Some organizations use software applications to manage their customers’ personal, medical, or financial
information. In the United States, those software applications are obligated to preserve users’ privacy and
to comply with the United States federal privacy laws and regulations. To formally guarantee compliance
with those regulations, it is essential to extract and model the privacy rules from the text of the law using a
formal framework. In this work we propose a goal-oriented framework for modeling and extracting the
privacy requirements from regulatory text using natural language processing techniques.
Establishing CCPA Compliance in Legacy PeopleSoft SystemsAppsian
July 1st represented the beginning of enforcement for The California Consumer Privacy Act (CCPA.) This could not come at a worse time, as COVID-19 has created a myriad of new data security and compliance risks that are taxing already extended resources.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Establishing CCPA Compliance in Legacy PeopleSoft SystemsAppsian
July 1st represented the beginning of enforcement for The California Consumer Privacy Act (CCPA.) This could not come at a worse time, as COVID-19 has created a myriad of new data security and compliance risks that are taxing already extended resources.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Can domain intelligence help healthcare service providers combat data breachesWhoisXML API
The Anthem breach reported in February 2015, which exposed around 78.8 million customer records, is one of the biggest #databreach in the health care industry. This presentation outlines the case facts and prevention techniques to safeguard against such data compromise.
Health care providers have become prime targets of cyber criminals, since they hold a treasure trove of irresistible data, including Social Security numbers and medical records (think access to prescription painkillers). As cyber criminals become more sophisticated, medical practices are more vulnerable than ever.
In this webinar "Data Breach: It Can Happen To You," hosted by the Cooperative of American Physicians, Inc. (CAP), viewers will learn:
+ What a data breach is
+ Its economic impact
+ Why the threat is growing
+ Steps to take to protect yourself
+ The must-dos in the event of a breach
Watch the webinar here —> https://youtu.be/mqdMA-UZNy0
About Our Presenters:
Melvin Osswald, Vice President Program Underwriting, NAS Insurance — Ms. Osswald joined NAS in 2002 and specializes in health care, cyber liability, employment practice, directors and officers coverage. Ms. Osswald currently supports NAS’ reinsurance programs and oversees the underwriting and product development of Billing Errors and Omissions, Cyber Liability, Employment Practices Liability, and Directors and Officers programs created to address the new exposures facing health care providers. She has been featured as a guest speaker at various industry conferences addressing the evolving professional liability risks in health care, and served on the Steering Committee of the Southern California Chapter of the Professional Liability Underwriting Society.
Chris Reese, Vice President, Director of Underwriting, NAS Insurance — As part of NAS’ key management team, Ms. Reese provides insurance solutions for clients in the health care industry. She has held leadership positions on both the underwriting and retail broker sides of the business, and has worked in the London market for a reinsurance intermediary. Ms. Reese has been involved with cyber risk insurance for the health care industry since 2004, providing coverage to physicians, medical groups, and integrated delivery systems.
MORE SLIDESHARE PRESENTATIONS
http://www.slideshare.net/capphysicians/presentations
VISIT OUR WEBSITE
http://www.cappphysicians.com
LET'S CONNECT
Twitter: http://www.twitter.com/CAPphysicians
LinkedIn: https://www.linkedin.com/company/cooperative-of-american-physicians-inc-
Facebook: http://www.facebook.com/CooperativeofAmericanPhysiciansInc
Youtube: http://youtube.com/CAPphysicians
Google+: http://www.google.com/+Capphysicians
"Apple has prepared this report on the requests we receive from governments seeking information about individual users or devices in the interest of transparency for our customers around
the world." Nov, 2013
While the Health Insurance Portability and Accountability Act (HIPAA) is best known for its multitude of requirements that govern the way health care providers can use, disclose, and safeguard protected health information (PHI), its reach goes far beyond that to health plans and business associates that only handle PHI on a limited basis. HIPAA implementation in these environments creates unique challenges—for example, which provisions actually need to be addressed—but with 2016 marking an all-time high for HIPAA enforcement cases, it may be more important now than ever to address HIPAA compliance.
Company names mentioned herein are the property of, and may be trademarks of, their respective owners and are for educational purposes only.
17 U.S. Code § 107 - Limitations on exclusive rights: Fair use
Notwithstanding the provisions of sections 106 and 106A, the fair use of a copyrighted work, including such use by reproduction in copies or phonorecords or by any other means specified by that section, for purposes such as criticism, comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research, is not an infringement of copyright.
ELECTRONIC MEDICAL RECORD (EMR) SYSTEMS ARE BEING IMPLEMENTED INCREASINGLY WORLDWIDE. SAUDI
ARABIA IS ONE OF DEVELOPING COUNTRIES THAT COMMENCED IMPLEMENTING SUCH SYSTEMS IN 1988. WHILST
EMR UPTAKE HAS BEEN LOW IN SAUDI ARABIA UNTIL NOW, A NUMBER OF HOSPITALS HAVE IMPLEMENTED EMR
SYSTEMS SUCCESSFULLY. THIS PAPER ANALYSES AVAILABLE STUDIES (N=28) IN THE LITERATURE REGARDING EMR
IMPLEMENTATION IN SAUDI ARABIA TO IDENTIFY THE PROGRESS OF EMR IMPLEMENTATION TO DATE AND TO
IDENTIFY THE FACILITATORS AND BARRIERS TO IMPLEMENTATION.
Ranking the micro level critical factors of electronic medical records adopti...hiij
In many countries, the health care sector is entering into a time of unprecedented change. Electronic
Medical Record (EMR) has been introduced into healthcare organizations in order to incorporate better
use of technology, to aid decision making, and to facilitate the search for medical solution. This needs
those professionals in healthcare organizations to be in the process of changing from the use of paper to
maintain medical records into computerized medical recordkeeping opportunities. However, the adoption
of these electronic medical records systems has been slow throughout the healthcare field. The critical
users are physicians which play an important role to success of health information technology including
Electronic Medical Record systems. As a result user adoption is necessary in order to understand the
benefits of an EMR. Therefore, in the current paper, a model of ranking factors of micro-level in EMRs
adoption was developed. Surveys distributed to physicians as this study’s respondent in two private
hospitals in Malaysia. The findings indicate that physicians have a high perception means for the
technology and showed that EMR would increase physician’s performance regarding to decision making.
