A decision support system to improve the efficiency of resource allocation in healthcare management

2007 ◽  
Vol 41 (2) ◽  
pp. 130-146 ◽  
Author(s):  
Emel Aktaş ◽  
Füsun Ülengin ◽  
Şule Önsel Şahin
Keyword(s):  
Resource Allocation ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Healthcare Management

Clinical Decision Support System for Early Disease Detection and Management

2019 ◽  
pp. 108-155
Author(s):  
Likewin Thomas ◽  
Manoj Kumar M. V. ◽  
Annappa B.
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Medical Error ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Healthcare Management ◽  
Statistical Techniques

Medical error is an adverse event of a failure in healthcare management, causing unintended injuries. Proper clinical care can be provided by employing a suitable clinical decision support system (CDSS) for healthcare management. CDSS assists the clinicians in identifying the severity of disease at the time of admission and predicting its progression. In this chapter, CDSS was developed with the help of statistical techniques. Modified cascade neural network (ModCNN) was built upon the architecture of cascade-correlation neural network (CCNN). ModCNN first identifies the independent factors associated with disease and using that factor; it predicts its progression. A case progressing towards severity can be given better care, avoiding later stage complications. Performance of ModCNN was evaluated and compared with artificial neural network (ANN) and CCNN. ModCNN showed better accuracy than other statistical techniques. Thus, CDSS developed in this chapter is aimed at providing better treatment planning by reducing medical error.

Design of a Decision Support System for Resource Allocation in Brazil Public Universities

2021 ◽  
pp. 470-486
Author(s):  
Carolina Lino Martins ◽  
Adiel Teixeira de Almeida ◽  
Danielle Costa Morais
Keyword(s):  
Resource Allocation ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
General Model ◽  
Decision Problem ◽  
Public Universities ◽  
Ministry Of Education ◽  
Allocation Model ◽  
Do So

This study aims to demonstrate how the design of a decision support system (DSS) can improve the process of internal resource allocation in Brazil public universities. Currently, there are not any kind of general DSS for such a problem. To do so, the analysis is carried out by identifying the general model from the Brazilian Ministry of Education and the models from every federal university, finding similarities between each model, and dividing the models into categories, according to their similarities. Thus, a DSS resource allocation model prototype was proposed. The perspectives are to contribute to the decision problem of how to allocate resources properly faced by Brazilians public universities, take safer and reliable decisions, seeking to reduce uncertainties and to maximize their results.

Study on Group Decision Support System for Production Resource Allocation of Engineering Machinery

2013 ◽  
Vol 427-429 ◽  
pp. 2609-2613
Author(s):  
Xuan Hua Xu ◽  
Yue Xia ◽  
Qiu Feng Wang ◽  
Hai Ming Zhao
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Group Decision ◽  
Group Decision Support ◽  
Collaborative Group ◽  
Group Decision Support System ◽  
Production Resource

Aiming at making the decision about production resource allocation of engineering machinery through the coordination of enterprises, firstly the collaborative group decision-making method of production resource allocation is proposed based on an information entropy model. On the basis of that, a new structure of group decision support system is constructed by Web Services technology. Finally the decision-making system of engineering machinery industry of Hunan province is taken as an example to verify and apply.

Clinical Decision Support System for Early Disease Detection and Management

2021 ◽  
pp. 1035-1075
Author(s):  
Likewin Thomas ◽  
Manoj Kumar M. V. ◽  
Annappa B.
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Medical Error ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Healthcare Management ◽  
Statistical Techniques

Medical error is an adverse event of a failure in healthcare management, causing unintended injuries. Proper clinical care can be provided by employing a suitable clinical decision support system (CDSS) for healthcare management. CDSS assists the clinicians in identifying the severity of disease at the time of admission and predicting its progression. In this chapter, CDSS was developed with the help of statistical techniques. Modified cascade neural network (ModCNN) was built upon the architecture of cascade-correlation neural network (CCNN). ModCNN first identifies the independent factors associated with disease and using that factor; it predicts its progression. A case progressing towards severity can be given better care, avoiding later stage complications. Performance of ModCNN was evaluated and compared with artificial neural network (ANN) and CCNN. ModCNN showed better accuracy than other statistical techniques. Thus, CDSS developed in this chapter is aimed at providing better treatment planning by reducing medical error.

Design of a Decision Support System for Resource Allocation in Brazil Public Universities

2019 ◽  
Vol 11 (1) ◽  
pp. 20-34 ◽  
Author(s):  
Carolina Lino Martins ◽  
Adiel Teixeira de Almeida ◽  
Danielle Costa Morais
Keyword(s):  
Resource Allocation ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
General Model ◽  
Decision Problem ◽  
Public Universities ◽  
Ministry Of Education ◽  
Allocation Model ◽  
Do So

This study aims to demonstrate how the design of a decision support system (DSS) can improve the process of internal resource allocation in Brazil public universities. Currently, there are not any kind of general DSS for such a problem. To do so, the analysis is carried out by identifying the general model from the Brazilian Ministry of Education and the models from every federal university, finding similarities between each model, and dividing the models into categories, according to their similarities. Thus, a DSS resource allocation model prototype was proposed. The perspectives are to contribute to the decision problem of how to allocate resources properly faced by Brazilians public universities, take safer and reliable decisions, seeking to reduce uncertainties and to maximize their results.

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