This document discusses the development of future-proof open source healthcare information systems. It reviews literature on successes and failures of healthcare information system implementations and integration projects. It then presents the fundamentals of developing the Open Source Health Information Platform (OSHIP), which is based on openEHR specifications and aims to facilitate interoperability between systems through a common reference model and clinical knowledge models.
CLOUD-BASED DEVELOPMENT OF SMART AND CONNECTED DATA IN HEALTHCARE APPLICATIONijdpsjournal
There is a need of data integration in cloud – based system, we propose an Information Integration and Informatics framework for cloud – based healthcare application. The data collected by the Electronic Health Record System need to be smart and connected, so we use informatica for the connection of data
from different database. Traditional Electronic Health Record Systems are based on different technologies, languages and Electronic Health Record Standards. Electronic Health Record System stores data based on interaction between patient and provider. There are scalable cloud infrastructures, distributed and heterogeneous healthcare systems and there is a need to develop advanced healthcare application. This advance healthcare application will improve the integration of required data and helps in fast interaction between the patient and the service providers. Thus there is the development of smart
and connected data in healthcare application of cloud. The proposed system is developed by using cloud platform Aneka.
Understanding the Need of Data Integration in E Healthcareijtsrd
This paper discusses the current scenario of e healthcare and different dimensions of Big data in healthcare and the importance of data integration in e health care and the challenges associated with data integration and associated uses of data integration with respect to different use cases which might be helpful to physician's decision making because the data driven decision making involves combination of heterogeneous data which includes Electronic Health Record containing different types of data and connected healthcare organization in order to provide value based connected healthcare which would be useful to primary healthcare center located at different location because patients suddenly expect their healthcare experiences to be as exceptional and as transparent as those of retail or banking, and physician's have to scramble to adjust to these new expectations due to lack of data integrity. Mrs. Shashi Rekha. H. | Dr. Chethana Prakash. M | Dr. K. Thippeswamy "Understanding the Need of Data Integration in E- Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31007.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31007/understanding-the-need-of-data-integration-in-e-healthcare/mrs-shashi-rekha-h
This document summarizes a survey on multiple patient data semantic conflicts and methods of electronically exchanging data. It discusses how heterogeneous healthcare systems can have different data formats, terminology, and semantics, leading to conflicts. It reviews literature on standardizing data using controlled terminologies and archetypes. Methods for resolving semantic conflicts include ontology mapping and mediation between standards like HL7 Version 2 and 3. Semantic conflicts can occur at the data or schema level and involve issues like naming inconsistencies or representing the same concept differently.
Understanding Physicians' Adoption of Health Cloudscsandit
This document summarizes a research study that aims to understand physicians' intentions to adopt health clouds (cloud-based health services) and identifies key factors that may influence adoption. The study develops a research model drawing on theories of technology acceptance. It hypothesizes that physicians' adoption intentions will be shaped by two conflicting beliefs: 1) performance expectations of health clouds and 2) security and privacy concerns regarding medical information in the cloud. The study aims to test this model through a survey measuring the hypothesized constructs and their relationships. It acknowledges some limitations but aims to provide insights to facilitate physicians' adoption of innovative cloud-based healthcare technologies.
DETERMINING BUSINESS INTELLIGENCE USAGE SUCCESSijcsit
Business intelligence systems are highly complex systems that senior executives use to process vast
amounts of information when making decisions. Business intelligence systems are rarely used to their full
potential due to a poor understanding of the factors that contribute to system success. Organizations using
business intelligence systems frequently find that it is not easy to evaluate the effectiveness of these
systems, and researchers have noted that there is limited scholarly and practical understanding of how
quality factors affect information use within these systems. This quantitative post positivist research used
the information system (IS) success model to analyze how information quality and system quality influence
information use in business intelligence systems. This study was also designed to investigate the
moderating effects of maturity constructs (i.e., data sources and analytical capabilities) on the
relationships between quality factors and information use.
A Proposed Security Architecture for Establishing Privacy Domains in Systems ...IJERA Editor
Information and communication technology (ICT) are becoming a natural part in healthcare. Instead of keeping patient information inside a written file, you can find all information stored in an organized database as well defined files using a specific system in almost every hospital. But those files sometimes got lost or information was split up in files in different hospitals or different departments so no one could see the whole picture from this point we come up with our idea. One of this paper targets is to keep that information available on the cloud so doctors and nurses can have an access to patient record everywhere, so patient history will be clear which helps doctors in giving the right decision. We present security architecture for establishing privacy domains in e-Health bases. In this case, we will improve the availability of medical data and provide the ability for patients to moderate their medical data. Moreover, e-Health system in cloud computing has more than one component to be attacked. The other target of this paper is to distinguish between different kinds of attackers and we point out several shortcomings of current e-Health solutions and standards, particularly they do not address the client platform security, which is a crucial aspect for the overall security of systems in cloud. To fill this gap, we present security architecture for establishing privacy domains in e-Health infrastructures. Our solution provides client platform security and appropriately combines this with network security concepts.
Presentation for UP Health Informatics HI201 under Dr. Iris Tan and Dr. Mike Muin. The topic for discussion Interoperability & Standards, a healthcare scenario was given regarding two disparate information systems, one found in a clinic, another with a hospital information system. #MSHI #HI201
An approach for transforming of relational databases to owl ontologyIJwest
Rapid growth of documents, web pages, and other types of text content is a huge challenge for the modern content management systems. One of the problems in the areas of information storage and retrieval is the lacking of semantic data. Ontologies can present knowledge in sharable and repeatedly usable manner and provide an effective way to reduce the data volume overhead by encoding the structure of a particular domain. Metadata in relational databases can be used to extract ontology from database in a special domain. According to solve the problem of sharing and reusing of data, approaches based on transforming relational database to ontology are proposed. In this paper we propose a method for automatic ontology construction based on relational database. Mining and obtaining further components from relational database leads to obtain knowledge with high semantic power and more expressiveness. Triggers are one of the database components which could be transformed to the ontology model and increase the amount of power and expressiveness of knowledge by presenting part of the knowledge dynamically.
CLOUD-BASED DEVELOPMENT OF SMART AND CONNECTED DATA IN HEALTHCARE APPLICATIONijdpsjournal
There is a need of data integration in cloud – based system, we propose an Information Integration and Informatics framework for cloud – based healthcare application. The data collected by the Electronic Health Record System need to be smart and connected, so we use informatica for the connection of data
from different database. Traditional Electronic Health Record Systems are based on different technologies, languages and Electronic Health Record Standards. Electronic Health Record System stores data based on interaction between patient and provider. There are scalable cloud infrastructures, distributed and heterogeneous healthcare systems and there is a need to develop advanced healthcare application. This advance healthcare application will improve the integration of required data and helps in fast interaction between the patient and the service providers. Thus there is the development of smart
and connected data in healthcare application of cloud. The proposed system is developed by using cloud platform Aneka.
Understanding the Need of Data Integration in E Healthcareijtsrd
This paper discusses the current scenario of e healthcare and different dimensions of Big data in healthcare and the importance of data integration in e health care and the challenges associated with data integration and associated uses of data integration with respect to different use cases which might be helpful to physician's decision making because the data driven decision making involves combination of heterogeneous data which includes Electronic Health Record containing different types of data and connected healthcare organization in order to provide value based connected healthcare which would be useful to primary healthcare center located at different location because patients suddenly expect their healthcare experiences to be as exceptional and as transparent as those of retail or banking, and physician's have to scramble to adjust to these new expectations due to lack of data integrity. Mrs. Shashi Rekha. H. | Dr. Chethana Prakash. M | Dr. K. Thippeswamy "Understanding the Need of Data Integration in E- Healthcare" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31007.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31007/understanding-the-need-of-data-integration-in-e-healthcare/mrs-shashi-rekha-h
This document summarizes a survey on multiple patient data semantic conflicts and methods of electronically exchanging data. It discusses how heterogeneous healthcare systems can have different data formats, terminology, and semantics, leading to conflicts. It reviews literature on standardizing data using controlled terminologies and archetypes. Methods for resolving semantic conflicts include ontology mapping and mediation between standards like HL7 Version 2 and 3. Semantic conflicts can occur at the data or schema level and involve issues like naming inconsistencies or representing the same concept differently.
Understanding Physicians' Adoption of Health Cloudscsandit
This document summarizes a research study that aims to understand physicians' intentions to adopt health clouds (cloud-based health services) and identifies key factors that may influence adoption. The study develops a research model drawing on theories of technology acceptance. It hypothesizes that physicians' adoption intentions will be shaped by two conflicting beliefs: 1) performance expectations of health clouds and 2) security and privacy concerns regarding medical information in the cloud. The study aims to test this model through a survey measuring the hypothesized constructs and their relationships. It acknowledges some limitations but aims to provide insights to facilitate physicians' adoption of innovative cloud-based healthcare technologies.