They have been and continue to be positively motivated to adopt and use the system. The relevant factors
according to micro-level perspective prioritized and ranked by using the Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS). The aim of ranking and using this approach is to
investigate which factors are more important in EMRs adoption from the micro-level perspectives. The
results of performing TOPSIS is as a novelty which assist health information systems (HIS) success and
also healthcare organizations to motivate their users in accepting of new technology.
Can domain intelligence help healthcare service providers combat data breachesWhoisXML API
The Anthem breach reported in February 2015, which exposed around 78.8 million customer records, is one of the biggest #databreach in the health care industry. This presentation outlines the case facts and prevention techniques to safeguard against such data compromise.
Health care providers have become prime targets of cyber criminals, since they hold a treasure trove of irresistible data, including Social Security numbers and medical records (think access to prescription painkillers). As cyber criminals become more sophisticated, medical practices are more vulnerable than ever.
In this webinar "Data Breach: It Can Happen To You," hosted by the Cooperative of American Physicians, Inc. (CAP), viewers will learn:
+ What a data breach is
+ Its economic impact
+ Why the threat is growing
+ Steps to take to protect yourself
+ The must-dos in the event of a breach
Watch the webinar here —> https://youtu.be/mqdMA-UZNy0
About Our Presenters:
Melvin Osswald, Vice President Program Underwriting, NAS Insurance — Ms. Osswald joined NAS in 2002 and specializes in health care, cyber liability, employment practice, directors and officers coverage. Ms. Osswald currently supports NAS’ reinsurance programs and oversees the underwriting and product development of Billing Errors and Omissions, Cyber Liability, Employment Practices Liability, and Directors and Officers programs created to address the new exposures facing health care providers. She has been featured as a guest speaker at various industry conferences addressing the evolving professional liability risks in health care, and served on the Steering Committee of the Southern California Chapter of the Professional Liability Underwriting Society.
Chris Reese, Vice President, Director of Underwriting, NAS Insurance — As part of NAS’ key management team, Ms. Reese provides insurance solutions for clients in the health care industry. She has held leadership positions on both the underwriting and retail broker sides of the business, and has worked in the London market for a reinsurance intermediary. Ms. Reese has been involved with cyber risk insurance for the health care industry since 2004, providing coverage to physicians, medical groups, and integrated delivery systems.
MORE SLIDESHARE PRESENTATIONS
http://www.slideshare.net/capphysicians/presentations
VISIT OUR WEBSITE
http://www.cappphysicians.com
LET'S CONNECT
Twitter: http://www.twitter.com/CAPphysicians
LinkedIn: https://www.linkedin.com/company/cooperative-of-american-physicians-inc-
Facebook: http://www.facebook.com/CooperativeofAmericanPhysiciansInc
Youtube: http://youtube.com/CAPphysicians
Google+: http://www.google.com/+Capphysicians
"Apple has prepared this report on the requests we receive from governments seeking information about individual users or devices in the interest of transparency for our customers around
the world." Nov, 2013
While the Health Insurance Portability and Accountability Act (HIPAA) is best known for its multitude of requirements that govern the way health care providers can use, disclose, and safeguard protected health information (PHI), its reach goes far beyond that to health plans and business associates that only handle PHI on a limited basis. HIPAA implementation in these environments creates unique challenges—for example, which provisions actually need to be addressed—but with 2016 marking an all-time high for HIPAA enforcement cases, it may be more important now than ever to address HIPAA compliance.
Company names mentioned herein are the property of, and may be trademarks of, their respective owners and are for educational purposes only.
17 U.S. Code § 107 - Limitations on exclusive rights: Fair use
Notwithstanding the provisions of sections 106 and 106A, the fair use of a copyrighted work, including such use by reproduction in copies or phonorecords or by any other means specified by that section, for purposes such as criticism, comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research, is not an infringement of copyright.
ELECTRONIC MEDICAL RECORD (EMR) SYSTEMS ARE BEING IMPLEMENTED INCREASINGLY WORLDWIDE. SAUDI
ARABIA IS ONE OF DEVELOPING COUNTRIES THAT COMMENCED IMPLEMENTING SUCH SYSTEMS IN 1988. WHILST
EMR UPTAKE HAS BEEN LOW IN SAUDI ARABIA UNTIL NOW, A NUMBER OF HOSPITALS HAVE IMPLEMENTED EMR
SYSTEMS SUCCESSFULLY. THIS PAPER ANALYSES AVAILABLE STUDIES (N=28) IN THE LITERATURE REGARDING EMR
IMPLEMENTATION IN SAUDI ARABIA TO IDENTIFY THE PROGRESS OF EMR IMPLEMENTATION TO DATE AND TO
IDENTIFY THE FACILITATORS AND BARRIERS TO IMPLEMENTATION.
Ranking the micro level critical factors of electronic medical records adopti...hiij
In many countries, the health care sector is entering into a time of unprecedented change. Electronic
Medical Record (EMR) has been introduced into healthcare organizations in order to incorporate better
use of technology, to aid decision making, and to facilitate the search for medical solution. This needs
those professionals in healthcare organizations to be in the process of changing from the use of paper to
maintain medical records into computerized medical recordkeeping opportunities. However, the adoption
of these electronic medical records systems has been slow throughout the healthcare field. The critical
users are physicians which play an important role to success of health information technology including
Electronic Medical Record systems. As a result user adoption is necessary in order to understand the
benefits of an EMR. Therefore, in the current paper, a model of ranking factors of micro-level in EMRs
adoption was developed. Surveys distributed to physicians as this study’s respondent in two private
hospitals in Malaysia. The findings indicate that physicians have a high perception means for the
technology and showed that EMR would increase physician’s performance regarding to decision making.
They have been and continue to be positively motivated to adopt and use the system. The relevant factors
according to micro-level perspective prioritized and ranked by using the Technique for Order of
Preference by Similarity to Ideal Solution (TOPSIS). The aim of ranking and using this approach is to
investigate which factors are more important in EMRs adoption from the micro-level perspectives. The
results of performing TOPSIS is as a novelty which assist health information systems (HIS) success and
also healthcare organizations to motivate their users in accepting of new technology.
Public Libraries News: How to produce a specialist news site in 2014Public Libraries News
Public Libraries News has become a key resource for those learning about the sector. This presentation shows how it uses Wordpress, Twitter, Facebook and Pinterest in varying ways to boost the message. It also looks at the strategy behind "PLN" including neutrality and news gathering.
This presentation is the basis for my talk to the Oxford University Press Advisory Council on Libraries, June 2014.
