Background : This study presented an analysis of healthcare quality indicators using data mining and a development of decision support system for quality improvement. Method : Specifically, important factors influencing the key quality indicators were identified using a decision tree method for data mining based on 8,405 patients who discharged from a medical center during the period between December 1, 2000 and January 31, 2001. In addition, a decision support system was developed to analyze and monitor trends of these quality indicators using a Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. Result : Among 12 selected quality indicators, decision tree analysis was performed for 3 indicators ; unscheduled readmission due to the same or related condition, unscheduled return to intensive care unit, and inpatient mortality which have a volume bigger than 100 cases during the period. The optimum range of target group in healthcare quality indicators were identified from the gain chart. Important influencing factors for these 3 indicators were: diagnosis, attribute of the disease, and age of the patient in unscheduled returns to ICU group ; and length of stay, diagnosis, and belonging department in inpatient mortality group. Conclusion : We developed a decision support system through analysis of healthcare quality indicators and data mining technique which can be effectively implemented for utilization review and quality management in a healthcare organization. In the future, further number of quality indicators should be developed to effectively support a hospital-wide Continuous Quality Improvement activity. Through these endevours, a decision support system can be developed and the newly developed decision support system should be well integrated with the hospital Order Communication System to support concurrent review, utilization review, quality and risk management.
The principal objective of this study was to reveal the relationship between the menu management indicators and menu performance indicators in contract-foodservice operations. Menu indicators differed according to the type of business, type of contract, type of serving, and number of service lines. In accordance with the results of our correlation analysis, we noted significant correlations between menu performance indicators and menu management indicators. The first of these was the correlation between the food cost ration and meal counts, food loss, and the use of prepared vegetables. The second of these was the correlation between food cost per meal and forecasting error, food loss, and inventory turnover. The last of these correlations was the negative correlation between menu CSI(customer satisfaction index) and the use of prepared vegetables. According to the results of our canonical correlation analysis, 2 significant functions were identified. In the first function, we noted significant correlations between meal counts, use of prepared vegetables, food loss, and food cost ratio. Additionally, we noted significant correlations between forecasting error, inventory turnover, food loss, and food cost per meal in the second function. Menu management indicators had no influence on customer satisfaction.
Kim, Ji-Myong;Park, Young Jun;Kim, Young-Jae;Yu, YeongJin
국제학술발표논문집
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The 6th International Conference on Construction Engineering and Project Management
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pp.192-194
/
2015
The growing size and complex process in construction project recently leads to increase risk and the losses as well. Even though researchers have identified the major risk indicators, there is lack of comprehensive and quantitative research for identifying the relationship between the risk indicators and economic losses associated with construction projects. To address this shortage of research, this study defines risk indicators and create a framework to assess the influence of economic losses from the indicators. An insurance company's claim payout record was accepted as the dependent variable to reflect the real economic losses. Based on the claims, we categorized the causes and results of accidents. To establish framework, built environment vulnerability indicators and geographical vulnerability indicators were employed as the risk indicators. A Pearson correlation analysis was adopted to validate the relationship with loss ratio and risk indicators. Consequently, this framework and its results may offer significant references for under writers of insurance companies and loss prevention activities.
Objectives This study was designed to investigate the correlation between the gait analysis indices and Lumbar X-ray indicators. Methods 21 cases of patients who received treatment from October 2013 to February 2017 for abnormal posture were analyzed. Three indicators were measured in the lumbar spine X-ray. These indicators include Ferguson's angle, Lumbar lordotic angle, L4-5 IVD angle. Gait analysis indices were estimated by Treadmill Gait Analysis system. The data were analyzed to find out correlation between the gait analysis indices and Lumbar X-ray indicators. Spearman correlation was used. Results Ferguson's angle and Difference of gait balance of front and rear had a negative linear relationship, but there was no statistical significance. Lumbar lordotic angle and Difference of gait balance of front and rear had a negative linear relationship, but there was no statistical significance. L4-5 IVD angle and Difference of gait balance of right and left had a negative linear relationship, but there was no statistical significance. Conclusions Difference of gait balance of front and rear had strong level of a negative linear relationship with Ferguson's angle and Lumbar lordotic angle.
