Download De-Identification

De-Identification
Privacy in Organizational
Processes
Patient
medical bills
Hospital
Aggregate
anonymized
patient
information
Patient
information
Insurance Company
Complex Process
within a Hospital
Drug Company
Advertising
PUBLIC
Patient
Transfer and Use Between
Organizations
Achieve organizational purpose while
respecting privacy expectations in the transfer
and use of personal information (individual
and aggregate) within and across
organizational boundaries
We Use the Health Data for
Research in Many Aspects
Two Swords in Health Research
• Informed Consent Form
• De-Identification
目前臨床研究兩種方式，可以說服
IRB 和社會大衆，它們是有盡到人身
和資料保護的方法
第一種方式，就是受試者簽署 ICF，
讓受試者(被研究者)預先或有條件的
放棄他們本應擁有權力的隱私。
第二種方式，是讓研究者無法透過
資料的比對獲得受試者個人的病歷資
料，進而傷害受試者的隱私。
HIPAA Background
• Commercial Healthcare Insurance
• Pharmaceutical Benefit Maker
(Intruder)
• Health Maintain Organization
holding hospitals’ stock share or
M&A hospitals
• Research Fraud and Scandal of
Clinical Trials
• Who can market our medical
record data?
Health Insurance Portability and
Accountability Act
•
•
•
HIPPA, enacted by US Congress in 1996
Title I: Health Care Access, Portability, and Renewability
Title II: Preventing Health Care Fraud and Abuse;
Administrative Simplification; Medical Liability Reform
1.
2.
3.
4.
5.
•
Privacy Rule
Transactions and Code Sets Rule
Security Rule
Unique Identifiers Rule
Enforcement Rule
HITECH Act: Privacy Requirements
ICF 的範本(KUSO版)
願參加 XXX 藥品的臨床試驗
如有生死，各安天命
受試者 X X X
De-Identification and
Re-Identification
–婦產科醫師
–慈濟醫院
–人體試驗審議委員會
–企業管理博士
–醫管系助理教授
–林錦鴻
What items are prohibited for
disclosure ?
HIPAA Privacy Rule and Research with
De-identified Information (1)
(1) Names
(2) All geographic subdivisions smaller than a State,
including: street, city, county, precinct, zip code - the first
three digits of the zip code can be used if this geocode
includes more than 20,000 people. If such geocode is less
than 20,000 persons, "000" must be used as the zip code.
(3) All elements of dates (except year) related to an
individual, including birth date, admission date, discharge
date, date of death. For individuals > 89 years of age, year
of birth cannot be used - all elements must be aggregated
into a category of 90 and older.
HIPAA Privacy Rule and Research with
De-identified Information (2)
(4) Telephone numbers
(5) FAX numbers
(6) Electronic mail addresses
(7) SSN
(8) Medical record numbers
(9) Health plan beneficiary numbers
(10) Account numbers
(11) Certificate/license numbers
(12) Vehicle identifiers and serial numbers, including license plates
(13) Device identifiers and serial numbers
(14) Web universal resource locators (URLs)
(15) Internet protocol (IP) address
(16) Biometric identifiers, including finger and voice prints
(17) Full face photos, and comparable images
(18) Any unique identifying number, characteristic or code and
Following the HIPAA Regulation
• Is it really a safe procedure to “deidentification” ? ( Yes or No )
• Are you sure that researchers can proceed
their research after deleting these tags or
codes ( Yes or No )
王X明
A 報紙
王小 x
B 報紙
X 小明
C 報紙
王小明
Re-Identification
Example
• To track those subjects of cervical cancer by
comparing the ICD9 and SCC data ( Date,
Tag and Result )
• Age and Location (Place) are very important
influencing factors. Will this data-linkdecoding spoil your research?
Categories of variables in a data set
• Directly Identifying Variables
• Quasi-identifiers
• Sensitive variables
– Sensitive Variable : like the financial or health
status of an individual.
– How many sensitive variables are allowed in a
limited database ?
Direct Identifiers
• Direct Identifiers are which can directly
link to a subject personal data by public
data information infrastructure.
Name, Account Number, Medical Record
Number, ID Number …..
In-direct Identifier (Quasi)
• Location
(Address, Zip-Code)
• Communication Identifier
( Telephone, FAX)
• Internet Identifier
( IP, Email, Machine Code )
• Any unique identifying number,
characteristic or code
Quasi-Identifier
• Date of Birth (DoB)
• DoB – Month and Year
• Day, Month and Year of Admission, Discharge or
Operation
• Gender
• Initials
• Address
• City
• Region
• Postal Code
The Difference
• Anonymous
• Confidential
• De-identified
The IRB often finds that the terms anonymous, confidential,
and de-identified are used incorrectly. These terms are
described below as they relate to an individual’s participation
in the research and the way that their data are collected and
maintained for analysis.
Anonymous
• It is impossible to know whether or not an
individual participated in the study directly.
• A study participant who is a member of a minority
ethnic group might be identifiable from even a
large data pool.
• Information regarding other unique individual
characteristics (indirect identifiers) might make it
possible to identify an individual from a pool of
dataset.
