Pub Date : 2014-10-15DOI: 10.1109/HealthCom.2014.7001856
Chonlatee Khorakhun, S. Bhatti
We propose the use of an open and publicly accessible online social media platform (OSMP) as a key component for ubiquitous and personal remote health monitoring. Remote monitoring is an essential part of future mHealth systems for the delivery of personal healthcare allowing the collection of personal bio-data outside clinical environments. Previous mHealth projects focused on building private and custom platforms using closed architectures, which have a high cost for implementation, take a long time to develop, and may provide limited access and usability. By exploiting existing and publicly accessible infrastructure using an OSMP, initial costs can be reduced, at the same time as allowing fast and flexible application development at scale, whilst presenting users with interfaces and interactions that they are familiar with. We survey and discuss suitability of OSMPs in terms of functionality, performance and the key challenge in ensuring appropriate levels of security and privacy.
{"title":"Using online social media platforms for ubiquitous, personal health monitoring","authors":"Chonlatee Khorakhun, S. Bhatti","doi":"10.1109/HealthCom.2014.7001856","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001856","url":null,"abstract":"We propose the use of an open and publicly accessible online social media platform (OSMP) as a key component for ubiquitous and personal remote health monitoring. Remote monitoring is an essential part of future mHealth systems for the delivery of personal healthcare allowing the collection of personal bio-data outside clinical environments. Previous mHealth projects focused on building private and custom platforms using closed architectures, which have a high cost for implementation, take a long time to develop, and may provide limited access and usability. By exploiting existing and publicly accessible infrastructure using an OSMP, initial costs can be reduced, at the same time as allowing fast and flexible application development at scale, whilst presenting users with interfaces and interactions that they are familiar with. We survey and discuss suitability of OSMPs in terms of functionality, performance and the key challenge in ensuring appropriate levels of security and privacy.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133430598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001897
A. M. Fonseca, Edgar T. Horta, S. Sendra, J. Rodrigues, J. Moutinho
The sudden infant death syndrome (SIDS) is an expert diagnosis when an apparently healthy baby dies without explanation. When physicians or coroners cannot explain the cause of death it is classified as sudden death. This paper reviews the related literature and proposes a mobile solution based on biofeedback monitoring that tries to prevent the sudden death in infants. The sudden death system uses real-time data collection from sensors to diagnose, in advance, baby health problems and prevent those are take care for a baby. When an issue is detected by this system (i.e., the sensors send abnormal data), it sends a warning to those responsible for the baby. It allows the access to data from sensors and their analysis in real-time (such as, the baby position and the crib). Signal processing algorithms are used in real-time to prevent a sudden death. Mobile devices (such as, smartphones or tablets) are used to process the sensed data and monitoring a baby performing alerts/warnings when an abnormal situation is detected. The proposed approach is evaluated and demonstrated through a prototype.
{"title":"A sudden infant death prevention system for babies","authors":"A. M. Fonseca, Edgar T. Horta, S. Sendra, J. Rodrigues, J. Moutinho","doi":"10.1109/HealthCom.2014.7001897","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001897","url":null,"abstract":"The sudden infant death syndrome (SIDS) is an expert diagnosis when an apparently healthy baby dies without explanation. When physicians or coroners cannot explain the cause of death it is classified as sudden death. This paper reviews the related literature and proposes a mobile solution based on biofeedback monitoring that tries to prevent the sudden death in infants. The sudden death system uses real-time data collection from sensors to diagnose, in advance, baby health problems and prevent those are take care for a baby. When an issue is detected by this system (i.e., the sensors send abnormal data), it sends a warning to those responsible for the baby. It allows the access to data from sensors and their analysis in real-time (such as, the baby position and the crib). Signal processing algorithms are used in real-time to prevent a sudden death. Mobile devices (such as, smartphones or tablets) are used to process the sensed data and monitoring a baby performing alerts/warnings when an abnormal situation is detected. The proposed approach is evaluated and demonstrated through a prototype.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115168123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001858
Andreas Kliem, Anett Bölke, Anne Grohnert, N. Traeder
E-Health systems need to dynamically integrate a huge variety of medical sensors in order to provide a meaningful survey of a patient's condition. Devices like smart phones or gateways usually used as integrators, often underlie resource constraints and have to cope with the mobility of the patient. Therefore it is difficult to realize an overall integration middleware, that allows to handle a sufficient amount of medical sensors and is able to quickly adapt to changing requirements (e.g. new sensors or data aggregation modules) while preserving mobility and resource constraints. We present a middleware solution for the integration of medical devices and the aggregation of resulting data streams, that is able to adapt itself to the requirements of patients and Care Delivery Operators, using a modular approach and external knowledge repositories. Knowledge in the shape of configurations and runtime pluggable software modules is used to properly integrate and handle discovered medical devices on demand.