As urbanization progresses, there is a growing and continuous demand for green spaces that provide ecosystem services. However, increasing the quantity of green spaces within major cities is challenging. Therefore, it is essential to pursue qualitative improvements that consider ecological characteristics of existing green spaces. In this study, we focus on local neighborhood parks in Seoul and present the following two questions through an evaluation utilizing ecological design indicators and land use data: 1. Which factor, design or location, has a greater influence on the ecological quality of neighborhood parks in Seoul? 2. Additionally, when evaluating ecological characteristics, is there similarity between assessments based on land-use data and those utilizing ecological design indicators? For this study, we conducted research on 30 neighborhood parks in Seoul and classified them into mountainous types (adjacent to mountains, natural terrain parks) and urban types (independently designed within 300m without existing forests) based on previous studies. Firstly, we conducted evaluations according to park location types. When comparing the evaluation scores of urban types (14 parks) and mountainous types (16 parks), significant differences were observed with scores of 16.86 and 35.94, respectively. Statistical analysis showed a significant difference between park types. In terms of habitat quality, the average values for urban and mountainous parks were 0.33 and 0.53, respectively, and statistically significant differences were observed between park types indicating differences in ecological potential according to park location. Secondly, when comparing the results of ecological potential evaluations based on park design and external connectivity, a correlation was found between habitat quality and total scores according to evaluation indicators. The correlation analysis showed significant linear relationships between habitat quality and total scores, biodiversity scores, and ecosystem function scores, with high positive correlation coefficients of 0.829, 0.861, and 0.802, respectively. This study holds significance in analyzing the ecological aspects of urban parks through the lens of both park location characteristics and design indicators. The analysis results underscore the importance of planning and managing ecologically sound urban parks contingent upon their location. Moreover, the utilization of appropriate ecological design indicators can help alleviate environmental limitations surrounding parks. Integrating these considerations could enhance the ecological quality and ecosystem services of urban green spaces.
The purposes of this study are (1) carrying out the case study for the urban park planning in point of landscape ecology, (2) analyzing and evaluating the indicator character of the landscape ecological view on the basis of the case study and (3) proposing the urban park planning in point of landscape ecology. The results of this study are as follows. As a result of the elongation analysis among the shape indicators, especially, Dalsung Park has the highest score 0.85 and Chimsan Park has the lowest score 0.34. In case of green shape index, Bummul Park has 1.70 and Chimsan Park has 1.40 respectively. As a result of the buffer analysis, Chimsan Park turned out to be the highest, Bummul Park turned out the lowest. Chimsan Park gets I grade in two indicators but Bummul Park gets III grade in four indicators contrastively. As a result of the possibility analysis of the urban park planning, increasing elongation index and the number of major lobes can be an improvement method. Also by changing multilayer structure, micro-multiformity and curvature are increased and buffer of edge is improved.In this study, the basic data of landscape ecology can be obtained by the character analysis of landscape ecology. This study has a significant meaning of possibility in planning of the urban park which reflects the character of landscape ecology. This research was only performed in Chimsan Park, so additional researches for various cases will be needed.
