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BACKGROUND: The Centers of Medicare & Medicaid Services (CMS) links hospital reimbursements to quality metrics. Likewise, the Hospital Value-Based Purchasing (VBP) program offers financial incentives to acute-care hospitals based on performance improvements on several quality measures included in the national Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. A research gap exists with regard to assessing the effectiveness of VBP incentives on improving the patient's quality of care. OBJECTIVE: This study is to determine whether hospitals which reported better patient quality metrics and lower frequency of pressure sores received higher reimbursements. METHODS: The data were retrieved from the CMS Care Compare website utilizing matched data from 2297 US hospitals. Information on HCAHPS, the VBP Program in Patient Safety Index, and Reimbursements was obtained for this study. Partial Least Square (PLS) was utilized thru SmartPLS 3.0 to test the hypotheses. RESULTS: The results did not reveal any financial penalties when hospitals reported lower patient quality outcomes and increased numbers of pressure sores. However, lower patient quality measures were associated with lower patient satisfaction. Controversially, lower patient satisfaction scores were associated with higher reimbursement rates overall. CONCLUSIONS: The main contribution of this study reveals that the effectiveness of value-based reimbursements and the concept of continuous improvement is constrained due to the lack of unified measurement objectives across US healthcare institutions. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.compeleceng.2005.02.003 Byline: Xianwei Wu (a), David Jeff Jackson (a), Hui-Chuan Chen (b) Keywords: Fractal encoding; Image compression; Intelligent classification Abstract: In this paper we present a fast fractal encoding method based on an intelligent search of a Standard Deviation (STD) value between range and domain blocks. First, we describe the basic fractal image compression theory and an improved bit allocation scheme for Jacquin's Iterated Function System (IFS) parameter. Experimental results show that using a Fixed Scale Parameter (FSP) can shorten encoding time without significantly affecting reconstructed image quality. Second, we present a search algorithm based on the STD introduced by Tong. We enhance Tong's STD search algorithm by introducing a domain Intelligent Classification Algorithm (ICA) based on STD-classified domain blocks. The domain block search pool is pruned by eliminating multiple domain blocks with similar STD values. We refer to this pruning as the De-Redundancy Method (DRM). The domain search process is adaptive with the range block STD value of interest controlling the size of the domain pool searched. We refer to this process as the Search Number Adaptive Control (SNAC). Finally, we present experimental results showing the efficiency of the proposed method, noting a significant improvement over Tong's original STD method without significant loss in the reconstructed image quality. Author Affiliation: (a) Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL 35487-0286, USA (b) Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487-0290, USA Article History: Received 29 September 2003; Accepted 14 February 2005

An artificial intelligence technique of fuzzy associative memory is used to determine rock types from well-log signatures. Fuzzy associative memory (FAM) is a hybrid of neural network and fuzzy expert system. This new approach combines the learning ability of neural network and the strengths of fuzzy linguistic modeling to adaptively infer lithologies from well-log signatures based on 1) the relationships between the lithology and log signature that the neural network have learned during the training and/or 2) geologist's knowledge about the rocks. The method is applied to a sequence of the Ordovician rock units in northern Kansas. This paper also compares the performances of two different methods, using the same data set for meaningful comparison. The advantages of FAM are 1) expert knowledge acquired by geologists is fully utilized; 2) this knowledge is augmented by the neural network learning from the data, when available; and 3) FAM is 'transparent' in that the knowledge is explicitly stated in the fuzzy rules.

Byline: Hui-Chuan Chen, Tzong-Ru (Jiun-Shen) Lee, Hsin-Yi Lin, Hsiao-Chen Wu The home life industry is an emerging industry and very closely related to consumer life. The objective of this research is to apply the modified Teorija Rezhenija Izobretate Zadach (TRIZ) method and the Kano method to discuss the strategy direction and process of the home life industry from the viewpoint of the supplier and consumer. The result of the research shows that the home life industry is very competitive. To solve the problem, we propose four innovative principles. In accordance with its application to marketing, we introduce an innovative strategy to the home life industry and improve on its competitive nature.

Byline: Tzong-Ru Lee, Jiun-Hung Lin, Be-You Din, Siau Ching Lenny Koh, Hui-Chuan Chen As a giant natural greenhouse, Taiwan is self sustaining in growing Phalaenopsis aphrodite from upstream seedling to downstream blooming. However, as a commodity, growing Phalaenopsis aphrodite from seedling to blooming is an intricate industry. Integration of upstream supply of raw materials and downstream delivery of products is the goal for agricultural management in a business mode. Using the five-flow business function, viz. information, business, logistics, cash and personnel, the operation model of Phalaenopsis aphrodite is analysed to identify the bottleneck and suggest possible solutions for future development and improvement.

Formation of machine cells often results in some intercellular movements between the cells. These movements cause lack of segregation among the cells. This is in conflict with the main objective of group technology which aims at independently operating cells. This paper presents a non-heuristic network approach to form manufacturing cells with minimum intercellular interactions. The machine-part matrix containing machining times is represented as a network which is subsequently partitioned by using a modified Gomory-Hu algorithm to find a minimum intercellular interaction. The modified algorithm improves the computational efficiency. [ABSTRACT FROM AUTHOR]