job elements and the association with other job elements.
Keywords: Workflow; Time-motion study; Discrete Fourier transformation (DFT); Spectrum analysis; Root-mean-square (RMS); Relational analysis
Fig. 1. Example of a histogram (Routine type job element of nurse: “moving”.). The horizontal axis indicates hours in a day and the vertical axis indicates working time.
Fig. 2. Example of the result of DFT (Routine type job element of nurse: “moving”.). The horizontal axis indicates frequency and the vertical axis indicates amplitude.
Fig. 3. Example of a histogram (Mixed type job element of nurse: “handing over”.). The horizontal axis indicates hours in a day and the vertical axis indicates working time.
Fig. 4. Example of the result of DFT (Mixed type job element of nurse: “handing over”.). The horizontal axis indicates frequency and the vertical axis indicates amplitude.
Fig. 5. Example of a histogram (Time-dependent type job element of nurse: “conference”.). The horizontal axis indicates hours in a day and the vertical axis indicates working time.
Fig. 6. Example of the result of DFT (Time-dependent type job element of nurse: “conference”.). The horizontal axis indicates frequency and the vertical axis indicates amplitude.
Fig. 7. Example of the calculation result of RMS value of the difference in number of cases between the job element of “bed-bath” and “preparation or clearing up of bed-bath”. The horizontal axis indicates time difference and the vertical axis indicates RMS value.
Fig. 8. Example of the calculation result of RMS value of the difference in number of cases between the job element of “collecting information from a chart” and “handing over”. The horizontal axis indicates time difference and the vertical axis indicates RMS value.
Fig. 9. Example of the calculation result of RMS value of the difference in number of cases between the job element of “answer patient–nurse call system” and “answer phones”. The horizontal axis indicates time difference and the vertical axis indicates RMS value.
Table 1.
The number of classifications of each stage by code classification
Table 2.
Example of the code classification result of the job elements (Extract from the job elements of nurses in 1999.)
Table 3.
Example of classification result by occurrence tendency for each job element (Classified job elements of nurse in 1999: 121 job elements in 169 job elements.)
Abstract
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