A talk given at the Software Engineering for Health Care workshop at ICSE 2010 (Cape Town). Reviews privacy and security issues for social networking in the health care domain, covers some existing work, and points out future directions.
Integration of Bayesian Theory and Association Rule Mining in Predicting User...Editor IJCATR
Bayesian theory and association rule mining methods are artificial intelligence techniques that have been used in various computing fields, especially in machine learning. Internet has been considered as an easy ground for vices like radicalization because of its diverse nature and ease of information access. These vices could be managed using recommender systems methods which are used to deliver users’ preference data based on their previous interests and in relation with the community around the user. The recommender systems are divided into two broad categories, i.e. collaborative systems which considers users which share the same preferences as the user in question and content-based recommender systems tends to recommend websites similar to those already liked by the user. Recent research and information from security organs indicate that, online radicalization has been growing at an alarming rate. The paper reviews in depth what has been carried out in recommender systems and looks at how these methods could be combined to from a strong system to monitor and manage online menace as a result of radicalization. The relationship between different websites and the trend from continuous access of these websites forms the basis for probabilistic reasoning in understanding the users’ behavior. Association rule mining method has been widely used in recommender systems in profiling and generating users’ preferences. To add probabilistic reasoning considering internet magnitude and more so in social media, Bayesian theory is incorporated. Combination of this two techniques provides better analysis of the results thereby adding reliability and knowledge to the results.
Crowdsource Application A Pragmatic Approach for Participation in Healthcare...Ayesha Saeed
Retrieval and management of Web data is now a complex problem, due to huge amount of information, variety of the information sources, data formats, and developing expectations of users. Crowdsourcing is an online problem solving paradigm that is used to tap the intelligence of the crowd. This research covers the idea that the medical paradigm is leaving the traditional doctor-patient relationship and adopting the patient-patient relationship. Physician centered model is evolving towards a new de-centralized model where patients are given more responsibility for their health.
This document discusses privacy-enhanced personalization by balancing user privacy and personalized experiences online. It summarizes research showing that contextual explanations of privacy practices and personalization benefits lead users to disclose more information and have more positive perceptions of websites. While privacy-enhancing technologies can help, interaction design is also important. User trust, understanding, and control play a key role in finding the right balance between privacy and personalization. More research is still needed on factors like website reputation and the visibility of privacy information.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
Mit anonymous dtpss_module 4_google health and microsoft health_vault launch (4)Enrique Mesones
Google Health and Microsoft HealthVault aimed to allow users to store and manage their personal health records online. However, both ventures ultimately failed due to a lack of adoption from several key groups. Users found the platforms cumbersome and not addressing basic needs. Health organizations were unwilling to share data due to legal and competitive concerns. Societally, issues of data privacy and lack of an established legal framework for health information sharing contributed to distrust in the platforms.
Mit wiroon dtpss_module 4_google health and ms health_vault launch (wiroon)Enrique Mesones
The document discusses issues that contributed to the failure of Google Health and Microsoft HealthVault from both the user/consumer side and the partner/health organization side. On the consumer side, key issues included lack of usefulness, privacy concerns, usability problems, and expectations not being met. On the partner side, issues were a lack of standardization among health institutions and difficulties with authorization and sharing information between partners.
Mit dtpss module 4_google health and microsoft health_vault launchEnrique Mesones
Both Google Health and Microsoft HealthVault aimed to organize personal health information online but failed to gain widespread adoption. Key issues included lack of trust in Google and Microsoft's ability to keep data private and secure, failure to integrate data from various sources, and lack of telehealth services to sync online records with virtual consultations. This scattered health data risks duplicate tests, procedural costs, and information gaps that could impact medicine and society.
Big data is more than just a buzzword in healthcare. It's the promise of being able to extract, cull, and interpret medical data to directly benefit population and individual health. learn more about the benefits of big data, roadblocks to leveraging it's potential, how Meaningful Use enablesbig data, what types of cross-country collaboration projects are advancing the use of big data on an international scale, big data's impact on patient privacy and much more! Special thanks to Mandi Bishop for her time on the podcast.