DETERMINING BUSINESS INTELLIGENCE USAGE SUCCESSijcsit
Business intelligence systems are highly complex systems that senior executives use to process vast
amounts of information when making decisions. Business intelligence systems are rarely used to their full
potential due to a poor understanding of the factors that contribute to system success. Organizations using
business intelligence systems frequently find that it is not easy to evaluate the effectiveness of these
systems, and researchers have noted that there is limited scholarly and practical understanding of how
quality factors affect information use within these systems. This quantitative post positivist research used
the information system (IS) success model to analyze how information quality and system quality influence
information use in business intelligence systems. This study was also designed to investigate the
moderating effects of maturity constructs (i.e., data sources and analytical capabilities) on the
relationships between quality factors and information use.
A Proposed Security Architecture for Establishing Privacy Domains in Systems ...IJERA Editor
Information and communication technology (ICT) are becoming a natural part in healthcare. Instead of keeping patient information inside a written file, you can find all information stored in an organized database as well defined files using a specific system in almost every hospital. But those files sometimes got lost or information was split up in files in different hospitals or different departments so no one could see the whole picture from this point we come up with our idea. One of this paper targets is to keep that information available on the cloud so doctors and nurses can have an access to patient record everywhere, so patient history will be clear which helps doctors in giving the right decision. We present security architecture for establishing privacy domains in e-Health bases. In this case, we will improve the availability of medical data and provide the ability for patients to moderate their medical data. Moreover, e-Health system in cloud computing has more than one component to be attacked. The other target of this paper is to distinguish between different kinds of attackers and we point out several shortcomings of current e-Health solutions and standards, particularly they do not address the client platform security, which is a crucial aspect for the overall security of systems in cloud. To fill this gap, we present security architecture for establishing privacy domains in e-Health infrastructures. Our solution provides client platform security and appropriately combines this with network security concepts.
Presentation for UP Health Informatics HI201 under Dr. Iris Tan and Dr. Mike Muin. The topic for discussion Interoperability & Standards, a healthcare scenario was given regarding two disparate information systems, one found in a clinic, another with a hospital information system. #MSHI #HI201
An approach for transforming of relational databases to owl ontologyIJwest
Rapid growth of documents, web pages, and other types of text content is a huge challenge for the modern content management systems. One of the problems in the areas of information storage and retrieval is the lacking of semantic data. Ontologies can present knowledge in sharable and repeatedly usable manner and provide an effective way to reduce the data volume overhead by encoding the structure of a particular domain. Metadata in relational databases can be used to extract ontology from database in a special domain. According to solve the problem of sharing and reusing of data, approaches based on transforming relational database to ontology are proposed. In this paper we propose a method for automatic ontology construction based on relational database. Mining and obtaining further components from relational database leads to obtain knowledge with high semantic power and more expressiveness. Triggers are one of the database components which could be transformed to the ontology model and increase the amount of power and expressiveness of knowledge by presenting part of the knowledge dynamically.
This document proposes extending the HL7 standard with a responsibility perspective to better manage access rights to patient health records. It presents the ReMMo responsibility metamodel, which defines actors' responsibilities and associated access rights. The paper aims to align ReMMo with the HL7-based eSanté healthcare platform model in Luxembourg to semantically enhance access controls based on users' real responsibilities rather than just roles. It will first map concepts between the two models, then evaluate the alignment through a prototype applying inference rules.
Framework Architecture for Improving Healthcare Information Systems using Age...IJMIT JOURNAL
The document proposes an agent-based framework architecture for improving healthcare information systems using agent technology and case-based reasoning. The framework aims to address issues of interoperability, integration, and information sharing across different healthcare systems and platforms. Intelligent agents and case-based reasoning can help provide accurate medical information for tasks like diagnosis and treatment, and increase the speed and reliability of information exchanges between different healthcare actors and systems.
A Codon Frequency Obfuscation Heuristic for Raw Genomic Data PrivacyKato Mivule
Genomic data provides clinical researchers with vast opportunities to study various patient ailments. Yet the same data contains revealing information, some of which a patient might want to remain concealed. The question then arises: how can an entity transact in full DNA data while concealing certain sensitive pieces of information in the genome sequence, and maintain DNA data utility? As a response to this question, we propose a codon frequency obfuscation heuristic, in which a redistribution of codon frequency values with highly expressed genes is done in the same amino acid group, generating an obfuscated DNA sequence. Our preliminary results show that it might be possible to publish an obfuscated DNA sequence with a desired level of similarity (utility) to the original DNA sequence. http://arxiv.org/abs/1405.5410
This document presents the Concept Definition Generator (CDG), an open source tool for defining healthcare concepts using multilevel modeling specifications. The CDG allows domain experts to graphically represent healthcare concepts and automatically generate associated XML schemas. It was developed in Python with a wxPython graphical interface to run cross-platform. The CDG addresses the significant challenges of knowledge representation for semantic interoperability of electronic health records. Future work includes further standardizing healthcare terminologies and developing proper modeling tools.
Assess data reliability from a set of criteria using the theory of belief fun...IAEME Publication
This document proposes a method to assess data reliability from metadata using belief functions. It discusses evaluating data reliability from a set of criteria as there is little existing work focused on this problem. The method aims to provide a general approach to calculate an overall reliability score by combining multiple criteria despite any conflicts between them. It models the information with evidence theory to handle uncertainty and provide useful ordering of reliability assessments for end users.
Data Linkage is an important step that can provide valuable insights for evidence-based decision making, especially for crucial events. Performing sensible queries across heterogeneous databases containing millions of records is a complex task that requires a complete understanding of each contributing database’s schema to define the structure of its information. The key aim is to approximate the structure
and content of the induced data into a concise synopsis in order to extract and link meaningful data-driven facts. We identify such problems as four major research issues in Data Linkage: associated costs in pairwise matching, record matching overheads, semantic flow of information restrictions, and single order classification limitations. In this paper, we give a literature review of research in Data Linkage. The
purpose for this review is to establish a basic understanding of Data Linkage, and to discuss the
background in the Data Linkage research domain. Particularly, we focus on the literature related to the recent advancements in Approximate Matching algorithms at Attribute Level and Structure Level. Their efficiency, functionality and limitations are critically analysed and open-ended problems have been
exposed.
Healthcare Data Integrity and Interoperability Standards Podcast SummaryM2SYS Technology
As the healthcare industry moves closer to full scale implementation of health information exchanges and integrated delivery networks, the call for data integrity and interoperability standards has grown increasingly louder to help ensure that data quality isn’t compromised so physicians and patients can have complete confidence in the information reflected by their electronic health records.
We interviewed John Donnelly, President of IntePro Solutions in Colonia NJ and an expert in healthcare technology standards, interoperability and innovation about data integrity and data standardization protocols in the context of the shift to electronic medical records and the subsequent data sharing across health information exchanges.
This document compares several open source tools that can be used for data science. It provides background on key concepts in data science like data mining, machine learning, predictive analytics and business intelligence. It also discusses techniques commonly used by data scientists like clustering, classification, regression etc. The document then reviews popular open source data science tools like Orange, RapidMiner, KNIME, Weka and R and compares their key features based on techniques covered in the EMC Data Science Associate certification. It finds that these tools provide capabilities for common data science techniques at no cost, making them suitable alternatives to expensive proprietary software, especially for small organizations.
ROLE OF CERTAINTY FACTOR IN GENERATING ROUGH-FUZZY RULEIJCSEA Journal
The generation of effective feature-based rules is essential to the development of any intelligent system. This paper presents an approach that integrates a powerful fuzzy rule generation algorithm with a rough set-assisted feature reduction method to generate diagnostic rule with a certainty factor. Certainty factor of each rule is calculated by considering both the membership value of each linguistic term introduced at time of fuzzyfication of data as well as possibility values, due to inconsistent data, generated by rough set theory at time of rule generation. In time of knowledge inferencing in an intelligent system, certainty factor of each rule will play an important role to find out the appropriate rule to be selected. Experimental results demonstrate the superiority of our approach.
Rule Optimization of Fuzzy Inference System Sugeno using Evolution Strategy f...IJECEIAES
The need for accurate load forecasts will increase in the future because of the dramatic changes occurring in the electricity consumption. Sugeno fuzzy inference system (FIS) can be used for short-term load forecasting. However, challenges in the electrical load forecasting are the data used the data trend. Therefore, it is difficult to develop appropriate fuzzy rules for Sugeno FIS. This paper proposes Evolution Strategy method to determine appropriate rules for Sugeno FIS that have minimum forecasting error. Root Mean Square Error (RMSE) is used to evaluate the goodness of the forecasting result. The numerical experiments show the effectiveness of the proposed optimized Sugeno FIS for several test-case problems. The optimized Sugeno FIS produce lower RMSE comparable to those achieved by other wellknown method in the literature.