{"title":"Self-adaptive middleware for ubiquitous medical device integration","authors":"Andreas Kliem, Anett Bölke, Anne Grohnert, N. Traeder","doi":"10.1109/HealthCom.2014.7001858","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001858","url":null,"abstract":"E-Health systems need to dynamically integrate a huge variety of medical sensors in order to provide a meaningful survey of a patient's condition. Devices like smart phones or gateways usually used as integrators, often underlie resource constraints and have to cope with the mobility of the patient. Therefore it is difficult to realize an overall integration middleware, that allows to handle a sufficient amount of medical sensors and is able to quickly adapt to changing requirements (e.g. new sensors or data aggregation modules) while preserving mobility and resource constraints. We present a middleware solution for the integration of medical devices and the aggregation of resulting data streams, that is able to adapt itself to the requirements of patients and Care Delivery Operators, using a modular approach and external knowledge repositories. Knowledge in the shape of configurations and runtime pluggable software modules is used to properly integrate and handle discovered medical devices on demand.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123330330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001827
D. Welfer, Renato Cassol Ferreira da Silva, J. Kazienko
This demonstration aims at presenting the MobiCAP prototype. MobiCAP is a mobile application system for management of Community-Acquired Pneumonia (CAP). The system supports experienced end beginner physicians to deal with the CAP's diagnosis process problem. Thus, MobiCAP enables physicians to handle a high amount of variables and take a quick and precise diagnosis based on rules described by the internal guidelines previously established by hospital physicians. MobiCAP was designed and developed in conjunction with specialist physicians from the Hospital Nossa Senhora da Conceicao (HNSC)-placed in Porto Alegre city-and based on HNSC internal guidelines for diagnosis and management of the CAP. The system was written in the Objective-C language using a development approach called Model View Controller (MVC). The application was implemented to run on the iOS platform, more specifically under iPhone type devices. As programming environment, it was used the Xcode 5.0.2 for the overall development of the application. In summary, three graphical interfaces correspond to the core functionality of the application, namely: (a) a graphical user interface for the risk stratification of pneumonia; (b) a graphical interface for the algorithm treatment; and (c) a graphical interface to the treatment according to etiology.
本演示旨在展示MobiCAP原型。MobiCAP是一个社区获得性肺炎(CAP)管理的移动应用系统。该系统支持有经验的初级医生处理CAP的诊断过程问题。因此，MobiCAP使医生能够处理大量变量，并根据医院医生先前建立的内部指南所描述的规则进行快速准确的诊断。MobiCAP是与位于阿雷格里港市的Nossa Senhora da Conceicao医院(HNSC)的专家医生共同设计和开发的，并基于HNSC诊断和管理CAP的内部指南。该系统使用Objective-C语言编写，使用一种称为模型-视图-控制器(MVC)的开发方法。该应用程序是在iOS平台上运行的，更具体地说，是在iPhone类型的设备上运行的。作为编程环境，使用Xcode 5.0.2进行应用程序的整体开发。综上所述，三个图形界面对应于应用程序的核心功能，即:(a)肺炎风险分层的图形用户界面;(b)算法处理的图形界面;(c)根据病因进行治疗的图形界面。
{"title":"MobiCAP: A mobile application prototype for management of community-acquired pneumonia","authors":"D. Welfer, Renato Cassol Ferreira da Silva, J. Kazienko","doi":"10.1109/HealthCom.2014.7001827","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001827","url":null,"abstract":"This demonstration aims at presenting the MobiCAP prototype. MobiCAP is a mobile application system for management of Community-Acquired Pneumonia (CAP). The system supports experienced end beginner physicians to deal with the CAP's diagnosis process problem. Thus, MobiCAP enables physicians to handle a high amount of variables and take a quick and precise diagnosis based on rules described by the internal guidelines previously established by hospital physicians. MobiCAP was designed and developed in conjunction with specialist physicians from the Hospital Nossa Senhora da Conceicao (HNSC)-placed in Porto Alegre city-and based on HNSC internal guidelines for diagnosis and management of the CAP. The system was written in the Objective-C language using a development approach called Model View Controller (MVC). The application was implemented to run on the iOS platform, more specifically under iPhone type devices. As programming environment, it was used the Xcode 5.0.2 for the overall development of the application. In summary, three graphical interfaces correspond to the core functionality of the application, namely: (a) a graphical user interface for the risk stratification of pneumonia; (b) a graphical interface for the algorithm treatment; and (c) a graphical interface to the treatment according to etiology.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126952420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001819
P. Swiatek, Pawel Stelmach, Lukasz Falas, Patryk Schauer
Delivery of e-health services is the main subject of multiple research projects carried on among others by national institutions, international consortia both in industry and academia. The goal of on-going research is to develop an efficient, scalable, flexible and multipurpose networking platform allowing for delivery of personalized, composable and high quality e-health services for various types of healthcare applications. This paper describes the ComSS Platform, which aims to achieve this goal, and the SmartFit application built with the use of ComSS Platform. This paper also discusses encountered problems, which stand in the way of fully automated composition of e-Health services based on Internet of Things paradigm. Finally, this paper also proposes a preliminary metamodel for description of Internet of Things enabled devices' capabilities, interfaces, services and data streams. This metamodel is intended to support the process of automated composition of streaming services.