Describe one safeguard that should be in place to protect the confid.pdfmohammedfootwear
Describe one safeguard that should be in place to protect the confidentiality of health information
when a health care organization uses a home-based medical transcriptionist and one safeguard
that should be in place to protect the security of that health information.Please support your
answer with APA references.Thanks
Solution
This is a summary of key elements of the Security Rule including who is covered, what
information is protected, and what safeguards must be in place to ensure appropriate protection
of electronic protected health information. Because it is an overview of the Security Rule, it does
not address every detail of each provision.
Introduction
The Health Insurance Portability and Accountability Act of 1996 (HIPAA) required the
Secretary of the U.S. Department of Health and Human Services (HHS) to develop regulations
protecting the privacy and security of certain health information.1 To fulfill this requirement,
HHS published what are commonly known as the HIPAA Privacy Rule and the HIPAA Security
Rule. The Privacy Rule, or Standards for Privacy of Individually Identifiable Health Information,
establishes national standards for the protection of certain health information. The Security
Standards for the Protection of Electronic Protected Health Information (the Security Rule)
establish a national set of security standards for protecting certain health information that is held
or transferred in electronic form. The Security Rule operationalizes the protections contained in
the Privacy Rule by addressing the technical and non-technical safeguards that organizations
called “covered entities” must put in place to secure individuals’ “electronic protected health
information” (e-PHI). Within HHS, the Office for Civil Rights (OCR) has responsibility for
enforcing the Privacy and Security Rules with voluntary compliance activities and civil money
penalties.
Prior to HIPAA, no generally accepted set of security standards or general requirements for
protecting health information existed in the health care industry. At the same time, new
technologies were evolving, and the health care industry began to move away from paper
processes and rely more heavily on the use of electronic information systems to pay claims,
answer eligibility questions, provide health information and conduct a host of other
administrative and clinically based functions.
Today, providers are using clinical applications such as computerized physician order entry
(CPOE) systems, electronic health records (EHR), and radiology, pharmacy, and laboratory
systems. Health plans are providing access to claims and care management, as well as member
self-service applications. While this means that the medical workforce can be more mobile and
efficient (i.e., physicians can check patient records and test results from wherever they are), the
rise in the adoption rate of these technologies increases the potential security risks.
A major goal of the Security Rule is to protect th.
What is HIPAA Compliance?
HIPAA stands for the Healthcare Insurance Portability and Accountability Act of 1996. This specifies laws for the protection and use of Personal (or Protected) Health Information (PHI) - essentially, your medical record. HIPAA sets the standard for protecting sensitive patient data. The Administrative Simplification provisions of the Act (HIPAA, Title II) require the U.S. Department of Health and Human Services (HHS) to adopt certain national standards. These cover electronic health care transactions, and national identifiers for providers, health plans, and employers.
Physical, network, and process security measures are involved. The HIPAA Privacy Rule covers the saving, accessing and sharing of medical and personal information for any individual. The HIPAA Security Rule outlines national security standards to protect health data created, received, maintained or transmitted electronically - also known as electronic protected health information (ePHI).
Meeting these standards? That's compliance.
Role-Based Access Governance and HIPAA Compliance: A Pragmatic ApproachEMC
This white paper discusses how some forward thinking organizations are using the passage of the HITECH Act as an opportunity to modernize how patient information is stored and accessed through electronic health records.
iSPIRT's Response on Digital Information Security in Healthcare Act (DISHA)ProductNation/iSPIRT
We believe that India is at a unique tipping point where only a fraction of its users have gone online, and a majority are yet to do so. Therefore, it is critical that we build the right set of protections and empowerments for these users as they enter the digital world.
It is equally important not to limit our thinking to simply “protection” of data. We must also question how we can “empower” individuals, who will be data rich before they are economically rich, with better access to their own healthcare data such that they can become more engaged participants and managers of their health care.
We welcome the proposed DISHA Act that seeks to Protect and Empower Individuals in regards to their electronic health data - we have provided our feedback on the DISHA Act and have also proposed technological approaches in this response
HIPAA's Title II- Administrative Simplification Rules: The Three Basic Rules ...Quinnipiac University
HIPAA Title II, The Administrative Simplification provisions were establish for a variety of reasons. The main rationale was to take advantage of twenty-first century technology, and increase efficiency by eliminating redundant and manual processes. By establishing electronic health information systems, electronic protected health information (ePHI) became Congress’ top priority, on how healthcare organizations should deal with such vital and confidential information.
The aim of this paper is to examine an in-depth look at HIPAA’s Title II on how technology has enhanced the way healthcare organizations conduct their business activities on a daily basis, while specifically addressing the privacy and security issues that many are concerned about. This paper will explain the background and history behind HIPAA and Title II, including Congress’ goals and objectives for this act, and then will go into great detail about the three basic rules that HIPAA, and more specifically Title II, are all about.
Chapter 10 Privacy and Security of Health RecordsLearnin.docxcravennichole326
Chapter 10 Privacy and Security of Health Records
Learning Outcomes
After completing this chapter, you should be able to:
♦ List HIPAA transactions and uniform identifiers
♦ Understand HIPAA privacy and security concepts
♦ Apply HIPAA privacy policy in a medical facility
♦ Discuss HIPAA security requirements and safeguards
♦ Follow security policy guidelines in a medical facility
♦ Explain electronic signatures
Understanding HIPAA
In Chapter 11 we will discuss various ways the Internet is being used for healthcare, including various implementations of EHR on the Internet, Internet-based personal health records (PHR), and remote access. In Chapter 12 we will explore the relationship of the EHR data to the determination of codes required for medical billing. Before moving to those topics it is prudent to understand HIPAA. HIPAA is an acronym for the Health Insurance Portability and Accountability Act, passed by Congress in 1996.
The HIPAA law was intended to:
♦ Improve portability and continuity of health insurance coverage.
♦ Combat waste, fraud, and abuse in health insurance and healthcare delivery.
♦ Promote use of medical savings accounts
♦ Improve access to long-term care
♦ Simplify administration of health insurance
HIPAA law regulates many things. However, a portion known as the Administrative Simplification Subsection1 of HIPAA covers entities such as health plans, clearinghouses, and healthcare providers. HIPAA refers to these as covered entities or a covered entity. This means a healthcare facility or health plan and all of its employees. If you work in the healthcare field, these regulations likely govern your job and behavior. Therefore, it is not uncommon for healthcare workers to use the acronym HIPAA when they actually mean only the Administrative Simplification Subsection of HIPAA.