Implementation of Data Privacy and Security in an Online Student Health Recor...Kato Mivule
Kato Mivule, Stephen Otunba, Tattwamasi Tripathy, Sharad and Sharma, "Implementation of Data Privacy and Security in an Online Student Health Records System", Proceedings at the ISCA 21th Int Conf on Software Engineering and Data Engineering (SEDE-2012), Pages 143-148, Los Angeles, CA, USA
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Abstract In early days information contain in increasingly corporate area, now IT organization help to right module to store, manage ,retrieve and transfer information in the more reliable and powerful manner. As part of an Information Lifecycle Management (ILM) best-practices strategy, organizations require solutions for migrating data between in heterogeneous environments and system storage. In early days information contain in increasingly corporate area, today IT organization help to right module to store, manage ,retrieve and transfer information in the more reliable and powerful manner. This paper helps to planned to design powerful modules that high-performances data migration of storage area with less time complexity. This project contain unique information of data migration in dynamic IT nature and business advantage that design to provide new tool used for data migration. Keywords— Heterogeneous Environment, data migration, data mapping
Towards A Differential Privacy and Utility Preserving Machine Learning Classi...Kato Mivule
Kato Mivule, Claude Turner, Soo-Yeon Ji, "Towards A Differential Privacy and Utility Preserving Machine Learning Classifier", Procedia Computer Science (Complex Adaptive Systems), 2012, Pages 176-181, Washington DC, USA.
A comparative study of cn2 rule and svm algorithmAlexander Decker
This document discusses using data mining techniques like decision trees, CN2 rule, SOM, and K-means clustering to predict heart disease. It provides background on heart disease prevalence and risk factors. The methodology section describes how classification trees, CN2 rule induction, self-organizing maps (SOM), and K-means clustering algorithms work and a comparative study is performed on heart disease data to evaluate the accuracy of each technique. Experimental results show CN2 rule and SOM achieved the highest classification accuracy rates above 93%.
This document summarizes an article from the International Journal of Computer Engineering and Technology (IJCET) that discusses applications of data mining in medical databases. It begins by noting that large amounts of patient data have been collected in hospital information systems, and data mining techniques can be used to extract valuable hidden information from this data. The document then provides an overview of common data mining methods like neural networks, decision trees, and cluster detection that are applicable to medical data. It also discusses the process of knowledge discovery in databases and some considerations for preprocessing medical data from different sources before performing data mining analysis.
Rule-based Information Extraction for Airplane Crashes ReportsCSCJournals
Over the last two decades, the internet has gained a widespread use in various aspects of everyday living. The amount of generated data in both structured and unstructured forms has increased rapidly, posing a number of challenges. Unstructured data are hard to manage, assess, and analyse in view of decision making. Extracting information from these large volumes of data is time-consuming and requires complex analysis. Information extraction (IE) technology is part of a text-mining framework for extracting useful knowledge for further analysis.
Various competitions, conferences and research projects have accelerated the development phases of IE. This project presents in detail the main aspects of the information extraction field. It focused on specific domain: airplane crash reports. Set of reports were used from 1001 Crash website to perform the extraction tasks such as: crash site, crash date and time, departure, destination, etc. As such, the common structures and textual expressions are considered in designing the extraction rules.
The evaluation framework used to examine the system's performance is executed for both working and test texts. It shows that the system's performance in extracting entities and relations is more accurate than for events. Generally, the good results reflect the high quality and good design of the extraction rules. It can be concluded that the rule-based approach has proved its efficiency of delivering reliable results. However, this approach does require an intensive work and a cycle process of rules testing and modification.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against developing mental illness and improve symptoms for those who already have a condition.
Este documento presenta el Primer Plan Socialista (PPS) de Venezuela para el período 2007-2013, el cual tiene como objetivo construir el socialismo del siglo XXI a través de una nueva ética socialista, la suprema felicidad social para todos los ciudadanos, y una democracia protagónica revolucionaria. El PPS también propone un modelo productivo socialista, una nueva geopolítica nacional y energética, y una nueva geopolítica internacional basada en la cooperación entre los pueblos.
The document discusses the concepts of awakening and quickening of the spirit from a Christian perspective. It defines key terms like awake, quicken, and spirit. Several Bible verses are presented that reference being quickened or made alive by God's word and righteousness. The document also discusses the resurrection of Christ and the promise that believers will be quickened and resurrected through their belief in Him. It aims to stir believers to actively grow in their faith through the power of the Holy Spirit.
This document shares random photos and thoughts from a computer class project. It includes pictures spray painted by a friend and expresses a desire to buy something seen as "MUST.....BUY.....NOWWWWW!!!!". The document has a casual, informal tone as it discusses photos put together while bored for a class project.
This document proposes extending the HL7 standard with a responsibility perspective to better manage access rights to patient health records. It presents the ReMMo responsibility metamodel, which defines actors' responsibilities and associated access rights. The paper aims to align ReMMo with the HL7-based eSanté healthcare platform model in Luxembourg to semantically enhance access controls based on users' real responsibilities rather than just roles. It will first map concepts between the two models, then evaluate the alignment through a prototype applying inference rules.
Framework Architecture for Improving Healthcare Information Systems using Age...IJMIT JOURNAL
The document proposes an agent-based framework architecture for improving healthcare information systems using agent technology and case-based reasoning. The framework aims to address issues of interoperability, integration, and information sharing across different healthcare systems and platforms. Intelligent agents and case-based reasoning can help provide accurate medical information for tasks like diagnosis and treatment, and increase the speed and reliability of information exchanges between different healthcare actors and systems.
A Codon Frequency Obfuscation Heuristic for Raw Genomic Data PrivacyKato Mivule
Genomic data provides clinical researchers with vast opportunities to study various patient ailments. Yet the same data contains revealing information, some of which a patient might want to remain concealed. The question then arises: how can an entity transact in full DNA data while concealing certain sensitive pieces of information in the genome sequence, and maintain DNA data utility? As a response to this question, we propose a codon frequency obfuscation heuristic, in which a redistribution of codon frequency values with highly expressed genes is done in the same amino acid group, generating an obfuscated DNA sequence. Our preliminary results show that it might be possible to publish an obfuscated DNA sequence with a desired level of similarity (utility) to the original DNA sequence. http://arxiv.org/abs/1405.5410
This document presents the Concept Definition Generator (CDG), an open source tool for defining healthcare concepts using multilevel modeling specifications. The CDG allows domain experts to graphically represent healthcare concepts and automatically generate associated XML schemas. It was developed in Python with a wxPython graphical interface to run cross-platform. The CDG addresses the significant challenges of knowledge representation for semantic interoperability of electronic health records. Future work includes further standardizing healthcare terminologies and developing proper modeling tools.
Assess data reliability from a set of criteria using the theory of belief fun...IAEME Publication
This document proposes a method to assess data reliability from metadata using belief functions. It discusses evaluating data reliability from a set of criteria as there is little existing work focused on this problem. The method aims to provide a general approach to calculate an overall reliability score by combining multiple criteria despite any conflicts between them. It models the information with evidence theory to handle uncertainty and provide useful ordering of reliability assessments for end users.
Data Linkage is an important step that can provide valuable insights for evidence-based decision making, especially for crucial events. Performing sensible queries across heterogeneous databases containing millions of records is a complex task that requires a complete understanding of each contributing database’s schema to define the structure of its information. The key aim is to approximate the structure
and content of the induced data into a concise synopsis in order to extract and link meaningful data-driven facts. We identify such problems as four major research issues in Data Linkage: associated costs in pairwise matching, record matching overheads, semantic flow of information restrictions, and single order classification limitations. In this paper, we give a literature review of research in Data Linkage. The
purpose for this review is to establish a basic understanding of Data Linkage, and to discuss the
background in the Data Linkage research domain. Particularly, we focus on the literature related to the recent advancements in Approximate Matching algorithms at Attribute Level and Structure Level. Their efficiency, functionality and limitations are critically analysed and open-ended problems have been
exposed.
Healthcare Data Integrity and Interoperability Standards Podcast SummaryM2SYS Technology
As the healthcare industry moves closer to full scale implementation of health information exchanges and integrated delivery networks, the call for data integrity and interoperability standards has grown increasingly louder to help ensure that data quality isn’t compromised so physicians and patients can have complete confidence in the information reflected by their electronic health records.
We interviewed John Donnelly, President of IntePro Solutions in Colonia NJ and an expert in healthcare technology standards, interoperability and innovation about data integrity and data standardization protocols in the context of the shift to electronic medical records and the subsequent data sharing across health information exchanges.
