scholarly journals Linking First Nations data to administrative health data within Manitoba

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Venkata Shravan Ramayanam ◽  
Leona Star
Keyword(s):  
First Nations ◽  
Health Information ◽  
Personal Health Information ◽  
Personal Health ◽  
Data Governance ◽  
Information Research ◽  
University Of Manitoba ◽  
Manitoba Health ◽  
First Time ◽  
Administrative Datasets

IntroductionFirst Nation peoples (FNs) were unable to track their own health care trends due to limitations in datasets. The key linked file enables FNs to identify themselves within administrative datasets and work with Crown governments to bring equity in all services and departments to support FNs understanding of wellness. Objectives and ApproachFirst Nations Health and Social Secretariat of Manitoba (FNHSSM) was established by 2013 resolution of Assembly of Manitoba Chiefs (AMC) and incorporated in 2014. FNHSSM leads and supports research according to FNs criteria approved by the Chiefs in Assembly. Information Sharing Agreements (ISA) have been developed with federal and provincial governments to mandate the processes for data linkage. The ISA allows Indian Status Register (ISR) data of Department of Indigenous Services Canada (DISC) to be transferred to FNHSSM to provide oversight, and link to Provincial Personal Health Information Numbers (PHINs) to create the de-identified, scrambled, and encrypted Key Linked file. ResultsPrevious linkages were done in early 2000s with FNs approval and oversight. The 2018 linkage is the first time that ISAs have been formally developed. ISA-1 is between FNHSSM and Manitoba Health Seniors and Active Living (MHSAL) to create Key Linked file. ISA-2 is between FNHSSM, MHSAL and Manitoba Centre for Health Policy (MCHP) at University of Manitoba, to create the FNs Research File. This research file can only be accessed with application to and approval by the MFNs Health Information Research Governance Committee. This key linked file allows FNHSSM to prepare community health profiles specifically and only for each FN, to respect FNs Data Governance under Chief and Council. A regional report on Manitoba FNs will be created for all MFNs, FNHSSM and MHSAL. Conclusion/ImplicationsLinking datasets helps to strengthen FNs data governance in re-building nations, recognizing FNs inherent right to self-determination. Linking files help to provide meaningful data to advocate for FNs rights and access to the resources and social determinants of health needed to achieve equity in Manitoba.

scholarly journals Creation of First Nations Health Profiles Through Data Linkage in Manitoba

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Shravan Ramayanam
Keyword(s):  
First Nations ◽  
Health Information ◽  
Data Linkage ◽  
Personal Health Information ◽  
Personal Health ◽  
Specific Information ◽  
Information Research ◽  
Manitoba Health ◽  
Governance Committee ◽  
Health Registry

BackgroundFirst Nation peoples (FNs) were not able to identify themselves within administrative datasets due to lack of FNs identifiers, which perpetuates a pan-indigenous approach in advocacy and evaluation capabilities. Linking databases improves the quality and accuracy of FNs health data and offsets the burden of survey fatigue in communities. Creating community profiles helps FNs in identifying health status priorities for communities, Tribal Council and other geographically defined areas. MethodsA resolution was passed in September 2017 to link Indian Status Registry (ISR) file with Manitoba Health Registry, with First Nations Health and Social Secretariat of Manitoba (FNHSSM) and Health Information Research Governance Committee (HIRGC) oversight to create a Key Linked file which has First Nations specific information. Encrypted Personal Health Information Numbers (PHINs) were added to the Key Linked file to create a Manitoba First Nations Research file which is linkable to other databases. Information Sharing Agreements (ISA) have been developed with federal and provincial governments to mandate the processes for data linkage. ResultsA resolution was passed in September 2017 to link Indian Status Registry (ISR) file with Manitoba Health Registry, with First Nations Health and Social Secretariat of Manitoba (FNHSSM) and Health Information Research Governance Committee (HIRGC) oversight to create a Key Linked file which has First Nations specific information. Encrypted Personal Health Information Numbers (PHINs) were added to the Key Linked file to create a Manitoba First Nations Research file which is linkable to other databases. Information Sharing Agreements (ISA) have been developed with federal and provincial governments to mandate the processes for data linkage. ConclusionData Linkage is a key process to assert self-determination, strengthen FNs data governance and achieve Data Sovereignty. Linking databases creates opportunities for FNs to access accurate data that will assist their Nations to lead their own health research and program evaluation that are driven by their own needs and priorities.

Governance of artificial intelligence and personal health information

2019 ◽  
Vol 21 (3) ◽  
pp. 280-290 ◽  
Author(s):  
Jenifer Sunrise Winter ◽  
Elizabeth Davidson
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Information ◽  
Health Data ◽  
Personal Health Information ◽  
System Level ◽  
Personal Health ◽  
Data Governance ◽  
Privacy Regulation ◽  
Content Type

Purpose This paper aims to assess the increasing challenges to governing the personal health information (PHI) essential for advancing artificial intelligence (AI) machine learning innovations in health care. Risks to privacy and justice/equity are discussed, along with potential solutions. Design/methodology/approach This conceptual paper highlights the scale and scope of PHI data consumed by deep learning algorithms and their opacity as novel challenges to health data governance. Findings This paper argues that these characteristics of machine learning will overwhelm existing data governance approaches such as privacy regulation and informed consent. Enhanced governance techniques and tools will be required to help preserve the autonomy and rights of individuals to control their PHI. Debate among all stakeholders and informed critique of how, and for whom, PHI-fueled health AI are developed and deployed are needed to channel these innovations in societally beneficial directions. Social implications Health data may be used to address pressing societal concerns, such as operational and system-level improvement, and innovations such as personalized medicine. This paper informs work seeking to harness these resources for societal good amidst many competing value claims and substantial risks for privacy and security. Originality/value This is the first paper focusing on health data governance in relation to AI/machine learning.

How Research Will Adapt to HIPAA: A View from Within the Healthcare Delivery System

2002 ◽  
Vol 28 (4) ◽  
pp. 491-502
Author(s):  
Mary L. Durham
Keyword(s):  
Health Information ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
The United States ◽  
Personal Health Information ◽  
Personal Health ◽  
Business Associations ◽  
Electronic Information ◽  
Healthcare Delivery System ◽  
Institutional Review

While the new Health Insurance Privacy and Accountability Act (HIPAA) research rules governing privacy, confidentiality and personal health information will challenge the research and medical communities, history teaches us that the difficulty of this challenge pales in comparison to the potential harms that such regulations are designed to avoid. Although revised following broad commentary from researchers and healthcare providers around the country, the HIPAA privacy requirements will dramatically change the way healthcare researchers do their jobs in the United States. Given our reluctance to change, we risk overlooking potentially valid reasons why access to personal health information is restricted and regulated. In an environment of electronic information, public concern, genetic information and decline of public trust, regulations are ever-changing. Six categories of HIPAA requirements stand out as transformative: disclosure accounting/tracking, business associations, institutional review board (IRB) changes, minimum necessary requirements, data de-identification, and criminal and civil penalties.

Keeping Personal Health Information Safe

JAMA ◽  
2015 ◽  
Vol 313 (14) ◽  
pp. 1424 ◽  
Author(s):  
David Blumenthal ◽  
Deven McGraw
Keyword(s):  
Health Information ◽  
Personal Health Information ◽  
Personal Health
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