Note Covered Entity
HIPAA documents refer to healthcare providers, plans, and clearing-houses as covered entities. In the context of this chapter, think of a covered entity as a healthcare organization and all of its employees.
As someone who will work with patients’ health records, it is especially important for you to understand the regulations regarding privacy and security. However, let us begin with a quick review of HIPAA, then study the privacy and security portions in more depth.
HIPAA implementation and enforcement is under the jurisdiction of several entities within the U.S. Department of Health and Human Services (HHS). This chapter will make extensive use of documents prepared by HHS.
Administrative Simplification Subsection
The Administrative Simplification Subsection has four distinct components:
1. Transactions and code sets
2. Uniform identifiers
3. Privacy
4. Security
HIPAA Transactions and Code Sets
The first section of the regulations to be implemented governed the electronic transfer of medical information for business purposes such as insurance claims, payme ...
Are NIST standards clouding the implementation of HIPAA security risk assessm...David Sweigert
The HIPAA Security Rule (at 45 C.F.R. §164.308(a)(1)(ii)(A)) requires an initial security risk analysis according to risk analysis guidance issued by HHS/OCR based on NIST standards.
OCR Audit Protocols for Risk Analysis are clear! CMS, as planned, has launched audits of organizations who have attested to Meaningful Use Objectives and Risk Analyses will be audited. Have you completed a bona fide HIPAA Security Risk Analysis?
We are publishing a draft of the technical standards of the Personal Health Records (PHR) component of the National Health Stack (NHS)!
As a refresher, these standards govern the consented sharing of health information between Health Information Providers (HIPs) - like hospitals, pathology labs, and clinics - and Health Information Users (HIUs) like pharmacies, medical consultants, doctors, and so on. The user’s consent to share their health data is issued via a new entity called a Health Data Consent Manager (HDCM).
The problem today is that the electronic health records listed in one app or ecosystem are not easily portable to other systems. There is no common standard that can be used to discover, share, and authenticate data between different networks or ecosystems. This means that the electronic medical records generated by users end up being confined to many different isolated silos, which can result in frustrating and complex experiences for patients wishing to manage data lying across different providers.
With the PHR system, a user is able to generate a longitudinal view of their health data across providers. The interoperability and security of the PHR architecture allows users to securely discover, share, and manage their health data in a safe, convenient, and universally acceptable manner. For instance, a user could use a HDCM to discover their account at one hospital or diagnostic lab, and then select certain electronic reports to share with a doctor from another hospital or clinic. The flow of data would be safe, and the user would have granular control over who can access their data and for how long. Here is a small demo of the PHR system in action.
The standards in the draft released today offers a high-level description of the architecture and flows that make this possible.
Healthcare organizations (HCOs) are facing three major IT security and compliance
challenges. First, IT regulations such as HIPAA are getting stricter and enforcement actions
are becoming more common and costly....
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Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care.
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Health Informatics - An International Journal (HIIJ)hiij
Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care.
The journal focuses on all of aspect in theory, practices, and applications of Digital Health Records, Knowledge Engineering in Health, E-Health Information, and Information Management in healthcare, Bio-Medical Expert Systems, ICT in health promotion and related topics. Original contributions are solicited on topics covered under the broad areas such as (but not limited to) listed below:
Health Informatics - An International Journal (HIIJ)hiij
Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care.
The journal focuses on all of aspect in theory, practices, and applications of Digital Health Records, Knowledge Engineering in Health, E-Health Information, and Information Management in healthcare, Bio-Medical Expert Systems, ICT in health promotion and related topics. Original contributions are solicited on topics covered under the broad areas such as (but not limited to) listed below:
Health Informatics - An International Journal (HIIJ)hiij
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Health Informatics - An International Journal (HIIJ)hiij
Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care.
The journal focuses on all of aspect in theory, practices, and applications of Digital Health Records, Knowledge Engineering in Health, E-Health Information, and Information Management in healthcare, Bio-Medical Expert Systems, ICT in health promotion and related topics. Original contributions are solicited on topics covered under the broad areas such as (but not limited to) listed below:
AUTOMATIC AND NON-INVASIVE CONTINUOUS GLUCOSE MONITORING IN PAEDIATRIC PATIENTShiij
Glycated haemoglobin does not allow you to highlight the effects that food choices, physical activity and
medications have on your glycaemic control day by day. The best way to monitor and keep track of the
immediate effects that these have on your blood sugar levels is self-monitoring, therefore the use of a
glucometer. Thanks to this tool you have the possibility to promptly receive information that helps you to
intervene in the most appropriate way, bringing or keeping your blood sugar levels as close as possible to
the reference values indicated by your doctor. Currently, blood glucose meters are used to measure and
control blood glucose. Diabetes is a fairly complex disease and it is important for those who suffer from it
to check their blood sugar (blood sugar) periodically throughout the day to prevent dangerous
complications. Many children newly diagnosed with diabetes and their families may face unique challenges
when dealing with the everyday management of diabetes, including treatments, adapting to dietary
changes, and the routine monitoring of blood glucose. Many questions may also arise when selecting a
blood glucose meter for paediatric patients. With current blood glucose meters, even with multiple daily
self-tests, high and low blood glucose levels may not be detected. Key factors that may be considered when
selecting a meter include accuracy of the meter; size of the meter; small sample size required for testing;
ease of use and easy-to-follow testing procedure; ability for alternate testing sites; quick testing time and
availability of results; ease of portability to allow testing at school and during leisure time; easyto- read
numbers on display; memory options; cost of meter and supplies. In this study we will show a new
automatic portable, non-invasive device and painless for the daily continuous monitoring (24 hours a day)
of blood glucose in paediatric patients.
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMShiij
This review article examines the role of machine learning (ML) in enhancing Clinical Decision Support
Systems (CDSSs) within the modern healthcare landscape. Focusing on the integration of various ML
algorithms, such as regression, random forest, and neural networks, the review aims to showcase their
potential in advancing patient care. A rapid review methodology was utilized, involving a survey of recent
articles from PubMed and Google Scholar on ML applications in healthcare. Key findings include the
demonstration of ML's predictive power in patient outcomes, its ability to augment clinician knowledge,
and the effectiveness of ensemble algorithmic approaches. The review highlights specific applications of
diverse ML models, including moment kernel machines in predicting surgical outcomes, k-means clustering
in simplifying disease phenotypes, and extreme gradient boosting in estimating injury risk. Emphasizing
the potential of ML to tackle current healthcare challenges, the article highlights the critical role of ML in
evolving CDSSs for improved clinical decision-making and patient care. This comprehensive review also
addresses the challenges and limitations of integrating ML into healthcare systems, advocating for a
collaborative approach to refine these systems for safety, efficacy, and equity.