Integration of Bayesian Theory and Association Rule Mining in Predicting User...Editor IJCATR
Bayesian theory and association rule mining methods are artificial intelligence techniques that have been used in various computing fields, especially in machine learning. Internet has been considered as an easy ground for vices like radicalization because of its diverse nature and ease of information access. These vices could be managed using recommender systems methods which are used to deliver users’ preference data based on their previous interests and in relation with the community around the user. The recommender systems are divided into two broad categories, i.e. collaborative systems which considers users which share the same preferences as the user in question and content-based recommender systems tends to recommend websites similar to those already liked by the user. Recent research and information from security organs indicate that, online radicalization has been growing at an alarming rate. The paper reviews in depth what has been carried out in recommender systems and looks at how these methods could be combined to from a strong system to monitor and manage online menace as a result of radicalization. The relationship between different websites and the trend from continuous access of these websites forms the basis for probabilistic reasoning in understanding the users’ behavior. Association rule mining method has been widely used in recommender systems in profiling and generating users’ preferences. To add probabilistic reasoning considering internet magnitude and more so in social media, Bayesian theory is incorporated. Combination of this two techniques provides better analysis of the results thereby adding reliability and knowledge to the results.
Crowdsource Application A Pragmatic Approach for Participation in Healthcare...Ayesha Saeed
Retrieval and management of Web data is now a complex problem, due to huge amount of information, variety of the information sources, data formats, and developing expectations of users. Crowdsourcing is an online problem solving paradigm that is used to tap the intelligence of the crowd. This research covers the idea that the medical paradigm is leaving the traditional doctor-patient relationship and adopting the patient-patient relationship. Physician centered model is evolving towards a new de-centralized model where patients are given more responsibility for their health.
This document discusses privacy-enhanced personalization by balancing user privacy and personalized experiences online. It summarizes research showing that contextual explanations of privacy practices and personalization benefits lead users to disclose more information and have more positive perceptions of websites. While privacy-enhancing technologies can help, interaction design is also important. User trust, understanding, and control play a key role in finding the right balance between privacy and personalization. More research is still needed on factors like website reputation and the visibility of privacy information.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
Mit anonymous dtpss_module 4_google health and microsoft health_vault launch (4)Enrique Mesones
Google Health and Microsoft HealthVault aimed to allow users to store and manage their personal health records online. However, both ventures ultimately failed due to a lack of adoption from several key groups. Users found the platforms cumbersome and not addressing basic needs. Health organizations were unwilling to share data due to legal and competitive concerns. Societally, issues of data privacy and lack of an established legal framework for health information sharing contributed to distrust in the platforms.
Mit wiroon dtpss_module 4_google health and ms health_vault launch (wiroon)Enrique Mesones
The document discusses issues that contributed to the failure of Google Health and Microsoft HealthVault from both the user/consumer side and the partner/health organization side. On the consumer side, key issues included lack of usefulness, privacy concerns, usability problems, and expectations not being met. On the partner side, issues were a lack of standardization among health institutions and difficulties with authorization and sharing information between partners.
Mit dtpss module 4_google health and microsoft health_vault launchEnrique Mesones
Both Google Health and Microsoft HealthVault aimed to organize personal health information online but failed to gain widespread adoption. Key issues included lack of trust in Google and Microsoft's ability to keep data private and secure, failure to integrate data from various sources, and lack of telehealth services to sync online records with virtual consultations. This scattered health data risks duplicate tests, procedural costs, and information gaps that could impact medicine and society.
Big data is more than just a buzzword in healthcare. It's the promise of being able to extract, cull, and interpret medical data to directly benefit population and individual health. learn more about the benefits of big data, roadblocks to leveraging it's potential, how Meaningful Use enablesbig data, what types of cross-country collaboration projects are advancing the use of big data on an international scale, big data's impact on patient privacy and much more! Special thanks to Mandi Bishop for her time on the podcast.
Presentation by Megan Douglas, JD for the Third Annual Policy Prescriptions® Symposium
She is the associate director of Health Information Technology Policy in the National Center for Primary Care at Morehouse School of Medicine.
The symposium is designed for clinicians, healthcare workers, and healthcare executives interested in exploring the major themes that will emerge in health policy throughout the year. This year, the symposium will emphasize value in healthcare, health information technology, gun violence, insurance choices, the Affordable Care Act, and the viewpoints of the Presidential candidates on health care.
Digital Health: Medicine at the CroosroadsSteven Peskin
This document discusses the implications of mobile health and social media in clinical practice. It describes the three components of digital health as applications, devices, and infrastructure. Mobile technologies and social media have tremendous potential to improve care delivery, patient safety, information dissemination, and chronic disease management. The document outlines how physician communities on social media can facilitate knowledge sharing and discusses the growth of medical apps. It predicts that mobile health and social media will become integrated into everyday healthcare through digital tools and communities.
HIMSS GSA e-Authentication whitepaper June 2007Richard Moore
HIMSS and the GSA, developed a pilot project to demonstrate the adoption of the GSA's secure and interoperable technical architecture for sharing medical information across multiple healthcare providers. The pilot utilized the GSA's E-Authentication Service Component program to provide digital certificates, technical architecture development support, and certificate validation services.
