2015 “Privacy In Action” Speaker Series

January 28, 2015

Innovative Technologies to Increase Privacy

Dial-in: 1-855-767-1051 and Conference ID: 34619328

PRIVACY AND RECORDS MANAGEMENT

Administrative Items

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PRIVACY AND RECORDS MANAGEMENT

Welcome and Introduction of Speakers

LaShaunne’ DavidDirector, VA Privacy Service

U. S. Department of Veterans Affairs

REPORT TO THE PRESIDENTBIG DATA AND PRIVACY:A TECHNOLOGICAL PERSPECTIVE

May 2014

Charge from President Obama January 17, 2014 speech requesting analysis of big-data implications for

policy

Scoping study, focusing on the wider economy and society

PCAST report to inform and accompany White House report Objectives of the PCAST report

Assess current technologies for managing and analyzing big data and preserving privacy

Consider how such technologies are evolving

Explain what technological capabilities and trends imply for design and enforcement of public policy to protect privacy in big-data contexts

Presidents Council of Advisors on Science and Technology (PCAST)

PCAST Working Group Members & Staff

Susan Graham, Co-Chair, UC BerkeleyWilliam Press, Co-Chair, University of Texas S. James Gates, Jr., University of MarylandMark Gorenberg, Zetta Venture PartnersJohn P. Holdren, OSTP DirectorEric Lander, Broad Institute of Harvard and MITCraig Mundie, Microsoft Corp.Maxine Savitz, National Academy of EngineeringEric Schmidt, Google, Inc.

Marjory S. Blumenthal, PCAST Executive DirectorMichael Johnson, OSTP (NSIA Assistant Director )

Other PCAST Members

Rosina Bierbaum, University of MichiganChristine Cassel, National Quality ForumChristopher Chyba, Princeton UniversityShirley Ann Jackson, RPI Chad Mirkin, Northwestern UniversityMario Molina, UC San DiegoEd Penhoet, Alta PartnersBarbara Schaal, Washington UniversityDaniel Schrag, Harvard University

Changing Technological Contexts

Privacy history conditioned on “small data” Collection of data/development of data sets used w/conventional

statistics

Context of a personal relationship (e.g., personal physician, local shop)

Big data attributes Quantity and variety of data available to be processed (3 Vs) Scale of analysis that can be applied to those data

(“analytics”) Expansion of metadata

Laws have not always kept pace w/technological realities

People Emit Data Continuously . . .

Born digital Generated for computer(s)

Clicks and taps, GPS, cookies

Born analog Byproduct of the physical world

Sensors collect (often invisibly)

Over-collection? Digital convergence?

Big-data analytics create new information Data mining and machine learning

Data fusion and integration (data from different sources)

Image/speech recognition

Social-network analysis (self-censorship won’t help…)

The Cloud as Dominant Infrastructure Easy ingestion, access, and use of data Replication and distribution Infrastructure for mobility (e.g., smart-phone

apps) Potential security benefits from automation,

procedures, oversight Democratization of analytics

Cybersecurity and Privacy: Distinctions and Dependency Cybersecurity: technologies enforce policies for computer

use and communication Systems to protect identity and to authenticate (are you who you

say)

Harder to codify privacy policy for tech implementation

Poor cybersecurity is a threat to privacy, but . . .

Violations of privacy are possible with no failure in computer security Misuse of data, fusion of data

Cybersecurity: necessary but not sufficient

Technologies and Strategies for Privacy Protection

Cryptography and encryption Anonymization and de-identification Data deletion and ephemerality Notice and consent

Areas of Concern: Examples

Healthcare: Personalized medicine (including genetic info); mobile

devices that monitor

Education: New online platforms collect masses of data, enable

longitudinal datasets

Home: More ways of collecting, storing, and communicating

What Might the Future Look Like?