This document compares several open source tools that can be used for data science. It provides background on key concepts in data science like data mining, machine learning, predictive analytics and business intelligence. It also discusses techniques commonly used by data scientists like clustering, classification, regression etc. The document then reviews popular open source data science tools like Orange, RapidMiner, KNIME, Weka and R and compares their key features based on techniques covered in the EMC Data Science Associate certification. It finds that these tools provide capabilities for common data science techniques at no cost, making them suitable alternatives to expensive proprietary software, especially for small organizations.
ROLE OF CERTAINTY FACTOR IN GENERATING ROUGH-FUZZY RULEIJCSEA Journal
The generation of effective feature-based rules is essential to the development of any intelligent system. This paper presents an approach that integrates a powerful fuzzy rule generation algorithm with a rough set-assisted feature reduction method to generate diagnostic rule with a certainty factor. Certainty factor of each rule is calculated by considering both the membership value of each linguistic term introduced at time of fuzzyfication of data as well as possibility values, due to inconsistent data, generated by rough set theory at time of rule generation. In time of knowledge inferencing in an intelligent system, certainty factor of each rule will play an important role to find out the appropriate rule to be selected. Experimental results demonstrate the superiority of our approach.
Rule Optimization of Fuzzy Inference System Sugeno using Evolution Strategy f...IJECEIAES
The need for accurate load forecasts will increase in the future because of the dramatic changes occurring in the electricity consumption. Sugeno fuzzy inference system (FIS) can be used for short-term load forecasting. However, challenges in the electrical load forecasting are the data used the data trend. Therefore, it is difficult to develop appropriate fuzzy rules for Sugeno FIS. This paper proposes Evolution Strategy method to determine appropriate rules for Sugeno FIS that have minimum forecasting error. Root Mean Square Error (RMSE) is used to evaluate the goodness of the forecasting result. The numerical experiments show the effectiveness of the proposed optimized Sugeno FIS for several test-case problems. The optimized Sugeno FIS produce lower RMSE comparable to those achieved by other wellknown method in the literature.
Implementation of Data Privacy and Security in an Online Student Health Recor...Kato Mivule
Kato Mivule, Stephen Otunba, Tattwamasi Tripathy, Sharad and Sharma, "Implementation of Data Privacy and Security in an Online Student Health Records System", Proceedings at the ISCA 21th Int Conf on Software Engineering and Data Engineering (SEDE-2012), Pages 143-148, Los Angeles, CA, USA
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Abstract In early days information contain in increasingly corporate area, now IT organization help to right module to store, manage ,retrieve and transfer information in the more reliable and powerful manner. As part of an Information Lifecycle Management (ILM) best-practices strategy, organizations require solutions for migrating data between in heterogeneous environments and system storage. In early days information contain in increasingly corporate area, today IT organization help to right module to store, manage ,retrieve and transfer information in the more reliable and powerful manner. This paper helps to planned to design powerful modules that high-performances data migration of storage area with less time complexity. This project contain unique information of data migration in dynamic IT nature and business advantage that design to provide new tool used for data migration. Keywords— Heterogeneous Environment, data migration, data mapping
Towards A Differential Privacy and Utility Preserving Machine Learning Classi...Kato Mivule
Kato Mivule, Claude Turner, Soo-Yeon Ji, "Towards A Differential Privacy and Utility Preserving Machine Learning Classifier", Procedia Computer Science (Complex Adaptive Systems), 2012, Pages 176-181, Washington DC, USA.
A comparative study of cn2 rule and svm algorithmAlexander Decker
This document discusses using data mining techniques like decision trees, CN2 rule, SOM, and K-means clustering to predict heart disease. It provides background on heart disease prevalence and risk factors. The methodology section describes how classification trees, CN2 rule induction, self-organizing maps (SOM), and K-means clustering algorithms work and a comparative study is performed on heart disease data to evaluate the accuracy of each technique. Experimental results show CN2 rule and SOM achieved the highest classification accuracy rates above 93%.
This document summarizes an article from the International Journal of Computer Engineering and Technology (IJCET) that discusses applications of data mining in medical databases. It begins by noting that large amounts of patient data have been collected in hospital information systems, and data mining techniques can be used to extract valuable hidden information from this data. The document then provides an overview of common data mining methods like neural networks, decision trees, and cluster detection that are applicable to medical data. It also discusses the process of knowledge discovery in databases and some considerations for preprocessing medical data from different sources before performing data mining analysis.
Rule-based Information Extraction for Airplane Crashes ReportsCSCJournals
Over the last two decades, the internet has gained a widespread use in various aspects of everyday living. The amount of generated data in both structured and unstructured forms has increased rapidly, posing a number of challenges. Unstructured data are hard to manage, assess, and analyse in view of decision making. Extracting information from these large volumes of data is time-consuming and requires complex analysis. Information extraction (IE) technology is part of a text-mining framework for extracting useful knowledge for further analysis.
Various competitions, conferences and research projects have accelerated the development phases of IE. This project presents in detail the main aspects of the information extraction field. It focused on specific domain: airplane crash reports. Set of reports were used from 1001 Crash website to perform the extraction tasks such as: crash site, crash date and time, departure, destination, etc. As such, the common structures and textual expressions are considered in designing the extraction rules.
The evaluation framework used to examine the system's performance is executed for both working and test texts. It shows that the system's performance in extracting entities and relations is more accurate than for events. Generally, the good results reflect the high quality and good design of the extraction rules. It can be concluded that the rule-based approach has proved its efficiency of delivering reliable results. However, this approach does require an intensive work and a cycle process of rules testing and modification.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against developing mental illness and improve symptoms for those who already have a condition.
Este documento presenta el Primer Plan Socialista (PPS) de Venezuela para el período 2007-2013, el cual tiene como objetivo construir el socialismo del siglo XXI a través de una nueva ética socialista, la suprema felicidad social para todos los ciudadanos, y una democracia protagónica revolucionaria. El PPS también propone un modelo productivo socialista, una nueva geopolítica nacional y energética, y una nueva geopolítica internacional basada en la cooperación entre los pueblos.
The document discusses the concepts of awakening and quickening of the spirit from a Christian perspective. It defines key terms like awake, quicken, and spirit. Several Bible verses are presented that reference being quickened or made alive by God's word and righteousness. The document also discusses the resurrection of Christ and the promise that believers will be quickened and resurrected through their belief in Him. It aims to stir believers to actively grow in their faith through the power of the Holy Spirit.
This document shares random photos and thoughts from a computer class project. It includes pictures spray painted by a friend and expresses a desire to buy something seen as "MUST.....BUY.....NOWWWWW!!!!". The document has a casual, informal tone as it discusses photos put together while bored for a class project.
This document provides information about a fashion campaign for the brand Contempo, including details about the event, organizers, models, publicity, makeup, music, and production. It also includes brief biographies and contact information for two fashion designers, Lorena Laing and Jain, who will be featured in the campaign. The event will take place at Prahran Town Hall in Melbourne, Australia on June 9, 2010 starting at 8:30pm.
Il Master SAFER (Master I livello Energy Management & Sustainability) è dedicato ai laureati, anche triennali, in materie tecniche, sientifiche, economiche e giuridiche. Si propone di fornire le competenze tecnico-scientifiche e gestionali, ma anche economiche, normative e manageriali, necessarie ad approcciare in maniera
equilibrata e poliedrica il complesso panorama
dei sistemi energetici.
This document discusses a new approach to healthcare information systems that focuses on semantic interoperability rather than data models. It proposes using a common reference model (CRM) of healthcare concepts implemented in software, along with clinical knowledge models (CKM) that provide instructions for representing specific clinical concepts using the CRM. This would allow healthcare information and context to be exchanged between systems without loss of meaning. The document argues the current approach of discrete data modeling does not adequately capture the full context and meaning of healthcare information.
Achieving Semantic Integration of Medical Knowledge for Clinical Decision Sup...AmrAlaaEldin12
Abstract. Enhancing the outputs of the Clinical Decision Support systems (CDS) is a permanent concern for many research communities, which have to deal with an abundance of entities, data, structures, methods, application, tools, and so on. In the few past decades, there were theorized and standardized tech- nologies that could help researchers to obtain better results. The paper presents a method to enrich the inputs of the CDS through a semantic integration of sev- eral medical knowledge sources, by using the Topic Maps standard, in order to obtain more refined medical recommendations. Future research directions and challenges are summarized and conclusions are issued.
This document discusses information systems and decision support systems. It provides characteristics and examples of each. Both systems utilize a system development life cycle to accomplish their objectives. An information system collects, processes, stores, and disseminates data to provide information to meet an objective. A decision support system is an organized collection of people, procedures, software, databases, and devices used to help make decisions by offering suggestions to solve problems. Examples of each in healthcare include electronic health records, patient health records, and clinical decision support systems used in nursing.