Seven RHIOs/Health Information Exchanges initially volunteered to participate in the project. One participant the Nevada Single Portal Medical Record HIE had to withdraw from the project due to a lack of resources.
Central Ohio HIE - Initiated by eHealth Ohio, and in conjunction with the Ohio Supercomputer Center, this project has focused on evaluating the viability of using the proposed national level user authentication process as a means of authenticating individual researchers, system developers and system administrators who will be both utilizing, creating and maintaining future health care research systems. An emerging area of software development focus, this pilot will also identify key issues faced by resource constrained development efforts.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
A SMART WIZARD SYSTEM SUITABLE FOR USE WITH INTERNET MOBILE DEVICES TO ADJUST...ijsptm
The privacy of personal information is an important issue affecting the confidence of internet users. The
widespread adoption of online social networks and access to these platforms using mobile devices has
encouraged developers to make the systems and interfaces acceptable to users who seek privacy. The aim
of this study is to test a wizard that allows users to control the sharing of personal information with others.
We also assess the concerns of users in terms of such sharing such as whether to hide personal data in
current online social network accounts. Survey results showed the wizard worked very well and that
females concealed more personal information than did males. In addition, most users who were concerned
about misuse of personal information hid those items. The results can be used to upgrade current privacy
systems or to design new systems that work on mobile internet devices. The system can also be used to save
time when setting personal privacy settings and makes users more aware of items that will be shared with
others.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
This document summarizes a presentation on how the User Managed Access (UMA) standard addresses challenges in health information interoperability and user control. It discusses how current health systems have data silos and lack of user access to their own health records. UMA allows for interoperability across services/data sources through a centralized authorization server. It enables user-directed delegation so others can access data on a user's behalf. Case studies demonstrate implementations like Trustee that use UMA to create a self-sovereign universal health record. Another case study discusses Ontario's FPX which uses UMA and standards for identity, authentication, and access in health care.
Social media in healthcare 2012 moore mb for the lancet 7 12-12Mike Moore
This document discusses social media in healthcare in 2012. It provides an overview of key concepts like web 2.0 and social media. It examines the landscape, demographics, and sociology of social media use in 2012, including for healthcare. Key examples of current and future healthcare uses are described, such as patients finding others with similar health concerns online or tracking health indicators. The document also looks at social media demographics for healthcare in 2012 and trends in how providers, patients, and payers are using public and private social media.
Mobile health is an ever expanding field, and shows great promise for delivering care to remote patients. In this presentation at the ATA 2012 conference, Dr. Robert Ciulla demonstrates the potential for mHealth to improve care availability and how T2 is supporting that goal.
The challenges and benefits of implementing and using personal health and car...Patients Know Best
This document discusses the challenges and benefits of implementing personal health records from the perspectives of suppliers, clinicians, and patients. It outlines how current systems fragment patient information across different providers and exclude patients from their own information. A patient-controlled integrated digital care record is proposed as a solution to integrate information and put patients in control by allowing them to share their health information with whoever they choose through granular consent options. Benefits include coordinated care through secure sharing, improved communication, remote management of care plans and test results, and collaborative care planning. The document provides examples of how Patients Know Best software enables these features and has been adopted widely in the UK and other countries.
This document provides an overview of social networks and media and how the ABA's Division of Media Relations and Communication Services can utilize social media platforms. It defines social networks and media and discusses key differences from traditional media. It then outlines the reach and usage of various social media platforms like Facebook, YouTube and Twitter. The document recommends developing a social media policy and utilizing platforms like Facebook pages, YouTube videos and Twitter to communicate ABA news, events and position the ABA as a legal expert resource for reporters, lawyers and the public.
Policy resolution of shared data in online social networks IJECEIAES
Online social networks have practically a go-to source for information divulging, social exchanges and finding new friends. The popularity of such sites is so profound that they are widely used by people belonging to different age groups and various regions. Widespread use of such sites has given rise to privacy and security issues. This paper proposes a set of rules to be incorporated to safeguard the privacy policies of related users while sharing information and other forms of media online. The proposed access control network takes into account the content sensitivity and confidence level of the accessor to resolve the conflicting privacy policies of the co-owners.
Opening Keynote: The Convergence of mHealth: A Consumer and Clinical Perspective
Description: In the opening keynote attendees will hear an overview from a current HIMSS mHealth Community Member which sets the stage for discussion. The keynote will highlight facts and figures which support the thesis of increased utilization of mobile and wireless technologies by healthcare providers. The keynote will also set the stage with current issues impacting the continued adoption.
Speaker(s): Ahmed Albaiti
Objectives: Assess the current landscape of mHealth. Illustrate the roles of consumers and patients. Define the current issues.
