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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…