THE REB Wizard Tool Khaled El Emam, CHEO RI & uOttawa Context - - PDF document

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THE REB Wizard Tool Khaled El Emam, CHEO RI & uOttawa Context - - PDF document

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THE REB Wizard Tool Khaled El Emam, CHEO RI & uOttawa Context There are two general scenarios for de- Th t l i f d identification: Before data is collected a decision needs to be made about whether the collected data is

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THE REB Wizard Tool

Khaled El Emam, CHEO RI & uOttawa Th t l i f d

Context

  • There are two general scenarios for de-

identification:

– Before data is collected a decision needs to be made about whether the collected data is de-identified – Data is available and it will be used or

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

Data is available and it will be used or disclosed and needs to be de-identified beforehand

  • Our focus today is on the first one
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Di tl id tif i

Variable Distinctions

  • Directly identifying

– Can uniquely identify an individual by itself

  • r in conjunction with other readily

available information

  • Quasi-identifiers

– Can identify an individual by itself or in

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

– Can identify an individual by itself or in conjunction with other information

  • Sensitive variables

N dd t l h b f

Examples of Direct I dentifiers

  • Name, address, telephone number, fax

number, MRN, health card number, health plan beneficiary number, license plate number, email address, photograph, biometrics, SSN, SIN, implanted device number

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

implanted device number

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SLIDE 3

3 d t f bi th hi l ti ( h

Examples of Quasi-I dentifiers

  • sex, date of birth or age, geographic locations (such

as postal codes, census geography, information about proximity to known or unique landmarks), language spoken at home, ethnic origin, aboriginal identity, total years of schooling, marital status, criminal history, total income, visible minority status, activity difficulties/reductions profession event

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

activity difficulties/reductions, profession, event dates (such as admission, discharge, procedure, death, specimen collection, visit/encounter), codes (such as diagnosis codes, procedure codes, and adverse event codes), country of birth, birth weight, and birth plurality

M ki

Methods

  • Masking

– Deals with the directly identifying variables

  • De-identification

– Deals with the quasi-identifiers

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

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S i

Masking - I

  • Suppression

– Removal of directly identifying fields

  • Pseudonymization

– Replace direct identifiers with unique keys that cannot be reversed

R d i ti

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • Randomization

– Replace direct identifiers with random values (eg, random names, MRNs, telephone numbers, postal codes)

Addi N i

Masking - I I

  • Adding Noise

– Sometimes people add noise to data – This is risky because filters can be applied to the data to remove the noise and recover the original signal

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

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R i d dd f

Masking is not enough

  • Removing names and addresses from a

data set does not de-identify it

  • It is possible to re-identify individuals

using residual information, such as date of birth and postal code d h d

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • Consider uniqueness in the Canadian

population … .. Th i l t i i d

Getting Demographics

  • The simplest scenario is an adversary

who is a nosey neighbor, co-worker, relative, ex-spouse who gets hold of the data

  • It is also possible to get that

information from public sources

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

information from public sources

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C di bli f

Examples of Public Sources - I

  • Canadian public sources of

demographics:

– Obituaries: available from newspapers and funeral homes; there are obituary aggregator sites that make this simple – PPSR: Private Property Security

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

PPSR: Private Property Security Registration; contains information on loans secured by property (e.g., cars) – Land Registry: information on house

  • wnership

M b hi Li t id h i li ti f

Examples of Public Sources - I I

  • Membership Lists: provide comprehensive listings of

professionals (e.g., doctors, lawyers, civil servants)

  • Salary Disclosure Reports: provided by governments

for those earning higher than a certain threshold

  • White Pages: public telephone directory
  • Job Sites: CVs posted in public and closed job web

sites

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • Donations: Disclosures of donations to political parties

(include address)

  • Sports Rosters: Include detailed information about

team members

  • Facebook: Individuals, especially teenagers, post a

considerable amount of information on-line

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C t l ll b d f

Voter Lists - I

  • Cannot legally be used for purposes
  • utside of an election (in Canada)
  • But, a charity allegedly supporting a

terrorist group (Tamil Tigers) was found by the RCMP to have Canadian voter lists

