• Korea Journal of Hospital Management
• /
• v.23 no.1
• /
• pp.87-106
• /
• 2018

Objective: The objective of this study is to examine the association between process quality of inpatient care and risk-adjusted, thirty-day potentially preventable hospital readmission (PPR) rates. Data Sources/Study Setting: This was an observational cross-sectional study of nonfederal acute-care hospitals located in two states California and Florida, discharging Medicare patients with a principal discharge diagnosis of heart failure, acute myocardial infarction, or pneumonia January through December 31, 2007. Data were obtained from the Healthcare Cost and Utilization Project State Inpatient Database of the Agency for Healthcare Research and Quality, Centers for Medicare and Medicaid Services Hospital Compare database, and the American Hospital Association Annual Survey of Hospitals. Study Design: The dependent variable of this study is condition-specific, risk-adjusted, thirty-day potentially preventable hospital readmission (PPR). 3M's PPR software was utilized to determine whether a readmission was potentially preventable. The independent variable of this study is hospital performance for process quality of inpatient care, measured by hospital adherence to recommended processes of care. We used multivariate hierarchical logistic models, clustered by hospitals, to examine the relationship between condition-specific, risk-adjusted, thirty-day PPR rates and process quality of inpatient care, after taking clinical and socio-demographic characteristics of patients and structural and operational characteristics of hospitals into account. Findings: Better performance on the process quality metrics was associated with better patient outcome (i.e., low thirty-day PPR rates) in pneumonia, but not generally in two cardiovascular conditions (i.e., heart failure and acute myocardial infarction). Practical Implication: Adherence to the process quality metrics currently in use by CMS is associated with risk-adjusted, thirty-day PPR rates for patients with pneumonia, but not with cardiovascular conditions. More evidence-based process quality metrics closely linked to 30-day PPR rates, particularly for cardiovascular conditions, need to be developed to serve as a guideline to reduce potentially preventable readmissions.

• Journal of Distribution Science
• /
• v.13 no.8
• /
• pp.91-96
• /
• 2015

Purpose - This study reviews the delivery of child welfare service quality and examines how the dimensions of the variables of customer satisfaction impact the results from a service distribution perspective. This study differs from existing research since it proposes that a recognized level of child welfare service quality is necessary to achieve customer satisfaction from the perspective of service distribution. Research design, data, and methodology - This study explores child welfare service quality factors that affect customer satisfaction. The study examines and analyzes demographic variables, service quality dimensions, and the causal relationships between child welfare service quality and customer satisfaction. Data from 300 child welfare cases were collected from organizations in Korea in the areas of Busan and Gyeongsangnamdo. The methods of analysis are as follow. First, using descriptive analysis frequency, the percentages were evaluated to assess the demographic variables. Second, Cronbach's α was used to test reliability and to evaluate the internal consistency of the measuring of items. Third, multiple regression analysis was conducted to find out how much the independent variable can affect customer satisfaction. Results - Five factors of child welfare service quality were identified in three categories: process quality (assurance, empathy), results quality (reliability, caring), and physical environment quality (tangibles). There were significant differences among the effects of the child welfare service quality factors on customer satisfaction. A multiple regression analysis was done with process quality (assurance, empathy), results quality (reliability, caring) and physical environment quality (tangibles) to test the hypothesis: assurance (t=2.434, p<0.05), empathy (t=3.677, p<0.001), reliability (t=3.271, p<0.05), caring (t=4.380, p<0.000), and tangibles (t=3.654, p<0.01) had a positive influence on child welfare service quality from a service distribution perspective. Therefore, hypotheses 1, 2, 3, 4, and 5 were supported. In addition, multiple regression analysis on the effects of the variables showed that caring (β=0.273), empathy (β=0.246), tangibles (β=0.265), reliability (β=0.152), and assurance (β=0.131) all had a positive and strong influence on child welfare service quality from a service distribution perspective. Therefore, all child welfare service quality categories (process, results and physical environment quality) were positively statistically significant. Conclusion - In this study, the main findings can be summarized as follows. First, the quality of service of child welfare consists of three dimensions of quality: process quality, results quality, and physical environment quality. The results of the multiple regression analysis also showed that caring and reliability were confirmed as more meaningful variables by the increasing loading factors. Second, the family members involved in child welfare proposed caring as the most important variable among the dimensions of service quality. Third, the results of the hypothesis testing using regression showed that all child welfare service quality factors had a positive impact on customer satisfaction. The results of the study could provide useful information to help increase the effectiveness of delivery strategies for child welfare service quality from a service distribution perspective.