{"title":"Enabling automatic composition of stream processing services through ontology-based standardization","authors":"P. Swiatek, Pawel Stelmach, Lukasz Falas, Patryk Schauer","doi":"10.1109/HealthCom.2014.7001819","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001819","url":null,"abstract":"Delivery of e-health services is the main subject of multiple research projects carried on among others by national institutions, international consortia both in industry and academia. The goal of on-going research is to develop an efficient, scalable, flexible and multipurpose networking platform allowing for delivery of personalized, composable and high quality e-health services for various types of healthcare applications. This paper describes the ComSS Platform, which aims to achieve this goal, and the SmartFit application built with the use of ComSS Platform. This paper also discusses encountered problems, which stand in the way of fully automated composition of e-Health services based on Internet of Things paradigm. Finally, this paper also proposes a preliminary metamodel for description of Internet of Things enabled devices' capabilities, interfaces, services and data streams. This metamodel is intended to support the process of automated composition of streaming services.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116401863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001854
E. Ferreira, H. Rausch, S. Campos, A. Faria-Campos, Enio Pietra, Lílian Silva dos Santos
Data mining applied to medical databases is a challenging process. The unavailability of large sources of data and data complexity are some of the difficulties encountered. This is especially true for rare and neglected diseases. Those databases are, in general, relatively small, wide and sparse, making them very challenging to analyze. There are also ethical, legal and social issues regarding privacy and clinical validation of the findings. This work proposes a way of dealing with this challenge with a case study of data mining applied in a Paracoccidioidomycosis (PCM) patients database. Paracoccidioidomycosis (PCM) is a typical Brazilian disease, caused by the yeast Paracoccidioides brasiliensis. This disease represents an important Public Health issue, due to its high incapacitating potential and the amount of premature deaths it causes if untreated. This paper discusses methods for the analysis of this complex dataset, to help increase the understanding of both the disease and this type of data. Despite the challenges of the dataset, some interesting findings were made being: flaws in form filling protocols, notably the lack of chest X-ray in 40% of the records; the discovery of a possible new relation between smoking habits and PCM evolution time. The average evolution time for smoking patients was 2.8 times longer; the successful classification/prediction of the cutaneous form of the disease with a 93% precision rate are some of the discoveries made.
{"title":"Medical data mining: A case study of a Paracoccidioidomycosis patient's database","authors":"E. Ferreira, H. Rausch, S. Campos, A. Faria-Campos, Enio Pietra, Lílian Silva dos Santos","doi":"10.1109/HealthCom.2014.7001854","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001854","url":null,"abstract":"Data mining applied to medical databases is a challenging process. The unavailability of large sources of data and data complexity are some of the difficulties encountered. This is especially true for rare and neglected diseases. Those databases are, in general, relatively small, wide and sparse, making them very challenging to analyze. There are also ethical, legal and social issues regarding privacy and clinical validation of the findings. This work proposes a way of dealing with this challenge with a case study of data mining applied in a Paracoccidioidomycosis (PCM) patients database. Paracoccidioidomycosis (PCM) is a typical Brazilian disease, caused by the yeast Paracoccidioides brasiliensis. This disease represents an important Public Health issue, due to its high incapacitating potential and the amount of premature deaths it causes if untreated. This paper discusses methods for the analysis of this complex dataset, to help increase the understanding of both the disease and this type of data. Despite the challenges of the dataset, some interesting findings were made being: flaws in form filling protocols, notably the lack of chest X-ray in 40% of the records; the discovery of a possible new relation between smoking habits and PCM evolution time. The average evolution time for smoking patients was 2.8 times longer; the successful classification/prediction of the cutaneous form of the disease with a 93% precision rate are some of the discoveries made.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121874773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001842
Mauro Oliveira, L. O. M. Andrade, Marcos Santos, Roberto Alcantra, Germanno Teles, N. Agoulmine
During the last decade, several ICT systems have been proposed to fulfill the needs of managing individuals' physical activities at home. Unfortunately, most of the developed products have been so far expensive and could not be afforded by the large majority of the population, especially in underdeveloped countries. Therefore, developing a low-cost system accessible to large portion of population in these countries or even in developed ones (Classes D and E) is still necessary. This paper presents a prototype called Diga-Saúde which proposes to develop a low-cost system using mobile phones and the Brazilian set-top box (stb) receptor for digital TV to provide home care services. Diga-Saúde is part of a larger project called LARIISA, a governance supporting framework for public health systems centered on the family.