Direct Boot Camp 2 0 Federal Agency requirements for exchange via directBrian Ahier
The FHA Directed Exchange Workgroup provides updates on efforts to increase the adoption of Direct for health information exchange between federal agencies and non-federal entities. They are educating federal partners on Direct technology and policies, developing common understanding of use cases and security requirements, and identifying baseline documents and FAQs. Establishing a common federal Direct policy would greatly increase its adoption for information exchange. Focused workgroups address Directed exchange, security, and interoperability issues. Risks to Directed exchange between agencies are being identified and recommendations will be provided to ONC.
The document proposes an architecture and process for nationwide patient-centric consent management. It discusses the need for improved electronic consent management given the limitations of paper-based consent. The proposed approach uses an internet-based consent service that stores a patient's consent preferences in one place and can provide the most current preferences to any record holder. This allows patients to manage consent in a centralized way without needing to interact directly with each individual record holder. The proposed architecture aims to balance the needs of patients, providers, and other stakeholders to enable greater data sharing while respecting patient privacy preferences.
Implications for risk management of digital health technologiesDavid Lee Scher, MD
Digital health technology is becoming a critical part of healthcare. As tools used in care (directly and indirectly), it has implications with regards to risk management. These are discussed from both liability and mitigation perspectives.
External hackers pose a major threat to healthcare data. The most common methods of attack are employee phishing (40%) and vendor compromise (28%), which can allow hackers to access networks and steal sensitive patient data like social security numbers. Once stolen, this data is often sold on the black market and used for medical identity theft and fraudulent billing. A data breach can cost organizations $398 per stolen record and damage their reputation, leading to increased scrutiny and loss of new patients. Healthcare providers can help protect data by vetting vendors, training employees, implementing authentication measures, and backing up important files.
Intelligent access control policies for Social network siteijcsit
This document describes a proposed system for intelligent access control policies for social network sites. It aims to automatically construct access control rules for users' privacy settings with minimal effort from the user. The system extracts features from users' profiles and community structures. It then uses decision tree learning to classify users and predict their access to different data items. The resulting rules are stored in an access control ontology along with existing rules. This allows fine-grained access control policies to be defined and enforced based on relationships and information in the social network ontology.
this presentation is helpful for all health professionals who are providing care. it show how to use and where to use social media. and what are the advantage and dis advantage of use of social media.
This document discusses various methods and tools for collecting, processing, and analyzing nursing data and information. It describes different sources of information like libraries, databases, and search engines. It also discusses ethical issues around copyright and fair use. Common data collection methods in nursing include questionnaires, interviews, and electronic documentation. Quantitative data is analyzed statistically while qualitative data requires identifying themes. Cohort and case-control studies are described as common research designs.
Presentation by Megan Douglas, JD for the Third Annual Policy Prescriptions® Symposium
She is the associate director of Health Information Technology Policy in the National Center for Primary Care at Morehouse School of Medicine.
The symposium is designed for clinicians, healthcare workers, and healthcare executives interested in exploring the major themes that will emerge in health policy throughout the year. This year, the symposium will emphasize value in healthcare, health information technology, gun violence, insurance choices, the Affordable Care Act, and the viewpoints of the Presidential candidates on health care.
Digital Health: Medicine at the CroosroadsSteven Peskin
This document discusses the implications of mobile health and social media in clinical practice. It describes the three components of digital health as applications, devices, and infrastructure. Mobile technologies and social media have tremendous potential to improve care delivery, patient safety, information dissemination, and chronic disease management. The document outlines how physician communities on social media can facilitate knowledge sharing and discusses the growth of medical apps. It predicts that mobile health and social media will become integrated into everyday healthcare through digital tools and communities.
HIMSS GSA e-Authentication whitepaper June 2007Richard Moore
HIMSS and the GSA, developed a pilot project to demonstrate the adoption of the GSA's secure and interoperable technical architecture for sharing medical information across multiple healthcare providers. The pilot utilized the GSA's E-Authentication Service Component program to provide digital certificates, technical architecture development support, and certificate validation services.
Seven RHIOs/Health Information Exchanges initially volunteered to participate in the project. One participant the Nevada Single Portal Medical Record HIE had to withdraw from the project due to a lack of resources.
Central Ohio HIE - Initiated by eHealth Ohio, and in conjunction with the Ohio Supercomputer Center, this project has focused on evaluating the viability of using the proposed national level user authentication process as a means of authenticating individual researchers, system developers and system administrators who will be both utilizing, creating and maintaining future health care research systems. An emerging area of software development focus, this pilot will also identify key issues faced by resource constrained development efforts.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
A SMART WIZARD SYSTEM SUITABLE FOR USE WITH INTERNET MOBILE DEVICES TO ADJUST...ijsptm
The privacy of personal information is an important issue affecting the confidence of internet users. The
widespread adoption of online social networks and access to these platforms using mobile devices has
encouraged developers to make the systems and interfaces acceptable to users who seek privacy. The aim
of this study is to test a wizard that allows users to control the sharing of personal information with others.