IntroductionHealthcare Information Systems are defined as Comp.docxvrickens
Introduction:
Healthcare Information Systems are defined as “Computerized systems designed to facilitate the management and operation of all technical (biomedical) and administrative data for the entire healthcare system, for a number of its functional units, for a single healthcare institution, or even for an institutional department or unit” [9]. The employment of computers in the healthcare sector can be traced back to the 1960s. During the early 1970s, the first attempts to adopt HIS were made [10]. However, in the past, HIS initiatives were limited to the automation of business processes related to (a) administration and (b) healthcare tools and techniques related to various medical procedures as: diagnostic, therapeutic and surgical. During the 80s, innovative patterns in database designs and applications related to HIS, concluded to developments in planning and administration of the healthcare data. In parallel, HIS also introduced low cost financial systems for hospitals under 200 beds in size [11]. It should be noted that the early computerized systems were limited in big hospitals and government projects (military).
As the IT industry flourish the HIS technology was populated with various network applications. The ‘net period with the internet, intranet and extranet affected the communication of data in hospitals especially in the 1990's. In the middle of the same decade the interface engine emerged as a product to support the integration of applications, as best-of-breed applications became harder to manage [12]. New experience and knowledge in applications such as Internet-based telemedicine, personal health records, asynchronous healthcare communication systems, m-health and picture archiving communication systems (PACS) have been applied in the healthcare sector [13]. The growth of the aforementioned applications has lead to the development of healthcare services that have been characterized as complex, redundant and transcriptive [14].
In shedding some light on the underlined services that exist in healthcare organizations, we reviewed the normative on HIS classification. Based on the services that HIS support, Mantzana [7] categorized them into: (a) clinical, (b) non-clinical, (c) pharmaceutical and (d) laboratory. The authors adopt this classification and extend it, by proposing that the patient record category should be added, as it refers to medical records that can be maintained by the citizen or the health professional. This category can be further broken down into (a) Electronic Patient Records Systems (EPR), which are detailed records of encounters between patients and their healthcare providers and (b) Electronic Personal Health Records (ePHR) that are citizen self-maintained health and healthcare records
Extensive and serious quality problems exist in health care delivery processes, resulting in tremendous harms and losses to stakeholders. An increasing concern for improving health care quality has been expressed fro ...
Framework for efficient transformation for complex medical data for improving...IJECEIAES
The adoption of various technological advancement has been already adopted in the area of healthcare sector. This adoption facilitates involuntary generation of medical data that can be autonomously programmed to be forwarded to a destined hub in the form of cloud storage units. However, owing to such technologies there is massive formation of complex medical data that significantly acts as an overhead towards performing analytical operation as well as unwanted storage utilization. Therefore, the proposed system implements a novel transformation technique that is capable of using a template based stucture over cloud for generating structured data from highly unstructured data in a non-conventional manner. The contribution of the propsoed methodology is that it offers faster processing and storage optimization. The study outcome also proves this fact to show propsoed scheme excels better in performance in contrast to existing data transformation scheme.
Framework for efficient transformation for complex medical data for improving...IJECEIAES
The adoption of various technological advancement has been already adopted in the area of healthcare sector. This adoption facilitates involuntary generation of medical data that can be autonomously programmed to be forwarded to a destined hub in the form of cloud storage units. However, owing to such technologies there is massive formation of complex medical data that significantly acts as an overhead towards performing analytical operation as well as unwanted storage utilization. Therefore, the proposed system implements a novel transformation technique that is capable of using a template based stucture over cloud for generating structured data from highly unstructured data in a non-conventional manner. The contribution of the propsoed methodology is that it offers faster processing and storage optimization. The study outcome also proves this fact to show propsoed scheme excels better in performance in contrast to existing data transformation scheme.
Written Assignment 1 HIT Strategic Plan .docxtroutmanboris
Written Assignment 1
HIT Strategic Plan
Information and Communication Technology for Health Professionals
Dr. Michelle Kameka
Florida International University
2
HIT Strategic Plan
Corporate/ Institutional Goals and Objectives
Our mission is to provide the best environment for our employees and patients. Providing
employees with a comfortable workplace and training to offer patients the best possible care.
Patients will be able to receive effective quality care at a low cost. Our goal is to expand and
diversify the market service base to the best of our ability (Glandon, Smaltz, Slovensky, 2014).
HIT Goals and Objectives
Our Health Information Technology systems will analyze changes in the service market
and resources for the development of new services (Glandon, Smaltz, Slovensky, 2014).
Supplying our physicians with top of the line tools and software will allow them to effectively
treat patients with the highest quality of care. New health information technology will strive to
improve quality, effectiveness and efficiency of healthcare services while keeping their personal
health information private (Aminpour, Sadoughi, Ahmadi, 2013).
Priorities for the applications portfolio
Each factor listed below is imperative to the success of a HIT system but for the
successful planning we must list priorities for the new computer applications from most
recommended priority to least below. (Glandon, Smaltz, Slovensky, 2014)
Financial information system that manages all financial transactions like
payments from patients, assets, and expenses.
Office automation system ensure communication and document storage
Facilities project management system to ensure meeting company goals by
planning and organization
3
Human resources system for the hiring and proper training of employees
Resource utilization and scheduling systems for patients and physicians to avoid
delays, missed appointments and unused equipment
Materials management system organizing and controlling the disbursement of
materials available to employees
Financial information and office automation is listed as top priorities because patient
financial and medical documents need to be ensured of their privacy. The Health Information
Portability and Accountability Act (HIPAA) ensures that a patient’s medical private information
will be protected when electronically transmitted (Glandon, Smaltz, Slovensky, 2014). There can
be serious consequences if violated, thus we must ensure a patient’s privacy is protected at all
times.
HIT Architecture and Infrastructure
The current HIT architecture has many flaws to its system like time consumption,
distribution, information security, and sever pressure (Yao, Han, Ma, Xue, Chen, Li, 2014). All
of these detrimental issues can be avoided by using a Cloud based Virtual Desktop
Infrastructure. The new Cloud syste.
Chapter 12 Page 209Discussion Questions 2. How does a d.docxcravennichole326
Chapter 12 Page 209
Discussion Questions
2. How does a data dictionary influence the design and implementation of an EHR? How does the data dictionary enhance and restrict the EHR?
3. In what circumstances might a clinical infrastructure based on either third-party service providers or mobile applications be desirable? What cautions would we place on these technologies in the same circumstances?
Chapter 12 Page 209
Discussion Questions
2. How does a data dictio
nary influence the design and implementation of an EHR? How does the data
dictionary enhance and restrict the EHR?
3. In what circumstances might a clinical infrastructure based on either third
-
party service providers
or mobile applications be desirabl
e? What cautions would we place on these technologies in the same
circumstances?
Chapter 12 Page 209
Discussion Questions
2. How does a data dictionary influence the design and implementation of an EHR? How does the data
dictionary enhance and restrict the EHR?
3. In what circumstances might a clinical infrastructure based on either third-party service providers
or mobile applications be desirable? What cautions would we place on these technologies in the same
circumstances?
Chapter 12 Technical Infrastructure to Support Healthcare
Scott P. Narus
No single off-the-shelf system today can support all needs of the healthcare environment. Therefore it is critical that the technical architecture be capable of supporting multiple system connections and data interoperability.
Objectives
At the completion of this chapter the reader will be prepared to:
1.Describe the key technical components of electronic health records and their interrelationships
2.Define interoperability and its major elements
3.Contrast networking arrangements such as regional health information organizations (RHIOs), health information exchanges (HIEs), and health information organizations (HIOs)
4.Provide information about newer technical models such as cloud computing and application service providers (ASPs)
5.Synthesize current challenges for informatics infrastructure
Key Terms
Application service provider (ASP), 205
Architecture, 197
Clinical data repository (CDR), 198
Cloud computing, 205
Data dictionary, 201
Health information organization (HIO), 204
Infrastructure, 197
Interface engine (IE), 203
Knowledge base, 202
Master person index (MPI), 199
Regional Health Information Organization (RHIO), 204
Service-oriented architecture (SOA), 207
Abstract
This chapter introduces the technical aspects of electronic health records (EHRs) and the current infrastructure components. Complementing the functional components discussed elsewhere, this chapter introduces terms such as clinical data repository, master person index, interface engine, and data dictionary and other technical components necessary for EHRs to function. Recent material about national efforts related to the infrastructure and electroni ...