{"title":"Towards a cost-effective homecare for a public health management system in Brazil","authors":"Mauro Oliveira, L. O. M. Andrade, Marcos Santos, Roberto Alcantra, Germanno Teles, N. Agoulmine","doi":"10.1109/HealthCom.2014.7001842","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001842","url":null,"abstract":"During the last decade, several ICT systems have been proposed to fulfill the needs of managing individuals' physical activities at home. Unfortunately, most of the developed products have been so far expensive and could not be afforded by the large majority of the population, especially in underdeveloped countries. Therefore, developing a low-cost system accessible to large portion of population in these countries or even in developed ones (Classes D and E) is still necessary. This paper presents a prototype called Diga-Saúde which proposes to develop a low-cost system using mobile phones and the Brazilian set-top box (stb) receptor for digital TV to provide home care services. Diga-Saúde is part of a larger project called LARIISA, a governance supporting framework for public health systems centered on the family.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129740309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001894
Raghid El-Yafouri, L. Klieb
The aim of this research is to explore the motives behind the adoption or rejection of Electronic Health Records (EHR) systems in the USA by medical offices. The current health care system in the United States suffers from high expenditures and poor quality. The Patient Protection and Affordable Care Act, passed in 2010, attempts to save costs and improve quality of care by offering incentives to use Electronic Health Records systems. Part of the reform by this law is dependent on the use of technology in managing patient medical and health records. The objective is to reduce redundancy and increase quality by sharing medical information amongst different health organizations like hospitals, physician offices, laboratories and clinical institutions. The success of such reform requires the participation and collaboration of all these entities and their patients. Prior research shows that adoption of Electronic Medical Records systems by hospitals and physician offices has been evident but at a rate that is slower than in other countries. Aside from financial barriers, technical, psychological, social/legal and organizational barriers exist. In order to understand the impact of those barriers on the adoption of Electronic Health Records management by small physician offices better, a five-level adoption model is presented to define the stages of diffusion of EHR systems. Fifteen consolidated barriers are mapped to each adoption level. This research concentrates on smaller physician offices because hospitals and larger institutions are more ready and capable of adoption, according to previous research. The Diffusion of Technology Model by Rogers, the Theory of Planned Behavior by Ajzen and Fishbein, and Davis' Technology Acceptance Model are combined and extended. This model will be used to empirically measure physicians' attitudes, knowledge, social and legal influences, subjective norm and systems' ease of use and usefulness amongst other variables. These variables are applied as mediators or moderators of the intention and decision to adopt or move into subsequent levels of adoption with the goal of seeing what drives those decisions.