We also assess the concerns of users in terms of such sharing such as whether to hide personal data in
current online social network accounts. Survey results showed the wizard worked very well and that
females concealed more personal information than did males. In addition, most users who were concerned
about misuse of personal information hid those items. The results can be used to upgrade current privacy
systems or to design new systems that work on mobile internet devices. The system can also be used to save
time when setting personal privacy settings and makes users more aware of items that will be shared with
others.
Part of the "2016 Annual Conference: Big Data, Health Law, and Bioethics" held at Harvard Law School on May 6, 2016.
This conference aimed to: (1) identify the various ways in which law and ethics intersect with the use of big data in health care and health research, particularly in the United States; (2) understand the way U.S. law (and potentially other legal systems) currently promotes or stands as an obstacle to these potential uses; (3) determine what might be learned from the legal and ethical treatment of uses of big data in other sectors and countries; and (4) examine potential solutions (industry best practices, common law, legislative, executive, domestic and international) for better use of big data in health care and health research in the U.S.
The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School 2016 annual conference was organized in collaboration with the Berkman Center for Internet & Society at Harvard University and the Health Ethics and Policy Lab, University of Zurich.
Learn more at http://petrieflom.law.harvard.edu/events/details/2016-annual-conference.
This document summarizes a presentation on how the User Managed Access (UMA) standard addresses challenges in health information interoperability and user control. It discusses how current health systems have data silos and lack of user access to their own health records. UMA allows for interoperability across services/data sources through a centralized authorization server. It enables user-directed delegation so others can access data on a user's behalf. Case studies demonstrate implementations like Trustee that use UMA to create a self-sovereign universal health record. Another case study discusses Ontario's FPX which uses UMA and standards for identity, authentication, and access in health care.
Social media in healthcare 2012 moore mb for the lancet 7 12-12Mike Moore
This document discusses social media in healthcare in 2012. It provides an overview of key concepts like web 2.0 and social media. It examines the landscape, demographics, and sociology of social media use in 2012, including for healthcare. Key examples of current and future healthcare uses are described, such as patients finding others with similar health concerns online or tracking health indicators. The document also looks at social media demographics for healthcare in 2012 and trends in how providers, patients, and payers are using public and private social media.
Mobile health is an ever expanding field, and shows great promise for delivering care to remote patients. In this presentation at the ATA 2012 conference, Dr. Robert Ciulla demonstrates the potential for mHealth to improve care availability and how T2 is supporting that goal.
The challenges and benefits of implementing and using personal health and car...Patients Know Best
This document discusses the challenges and benefits of implementing personal health records from the perspectives of suppliers, clinicians, and patients. It outlines how current systems fragment patient information across different providers and exclude patients from their own information. A patient-controlled integrated digital care record is proposed as a solution to integrate information and put patients in control by allowing them to share their health information with whoever they choose through granular consent options. Benefits include coordinated care through secure sharing, improved communication, remote management of care plans and test results, and collaborative care planning. The document provides examples of how Patients Know Best software enables these features and has been adopted widely in the UK and other countries.
This document provides an overview of social networks and media and how the ABA's Division of Media Relations and Communication Services can utilize social media platforms. It defines social networks and media and discusses key differences from traditional media. It then outlines the reach and usage of various social media platforms like Facebook, YouTube and Twitter. The document recommends developing a social media policy and utilizing platforms like Facebook pages, YouTube videos and Twitter to communicate ABA news, events and position the ABA as a legal expert resource for reporters, lawyers and the public.
Policy resolution of shared data in online social networks IJECEIAES
Online social networks have practically a go-to source for information divulging, social exchanges and finding new friends. The popularity of such sites is so profound that they are widely used by people belonging to different age groups and various regions. Widespread use of such sites has given rise to privacy and security issues. This paper proposes a set of rules to be incorporated to safeguard the privacy policies of related users while sharing information and other forms of media online. The proposed access control network takes into account the content sensitivity and confidence level of the accessor to resolve the conflicting privacy policies of the co-owners.
Opening Keynote: The Convergence of mHealth: A Consumer and Clinical Perspective
Description: In the opening keynote attendees will hear an overview from a current HIMSS mHealth Community Member which sets the stage for discussion. The keynote will highlight facts and figures which support the thesis of increased utilization of mobile and wireless technologies by healthcare providers. The keynote will also set the stage with current issues impacting the continued adoption.