GM502 Leadership Theory and Practice I 1 A.docxaryan532920
GM502 | Leadership Theory and Practice I
1
Assignment Rubric
Unit 2 Assignment: The Leadership Challenge – Leadership Credibility
This Assignment will assess your knowledge based on the following outcome:
GM502-2: Develop leadership practice through the application and integration of leadership theory.
Kouzes, and Posner (2012) state “What people most look for in a leader (a person they would be willing to
follow) has been constant over time,” and cite these characteristics as:
Honest
Forward-looking
Inspiring
Competent
(Kouzes & Posner, 2012).
Using the Kouzes & Posner, and Northouse readings in a 4–5 page APA compliant paper you will:
1. Provide an overview of the four characteristics described in Kouzes and Posner.
2. Determine if these characteristics are indicative of the skills or trait approach as described in Northouse.
3. Provide at least one example of a leader you have known or have identified through research that has
demonstrated these characteristics. Include detail on how this leader used these characteristics to increase the
effectiveness of the organization.
4. Identify the trait or characteristic that resonates with you the most. Then provide a detailed action plan on how you
will incorporate this trait or characteristic into your own leadership practice.
Reference
Kouzes, J. M., & Posner, B. Z. (2012). The leadership challenge (5th ed.). San Francisco, CA: Wiley.
Northouse, P. G. (2016). Leadership theory and practice (7th ed.). Thousand Oaks, CA: Sage.
Review the grading Rubric below before beginning this Assignment.
Directions for Submitting your Assignment
Compose your Assignment in a Microsoft Word document and save it as Username-GM502 Assignment-
Unit#.doc (Example: TAllen- GM502 Assignment-Unit 2.doc). Submit your file by selecting the Unit 2:
Assignment in the Dropbox by the end of Unit 2.
GM502 | Leadership Theory and Practice I
2
GM502 Unit 2 Assignment: The Leadership Challenge –
Leadership Credibility
Point
Value
Your
Score
Content (50 points)
● Provide an overview of the four characteristics described in
Kouzes and Posner.
● Determine if these characteristics are indicative of the skills or
trait approach as described in Northouse.
25
● Identify a leader that you have known or have identified through
research that has demonstrated these characteristics.
● Cite examples of what this leader has done to support your
choice.
● Identify the trait or characteristic that resonates with you the most.
● Provide a detailed action plan on how you will incorporate this
trait or characteristic into your own leadership practice. Be sure to
include specifics on how you will incorporate this skill/trait and
how you will measure its effectiveness and results.
25
Analysis (30 points)
Work demonstrates synthesis of concepts, research, and experience. 10
Work demonstrates the student’s ability to tie ...
This document summarizes the challenges of integrating data from different modeling and simulation (M&S) architectures used in a live-virtual-constructive simulation network. It discusses how differing data formats, representations, and structures between architectures like Distributed Interactive Simulation (DIS) and High Level Architecture (HLA) can introduce complexity. Standards, tools like gateways and the Federated Engineering Agreements Template (FEAT), and processes like the Distributed Simulation Engineering and Execution Process (DSEEP) can help address these challenges and reduce complexity when combining M&S architectures. The author recommends questioning if combining architectures is truly needed, using recognized standards, and maintaining good documentation records.
ORIGINAL ARTICLEAn informatics framework for public health.docxgerardkortney
ORIGINAL ARTICLE
An informatics framework for public health
information systems: a case study
on how an informatics structure for integrated
information systems provides benefit in supporting
a statewide response to a public health emergency
Ivan J. Gotham • Linh H. Le • Debra L. Sottolano •
Kathryn J. Schmit
Received: 17 April 2013 / Revised: 8 October 2013 / Accepted: 23 January 2014 /
Published online: 8 February 2014
� Springer-Verlag Berlin Heidelberg 2014
Abstract This chapter illustrates how a well-established public health informatics
framework provides an integrated information system infrastructure that assures and
enhances the efficacy of public health emergency preparedness (PHEP) actions
throughout the phases of the health emergency event life cycle. Key PHEP activities
involved in supporting this cycle include planning; surveillance; alerting; resource
assessment and management; data-driven decision support; and intervention for
prevention and control of disease or injury in populations. Information systems
supporting these activities are most effective in assuring optimal response to an
emergent health event when they are integrated within an informatics framework
that supports routine (day to day) information exchange within the health infor-
mation exchange community. In late April 2009, New York State (NYS) initiated a
statewide PHEP response to the emergence of Novel Influenza A (H1N1), culmi-
nating in a statewide vaccination campaign during the last quarter of 2009. The
I. J. Gotham (&)
School of Public Health, Department of Health Policy Management University at Albany,
State University of New York , 1 University Place, Rensselaer, NY 12144, USA
e-mail: [email protected]
L. H. Le � K. J. Schmit
New York State Department of Health, Office of Information Technology Service,
Empire State Plaza, Room 148, Albany, NY 12237, USA
e-mail: [email protected]
K. J. Schmit
e-mail: [email protected]
L. H. Le
Department of Nursing, Sage College, Albany, NY 12180, USA
D. L. Sottolano
Center for Health Care Quality & Surveillance, New York State Department of Health,
875 Central Avenue, Albany, NY 12206, USA
e-mail: [email protected]
123
Inf Syst E-Bus Manage (2015) 13:713–749
DOI 10.1007/s10257-014-0240-9
http://crossmark.crossref.org/dialog/?doi=10.1007/s10257-014-0240-9&domain=pdf
http://crossmark.crossref.org/dialog/?doi=10.1007/s10257-014-0240-9&domain=pdf
established informatics framework of integrated information systems within NYS
conveyed significant advantages and flexibility in supporting the range of PHEP
activities required for an effective response to this health event. This chapter
describes, and provides, performance metrics to illustrate how a public health
informatics framework can enhance the efficacy of all phases of a public health
emergency response. It also provides informatics lessons learned from the event.
Keywords Public health informatics � Information systems �
.
THE TECHNOLOGY OF USING A DATA WAREHOUSE TO SUPPORT DECISION-MAKING IN HEALTH...ijdms
This paper describes the technology of data warehouse in healthcare decision-making and tools for support
of these technologies, which is used to cancer diseases. The healthcare executive managers and doctors
needs information about and insight into the existing health data, so as to make decision more efficiently
without interrupting the daily work of an On-Line Transaction Processing (OLTP) system. This is a
complex problem during the healthcare decision-making process. To solve this problem, the building a
healthcare data warehouse seems to be efficient. First in this paper we explain the concepts of the data
warehouse, On-Line Analysis Processing (OLAP). Changing the data in the data warehouse into a
multidimensional data cube is then shown. Finally, an application example is given to illustrate the use of
the healthcare data warehouse specific to cancer diseases developed in this study. The executive managers
and doctors can view data from more than one perspective with reduced query time, thus making decisions
faster and more comprehensive
The document discusses the importance of information governance (IG) in healthcare based on studies conducted by Cohasset Associates and AHIMA. It defines IG as an organization-wide framework for managing information throughout its lifecycle while supporting organizational strategy, operations, and regulatory requirements. The definition covers policy creation, information accountability and management, processes and controls, and the importance of investment. IG implementation means more rules and redundancy, but compliance, quality improvement, IT, and other departments should continue their existing functions and also complete IG tasks as needed.
The objective of our study is to focus on the basic concepts of the medical information systems used for the management of IT information taking place in a hospital center and to share the information in databases depending on its use [2]. Nowadays, many softwares exist for the management of information in a hospital. The professional applications are oriented towards invoicing and accounting, while our application focuses on the systems used in a hospital center such as system of medical services, accounting system, storage system, human resources system, and administrative system (Figure 1)... These systems are considered as subsystems which make up the global system [1]. Our hospital information system is based on different the subsystems for the management of: laboratory results, clinic, images, pharmalogical, and pathological results[8]... So, this rate of huge information must be handled by a database management system like SQL [4,5], and its concept must be detailed using a language like UML [6]. In addition, the graphical user interface (gui) [19] is essential to complete our work, by using the software Visual Basic [10, 11], in order to achieve our software the manipulation of data must have a calibration between the execution time and the amount of data storage[14,15,20]. Hence, the distribution of databases is done according to their rate of use is an encouraging solution
System Dynamics Modeling for IntellectualDisability Services.docxmabelf3
System Dynamics Modeling for Intellectual
Disability Services: A Case Studyjppi_342 112..119
Meri Duryan*,†, Dragan Nikolik‡, Godefridus van Merode§, and Leopold Curfs*,§
*Gouverneur Kremers Centrum; †University of Maastricht; ‡Maastricht School of Management; and §Maastricht University Medical
Center, Maastricht, the Netherlands
Abstract Organizations providing services to persons with intellectual disabilities (ID) are complex because of many interacting
stakeholders with often different and competing interests. The combination of increased consumer demand and diminished resources
makes organizational planning a challenge for the managers of such organizations. Such challenges are confounded by significant
demands for the optimization of resources and the goal to reduce expenses and to more effectively and efficiently use existing
resources while at the same time providing high quality services. The authors explore the possibilities of using “system dynamics
modelling” in organizational decision-making processes related to resource allocations. System dynamics suggests the application of
generic systems archetypes as a first step in interpreting complex situations in an organization. The authors illustrate the application
of this method via a case study in one provider organization in the Netherlands. The authors contend that such a modeling approach
can be used by the management of similar organizations serving people with ID as a tool to support decision making that can result
in optimal resource allocation.
