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The Norwegian Primary Care Research
Network IT infrastructure: The Snow system
Johan Gustav Bellika
Professor Nasjonalt Senter for e-helseforskning
Professor II Institutt for Klinisk Medisin, Helsevitenskapelig fakultet, UiT
Seminar on Practical Privacy-Preserving Distributed Statistical Computations
2018.03.05
Dr. John Snow
(1813 – 1858)
Source: WMA Declaration of Helsinki. URL: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/
http://chrisricecooper.blogspot.no/2015/02/photoessay-on-year-of-ram-by-asian.html
Declaration of Helsinki, Article 6
The primary purpose of medical research involving human
subjects is to understand the causes, development and effects of
diseases and improve preventive, diagnostic and therapeutic
interventions (methods, procedures and treatments).
Even the best proven interventions must be evaluated
continually through research for their safety, effectiveness,
efficiency, accessibility and quality.
Declaration of Helsinki, Article 9
It is the duty of physicians who are involved in medical
research to protect the life, health, dignity, integrity, right to
self-determination, privacy, and confidentiality of personal
information of research subjects.
Source: WMA Declaration of Helsinki. URL: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/
Medical research should be privacy preserving!
Objectives for the research infrastructure
• Make participation in research projects easier and more efficient for the GPs
• Reuse health data in a safe and privacy preserving manner
• Complete research projects according to scheduled time and resources
consumption
• Recruit 90-110 GP practices
• Cover 7,5 % of the Norwegian population
The IT infrastructure
What is Snow?
• A distributed system
• Enables collection and reuse of anonymous medical data
• Builds and maintains a national online epidemiology-model
• Use the epidemiology model to provide automated IT based health services
• Enable privacy preserving distributed computations on EHR data
• Directed at research, quality improvements, audit, disease surveillance,…
Source:http://upload.wikimedia.org/wikipedia/commons/f/f6/Vibrio_cholerae.jpg
Snow architecture
- enables coordinated computations on distributed resources
- a “collaborative Edge computing” infrastructure [1]
S Coord
S
S
S
S
ClientCoord=Snow Coordination server
S= Snow Server in local health institution
Source: [1] Shi W, Cao J, Zhang Q, Li Y, Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. oktober 2016;3(5):637–46.
Edge computing
“Edge computing refers to the enabling technologies allowing computation to be
performed at the edge of the network”[1].
Beneficial when data is:
• To sensitive (health data)
• To big (genetic data)
• To competitive (data will expose profile of owner)
• +++
Source: [1] Shi W, Cao J, Zhang Q, Li Y, Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. oktober 2016;3(5):637–46.
The computing entities
• The individual computing process – an “agent”
• One instantiation at each participating Snow server
• One unique communication address for each agent:
agent-user@snow-server-domain/mission_id
• Agents communicates among each other using XMPP messages
• Coordinated computations: “Missions” of multiple agents:
• One “main” coordinating agent
• Multiple computation agents performing computations in parallel
Agent distribution scheme
(Collaborative computations at the edges)
Snow coordinator
Main
agent
Snow server Snow server Snow server
Health network
Comput.
agent
Comput.
agent
Comput.
agent
Health institution Health institutionHealth institution
• A small computer that fits everywhere
• Snow server software is pre-installed
• Very easy installation
• Remote system administration by the Snow
team at UiT / NSE
• Remove the risk of affecting the stability or
performance of operation critical IT systems
– the electronic health record system
• All data in the box is pseudonymised, both
patient and GPs
• Agents compute on the box
Snow appliance box:
The nodes of the
network
11
Data flow in PCRN
Internet Secure health net
GP office 1
Snow
GP
server
EMR
GP office 2
Snow
GP
server
EMR
GP office 3
Snow
GP
server
EMR
Aggregated
data/statistics
Snow
coordinator
server
PCRN net portal
• Distributed data analysis
• Establish projects, invite GPs,
initiate data extraction etc
PCRN internal data
• Epidemiological analyses
• GP and patient data
• Consultation statistics
PCRN CN
Safe haven for data
Research data set
(individual patient data)Secure data storage for
research data set and
advanced data analyses
Local net
= data storage
Using secure multiparty computations to support
research in primary care
Virtualdataset
Creating a virtual dataset with Emnet/Snow
Researcher/PCRN staff Coordinator
Def Def
Def
Def
Clinical
practice 1
Clinical
practice 2
Clinical
practice 3
Aimed at:
1. Make participation in research projects easier and more efficient for the GPs
2. Support researchers in inclusion of sufficient number of patients in clinical research
3. Support article 9 in Helsinki declaration: Privacy preservation
GP tool to identify the eligible patients
Virtualdataset
Distributed statistical computations with Emnet/Snow
Clinical
practice 1
Clinical
practice 2
Clinical
practice 3
Researcher/PCRN staff Coordinator
Query Query
Query
Query
Result
Secure multi-party computation
(SMC)
Aimed at:
1. Support researchers in inclusion of sufficient number of patients in clinical research
Report
database
Virtualdataset
Automated processing
Clinical
practice 1
Clinical
practice 2
Clinical
practice 3
Coordinator
Query
Query
Query
Resultat
Secure multi-party computation
(SMC)
PCRN interne data
Aimed at:
1. Supporting article 6 in the Helsinki declaration: Continuous evaluation
Benefits
• Centralised resources as PCRN staff/researchers can help GPs become more
efficient in research.
• Knowledge about the patient populations can be generated directly from the
distributed sources, spanning administrative borders as municipalities, regions,
countries and continents
• Aggregated (non sensitive) statistics can be produced automatically directly from
the sources.
Drawbacks
• Two other comparable approaches exists, no standard established
• How to validate correctness of computed statistics is an open research question
Thanks for listening
Questions?