Speaker(s): Ahmed Albaiti
Objectives: Assess the current landscape of mHealth. Illustrate the roles of consumers and patients. Define the current issues.
Direct Boot Camp 2 0 Federal Agency requirements for exchange via directBrian Ahier
The FHA Directed Exchange Workgroup provides updates on efforts to increase the adoption of Direct for health information exchange between federal agencies and non-federal entities. They are educating federal partners on Direct technology and policies, developing common understanding of use cases and security requirements, and identifying baseline documents and FAQs. Establishing a common federal Direct policy would greatly increase its adoption for information exchange. Focused workgroups address Directed exchange, security, and interoperability issues. Risks to Directed exchange between agencies are being identified and recommendations will be provided to ONC.
The document proposes an architecture and process for nationwide patient-centric consent management. It discusses the need for improved electronic consent management given the limitations of paper-based consent. The proposed approach uses an internet-based consent service that stores a patient's consent preferences in one place and can provide the most current preferences to any record holder. This allows patients to manage consent in a centralized way without needing to interact directly with each individual record holder. The proposed architecture aims to balance the needs of patients, providers, and other stakeholders to enable greater data sharing while respecting patient privacy preferences.
Implications for risk management of digital health technologiesDavid Lee Scher, MD
Digital health technology is becoming a critical part of healthcare. As tools used in care (directly and indirectly), it has implications with regards to risk management. These are discussed from both liability and mitigation perspectives.
External hackers pose a major threat to healthcare data. The most common methods of attack are employee phishing (40%) and vendor compromise (28%), which can allow hackers to access networks and steal sensitive patient data like social security numbers. Once stolen, this data is often sold on the black market and used for medical identity theft and fraudulent billing. A data breach can cost organizations $398 per stolen record and damage their reputation, leading to increased scrutiny and loss of new patients. Healthcare providers can help protect data by vetting vendors, training employees, implementing authentication measures, and backing up important files.
Intelligent access control policies for Social network siteijcsit
This document describes a proposed system for intelligent access control policies for social network sites. It aims to automatically construct access control rules for users' privacy settings with minimal effort from the user. The system extracts features from users' profiles and community structures. It then uses decision tree learning to classify users and predict their access to different data items. The resulting rules are stored in an access control ontology along with existing rules. This allows fine-grained access control policies to be defined and enforced based on relationships and information in the social network ontology.
this presentation is helpful for all health professionals who are providing care. it show how to use and where to use social media. and what are the advantage and dis advantage of use of social media.
This document discusses various methods and tools for collecting, processing, and analyzing nursing data and information. It describes different sources of information like libraries, databases, and search engines. It also discusses ethical issues around copyright and fair use. Common data collection methods in nursing include questionnaires, interviews, and electronic documentation. Quantitative data is analyzed statistically while qualitative data requires identifying themes. Cohort and case-control studies are described as common research designs.
The document discusses ethical and social issues related to information systems in business. It covers topics like ethics in information system design and use, identifying and addressing ethical issues, examples of organizations violating ethics, and the relationship between society, information systems, and business. The document also provides examples of how businesses can address ethical concerns through codes of conduct, clear policies, transparency, and decision-making frameworks. Additionally, it discusses social issues such as privacy, responsibility, isolation, and how businesses can contribute to sustainability and social causes through responsible use of information systems.
The document discusses challenges with information sharing across health and social care systems in the UK, including different data formats, lack of integration, and lack of trust. It describes a project by Symphonic Software to deliver a governance layer for the London Digital Programme, which aims to allow the 7,000 organizations involved in patient care in London to access patient records while meeting data controller agreements and patient consent preferences. The governance layer will provide policy translation, identity management, and automated generation of information sharing policies to improve integrated care.
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Social Networks in Health Care - Talk at ICSE 2010
1. Social Networking in Health
Care
Towards secure, privacy-preserving systems
James Williams,
BA, BSc, JD,
Privacy Officer, Ontario Telemedicine Network.
PhD candidate, University of Victoria.
2. Goal
This presentation is an introduction to an
understudied area in health informatics. We will
address the following issues:
1. What are social networking applications for
health care?
2. What unique security and privacy issues
exist?
3. What techniques can address them?
4. What remains to be done?
3. OUTLINE
Background
•Basics of Social Networking (SN) applications.
•Social Networking for Health Care
•Examples
Security/Privacy Issues
•Issues with SN apps in general.
•Unique features of the healthcare domain.
•Current work.
Future work.
4. Basics of Social Networking
The social web
•The term ‘Web 2.0’ has been used to refer to
internet architectures that permit content to be easily
generated and published by users
•Users are enabled to act both as readers and
writers, generating content and creating a visible
history of their activities.
