A new approach to systematization of the management of paper-based clinical pathways

Wakamiya, Shunji; Yamauchi, Kazunobu

doi:10.1016/j.cmpb.2006.03.001

Cited by 19 publications

(12 citation statements)

References 2 publications

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“…Although the clinical pathway (CP) predefines predictable standardized care process for a particular diagnosis or procedure, many variances may still unavoidably occur [1,2]. For example, during the CP of osteosarcoma preoperative chemotherapy, many variances (such as white and red blood cells decreasing, platelets decreasing, liver, kidney damage, stomatitis, neuropathy, etc.)…”

Section: Introductionmentioning

confidence: 98%

Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO

Jiang

Diao

et al. 2010

J Med Syst

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Although the clinical pathway (CP) predefines predictable standardized care process for a particular diagnosis or procedure, many variances may still unavoidably occur. Some key index parameters have strong relationship with variances handling measures of CP. In real world, these problems are highly nonlinear in nature so that it's hard to develop a comprehensive mathematic model. In this paper, a rule extraction approach based on combing hybrid genetic double multi-group cooperative particle swarm optimization algorithm (PSO) and discrete PSO algorithm (named HGDMCPSO/DPSO) is developed to discovery the previously unknown and potentially complicated nonlinear relationship between key parameters and variances handling measures of CP. Then these extracted rules can provide abnormal variances handling warning for medical professionals. Three numerical experiments on Iris of UCI data sets, Wisconsin breast cancer data sets and CP variances data sets of osteosarcoma preoperative chemotherapy are used to validate the proposed method. When compared with the previous researches, the proposed rule extraction algorithm can obtain the high prediction accuracy, less computing time, more stability and easily comprehended by users, thus it is an effective knowledge extraction tool for CP variances handling.

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Section: Introductionmentioning

confidence: 98%

Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO

Jiang

Diao

et al. 2010

J Med Syst

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“…In Wakamiya et. al's research [9], they constructed the paper based CP management system for organizations that can not introduce a computerized pathway's system because of financial problem. A new system was developed and incorporated into an existing network at a hospital with a paper-based clinical pathway management system.…”

Section: Introductionmentioning

confidence: 99%

Developing the Method of Server Controlled Outcomes Management and Variance Analysis

Matsumoto

Tanioka

Osaka

et al. 2009

Electronic Notes in Theoretical Computer Science

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This paper is to describe a way to develop the Psychoms process for mental health patient management and variance analysis system has been developed using artificial intelligence. Although it is agreed that there is a need for clinical pathway variance analysis, methods for creating a system are less well defined. The procedure and systematic process described aims to improve patients' quality of life through consistent and timely care. Ultimately, its potential influence is to assist in the improvement of quality health care services. This paper illustrates a method of outcomes management and variance analysis as the prospective development of future research.

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“…Currently, CPs are mainly implemented in traditional paper-based manual way, which has several inherent deficiencies impairing total implementation effectiveness, such as difficulty in real-time monitoring CP-based care workflows and systematically collecting and analyzing relevant information. Therefore, their computerized implementation has been considered as an important facilitator for healthcare services and has received much attention from some researches, such as [2,3]. In the computerized CP system, variance handling plays a key role in realizing dynamic management of patient care processes.…”

Section: Introductionmentioning

confidence: 99%

A Knowledge-Based Variance Management System for Supporting the Implementation of Clinical Pathways

Yan

Diao

Jiang

et al. 2009

2009 International Conference on Management and Service Science

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Variance management is important for computerized implementation of clinical pathways (CPs) to dynamically execute patient care processes and effectively provide high quality and efficient healthcare services. However, current related efforts are not adequate to support variance handling process involving two decision strategies, imprecise knowledge and the interaction with standardized CP workflow. This paper presents a knowledge-based variance management system that is developed using object-oriented analysis and design techniques, especially unified modeling language (UML), and implements effective analysis and handling of various variances through the construction and fuzzy reasoning of generalized fuzzy ECA (GFECA) rules and typed fuzzy Petri net extended by process knowledge (TFPN-PK) models related to the clinical pathway ontology and healthcare domain ontology.

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A new approach to systematization of the management of paper-based clinical pathways

Cited by 19 publications

References 2 publications

Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO

Knowledge Extraction Algorithm for Variances Handling of CP Using Integrated Hybrid Genetic Double Multi-group Cooperative PSO and DPSO

Developing the Method of Server Controlled Outcomes Management and Variance Analysis

A Knowledge-Based Variance Management System for Supporting the Implementation of Clinical Pathways

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