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BigInsight seminar on Practical Privacy-Preserving Distributed Statistical Computation

  • 1. The Norwegian Primary Care Research Network IT infrastructure: The Snow system Johan Gustav Bellika Professor Nasjonalt Senter for e-helseforskning Professor II Institutt for Klinisk Medisin, Helsevitenskapelig fakultet, UiT Seminar on Practical Privacy-Preserving Distributed Statistical Computations 2018.03.05 Dr. John Snow (1813 – 1858)
  • 2. Source: WMA Declaration of Helsinki. URL: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/ http://chrisricecooper.blogspot.no/2015/02/photoessay-on-year-of-ram-by-asian.html Declaration of Helsinki, Article 6 The primary purpose of medical research involving human subjects is to understand the causes, development and effects of diseases and improve preventive, diagnostic and therapeutic interventions (methods, procedures and treatments). Even the best proven interventions must be evaluated continually through research for their safety, effectiveness, efficiency, accessibility and quality.
  • 3. Declaration of Helsinki, Article 9 It is the duty of physicians who are involved in medical research to protect the life, health, dignity, integrity, right to self-determination, privacy, and confidentiality of personal information of research subjects. Source: WMA Declaration of Helsinki. URL: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/ Medical research should be privacy preserving!
  • 4. Objectives for the research infrastructure • Make participation in research projects easier and more efficient for the GPs • Reuse health data in a safe and privacy preserving manner • Complete research projects according to scheduled time and resources consumption • Recruit 90-110 GP practices • Cover 7,5 % of the Norwegian population
  • 6. What is Snow? • A distributed system • Enables collection and reuse of anonymous medical data • Builds and maintains a national online epidemiology-model • Use the epidemiology model to provide automated IT based health services • Enable privacy preserving distributed computations on EHR data • Directed at research, quality improvements, audit, disease surveillance,… Source:http://upload.wikimedia.org/wikipedia/commons/f/f6/Vibrio_cholerae.jpg
  • 7. Snow architecture - enables coordinated computations on distributed resources - a “collaborative Edge computing” infrastructure [1] S Coord S S S S ClientCoord=Snow Coordination server S= Snow Server in local health institution Source: [1] Shi W, Cao J, Zhang Q, Li Y, Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. oktober 2016;3(5):637–46.
  • 8. Edge computing “Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network”[1]. Beneficial when data is: • To sensitive (health data) • To big (genetic data) • To competitive (data will expose profile of owner) • +++ Source: [1] Shi W, Cao J, Zhang Q, Li Y, Xu L. Edge Computing: Vision and Challenges. IEEE Internet Things J. oktober 2016;3(5):637–46.
  • 9. The computing entities • The individual computing process – an “agent” • One instantiation at each participating Snow server • One unique communication address for each agent: agent-user@snow-server-domain/mission_id • Agents communicates among each other using XMPP messages • Coordinated computations: “Missions” of multiple agents: • One “main” coordinating agent • Multiple computation agents performing computations in parallel
  • 10. Agent distribution scheme (Collaborative computations at the edges) Snow coordinator Main agent Snow server Snow server Snow server Health network Comput. agent Comput. agent Comput. agent Health institution Health institutionHealth institution
  • 11. • A small computer that fits everywhere • Snow server software is pre-installed • Very easy installation • Remote system administration by the Snow team at UiT / NSE • Remove the risk of affecting the stability or performance of operation critical IT systems – the electronic health record system • All data in the box is pseudonymised, both patient and GPs • Agents compute on the box Snow appliance box: The nodes of the network 11
  • 12. Data flow in PCRN Internet Secure health net GP office 1 Snow GP server EMR GP office 2 Snow GP server EMR GP office 3 Snow GP server EMR Aggregated data/statistics Snow coordinator server PCRN net portal • Distributed data analysis • Establish projects, invite GPs, initiate data extraction etc PCRN internal data • Epidemiological analyses • GP and patient data • Consultation statistics PCRN CN Safe haven for data Research data set (individual patient data)Secure data storage for research data set and advanced data analyses Local net = data storage
  • 13. Using secure multiparty computations to support research in primary care
  • 14. Virtualdataset Creating a virtual dataset with Emnet/Snow Researcher/PCRN staff Coordinator Def Def Def Def Clinical practice 1 Clinical practice 2 Clinical practice 3 Aimed at: 1. Make participation in research projects easier and more efficient for the GPs 2. Support researchers in inclusion of sufficient number of patients in clinical research 3. Support article 9 in Helsinki declaration: Privacy preservation
  • 15. GP tool to identify the eligible patients
  • 16. Virtualdataset Distributed statistical computations with Emnet/Snow Clinical practice 1 Clinical practice 2 Clinical practice 3 Researcher/PCRN staff Coordinator Query Query Query Query Result Secure multi-party computation (SMC) Aimed at: 1. Support researchers in inclusion of sufficient number of patients in clinical research
  • 17. Report database Virtualdataset Automated processing Clinical practice 1 Clinical practice 2 Clinical practice 3 Coordinator Query Query Query Resultat Secure multi-party computation (SMC) PCRN interne data Aimed at: 1. Supporting article 6 in the Helsinki declaration: Continuous evaluation
  • 18. Benefits • Centralised resources as PCRN staff/researchers can help GPs become more efficient in research. • Knowledge about the patient populations can be generated directly from the distributed sources, spanning administrative borders as municipalities, regions, countries and continents • Aggregated (non sensitive) statistics can be produced automatically directly from the sources.
  • 19. Drawbacks • Two other comparable approaches exists, no standard established • How to validate correctness of computed statistics is an open research question