•Key notions include:
•interpersonal networking,
•personalization
•individualism
•empowerment
5. Basics of Social Networking
Online networks
•First generation web applications like bulletin boards
allowed users to communicate and collaborate.
•Social networking (SN) applications expand upon
Web 1.0 apps by:
•providing a persistent, explicit and publically
visible representation of social networks.
•providing a variety of mechanisms by which
users may organize themselves. (ie: groups)
•incorporating privacy protection.
6. Basics of Social Networks
A social network involves:
1. A set of users, represented by individual user
profiles.
2. A set of mechanisms for exchanging
information, such as message boards, email,
and wall posts.
3. A set of binary relationship types.
4. A set of search functions, to locate user
profiles.
5. A site operator, who controls the site.
•A social network is naturally represented as a
dynamic graph in which an edge between two
8. Social Networks in Health
Care
Rationale
‘Healthcare 2.0’ has been used to denote the use of
social software, with an emphasis on its ability to
promote collaboration between patients, caregivers
and medical professionals.
Patient empowerment may be a critical factor in
achieving sustainability of the health care system.
•Traditionally, the physician-patient relationship has
exhibited a degree of information asymmetry.
•SNAHC systems emphasize collaboration and
independence.
•User communities are springing up around ailments.
•Active management may make patients more health
conscious.
9. Social Networks in Health
Care
Differences
In the case of health care, we have more than one
type of user:
•Patients
•Providers
•Care givers
•Support staff
•Family members
•Substitute decision makers.
10. Social Networks in Health
Care
Examples: PHRs.
Basic social networking features are found in
personal health record (PHR) systems, including
Google Health, Microsoft HealthVault, and Dossia.
Google Health:
•Allows users to store/manage PHI, including medical
conditions, allergies and medication histories.
•Users can search for information about medical
conditions or adverse drug interactions.
•Information in the health record can be shared.
Users invite others to view their profile through email.
11.
12. Social Networks in Health
Care
Examples
Microsoft Healthvault:
•Platform that provides basic services for PHR and
social networking products.
•Vendors can build customized products on top of it.
•Each individual owns his or her record.
•Others can be granted access to it, if desired.
•The mapping between records to users is many-
many, allowing for substitute decision makers and
other scenarios.
13.
14. Social Networks in Health
Care
Examples
Healthy Circles
•Patients can store emergency contacts, insurance
plans, medications, immunizations, past procedures,
test results, medical conditions, allergies and family
histories
•Users can enter basic health metrics and view
reports.
•Programs are interactive applications that typically
require users to enter personal information in order
to provide diagnoses or recommend treatment
regimens or health management strategies.
•users can purchase consultation or monitoring
services from registered health care providers
15. Social Networks in Health
Care
Examples
Patients Like Me
•Patients can store a wide array of information.
•The site operator encourages users to share as
much information as possible.
•Pharmaceutical companies are partners, using the
site as a repository for voluntarily contributed data on
outcomes.
•Uses a more advanced social networking model.
16.
17. Security / Privacy Issues in
SN
Awareness of Risk:
Empirical studies show that users:
•do value informational privacy.
•typically do not change default settings.
•are inclined to disclose information freely online.
•often restrict their information only after
breaches have occurred.
•Users may lack a method for assessing risks in
social networks. Social cues are missing.
•They may also be unaware of the mechanisms for
reducing risk.
18. Security / Privacy Issues in
SN
Ease of Network Formation:
•An individual’s online social network tends to be
more expansive, (containing more weak ties), than
the same individual’s offline network
•users often misjudge the extent, activity and
accessibility of their online social networks
Complex Workflows:
•In general, social networking applications offer
complex, many-to-many communications
mechanisms.
•The workflows are not easy to grasp, which makes
19. Security / Privacy Issues in
SN
Trust:
•Attackers may create fake profiles, and site
operators may not follow their privacy policies.
•Trust is a ‘social glue’ in a SN system.
Data Lifecycle:
•Users have little knowledge about retention periods,
backups, and the like.
•Information posted on a SN may have ramifications
for the user.
20. Security / Privacy Issues in
SN
Unauthorized Uses and Disclosures:
•Site operators may use or disclose the data.
•As an example, SN operators report increased
demands for bulk data from governments.
Leakage to Applications:
•Applications typically draw data from the system in
order to deliver personalized experiences.
•In many early architectures, they could retrieve quite
a lot of information, including information about one’s
friends.
21. Security / Privacy Issues in
SN
Aggregation by Third Parties:
•Third parties (ie: ad servers) can receive personal
information.