Example A
• Taiwan Health Insurance Claim Data Set
for Physician Behavior of Prescription in
Commercial Use (PBMs know which
physician prescribed their medications)
Confidential
• The research team is obligated to protect the data
from disclosure outside the research according to
the terms of the research protocol and the
informed consent document.
• In order to protect against accidental disclosure,
the subject’s name or other identifiers should be
stored separately from their research data and
replaced with a unique code to create a new
identity for the subject.
• Note that coded data are not anonymous.
Example B
• Use distrust or conflict mechanism between
different individuals or branches
• Congressmen and Officers
• Accounting and Financial Branch
• Market and Sale
• IRB and Researcher
De-identified
• When any direct or indirect identifiers or
codes linking the data to the individual
subject’s identity are destroyed.
Data have been de-identified. There were no risk
to re-identify. However, in the research aspect,
there were a lot of details and facts would be
ignored and loosed.
Safe
Limited
De-Identified
Confidential
Anonymous
Re-Identification
• Re-Link with some identifier or quasiidentifier to access original identification.
• Evaluation the risk of re-identification is an
attitude or consensus for a reviewer.
Limited or De-Identified
• Contract or not ?
– (Non-Disclosure Agreement)
• Regulation or not ?
• Expiated or Full Board ?
• Preservation or Time Period Available ?
– Indefinite
– With Date to be Expired
• Database Access Committee ?
• Database Administrator ?
Heuristics
A Perfect Data Security
Management & Infrastructure
IRB Role and Review FAQ
Are subjects identifiable by their
age, gender, and residence ?
原住民、少數族群、特殊疾病，能夠透過不同
資料庫的比對，讓受試者或被研究者的個人資
料重新再被連結。
某些研究需要年紀、性別和居住地的資料，年
紀可以限制在一定的 Interval，如 10年、5年
為一個單位，ZIPCode 要重新編碼
Can a person be re-identified
from their diagnosis code ?
• Many data sets also include diagnosis codes (for
example, ICD-10 codes).
• Hospital medical record abstract data is almost
publicly available.
• A set of diagnosis codes can make an individual
very unique.
• Some of the records in the disclosed data set have
diagnosis codes for rare and visible
diseases/conditions
Can a claim database be used for
re-identification ?
• A lot of literature makes the point that
claim database can be used for reidentification. However, the accuracy of this
statement will depend on your jurisdiction.
• Other sources of public information they
can still be very useful for re-identification.
Can individuals be re-identified
from disease maps ?
Do these maps risk identifying any
of the individuals ?
• There are three questions that need
to be answered to determine the risk:
1. Is the disease visible ?
2. Is the disease rare in the geography ?
3. If I re-identify an individual, will I
learn something new about them ?
Can postal codes re-identify
individuals ?
• 5 codes are the smallest geographic unit that is used
by Taiwan post to deliver mail. In a health care
context they are the most common geographic unit
because that is what patients know and are able to
provide.
• The postal code is the only demographic information
that is being disclosed in this data set.
• The smallest postal codes in all provinces and
territories have very few people living there. Any
information about the postal code would pertain to a
very small number of individuals.
Definition of identifiable dataset
if a person can find their record(s)
in the dataset
• Who is most sensitive to a data deidentification ? (Individual or reviewer)
• Best de-identification of dataset is that a
individual cannot point out his/her record.
How can I de-identify
longitudinal records ?
• Time Series Record is just a DNA (unique)sequential dataset.
• It can easily re-identified.
• It should be considered a limited database.
• Intervals are less likely to be unique than
actual dates.
How can I safely release data to
multiple researchers?
•
•
•
•
•
Re-numbering
Re-ranking
Different Sampling
Shuffle your data before disclosure
Strong dis-incentive to match the two data
sets
• Change (Say 0.4 to 40%, English style to
metric)
Is sampling sufficient to deidentify a data set ?
• Not only statistical significance but also risk
re-identification would be taken into
consideration.
• Intruder may not know their target within
disclosure database
• Sampling fraction if it is higher ? (Similar
as public database)
Is there a secondary use market
for health information ?
•
•
•
•
Yes or No
Pharmaceutical Benefit Maker
Private Health Insurance Service
Other service ( Women and Children)
Should de-identified data go
through a research ethics review ?
• In the first approach the IRB form has a checkbox
question asking the investigator if the data is deidentified. (UM forms)
• If the investigator checks that box then the IRB does
not review the protocol and it is automatically
approved.
• The reasoning is that it is de-identified data and
therefore there is no requirement to review the
protocol.
Should IRBs decide if a data set
is de-identified ?
• Yes or No ? (No)
• We don’t have a privacy expert.
• Whether a particular data set is identifiable,
and resolving any re-identification risk
concerns is iterative.
• If these interactions are attempted they can
be very slow and consequently frustrating.
Should we de-identify if
technology is moving so fast ?
• Re-Identification technology moves faster
than De-Identification
–道高一尺，魔高一丈
• Educations for data security is cheaper than
new technology.