本研究的目的是探讨美国医疗机构采用或拒绝电子健康记录(EHR)系统背后的动机。美国目前的医疗保健系统存在高支出和低质量的问题。2010年通过的《患者保护和平价医疗法案》(Patient Protection and Affordable Care Act)试图通过鼓励使用电子健康记录系统来节省成本，提高医疗质量。这项法律的部分改革取决于在管理病人医疗和健康记录方面使用技术。目标是通过在医院、医生办公室、实验室和临床机构等不同卫生组织之间共享医疗信息来减少冗余并提高质量。这种改革的成功需要所有这些实体及其病人的参与和合作。先前的研究表明，医院和医生办公室采用电子医疗记录系统已经很明显，但速度比其他国家慢。除了财务障碍外，还存在技术、心理、社会/法律和组织方面的障碍。为了更好地了解这些障碍对小型医生办公室采用电子病历管理的影响，本文提出了一个五层采用模型来定义电子病历系统的扩散阶段。将15个整合障碍映射到每个采用级别。根据之前的研究，这项研究主要集中在小型医生办公室，因为医院和大型机构更有准备和能力采用。罗杰斯的技术扩散模型、Ajzen和Fishbein的计划行为理论以及Davis的技术接受模型进行了结合和扩展。该模型将用于实证测量医生的态度，知识，社会和法律的影响，主观规范和系统的易用性和有用性等变量。这些变量被用作意图和决定采用或进入后续采用级别的中介或调节者，目的是查看驱动这些决策的因素。
{"title":"Electronic medical records adoption and use: Understanding the barriers and the levels of adoption for physicians in the USA","authors":"Raghid El-Yafouri, L. Klieb","doi":"10.1109/HealthCom.2014.7001894","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001894","url":null,"abstract":"The aim of this research is to explore the motives behind the adoption or rejection of Electronic Health Records (EHR) systems in the USA by medical offices. The current health care system in the United States suffers from high expenditures and poor quality. The Patient Protection and Affordable Care Act, passed in 2010, attempts to save costs and improve quality of care by offering incentives to use Electronic Health Records systems. Part of the reform by this law is dependent on the use of technology in managing patient medical and health records. The objective is to reduce redundancy and increase quality by sharing medical information amongst different health organizations like hospitals, physician offices, laboratories and clinical institutions. The success of such reform requires the participation and collaboration of all these entities and their patients. Prior research shows that adoption of Electronic Medical Records systems by hospitals and physician offices has been evident but at a rate that is slower than in other countries. Aside from financial barriers, technical, psychological, social/legal and organizational barriers exist. In order to understand the impact of those barriers on the adoption of Electronic Health Records management by small physician offices better, a five-level adoption model is presented to define the stages of diffusion of EHR systems. Fifteen consolidated barriers are mapped to each adoption level. This research concentrates on smaller physician offices because hospitals and larger institutions are more ready and capable of adoption, according to previous research. The Diffusion of Technology Model by Rogers, the Theory of Planned Behavior by Ajzen and Fishbein, and Davis' Technology Acceptance Model are combined and extended. This model will be used to empirically measure physicians' attitudes, knowledge, social and legal influences, subjective norm and systems' ease of use and usefulness amongst other variables. These variables are applied as mediators or moderators of the intention and decision to adopt or move into subsequent levels of adoption with the goal of seeing what drives those decisions.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124254560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/HEALTHCOM.2014.7001884
Nicholas R. Smith, Teekayu Klongtruagrok, G. DeSouza, C. Shyu, Maria Dietrich, M. Page
Voice disorders are non-trivial when it comes to their early detection. Symptoms range from slight hoarseness to complete loss of voice, and may seriously impact personal and professional life. To date, we are still largely missing reliable data to help us better understand and screen voice pathologies. In this paper, we present an ambulatory voice monitoring system using surface electromyography (sEMG) and a robust algorithm for pattern recognition of vocal gestures. The system, which can process up to four sEMG channels simultaneously, also can store large amounts of data (up to 13 hours of continuous use) and in the future will be used to analyze on-the-fly various patterns of sEMG activation in the search for maladaptive laryngeal activity that may lead to voice disorders. In the preliminary results presented here, our pattern recognition algorithm (Hierarchical GUSSS) detected six different sEMG patterns of activation, and it achieved 90% accuracy.
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Pub Date : 2014-10-01DOI: 10.1109/HealthCom.2014.7001810
Diana Costa, M. Martins
In this paper we focus in health care knowledge, specified by hybrid formulas, representing flows of medical assistance in the care delivery process in a hospital. As in standard knowledgebases inconsistencies may arise. In fact, Medical Informatics is one field where the ability to reason with inconsistent information is crucial. Patients can receive different, and moreover contradictory, diagnoses from different physicians, and the same can happen with medical treatments: they can exhibit contradictory symptoms. We introduce a paraconsistent version of multimodal hybrid logic to help with this medical issue, specially through the diagnosis.
{"title":"Inconsistencies in health care knowledge","authors":"Diana Costa, M. Martins","doi":"10.1109/HealthCom.2014.7001810","DOIUrl":"https://doi.org/10.1109/HealthCom.2014.7001810","url":null,"abstract":"In this paper we focus in health care knowledge, specified by hybrid formulas, representing flows of medical assistance in the care delivery process in a hospital. As in standard knowledgebases inconsistencies may arise. In fact, Medical Informatics is one field where the ability to reason with inconsistent information is crucial. Patients can receive different, and moreover contradictory, diagnoses from different physicians, and the same can happen with medical treatments: they can exhibit contradictory symptoms. We introduce a paraconsistent version of multimodal hybrid logic to help with this medical issue, specially through the diagnosis.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125643079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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