Taylor Rodriguez packs for a trip, leaves suitcase outside home for pick-up Camera on streetlight watches the suitcase, which has an RFID tag (anti-theft)

Her suitcase is picked up at night by delivery company Shipper knows Taylor’s itinerary and plans

Self-driving car arrives, its instructions for her itinerary delivered by the cloud

No boarding passes or queues at the airport Everyone is tracked by phone, facial recognition, gait, emotional state, RFID

tags

In this world, the cloud and robotic aides are trustworthy WRT personal privacy Improvements in convenience and security of everyday life become

possible . . .

Not an endorsement, just food for thought!

PCAST Perspectives and Conclusions

New sources of big data are abundant; new analytics tools will emerge New data aggregation and processing can bring enormous economic and social benefits.

Unintentional leaking of data and deliberate systemic attacks on privacy are potential risks

Cannot always recognize privacy-sensitive data when collected—may emerge w/analytics, may be able to home in on the moment of particularization to an individual

Government role to prevent breaches of privacy that can harm individuals, groups Tech plus law/regulation to generate incentives, contend with measure-countermeasure

cycle

Data collectors, data analyzers, and users of analyzed data as different actors Policy can intervene at various stages of this value chain

Attention to collecting practices may reduce risk, but use is the most technically feasible place to apply regulation

Technological feasibility matters

Recommendation 1: Policy attention should focus more on the actual uses of big data and less on its collection and analysis

Any adverse consequences of big data arise from a program/app interacting with raw data or information refined via analytics

Policies focused on the regulation of data collection, storage, retention, a priori limitations on applications, and analysis (absent identifiable actual uses of the data or products of analysis) are unlikely to yield effective strategies for improving privacy

It is not the data themselves that cause the harm, nor the program itself (absent any data), but the confluence of the two

Recommendation 2: Policies and regulation should not embed particular technological solutions, but rather should be stated in terms of intended outcomes Technology alone is not sufficient to protect privacy To avoid overly lagging the technology, policy concerning

privacy protection should address the purpose—the “what” — rather than prescribe the mechanism—the “how”

Controlling the use of personal data is more effective than regulating technologies of data collection, storage, and retention (these may evolve rapidly)

Recommendation 3: With support from OSTP, the NITRD agencies should strengthen U.S. research in privacy-related technologies and in the relevant areas of social science that inform the successful application of those technologies Some of the technology for controlling uses already exists Research and research funding are needed for (1)

technologies that help to protect privacy, (2) social mechanisms that influence privacy-preserving behavior, and (3) legal options that are robust to changes in technology and create appropriate balance among economic opportunity, national priorities, and privacy protection

Recommendation 4: OSTP, together with the appropriate educational institutions and professional societies, should encourage increased education and training opportunities concerning privacy protection Career paths for professionals (e.g., digital-privacy

experts both on the software-development side and on the technical-management side)

Programs that provide education leading to privacy expertise are essential and need encouragement

Recommendation 5: The United States should adopt policies that stimulate the use of practical privacy-protecting technologies that exist today. It can exhibit global leadership both by its convening power and also by its own procurement practices Nurture the commercial potential of privacy-enhancing

technologies through U.S. government procurement and through the larger policy framework

Promote the creation and adoption of standards Cloud computing offers positive new opportunities for privacy

Privacy-Preserving Cloud Services?

PCAST is not aware of more effective innovation or strategies being developed abroad

White House/“Podesta” Policy Recommendations

1. Advance the Consumer Privacy Bill of Rights

2. Pass National Data Breach Legislation

3. Extend Privacy Protections to Non-U.S. Persons

4. Ensure Data Collected on Students in School is used for Educational Purposes

5. Expand Technical Expertise to Stop Discrimination

6. Amend the Electronic Communications Privacy Act

Questions?