Objectives : The objective is that we measure and analyze Pulse-Respiration Ratio and Body Composition Analysis to study the correlation between both. Methods : First, after subjects take a rest over 10 minutes, we measure their electrocardiogram and respiration pattern through which we take average peak interval to calculate an average pulse cycle and a respiration cycle. An average respiration cycle divided by an average Pulse Rate gives Pulse-Respiration Ratio. Next, we draw out 22 Body Composition Analysis indicators by using In-Body 720 model. Last, we analyze and take statistics on them by using SPSS 13.0 program. Results : Negative is the correlation between P/R Ratio and Body Composition Analysis indicator like fatness degree, body fat volume, body fat rate, abdominal fatness, BMI. Conclusions : 1. The higher P/R Ratio the more likely to be thin, the lower P/R Ratio the more likely to be fat. 2. We separately analyze P/R Ratio depending on each breathing frequency and pulse frequency to find out that breathing frequency has great influence and that breathing frequency decides the fatness degree. 3. In study on the correlation between P/R Ratio and Body Composition Analysis, fatness degree, in-body fat volume, in-body fat rate, BMI are the related indicators, which shows the connection with the fatness indicators. 4. In study on the correlation between Han-Yeol [寒熱] grade and Body Composition Analysis indicators, the result is that Han[寒] has no connection and that only Yeol[熱] grade has something to do with it, which means the higher heat symptom subjects have, the more basic metabolism volume and muscular build they have.
Now days, firm's technology capability is recognized as important factor to forecast and to evaluate firm's business performance. There are many efforts to develop useful indicators by applying patent information that includes concrete description about technology. Many previous studies analyzed relationship between patent indicators and firm's performance. But they didn't consider time gap between a point of firm's invention activity and a point of firm's performance improvement. They didn't considered a character of industrial fields either. To overcome these limitations, we selected IT industry for target analysis industry. Time-series patent data and financial data from 41 American IT firms between 2000 and 2011 were used to analyze. In this study, We empirically analyzed subsequent effect of patent indicators on firm's business performance by using correlation analysis and regression analysis.
The purpose of this study is to analyze effect of Army Risk Assessment System(ARAS) which is used to prevent safety accident in ROK army. Based on prior research, we select 4 indicators which are related to accident prevention effect and analyze the differences before and after ARAS operation for each indicators by using Paired-Samples T-Test. Also, we analyze the correlation between degree of ARAS operation and status of safety accidents of 112 ROK Army units. We conduct an evaluation of each function within the system using IPA method. The results of this study are as follows; All 4 indicators are improved compared to before ARAS operation, and the differences are statistically significant. Also, there is negative correlation between the degree of ARAS operation and the occurrence of safety accidents. So, the operation of ARAS has a positive effect on preventing safety accidents. Finally among the 15 functions of ARAS, 4 functions require improvement. The findings of this study have implications for proposing necessity of computerized system in enforcing Risk Assessment. Also, whether or not operating ARAS is important, but it is also important to operate it well. Lastly, We propose improvement plans for each function to operate it well.
This study aimed to develop strategies to re-establish the Park Nature Conservation Area in Bukhansan National Park, reflecting landscape ecological value by using the zonation program Marxan with Zones. Planning unit was set by watershed, and the basic data were mapped, considering topographical and ecological values. Mapped indicators were analyzed with the application framework of Marxan with Zones by indexing some indicators. The zones divided into Park Nature Conservation Area (Zone A), Park Nature Environment Area I(Zone B) which is reflected on the concept of Potential Park Nature Conservation Area and Park Nature Environment Area II(Zone C). The best solution for each of the scenarios was fixed through the sensitiveness analysis. From these, the final solution was selected considering five criteria including area ratio of conservation area and grouping. Lastly, the final solution was verified in the overlapped analysis with recent zonation. According to the results, the number of watersheds was 77, with an average area of $1,007,481m^2$. In terms of basic mapping and indexation, the slope index and number of landscape resources for topographical property were average 0.22 and 38 places, respectively. Biotope index was average 0.69 and legally protected species was 14 species, reflecting ecological values. As the social and economic indicators, trail index was average 0.04, and the number of tour and management facilities was 43 places. Through the framework of Marxan with Zones, the best solution for scenario 1 which was set by the highest conservation criteria was selected as the final solution, and the area ratio of Park Nature Conservation Area and grouping was excellent. As the result of overlapped analysis, suggested zonation of the Park Nature Conservation was better than the recent zonation in the area raito (28.3%), biotope grade I(15.4%) and the distribution points (10 places) of legally protected species with verification of proper distribution of conservation features according to the zone.
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