BRIEF COMMENTARY: USING A LOGIC MODEL TO INTEGRATE PUBLIC HEALTH INFORMATICS ...hiij
The COVID-19 pandemic has been a watershed moment in public health surveillance, highlighting the
crucial role of data-driven insights in informing health actions and policies. Revisiting key concepts—
public health, epidemiology in public health practice, public health surveillance, and public health
informatics—lays the foundation for understanding how these elements converge to create a robust public
health surveillance system framework. Especially during the COVID-19 pandemic, this integration was
exemplified by the WHO efforts in data dissemination and the subsequent global response. The role of
public health informatics emerged as instrumental in this context, enhancing data collection, management,
analysis, interpretation, and dissemination processes. A logic model for public health surveillance systems
encapsulates the integration of these concepts. It outlines the inputs and outcomes and emphasizes the
crucial actions and resources for effective system operation, including the imperative of training and
capacity development.
INTEGRATING MACHINE LEARNING IN CLINICAL DECISION SUPPORT SYSTEMShiij
This review article examines the role of machine learning (ML) in enhancing Clinical Decision Support
Systems (CDSSs) within the modern healthcare landscape. Focusing on the integration of various ML
algorithms, such as regression, random forest, and neural networks, the review aims to showcase their
potential in advancing patient care. A rapid review methodology was utilized, involving a survey of recent
articles from PubMed and Google Scholar on ML applications in healthcare. Key findings include the
demonstration of ML's predictive power in patient outcomes, its ability to augment clinician knowledge,
and the effectiveness of ensemble algorithmic approaches. The review highlights specific applications of
diverse ML models, including moment kernel machines in predicting surgical outcomes, k-means clustering
in simplifying disease phenotypes, and extreme gradient boosting in estimating injury risk. Emphasizing
the potential of ML to tackle current healthcare challenges, the article highlights the critical role of ML in
evolving CDSSs for improved clinical decision-making and patient care. This comprehensive review also
addresses the challenges and limitations of integrating ML into healthcare systems, advocating for a
collaborative approach to refine these systems for safety, efficacy, and equity.
Health Informatics - An International Journal (HIIJ)hiij
Healthcare Informatics: An International Journal is a quarterly open access peer-reviewed journal that Publishes articles which contribute new results in all areas of the health care.
The journal focuses on all of aspect in theory, practices, and applications of Digital Health Records, Knowledge Engineering in Health, E-Health Information, and Information Management in healthcare, Bio-Medical Expert Systems, ICT in health promotion and related topics. Original contributions are solicited on topics covered under the broad areas such as (but not limited to) listed below:
The Proposed Guidelines for Cloud Computing Migration for South African Rural...hiij
It is now overdue for the hospitals in South African rural areas to implement cloud computing technologies in order to access patient data quickly in an emergency. Sometimes medical practitioners take time to attend patients due to the unavailability of kept records, leading to either a loss of time or the reassembling of processes to recapture lost patient files. However, there are few studies that highlight challenges faced by rural hospitals but they do not recommend strategies on how they can migrate to cloud computing. The purpose of this paper was to review recent papers about the critical factors that influence South African hospitals in adopting cloud computing. The contribution of the study is to lay out the importance of cloud computing in the health sectors and to suggest guidelines that South African rural hospitals can follow in order to successfully relocate into cloud computing.The existing literature revealed that Hospitals may enhance their record-keeping procedures and conduct business more effectively with the help of the cloud computing. In conclusion, if hospitals in South African rural areas is to fully benefit from cloud-based records management systems, challenges relating to data storage, privacy, security, and the digital divide must be overcome.
SUPPORTING LARGE-SCALE NUTRITION ANALYSIS BASED ON DIETARY SURVEY DATAhiij
While online survey systems facilitate the collection on copious records on diet, exercise and other healthrelated data, scientists and other public health experts typically must download data from those systems
into external tools for conducting statistical analyses. A more convenient approach would enable
researchers to perform analyses online, without the need to coordinate additional analysis tools. This
paper presents a system illustrating such an approach, using as a testbed the WAVE project, which is a 5-
year childhood obesity prevention initiative being conducted at Oregon State University by health scientists
utilizing a web application called WavePipe. This web application has enabled health scientists to create
studies, enrol subjects, collect physical activity data, and collect nutritional data through online surveys.
This paper presents a new sub-system that enables health scientists to analyse and visualize nutritional
profiles based on large quantities of 24-hour dietary recall records for sub-groups of study subjects over
any desired period of time. In addition, the sub-system enables scientists to enter new food information
from food composition databases to build a comprehensive food profile. Interview feedback from novice
health science researchers using the new functionality indicated that it provided a usable interface and
generated high receptiveness to using the system in practice.
AN EHEALTH ADOPTION FRAMEWORK FOR DEVELOPING COUNTRIES: A SYSTEMATIC REVIEWhiij
#Health #clinic #education #StaySafe #pharmacy #healthylifestyle
call for papers..!
-----------------------------
Health Informatics: An International Journal (HIIJ)
ISSN : 2319 - 2046 (Online); 2319 - 3190 (Print)
Here's where you can reach us : hiij@aircconline.com
visit us on : https://airccse.org/journal/hiij/index.html
**************
published articles..!
AN EHEALTH ADOPTION FRAMEWORK FOR
DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW
https://aircconline.com/hiij/V10N3/10321hiij01.pdf
GENDER DISPARITYOF TUBERCULOSISBURDENIN LOW-AND MIDDLE-INCOME COUNTRIES: A SY...hiij
The tuberculosis burden is higher in the population from low- and middle-income countries (LMICs) and
differently affects gender. This review explored risk factors that determine gender disparity in tuberculosis
in LMICs. The research design was a systematic review. Three databases; Google Scholar, PubMed, and
HINARI provided 69 eligible papers.The synthesized data were coded, grouped and written in a descriptive
narrative style. HIV-TB co-infected women had a higher risk of mortality than TB-HIV-infected men. The
risk of Vitamin-D deficiency-induced tuberculosis was higher in women than in men. Lymph node TB,
breast TB, and cutaneous and abdominal TB occurred commonly in women whereas pleuritis, miliary TB,
meningeal TB, pleural TB and bone and joint TB were common in men. Employed men had higher contact
with tuberculosis patients and an increased chance of getting the disease. Migrant women were more likely
to develop tuberculosis than migrant men. The TB programmers and policymakers should balance the
different gaps of gender in TB-related activities and consider more appropriate approaches to be genderbased and have equal access to every TB-associated healthcare.
