• Clinical and Experimental Pediatrics
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• v.48 no.7
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• pp.737-744
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• 2005

Purpose : Infants and children with cardiovascular diseases often present with respiratory symptoms. However, missed or delayed evaluation for potential airway problem may complicate overall prognosis. The aim of this study is to determine the clinical characteristics of these patients and explore the cause of airway problem. Methods : We reviewed the medical records of 64 patients(M : F=33:31, mean age : $6.3{\pm}7.5$ months) whose airway problems were proven by computed tomography or bronchoscopy in perioperative periods at the Asan Medical Center from January 1997 to June 2004. Patients were divided into two groups based on the duration of ventilator care : ${\leq}7$ days(group 1 : 23 cases, M : F=10 : 13) and >7 days(group 2 : 41 cases, M : F=23 : 18). Results : The patients in group 2 significantly developed more post-operative respiratory symptoms than group 1(P<0.001) and had more airway problems including extrinsic obstruction, intrinsic anomaly, and combined problem than group 1 although not significantly different(P=0.082). Among underlying diseases, the most common diseases were vascular anomaly(26.2 percent) and aortic arch anomaly(26.2 percent) in group 1 and pulmonary atresia with ventricular septal defect(22.4 percent) in group 2. The most frequent respiratory symptoms were recurrent wheezing pre-operatively and failure of ventilator weaning post-operatively. The major types of airway anomaly were tracheomalacia and tracheal stenosis(in each case 18.2 percent). Nineteen patients with persistent airway problems underwent aortopexy or other vascular correction. Of the 19 patients, 13(68.4 percent) were improved, but 2 failed in weaning ventilator and 4 died of non-airway problems. Conclusion : Early evaluation and treatment for potential airway problems may affect natural or surgical prognosis in patients with cardiovascular diseases presenting with respiratory symptoms.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.