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • Volunteers do not necessarily destroy
  • r dispose of the lists after an election

(and in many cases do not sign anything before they get them) It i t i ( diffi lt) t

Voter Lists - I I

  • It is not expensive (or difficult) to

become a candidate in an election and get the voter list:

– Alberta: $500 – BC: $100 – NB: $100 (+ nominated by 25 electors)

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

– Ontario: $100 – Quebec: 0$ (+ nominated by 100 electors)

  • Canadian voter lists do not contain the

DoB

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I th f ll i lid I ill l i

Public Registries

  • In the following slides I will explain

how to use public sources to create demographic profiles of individuals

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

Professional Groups - I

W t t id tifi ti d t b f ifi We can construct identification databases for specific professional groups

Membership Lists PPSR

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

White Pages

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  • College of Physicians and Surgeons of Ontario

Professional Groups - I I

  • College of Physicians and Surgeons of Ontario
  • Law Society of Upper Canada
  • Professional Engineers Ontario
  • College of Occupational Therapists
  • College of Physical Therapists
  • Public servants (eg, GEDS)
  • …

… .

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

What is the success rate ?

CPSO LSUC

  • Ability to get home postal codes (source: PPSR and

telephone directory) 60% 45%

  • Ability to get practice/firm postal codes (source:

CPSO/LSUC) 100% 100%

  • Ability to get date of birth (source: PPSR)

40% 45%

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

y g ( )

  • Ability to get gender (source: CPSO/genderizing

LSUC) 100% 100%

  • Ability to get initials (source: CPSO/LSUC)

100% 100%

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What is the success rate by gender?

CPSO LSUC MALE

  • Ability to get home postal codes (source: PPSR and

telephone directory) 63% 48%

  • Ability to get date of birth (source: PPSR)

45% 48% FEMALE

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

FEMALE

  • Ability to get home postal codes (source: PPSR and

telephone directory) 49% 40%

  • Ability to get date of birth (source: PPSR)

29% 40%

Homeowners

W t t id tifi ti d t b f ifi

Land Registry PPSR Canada Post

  • We can construct identification databases for specific

postal codes

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

White Pages

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What is the success rate ?

Ott To

  • Ability to get initials

93% 100%

  • Ability to get DoB

33% 40% Ability to get telephone number 80% 50%

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • Ability to get telephone number

80% 50%

  • Ability to get gender

87% 95%

  • The number of households per postal

Re-id Risk for Homeowners

  • The number of households per postal

code is quite small (Ott: 15; To: 20)

  • The individuals (homeowners) were

unique on common combinations of quasi-identifiers (eg, gender and DoB) For these individuals re identification

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

  • For these individuals re-identification

risk is very high

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  • GEDS is on the Internet: Government

Civil Servants - I

  • GEDS is on the Internet: Government

Electronic Directory Services

  • There are 386,630 individuals in the

federal government and GEDS has

  • approx. 170,000 entries
  • Incomplete because: organizations can

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

p g

  • pt-out, some individuals need to opt-

in, and some employees and orgs are exempted (eg, CSIS, DND)

  • We selected a sample of 40 individuals

Civil Servants - I I

  • We selected a sample of 40 individuals

in health care related federal departments in Ontario

  • Able to get home address for 50% ,

home telephone number for 40% , gender for 100% DoB for 22 5%

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

gender for 100% , DoB for 22.5%

  • Provincial governments have similar

sources

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Example Protocol

  • Consider a protocol with basic demographics about

p g p the patients:

– Age – Gender – Language spoken at home – Visible minority status

  • The REB Wizard tool is here:

Electronic Health Information Laboratory, CHEO Research Institute, 401 Smyth Road, Ottawa K1H 8L1, Ontario; www.ehealthinformation.ca

The REB Wizard tool is here:

http://www.ehealthinformation.ca/rebwizard/ca/

www.ehealthinformation.ca

www.ehealthinformation.ca/ knowledgebase

kelemam@uottawa.ca