BRIEF COMMUNICATIONS DATA HYGIENE: IMPORTANT STEP IN DECISIONMAKING WITH IMPL...hiij
Medical and health data that have been entered into an electronic data system in real-time cannot be
assumed to be accurate and of high quality without verification. The adoption of the electronic health
record (EHR) by many countries to the support care and treatment of patients illustrates the importance of
high quality data that can be shared for efficient patient care and the operation of healthcare systems.
This brief communication provides a high-level overview of an EHR system and practices related to high
data quality and data hygiene that could contribute to the analysis and interpretation of EHR data for use
in patient care and healthcare system administration.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
When stars align: studies in data quality, knowledge graphs, and machine lear...
A FRAMEWORK FOR EXTRACTING AND MODELING HIPAA PRIVACY RULES FOR HEALTHCARE APPLICATIONS
1. Health Informatics - An International Journal (HIIJ) Vol.5, No.1, February 2016
DOI: 10.5121/hiij.2016.5101 1
A FRAMEWORK FOR EXTRACTING AND MODELING
HIPAA PRIVACY RULES FOR HEALTHCARE
APPLICATIONS
Tariq Alshugran and Julius Dichter
Department of Computer Science and Engineering, University of Bridgeport, Bridgeport,
CT, USA
ABSTRACT
Some organizations use software applications to manage their customers’ personal, medical, or financial
information. In the United States, those software applications are obligated to preserve users’ privacy and
to comply with the United States federal privacy laws and regulations. To formally guarantee compliance
with those regulations, it is essential to extract and model the privacy rules from the text of the law using a
formal framework. In this work we propose a goal-oriented framework for modeling and extracting the
privacy requirements from regulatory text using natural language processing techniques.
KEYWORDS
Privacy Policies, Data Modelling, Law Formalization, Data privacy, Role engineering
1. INTRODUCTION
Software applications are developed to help companies and organizations to process and manage
data that support their daily operations. However, this data might contain sensitive clients’
information that should be protected to ensure clients’ privacy. Besides losing clients’ trust,
neglecting to ensure the clients’ data privacy may also be unlawful and inflict serious legal and
financial consequences. Lately, different laws and regulations [1]–[3] related to data privacy have
been enacted specially in vital sectors such as health care, finance, and accounting. Those
regulations dictate how clients’ data should be disclosed and transmitted within the organization
and also with external partners. The privacy rules in laws and regulations presented a challenge
for software engineers who design and implement software applications that process
private client data. The difficulty is linked to the complexity and length of the letter of the
law and the how to guarantee that the software application is maintaining the clients’ data
privacy in compliance with the law.
Some healthcare organizations are trying to perform their own interpretation of the law privacy
rules by creating custom systems. However, the problems with such approach is that the margin
of error while interpreting the letter of the law is high specially with separate efforts carried out
by individual companies. According to a survey carried out to check the Healthcare Insurance
Portability and Accountability Act (HIPAA) requirements interpretation created for medical and
healthcare related applications, none of the frameworks were well developed to capture the
relationships specified in the law [4]. To solve this problem, a standard framework is required that
will analyze the regulatory text and provide a method to extract the relevant component that can
be used during software roles engineering and development. The extracted components will
include all the possible arrangements of roles, purposes, permissions, temporal factors, and any
carried out obligations.
2. Health Informatics - An International Journal (HIIJ) Vol.5, No.1, February 2016
2
In this work we propose a framework to analyzes, extracts, and models the privacy requirements
from HIPAA regulatory text. The framework goal is to translate the law privacy rules text into
more manageable components in the form of entities, roles, purposes, and obligations. Those
components together can be used as building blocks to create formal privacy policies. The process
concentrate on two main components; entities and their roles, and data access context. To get the
first part, the framework will parse the privacy sections of the regulatory text to mine all the
subjects, and then categorize those subjects into roles based on their characterization in the law.
To acquire the access context, the process will extract all the purposes, temporal clauses and any
carried out obligations and classify them based on their permissibility.
The rest of this work is organized as follows. Section 2 examines the complexity of HIPAA and
other regulatory text modeling. In section 3, we cover access control models and the elements that
should be extracted based on the selected access control mode. Whereas section 4 describes the
proposed framework for extracting and modeling the access requires context from the regulatory
text. Section 5 provides a literature survey of laws and regulations modeling and current proposed
approaches. Finally, we discuss our future work and conclude in section 6.
2. LAWS’ PRIVACY RULES AND MODELING COMPLEXITY
In the U.S., numerous federal laws and regulations were legislated to guarantee individuals’ right
to be able to access and port their private information stored and managed by service providers
while protecting that information from unauthorized access. For example, the Gramm-Leach-
Bliley Act (GLBA) of 1999 [2] is designed to protect individuals’ financial information from
being breached without proper authorization. The Health Insurance Portability and Accountability
Act (HIPAA) of 1996 [1] is another example, section 164 of HIPAA is intended explicitly to
protect patients’ healthcare information and medical records from unauthorized disclosure [5].
According to HIPAA, any healthcare related information that can identify an individual and can
be stored or transmitted via any media format is defined as Protected Health Information (PHI).
HIPAA privacy rules control the storage, transmission, and disclosure of all Protected Health
Information. Usually the PHI is collected and maintained by healthcare insurance plan, healthcare
provider, healthcare clearinghouse or any other similar organization identified by HIPAA as
Covered Entity. Comparable privacy rules can also be found in other federal regulations as well.
2.1. Modeling Complexity
The U.S. federal regulations documents are written in a complex format and technical language
known as legalese. Legalese or legal English uses different vocabulary and syntax than that used
in ordinary English. The complex format and legal terminologies makes legal documents hard to
read and interpret.