•Since 70% of the market is controlled by a small
number of firms, these companies are in a position to
aggregate data from various sources.
•Users typically are not aware that disclosures on
one site may be linked to disclosures on another site.
22. Security / Privacy Issues in
SN
Complex Privacy Policies:
•Because of the complex user scenarios, privacy
policies for SN systems tend to be complex.
•Studies indicate that some are inaccessible to users.
•Enforcement is more difficult. Unlike ecommerce, a
user may see another’s activities.
•Market lacks competition for comprehensible privacy
policies.
•There are few methods for negotiating policies on a
user’s behalf.
23. Security / Privacy Issues in
SN
Sunken Costs:
•In Ecommerce, it is fairly easy to switch service
providers.
•In SN settings, the costs associated with switching
providers are fairly severe.
•Users may stay with an insecure and non-private
system.
Shared Content:
•Shared content creates privacy risks for users, since
information may be linked to their profile without
consent or knowledge
24. Features of the Heath
Domain
Sensitivity of Information:
•Tends to be very high, and protected by law.
Motivated Data Recipients:
•Employers, insurers, researchers.
Secondary Damage:
•Since many serious health concerns are genetically
based, information about an individual can convey
information about a family member.
25. Features of the Heath
Domain
Community Interests:
•Individuals sharing information on health trends can,
if their submissions are aggregated, reveal
information about the health issues affecting groups.
Motivated Data Recipients:
•Employers, insurers, researchers.
Signaling:
•The mere act of making an inquiry about a condition
can be a signal that the individual in question has the
condition. The same is true of an individual’s
26. Features of the Heath
Domain
Compensability:
•Difficult to value PHI.
•Indemnification and compensation is much more
difficult.
Dynamic Networks:
•Health teams form around episodes.
•They are ephemeral.
27. What can we do (as software
engineers, developers and systems
architects) to alleviate some of these
issues?
28. Current Work
Securing the Framework
Restrict information flowing to apps:
•Privacy by Proxy.
•User-to-application policies.
New Access Models:
•‘proof’ to access particular resources.
•Social Access Control List.
• Walk through trusted nodes in the network
structure.
29. Current Work
Securing the Framework
Anonymizing Users
•Use encryption and various key exchange
mechanisms.
•FlybyNight: uses client side javascript.
•Respondent k-anonymity.
•Fake data.
•NOYB: map operations on fake data back to real
data. Avoid ciphertext. Replace values
pseudonoymously from a dictionary. Keys
distributed out of band. Only works for small # of
users.
•FaceCloak: another approach using dictionary
30. Current Work
Dealing with Extracts
•Social network data can be extracted for processing
or data mining.
•Attacker may have background information,
including knowledge of certain properties of the
network.
•Most of the techniques are based on anonymization.
•Tabular algorithms don’t work well with network
data.
•Need to know privacy risk model, background
knowledge, and intended use of data.
•Two camps:
1. Clustering based.
31. Future Work
Improved Privacy Controls:
•Current social network applications allow the
construction of hierarchies, including groups.
•We need efficient, concise and usable controls for
this.
•Taking advantage of automation or group
knowledge:
•Agents
•Automatically assigning trust to users/resources.
•Heuristics (weighting), voting, reputation
mechanisms.
•Better user interfaces for privacy control
32. Future Work
Network Visualization Tools:
•Some of the uncertainty surrounding privacy risks
could be dispelled if users were able to visualize their
networks.
• To this end, user interfaces for displaying a user’s
profile accessibility would be highly useful
•increase the utilization of privacy options by clear
representations of social networks, friend proximity,
and availability of profile features.
33. Future Work
Detecting Attacks:
•Future software architectures for health care could
include facilities to discourage or detect common
attacks.
•For instance, prototypes could be developed that
scan for fake user profiles
•Also, search functionality can serve as a form of
querying that can reveal both user identities and
protected user information.
•Find heuristic approaches for limiting queries.
34. Future Work
Security in the Architecture:
•We need to do further work on secure architectures,
along the lines of the efforts we have discussed
above.
•In particular, we should develop architectures that:
•Work for all users (not just a subset)
•Provide anonymity against the platform.
•Make it easy to exchange keys.
35. Future Work
Shared Content Management:
•We need mechanisms for assigning permissions to
shared content.
•This is particularly relevant in the health domain,
where secondary disclosures may cause information
to be revealed about the health of family members.
36. Future Work
Policy Negotiation and Representation:
•Continue the development of tools and languages
for representing policies.
•Many privacy policy tools were developed with a
single organization’s behaviour in mind. We also
need tools for data exchange.
•Methods for evaluating formal requirements in the
context of policies would be highly useful.