Keywords: allocation of resources, intellectual disabilities, system dynamics modeling, systems thinking, waiting lists
INTRODUCTION
Healthcare organizations are complex entities as they have
multiple stakeholders with often conflicting objectives and goals
(Drucker, 1993). Provider organizations specializing in intellec-
tual disabilities (ID) are also complex because of the nature of the
care and supports they provide and how they are organized. Some
of the complexities relate to the difficulties that adults with ID
might have in expressing themselves. Moreover, the specifics of
the care often require a deeper involvement of carers with respect
to their relationships with families and other sectors of society.
Because of their complexity, ID provider organizations, com-
pared with healthcare providers, often require a higher level of
resource planning, collaboration, and cooperation among social,
health, and education services, mental health services, and other
sectors (WHO, 2010).
To manage the complexities and challenges ID provider orga-
nizations face, managers need to analyze and understand complex
interdependencies among the systems with which they are dealing.
In order to achieve that, ID provider managers need to examine
and shift their mental models regarding their role in managing
the organization and in establishing relationships with all the
stakeholders involved. However, as Forrester (1980) has noted,
traditiona.
MULTI MODEL DATA MINING APPROACH FOR HEART FAILURE PREDICTIONIJDKP
Developing predictive modelling solutions for risk estimation is extremely challenging in health-care
informatics. Risk estimation involves integration of heterogeneous clinical sources having different
representation from different health-care provider making the task increasingly complex. Such sources are
typically voluminous, diverse, and significantly change over the time. Therefore, distributed and parallel
computing tools collectively termed big data tools are in need which can synthesize and assist the physician
to make right clinical decisions. In this work we propose multi-model predictive architecture, a novel
approach for combining the predictive ability of multiple models for better prediction accuracy. We
demonstrate the effectiveness and efficiency of the proposed work on data from Framingham Heart study.
Results show that the proposed multi-model predictive architecture is able to provide better accuracy than
best model approach. By modelling the error of predictive models we are able to choose sub set of models
which yields accurate results. More information was modelled into system by multi-level mining which has
resulted in enhanced predictive accuracy.
CLOUD COMPUTING71Dissertation Factors affecting the adoptWilheminaRossi174
This dissertation examines factors affecting the adoption of cloud computing in healthcare. Through a literature review and regression analysis, it identifies several key factors influencing healthcare organizations' decisions to adopt cloud computing. The analysis found that perceived benefits, risks, productivity, availability, and interoperability significantly impact adoption rates. These findings provide insights into improving cloud computing adoption in the healthcare industry.
The Human/Technology Adaptation Fit (HTAF) model focuses on the intersection of how users adapt technologies and how technologies adapt under contexts of voluntary or mandatory IT use. HTAF helps understand why certain phenomena occur in healthcare IT implementation and how this insight can benefit practitioners and administrators in attempting to understand the relationship between how well an IT fits an individual user's tasks and their willingness to adapt the technology or their behaviors. The model considers how social structures, individual tasks, and the relationship between users and healthcare technologies can enhance effective healthcare information systems that meet the needs of various stakeholders.
IRJET- A Survey on Big Data Frameworks and Approaches in Health Care SectorIRJET Journal
This document discusses how big data frameworks and approaches can benefit the healthcare sector. It first introduces common big data tools like Hadoop, MapReduce, and Apache Sqoop that can be used to analyze large amounts of healthcare data from sources like electronic health records. It then discusses how data warehouse platforms like OpenEHR and EHR4CR can be used to store this healthcare data. The document proposes a framework to retrieve and analyze electronic health records using big data systems. Potential applications of this approach mentioned include improved healthcare analysis, prognosis, report management, and follow-up systems. In conclusion, the integration of big data technologies with healthcare data platforms and sources can provide benefits like personalized care, disease prediction, and support for clinical decision
Este documento presenta una actualización sobre el Modelado Multinivel de la Información en Salud (MLHIM). Describe los retos actuales y futuros de la informática en salud, incluyendo el Big Data y la salud móvil. Explica cómo los estándares tradicionales no están preparados para estos nuevos retos y propone el modelado multinivel como una solución. Detalla las especificaciones MLHIM, incluyendo el Modelo de Referencia minimalista implementado en XML Schema y los Modelos de Dominio para modelar el conocimiento clínico.
AeHIN 28 August, 2014 - Innovation in Healthcare IT Standards: The Path to Bi...Timothy Cook
This document discusses myths and facts about big data in healthcare and proposes an innovation in healthcare IT standards called Multilevel Healthcare Information Modeling (MLHIM) to address some limitations of traditional standards. MLHIM uses XML schemas rather than ADL to define clinical concept constraints in a bottom-up way. This allows for multiple definitions of a concept and makes the standards more adaptable to big data. Tools are being developed to generate, edit, and work with MLHIM clinical models to facilitate reliable big data collection and interchange.
Prof. Luciana Tricai Cavalini, MD, PhD. presents the Multi-Level Healthcare Information Modelling specifications for Third International Symposium on Foundations of Health Information Engineering and Systems (FHIES) 2013 conference. There is also a video on YouTube http://goo.gl/9QPW5x
It is based on the paper: "Use of XML Schema Definition for the Development of Semantically Interoperable Healthcare Applications" to be published in an upcoming issue of Springer LNCS.
Presentation at the Escola Regional de Computação Aplicada à SaúdeTimothy Cook
O documento discute a complexidade do sistema de saúde e os desafios da informatização no setor. A saúde é mais complexa do que outros setores devido a três dimensões: espaço, tempo e ontologia. Isso torna difícil a interoperabilidade semântica entre sistemas. Padrões como HL7 e normas da ISO tentam resolver esses problemas, mas a alta dinâmica do conhecimento médico dificulta a padronização.
Poster presented at the 2nd ACM International Health Informatics Symposium SIGHIT in 2012
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Poster presented at the 2nd ACM International Health Informatics Symposium SIGHIT in 2012
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Poster presented at the 2nd ACM International Health Informatics Symposium SIGHIT in 2012
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Poster presented at the XIII Brazilian Congress of Health Informatics -2012.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Dr. Luciana Cavalini's presentation at the XI Workshop on Medical Informatics in 2012.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Presentation at the 14th International Conference on e-Health Networking - Application and Services in 2012 .
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
1) O documento discute a modelagem de conceitos clínicos e psicológicos relacionados ao diagnóstico de demências para auxiliar no diagnóstico médico computadorizado.
2) É apresentada uma revisão sistemática da literatura sobre testes neurológicos utilizados no diagnóstico de suspeita de demência em atenção primária.
3) O teste Free and Cued Selective Reminding é destacado e seus componentes são modelados em arquétipos segundo as especificações do framework openEHR para modelagem de sistemas
Este documento apresenta uma estratégia de modelagem do conhecimento de enfermagem baseada na modelagem multinível de sistemas de informação em saúde. Através de uma revisão sistemática, instrumentos de coleta de dados da área de enfermagem foram obtidos e o modelo de Fehring para débito cardíaco reduzido foi selecionado para modelagem. Os conceitos clínicos deste modelo foram mapeados para arquétipos openEHR e modelados como Constraint Definition Designs de acordo com as especificações MLHIM.
MSc. Timothy Cook's presentation at the 1st Workshop on Scientific Computing Applications in Health - 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Presentation WSCHA 2010 - in portugueseTimothy Cook
O documento discute os desafios da modelagem de sistemas de informação em saúde devido à complexidade do sistema de saúde e propõe a abordagem da modelagem multinível como uma solução mais eficiente, na qual o conhecimento do domínio é modelado separadamente da implementação do software por meio de arquétipos.
Presentation at the 1st Workshop on Scientific Computing Applications in Health - 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Presentation Minicourse for Summer Program LNCC 2010Timothy Cook
Presentation of the Minicourse for Summer Program at the National Laboratory for Scientific Computing - LNCC - in 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Dr. Luciana Cavalini's presentation at the 6th meeting of the Brazilian Python Community in 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
Poster presented at the 13th International Congress on Medical Informatics - MEDINFO - in 2010.
See: http://www.mlhim.org http://gplus.to/MLHIM and http://gplus.to/MLHIMComm for more information about semantic interoperability in healthcare.