• High technology stands for high risk
The difference between
consenters and non-consenters
• Secondary use of previous dataset which is
contributed from previous consenter. (對原提供者
有益)
• Should the data of drop out consenter would be
included (Consenter 是否認同提供)?
• Were there any words of consent to use his/her
personal information found in the ICF. (Usually,
to agree specimen but no personal Information)
• Non-consenter would be reviewed by a data access
center or the privacy expert. (沒有同意資料使用)
The five levels of identifiability
• Level 1. The full data set as is.
• Level 2. The names are replaced by fake names, the health
insurance number is replaced with a fake number, and the
street address field is removed altogether.
• Level 3. The data set at Level 2 also has the postal code
generalized from six characters to five characters. The risk
at Level 3 is the same as Level 2, but the organization
believes it has de-identified the data and discloses it.
Therefore, the organization is exposed.
The five levels of identifiability
• Level 4. The data set at Level 3 is further modified
by replacing the 5 digit postal code with a single
character postal code, the date of birth is replaced
by age, and the date of visit is replaced by the
month of the visit. A re-identification risk
assessment is then performed on this data set and
the risk was found to be below a pre-specified
threshold.
• Level 5. The number of individuals with a sexually
transmitted disease.
What are the quasi-identifiers that I
should use for managing risk ?
(Neighborhood)
• Address and telephone information about the target
individual
• Household and dwelling information (number of children,
value of property, type of property)
• Key dates (births, deaths, weddings, admissions,
discharges)
• Visible characteristics: gender, race, ethnicity, language
spoken at home, weight, height, physical disabilities
• Profession
What are the quasi-identifiers that I
should use for managing prosecutor
risk ? (Ex-Spouse)
• The same things that a neighbor would
know
• Basic medical history (allergies, chronic
diseases)
• Income, Years of schooling
What de-identification software
tools are there ?
• The PARAT tool from Privacy Analytics
implements comprehensive risk management for
three types of identity disclosure risk.
• mu-Argus, developed by the Netherlands national
statistical agency.
• The Cornell Anonymization Toolkit (CAT)
implements a k-anonymity algorithm.
• The University of Texas at Dallas Anonymization
Toolbox
Who cares about my medical
records ? (Finance)
• Some medical records have financial information
in them (e.g. information used for billing purposes)
• For example, date of birth, address, and mother's
maiden name. It is used as pin or password
frequently.
• Even if medical records do not have information
in them that is suitable for financial fraud, if your
record has information about your health
insurance then it can be very valuable.
Who cares about my medical
records ? (Media)
• If you ever become of interest to the media and they want
to do a story on you or your family, then reporters may be
interested in re-identifying records about you.
• Medical records are a good source of revenue if you are in
the extortion business.
• Even if there is no financial impact, some people feel
violated if there is a breach of privacy of their medical
information and change their behavior by adopting
privacy protective behaviors.
• There are a number of attempts to make your health
information publicly (or at least very widely) available.
Other researchers’ questions
• What genes predict better prognosis or
response to treatment?
• Can study these questions using cancer
registries, claims data
61
Ethical questions
1. May you share (coded genomewide) data with other researchers?
2. May you use (coded genome-wide)
data for additional research without
consent?
3. May you do whole genome
sequencing on existing coded
samples without consent?
62
Ethical concerns
4. May you follow participants as prospective
cohort using medical records without
consent?
–
With identifiers can link to cancer registry, Medicare
claims databases
63
Federal regulations on human
subjects research
• IRB review
• Informed consent
• Not apply if
– Researcher not interact with participant AND
– Information not “identifiable”
64
What are de-identified data?
• 18 HIPAA specific identifiers
– Overt identifiers, including SSN,
medical record number
– Geographic data more precise than
first 3 digits of zip code
– Dates except for year
– Biometric identifiers
– Any other unique identifying
characteristic
65
Ethical issues
1. Informed consent
–
When giving broad permission for future
research, do donors appreciate
•
•
Whole genome sequencing?
Very sensitive downstream research?
66
Sensitive research projects
• Some donors may object to research
– Genetics of antisocial behavior
– Human evolution
– Beliefs about group ancestry
67
Ethical issues
2. Privacy and confidentiality
–
Heightened concerns, particularly about whole
genome sequencing
68
Special concerns about genetic
confidentiality
• Information considered particularly sensitive
– About relatives and groups
– Highly predictive of future illness
• “Future diaries”
69
Genetic Information
Nondiscrimination Act (2008)
• Remove barriers to genetic testing
• Health insurers may not
– Use genetic information to set eligibility or
premiums
– Require or request genetic testing
70
Genetic Information
Nondiscrimination Act (2008)
• Employers may not
– Use genetic information in employment or
promotion decisions
– Require or request genetic testing
71
Limitations of GINA
• After job offer, employer may request medical
records
– Impractical to delete genetic information
• Not apply to disability, life, long-term care
insurance
– Adverse selection if individual rating
72
HIPAA fails to protect privacy
• Weak security protections
• Applies only to “covered entities”
– Protection does not follow information technology
advancing
73
Thanks for Your Attention