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Table 4 Heuristics to identify names, with entirely fictitious examples, as they would appear in the source record and CRIS output

From: Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records

 

Algorithm to identify names

 

<beginning > <name term > <optional_name_delimiters > <optional_s > <end >

Source record

<beginning>

< name term>

< optional_name_delimiters>

< optional_s>

<end>

CRIS de-identified output

…replaced. Mark will also be able…

.(space)

Mark

None

None

(space)

…replaced. ZZZZZ will also be able…

…knowing Mark’s diagnosis…

(space)

Mark

‘

S

(space)

…knowing ZZZZZ diagnosis…

…7)Mark is compliant…

)

Mark

None

None

(space)

…7)ZZZZZ is compliant…

…OMark is compliant…

No beginning identified

None

None

None

None

…OMark is compliant…

…was awarded 9 mark out of 30 in…

(space)

mark

None

None

(space)

…was awarded 9 ZZZZZ out of 30 in…

…Nurse informed Mark. Earlier…

(space)

Mark

None

None

.

…Nurse informed ZZZZZ. Earlier…

…Marik will be attending…

(space)

None identified due to misspelling

None

None

None

…Marik will be attending…

…O’Mark is at the…

O’

Mark

None

None

(space)

…ZZZZZ is at the…

…his father, John, was also present…

, (space)

John

,

None

(space)

…his father, QQQQQ, was also present…