A part from the document language, the structured format makes the text prone to
misinterpretations and other ambiguities like cross references and exceptions. The document is
usually structured into parts (e.g. Part 164 of HIPAA). Each part is then divided into subparts,
which is additionally divided into sections (e.g. Section §164.528). Some sections are also
divided into subparagraphs with multiple points in the same sentence. This create some
inconsistency as some privacy rules are spanning multiple points, subparagraphs, paragraphs,
or event sections. For example, the subparagraph §164.528(a)(2)(ii) contains three points (A),
(B), and (C) in the same sentence: “the covered entity must:(A)...;(B)...; and (C)...”, where each
one of these points defines a different obligation that should be carried out by the covered entity.
3. Health Informatics - An International Journal (HIIJ) Vol.5, No.1, February 2016
3
Exceptions and Cross-references to other sections add more complexity to the modeling process
as they require an additional processing effort. References usually entail priority between
paragraphs and add more clarity to the privacy requirements. However, sometimes references
might introduce ambiguities due to the possibility of nested and multilevel referencing in the form
of cross-references. Cross-references occur when a section or a paragraph in the law is
referencing another section/paragraph that has a reference to another rule. For example, the
subparagraph §164.528 (a)(2)(i) describes individuals’ suspension of rights obligation. This right
is also addressed in a different paragraph as highlighted by the phrase “as provided in
§164.512(d)” at the end of the paragraph establishing a reference. Nevertheless, in the subsequent
paragraph §164.528(a)(2)(ii), the phrase “pursuant to paragraph (i)” is a reference to the
preceding paragraph. Hence, to model the right indicated in §164.528(a)(2)(ii), we need to refer
to §164.512(d) creating an indirect relation between the two paragraphs. On the other hand,
exceptions are rules that contradict or negate other rules by changing the permissibility right or by
adding more conditions or obligation. So, if the first rule grants a right to access a PHI, the
exception would either add more conditions to clarify that right or grant permission and vice
versa. For instance, §164.512(c)(1) in HIPAA grants the right to disclose a PHI if the information
is about adult victims of abuse, neglect or domestic violence, however, §164.512(c)(1)(ii)
presents an exception to this right by adding victims agreement as a condition for such a
disclosure.
3. ACCESS CONTEXT
Access context represents the elements that can be used as an input to the to an access control
system. To create a privacy preserving access control system that enforces the privacy rules from
the regulatory text, we need to extract the access context. In this section we show those
components and the importance of formalizing them.
3.1. Context-Based Access Control
In information security, Access Control is implemented as a mean to decide whether any specific
authenticated system user has the proper permission to access a certain data object, or carry out a
particular type of operation (e.g. read, write, delete …etc.) on that object [6].
Most access control models are described using three terms: subject, object, and operation.
Subject refers to any authenticated user, it could be a system, a person, or a process. Whereas
object is defined as the private data that the access control system is protecting. Finally, operation
is any action that can be taken by the subject on the object. Figure 1 shows the three terms of
simple access control model. The permissibility to carry out those operations is ruled by a
collection of access rights expressed in the format:
ALLOW [Subject]
TO PERFORM [Operation] ON [Object]
4. Health Informatics - An International Journal (HIIJ) Vol.5, No.1, February 2016
4
Figure 1. Simple Access Control Model
Access control models evolved over time to solve particular issues the traditional model was not
able to handle correctly. For instance, Role-Based Access Control model (RBAC) [7] extended
the traditional simple access control model described above to add the subject role. In RBAC
users’ role is used in the access right rules instead of users’ identities. RBAC model was
introduced to solve the any inconsistency faced by dynamic systems where users’ role is prone to
change, and hence, there permission and access rights should change as well to adapt the new
roles. Figure 2 below illustrate RBAC components and the relation with the system users. RBAC
access rights rules are formally formatted and expressed as:
ALLOW [Role]
TO PERFORM [Operation] ON [Object]
Figure 2. Role-Based Access Control (RBAC) Model
In order to facilitate a more fine-grained detail that will capture the privacy rules and
requirements of HIPAA regulatory text, a new model was introduced to capture the access
context. The Context-Based Access Control (CBAC) model is an extension to RBAC with more
details to allow higher flexibility and regulatory compliance. CBAC depends on the user roles,
request purpose, and object type to determine the permissibility of the access request. CBAC also
provides a mechanism to log any carried out obligations as a result of granting access to the
object. Recently, many formats were suggested to represent CBAC, in this work we propose a
modified version Powers et al [6] version of the Privacy Access Control model as shown in figure
3. CBAC access rules can be formally expressed in the format below:
ALLOW [Active Role]
TO PERFORM [Operation]
ON [Data Type]
RELATED TO [Data Owner Type]
FOR [Purpose]
5. Health Informatics - An International Journal (HIIJ) Vol.5, No.1, February 2016
5
PROVIDED [Condition]
CARRY OUT [Obligation]
Figure 3. Context-Based Access Control (CBAC) Model
3.2. CBAC Components
To better understand what elements and components the framework should extract from
regulatory text, we need to align the extraction and modeling process with CBAC access rules. In
this section we will describe each component and how to formally model that component in order
to extract it.
Requester Active Role: As CBAC is an extension of RBAC, it also uses the requester role
instead of the requester identity. However, due to the fact that any user can be in multiple roles,
we use the current active role only. For example, if Alice is a doctor and a patient at the same
time, when accessing her own medical file she will be treated as a patient only as that is the
current active role of Alice.
Operation: any set of actions that can be applied to data objects, similar to the traditional
model. The set contains read, write, and delete action in addition to any other applicable
operation provided by the system.
Data Type: Context-Based access rules are not tied directly to a particular data object, but
rather to the type of data object. The data type can be defined at high-level (e.g. treatment
related files), or at a much lower-level (e.g. Medical chart files, CT scan images …etc.).
This introduces the notion of attaching attributes or metadata to the data itself.
Data Owner Type: The data owner type element specifies the state and the type of the
owner of the data object. By capturing this element, we can establish a relation between
the PHI, its owner, and the requester. For example, if Alice is a doctor requesting access
to Bob’s medical file, we can check if Alice is role as a doctor is relevant to Bob’s file as
a patient of Alice. If the relation is established then in this case Bob is the owner of the
PHI and his type in relation to Alice is a patient.
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Purpose: This element represents the reason why the access requester is requesting
access to the specified data object type. Purposes can also be classified at a high-level or
low-level depending on the provided request context and the letter of the law. It could be
healthcare related like treatment or medical consulting, financial for the purpose of
accounting, or legal like violence and crime investigations.
Conditions: Any pre-defined additional conditions and criteria required to be fulfilled
before accessing the protected data object or allowing the disclosure. A common example
of conditions in HIPAA is obtaining the data owner permission and consent before
sharing their data with any third party.