Marjory S. Blumenthal, Executive Director, PCASTmblumenthal@ostp.eop.gov

Lucia SavageChief Privacy Officer

ONC Update and Data Segmentation for Privacy (DS4P) Update

Veterans Administration Data Privacy Day

January 28, 2015

10 Year Interoperability Vision ( fall 2014)

• Leverage health IT to increase health care quality, lower health care costs and increase population health

• Focus on supporting health broadly, including but not limited to health care delivery

• Build incrementally over time from current technology – multiple methods of exchange required

• Establish best minimum possible interoperability for all; create opportunities for innovation

• Empower and maintain focus on individuals

23http://healthit.gov/sites/default/files/ONC10yearInteroperabilityConceptPaper.pdf

Vision for the Decade Ahead – Improvements Due to the Sharing of Interoperable Data

2017Connect Care:

Ensure providers and individuals can send, receive, find and use a

basic set of essential health information

2020Connect for Health:

Expand sources and users of information; Continue improving

quality and lowering cost; Increase automation

Scale broadly

2024Learning Health System:

Precision medicineReduce time from evidence to

practiceVirtuous learning cycle

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Core technical standards and functions

Certification to support adoption and optimization of health IT products & services

Privacy and security protections for health information

Supportive business, clinical, cultural, and regulatory environments

Rules of engagement and governance

Data Segmentation for Privacy (DS4P)

• Goal:– Develop technical standards, develop use case, and pilot use case

testing whether:• Patient choice to disclose, or not, information regulated by 42 CFR Part 2

(substance abuse treatment at a federally regulated facility), can be captured, documented and persisted electronically.

Office of the National Coordinator for Health Information Technology

• Purpose of Use: – Defines the allowed purposes for the disclosure (e.g. Treatment, Emergency

Treatment etc).

• Obligations:– Refrain Codes: Specific obligations being placed on the receiving system (e.g. do

not re-disclose without consent)

• Confidentiality Codes:– Used by systems to help convey or enforce rules

regarding access to data requiring enhanced protection. Uses “highest watermark” approach.

Types of Privacy Metadata used by DS4P

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Selected Standards

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STANDARD: HL7 Implementation Guide: Data Segmentation for Privacy (DS4P), Release 1(Includes Content Profile, Profile for Direct, Profile for exchange)

Capability Standards/Profiles used by the HL7 DS4P R1 Standard

Specific Usage

Metadata Vocabularies (for Transport and/or Document Metadata)

HL7 RefrainPolicy Conveys specific prohibitions on the use of disclosed health information (e.g. prohibition of redisclosure without consent)

HL7 PurposeofUse Conveys the purpose of the disclosure of health information (e.g. treatment, research, emergency)

HL7 BasicConfidentialityCodeKind Used to represent confidentiality codes associated with disclosed health information (e.g. restricted) as specified in the HL7 Healthcare Security Classification standard (HCS).

HL7 ObligationCode Used to convey specific obligations associated with disclosed health information (e.g. encryption)

HL7 ActPolicyType Used to convey a type of policyHL7 SensitivityPrivacyPolicy Used to convey the sensitivity level of a specific policy

• HL7 normative standard which has been approved by ANSI May 2014• Standards facilitate tagging at document and section level

• ONC pilots tested at document level

DS4P Standards

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DS4P PILOT ACCOMPLISHMENTSData Segmentation for Privacy Initiative

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NETSMART Pilot:

• The Netsmart DS4P Part 2 solution has been implemented with the community services referral network in Tampa Bay (2-1-1 system), helping them manage restricted data associated with programs regulated by 42 CFR part 2.

Pilot Accomplishments

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VA/SAMHSA Pilot:

• The pilot was successfully tested and demonstrated in multiple venues, including the Interoperability showcase at HIMSS 2013 and the HL7 Plenary meeting in Baltimore, September 2013.

• VA have extended the DS4P capabilities to demonstrate utilization of FHIR for DS4P (demonstrated at HL7 in Jan 14, in real time, using resources from Australia, Canada and USA).

Pilot Accomplishments

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HITPC Recommendations re Incorporating Standards into EHRs

• Context– ONC contemplating expanding certification program to “voluntary”

EHRs for Behavioral Health and Long Term and Acute Care• No MU incentives• Aim of promoting exchange of data with primary care providers

Office of the National Coordinator for Health Information Technology

Questions?

PRIVACY AND RECORDS MANAGEMENT

Thanks for Attending!

• Thank you for attending the first of four 2015 VA Privacy Service “Speaker Series.” – We value your feedback, opinions and comments! – After this session, you will receive a short questionnaire via email. Please take a moment to

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