#mlhim #semantic_interoperability #health_informatics
1. Developing future-proof open source information systems for
healthcare
Abstract. Healthcare information is full of context. The current design
approach to healthcare information systems (HIS) doesn't provide a facility to
transfer that context when the data is exchanged with other systems. This
paper aims to review the scientific literature regarding success and failures in
HIS implementation and integration projects and to present the fundamentals
of the development of a future-proof HIS, the Open Source Health Information
Platform (OSHIP).
1. Introduction
It has long been recognized that there is an inherent need for full semantic
interoperability between information systems that are used to manage healthcare
information [Lopez and Blobel 2009], [Hovenga 2008], [Ma et al. 2007], [Engel et al.
2006], [Nykanen and Karimaa 2006], [Rossi Mori and Consorti 1998]. Thus, in the
broadest sense, a Healthcare Information System (HIS) is any information system that
maintains and manages information affecting the health of a person or population
[Wikimedia Foundation, Inc. 2009].
Healthcare information has many complex temporal and spatial components and
then mix in the fact that medical and healthcare knowledge changes rapidly. It is widely
accepted that not only the medical condition of a person is significant to their health but
a host of social, economic and environmental conditions place direct and indirect effects
on personal and population health [Ghosh 2007], [Norgall et al. 2006], [Ruland and
Bakken 2001], [Starr and Starr 1995]. This is the crux of why HIS re so complex and
typically 'purpose-built' without any real interoperability built into them.
While the science of information design encompasses much more than
computerized information systems, the aim of this paper is discussing the
computerization of healthcare information. Expressed in its simplest terms, the current
approach to developing an information system follows these steps: (a) requirements
gathering, using one or more of the many standard methodologies; (b) systems analysis,
in order to determine from the requirements the systems involved to meet the needs of
the requirements; (c) data modeling, which means building a model of the data elements
available from the information sources (systems) to meet the needs of the requirements;
(d) implementation of the data model in some persistent storage facility; (e)
implementation of the software required to add, edit and manage the storage and use of
the data elements defined in the model; and (f) maintenance of the system then entails
modifying the data model and the software as the requirements change. This process has
proven robust and reliable over many years and millions of software applications being
deployed when sound software engineering principles are adhered to in the entire
process [Covitz et al. 2003], [Xu et al. 2001], [Kanoui et al. 2000].
Looking into how typical applications handle the information management
aspect a bit more, we see how an application like this actually manages information. We
see that the data elements are discretely persisted and the software and/or data
management layer manages the relationships between these data elements.
2. Data elements are simply data elements. It is their relationship to each other and
their relationship to the user, via input and output design in each application, which
gives them their semantic context in order to create information from their existence
[Schuurman and Leszczynski 2008], [Rector et al. 2002], [Degoulet et al. 1998]. As an
example of the data versus information conundrum, let us say that we have a data
element of the integer 102. That integer can represent a systolic blood pressure
measurement, a heart rate, a body temperature, and so on. The validity, reliability and
clinical significance of this data element necessarily depends upon the context (that
includes, e.g., units of measurement, patient position, point of measurement, device
used, demographic data from the patient, etc.).
There are certain elements of a database management system that lend to this
context, but this feature is a part of the software layer, not the actual persistence of the
data. While it is often conceived that table names and column names in, for example,
SQL databases, provide this functionality, it is important to consider situations when the
data needs to be exchanged with an application that uses a hierarchical or object or
XML database. In this case, there is no standard way to do this translation. In fact, even
between applications based on SQL databases, the migration of data must be performed
on a case-by-case basis where the table and column names are not the same and a
custom translation must be built for every case [Huang et al. 2005], [Stitt 1995].
Certainly the development of standardized HL7 messages was a big leap
forward in information exchange in healthcare [Tracy and Dougherty 2002], [Hettinger
and Brazile 1994]. Two big drawbacks to this approach are that the message formats
had to be made very generic in order to accommodate systems that may or may not have
all of the data elements in a specific message and this exchange process requires a
manual mapping on both the sending and receiving ends for each message to their local
database. An entire industry developed around providing these mapping engines and the
expertise to setup the complex mapping routines. Even if the development of the
message formats were defined by domain experts, the mapping is typically performed
by software experts, not clinicians [Hiroi et al. 2007], [Lin et al. 2006], [Ma et al.
2005], [McDonald et al. 2003], [Kinsey et al. 2000], [Ma 1995].
It is important to highlight that information should be universally available
inside the healthcare sector, from professionals at the point of care up to
epidemiologists, policy makers and economists [Hartz and John 2009], [Iglehart 2004].
Nevertheless, the immense amount of standardized data sets built into applications
published on literature are almost entirely made based on the interests of specific
research projects [Elisa and Heimar 2006], [Tierney et al. 2006], [Innes et al. 2001],
[Studnicki et al. 2001]. It is not possible for every healthcare application to incorporate
all the “minimum data sets” being requested by these competing interests. Even if it
happened, the real semantic context of collected data that results in information is in the
software of the original application, not in the data itself [Mead, 2006].
Completely controlled environments like the U.S. Veterans Administration and
Kaiser-Permanente have demonstrated that a centrally controlled approach to HIS
development and management using current approaches does work and does reduce
adverse events as well as improve access to patient information at the point of care
[Protti and Groen 2008], [Raymond 2005]. The evidence exists that interoperable HIS
are a benefit to those organizations as well as to their patient population [Brennan et al.
2008]. However, even in countries with nationalized healthcare services it is still a
challenge to mandate a common data set for all HIS that meets the needs of all
3. healthcare information users [Halamka et al. 2005], [Suselj and Cuber 1998]. So, we
believe that what is needed is a new way of thinking about complex information
systems. The objective of this paper is to present an implementation of an information
model that addresses those challenges in healthcare information.
2. Method
As an analogy, the idea of Lego® blocks is suggested. A box of these blocks contains
various sizes and shapes of components designed to work together to form objects. The
kit comes with instructions so that a certain sub-group of the blocks can be used to build
a specific object (e.g., a truck). Some of those same blocks can be used in combination
with additional ones, to build another specific object (e.g., a helicopter) according to a
different set of instructions. There are other instructions to build various other objects
all based on the same set of common blocks, all according to the restrictions described
in the instructions.
In healthcare information, we define a Common Reference Model (CRM) as the
common set of healthcare information blocks implemented in software that represent
clinical concepts as an information instance, and the instructions about the
representation of each clinical concept, as Clinical Knowledge Model (CKM).
If the CRM is abstract enough then it could be implemented in any object-
oriented language on any hardware platform. It therefore provides the freedom of use
and creativity to meet the needs and desires of application developers. The CKM units
(instructions) can be described by the domain experts for each concept because they
exist as constraint descriptions of the very broad based CRM, not existing in software
themselves, but simply informing the software about what they are representing. In fact,
the CKM units describe themselves completely with their entire semantic context. Since
they exist as data instances and not lines of software code, they can be exchanged with
other applications based on the CRM without any loss of semantics, and be persisted in
any type of data management system. CKM units can also be queried with a
standardized query language so that even the queries only have to be built one time,
since the data structure is standardized. Additionally, for every change either of the
healthcare science or management, a new version of a specific CKM unit can be
adapted from the existing version, with no need to change the software nor is there any
loss to the semantic integrity of the existing data.
The openEHR specifications are designed following those principles, and it has
been proven in multiple programming languages using multiple persistence layers and
hardware platforms, and also provides definitions for service and support layers in order
to allow the development of real healthcare applications [Beale and Heard 2007].
The Open Source Health Information Platform (OSHIP) is the reference
implementation of the openEHR specifications release 1.0.2 in Python language,
heavily dependent on the Zope Component Architecture (ZCA) version 3.4.x. It is a
library combined with other open source components designed to facilitate the creation
of interoperable healthcare applications. The persistence (storage) layer is completely
independent of the reference model and component libraries. Any type of database can
be used, such as object database or any SQL databases, but a native Python object
database such as the Zope Object Database (ZODB) provides transparent object
persistence, which eliminates the issues of mapping objects to SQL tables. OSHIP itself
4. uses the ZODB for the Archetype Server and Terminology Server. The current status of
development of the project can be found on http://launchpad.net/oship.
3. Conclusions
The approach for designing HIS here presented requires the adoption of a new way of
thinking, but not letting go of sound software engineering principles. In fact, this
approach enforces the sound principles of separation of software and data. Of course
high quality, rapidly delivered information is needed by healthcare decision makers; but
the mainstream approach on this matter leads to wasted time and effort and even poor
quality results due to a lack of interoperability across applications causing
misinterpretation of existing data. The context currently lies in the software, where it
can’t be exchanged. There is a need to return it to the data, where it belongs.
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