Obligations: Obligations in access request refer to the action that should be carried out by
the covered entity, the access requester, or the system itself after permission was granted
and the data was transmitted. It might include operations like logging for audit purposes
or notifying the data owner of the disclosure action.
4. THE MODELING PROCESS
This section presents the proposed framework process and steps used to extract privacy
requirements from the regulatory text. The process is divided into two activities: firstly is the
model and analysis activity to model the regulatory text, and secondly the identification and
extraction activity to extract the privacy requirements context. Each one of the two activities
contains a number of steps. Figure 4 demonstrates the extraction process with the two activities as
well as each activity initial inputs and the expected outputs.
4.1. Model and Analyze HIPAA
The purpose of this activity is to overcome the difficulties and issues that complicate HIPAA
modeling as explained in section II.B. Raw HIPAA rules are used as an input to the activity, and
then the following steps are performed:
Step 1: Identify scopes and definitions: the first step is to outline the extraction scope. In this
framework, the emphasis will be on the privacy rules related to preserving patients’ identity and
PHI disclosure. After analyzing HIPAA regulatory text and excluding all the abstract, non-
technical requirements, we found that the extraction process should only be applied to the privacy
requirements from the following subsections of HIPAA: §164.502, §164.506, §164.510,
§164.512, §164.514, and §164.524.
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Figure 4. HIPAA privacy requirements extraction process
Step 2: Identify and resolve rules dependencies, cross-references, and exceptions: the goal of this
step is to validate the subset of selected rules from step 1 and to add more clarity to HIPAA legal
text. This goal is attained by replacing self-references, dependencies, and cross-references, with
the exact description from the referenced rule, or by applying a similar depiction to improve the
rule readability and interpretation. Alternatively, if the reference is identified as a condition it
might be replaced with a rule identifier placeholder for further processing in an advanced stage of
the process.
The output of the first activity is a reference-free less-ambiguous subset of HIPAA rules that is
focused only on patients’ privacy. This output will then be used as an input in the following
activity.
4.2. Identify and Extract the Context Elements
The second activity aims to perform the extraction process. Similar to the preceding activity, this
activity also is divided into multiple steps where the final step is the responsible for the context
elements extraction. In this activity the regulatory text is parsed using a Natural Language
Processing (NLP) application to highlight phrases that may establish a possible context element.
Figure 5 outlines the components of the rule §164.528 (a)(2)(i) of HIPAA as an example of the
expected results.
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Figure 5. An outline of HIPAA rule §164.528 (a)(2)(i) components.
Step 1: Clearing ambiguities: HIPAA legal text contains domain-specific wording and
terminologies that will require the assistance of law professional to provide a precise
interpretation and definition of the text. As some words, terms, and phrases might carry multiple
meanings causing further ambiguity and a higher chance of misinterpretation. At this step, all the
ambiguous terms, words, and phrases will be mapped to a set of possible meanings as proposed
by the work of Otto et al [8].
Step 2: Text parsing and elements extraction: a text parser is used to identify any possible context
element. Rules of generalization and specialization are also applied to specify generic roles.
Table 1. Subparagraph §164.528 (a)(2)(i) Elements Classification
Element Element Classification
R164_528_a_2_i Rule Id
covered entity Role
must Operator
temporarily Temporal factor
suspend rights to receive an accounting
of disclosure
Action
health oversight agency Role
law enforcement official Role
(R164_512_d) OR (R164_512_d) Condition
Step 3: Elements Classification: Numerous approaches were proposed to classify elements [8]–
[12]. Nevertheless, each approach was proposed to solve a particular problem or introduced a
special notation that might not be applicable for generic access control. For instance, Hohfeld
classification presented the notion of rights and responsibilities. Hohfeld theory represents the
relationships between actors and the law based on their responsibilities and rights within the legal
text context [13]. However, our framework is more concentrated on the concept of Context-Based
Access Control (CBAC) where the core focus is to identify roles, data type, purposes, conditions,
temporal factors, and obligations. Hence, a Goal-Driven approach can be applied where the goal
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is to extract the CBAC components. Table 1 shows an example of elements classification
constructed using a goal-driven approach on the data from §164.528 (a)(2)(i) of HIPAA.
5. RELATED WORK
Recent researches in the area of role extraction and engineering reveals a variety of proposed
methods for extracting and modeling regulation components for different purposes. One of the
oldest recognized efforts to classify the contents of regulatory text is attributed to Wesley Hohfeld
which is known as Hohfeld legal taxonomy published in 1917 in Yale Law Journal [13]. Hohfeld
taxonomy classifies regulatory text based on the notion of rights and obligations. Few recent
researches have built their extraction models based on Hohfeld legal taxonomy like the work of
Siena et al [14] and Islam et al [12]. Other approaches used Natural Language Processing (NLP)
techniques to spot linguistic patterns to model the law and extract the context from the legal text
[15]. In addition to the language patterns and Hohfeld taxonomy, other researchers used different
methods including: analytical modeling based on organizational structure as in the work of
Crook[9], UML-based [16], [11] method for the extraction of privacy requirements from
organizations privacy requirements, and scenario-driven methods established for predefined set of
tasks and scenarios [10]. Jorshari et al. work [17] focused on eliciting the security requirements in
general without making the approach close enough to be adapted for extracting privacy
requirements. Darimont et al [17] proposed a Goal-Oriented Requirements Engineering (GORE)
approach to classify rules and form goals where those goals are then refined in an incremental
fashion until all related tasks, actors, and uses-cases are discovered and extracted.
6. CONCLUSIONS
In this work, we proposed a framework to model the privacy requirements from regulatory text
and to extract the possible context elements in the form roles, purposes, and obligations. The
framework is designed to overcome the traditional complexities and challenges that face laws and
regulations modeling. The framework consists of multiple steps starting by closely inspecting and
analyzing the regulatory text to identify the parts of interest of the law that is related to the
privacy requirements. Then it clarifies ambiguities from the letter of the law by resolving cross-
references, dependencies, and handling rules exceptions. Next, a Goal-Driven approach is applied
to examine the identified targeted rules text to extract all keywords that may define a context
element.
In a later phase of this research, the context elements extracted using this framework will be used
to create privacy policies as well as in the decision engine in an access control model. In order to
implement such a model, the next phase will also include identifying the decision engine logic
and the specification language that will be used for privacy policy representation.
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