• Korean Journal of Social Welfare
• /
• v.58 no.1
• /
• pp.265-290
• /
• 2006

The purposes of this study are: First, to investigate how the juvenile delinquents in the juvenile justice process evaluate their quality of life. Second, to examining which factors influence their quality of life. To accomplish these purposes, this study used sample of 570 juvenile delinquents in Seoul, Busan, Daejeon who are in the process of the juvenile justice and used the Korean Version of WHOQOL-BREF (brief version of WHO quality of life measure). To examine this purpose, Mean, standard deviation, t-test, One way ANOVA, multiple regression were conducted. The results are as follows: 1) juvenile delinquent in the process of the juvenile justice have complex problems and needs, and their quality of life are lower than the civil in the psychological, social relations, environment domain. 2) The factors influencing their quality of life in the general domain are stigma by parent, violent, undemocratic treatment in the process of the juvenile justice, family income level. But the factors of each domain of quality of life differ to some extent. Statistically significant factors of physical health domain are violent, undemocratic treatment in the process of the juvenile justice, first arrest time, stigma by others, sex, juvenile justice process. Significant factors of psychological health domain are delinquency frequency, stigma by parent, stigma by others, first arrest time, family income level, sex. Significant factors of social relations domain are first arrest time, stigma by parent, delinquency frequency, family income level, stigma by friend. Environment is significantly influenced by family income level, stigma by parent, sex, delinquency frequency, juvenile justice process.

• Journal of Korean Society for Quality Management
• /
• v.20 no.1
• /
• pp.136-146
• /
• 1992

Most of scheduling papers on FMS have been considered that the fabrication process, the machining process and the assembly process etc. are independent and the releasing, routing, dependent, batching, loading problem are treated separetely. In this paper, we discuss that the integrated scheduling problem which can be solved for efficient use. We combine two systems that each process system which in order to produce a product is treated dependently, the releasing and the routing problem are combined one system and we present the efficient flexible manufacturing system as including the alternate process.

• Journal of Korean Society for Quality Management
• /
• v.25 no.1
• /
• pp.116-134
• /
• 1997

The present automated manufacturing environment is very different when the classical statistical process control method based on batch processing were used. Therefore these must be replaced by automated statistical process control method. In this point of view, this paper intends to develop the automated statistical process control method which can be implemented in the present automated manufacturing environment. Specially this study developed the rules to identify the special causes of the manufacturing process in the aspect of the 100 PPM management, and a numerical example is demonstrated to verify the usefulness of these rules.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2004.04a
• /
• pp.436-441
• /
• 2004

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a generalized maximum likelihood estimate. (MLE) of the process change point when a control chart with variable sample size (VSS) scheme signals a change in the process mean, and evaluate the performance of this estimator when it mi used with a VSS EWMA chart.

• Journal of Korean Society for Quality Management
• /
• v.15 no.1
• /
• pp.47-54
• /
• 1987

It is common that the process capability fluctuates as time passes, but concentrates to the mean value. To keep up process capability with given limits is vital to stability of process. Various control charts, especially ${\sigma}-chart$, have been used for analyzing process capability, but It sometimes can not give distinct answer. So this paper introduces another analyzing method by ARMA (autoregressive moving average) which is originally developed for forecasting, and demonstrates the analyzing methodology through a case study.

• Proceedings of the Safety Management and Science Conference
• /
• 2012.04a
• /
• pp.573-577
• /
• 2012

Based on latest research, the parametric quality statistics cannot be used in non-normal process with demand pattern of many-variety and small-volume, since it involves extremely small sample size. The research proposes nonparametric quality statistics according to the number of lot or batch in the non-normal process. Additionally, the nonparametric Process Capability Index (PCI) is used with 14 identified non-normal distributions.

• Journal of Korean Society for Quality Management
• /
• v.26 no.1
• /
• pp.88-98
• /
• 1998

Process capability indices are used to determine whether a production process is capable of producing items within a specified tolerance. Using conditional distribution, we study some process capability indices ${\hat{C}}_{Gp}$, ${\hat{C}}_{Gpk}$, ${\hat{C}}_{Gpm}$ under conjugate prior distribution. We consider some process capability indices with Gibbs sampling method. Also, we examine some small sample properties related to these estimaters by some simulations.

• Journal of Korean Society for Quality Management
• /
• v.24 no.2
• /
• pp.172-178
• /
• 1996

In this study, we developed a software for statistical process control. This software presents $\bar{x}$, R, CUSUM, EWMA control chart and process capability index. In this system, statistical process control methods are integrated into the automated method on a real time base. It is available in process control of specified type and can be performed on personal computer with network system.