Preauthorization records

Identifies patient prior-authorisation / pre-approval records - authorisation requests, coverage determinations and utilisation or medical-necessity reviews for a named patient - when the phrase sits with populated patient identifiers and authorisation fields. Health and insurance information under applicable data protection regulations.

Type: regex
Engine: boost_regex
Confidence: medium
Confidence justification: Medium: enforce tiers need a populated patient identifier; 85 also needs an authorisation field and decision evidence. Payer policy pages and provider manuals carry the phrases without a patient record and stay at 65.
Detection quality: Not detected
Jurisdictions: global
Regulations: Privacy Act 1988 (Cth), NDB Scheme (Cth), Information Privacy Act 2009 (Qld), GDPR, HIPAA
Frameworks: ISO 27001, ISO 27701
Data categories: healthcare, phi
Scope: wide
Risk rating: 6
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Degraded, Netskope: Unsupported

Pattern

(?i)\b(?:prior\s+authori[sz]ation|pre-?authori[sz]ation|pre-?approval\s+request|insurance\s+authori[sz]ation|coverage\s+determination|medical\s+necessity\s+review|utili[sz]ation\s+review|authori[sz]ation\s+request)\b

Corroborative evidence keywords

approved, denied, pended, appeal, peer-to-peer, units requested

Proximity: 300 characters

Should match

PRIOR AUTHORIZATION REQUEST Patient name: Avery Teston DOB: 04/02/1991 Member ID: HFX44718202 Requested service: MRI lumbar spine CPT code: 72148 Diagnosis code: M54.16 Determination: pended for peer-to-peer review; clinical notes attached — Populated prior authorisation request with patient, authorisation fields and decision evidence (85)
Utilization review note Patient: Casey Rourke MRN: 5540921 Reviewer to contact the treating team tomorrow. — Utilisation review note with labelled patient identifiers only (75)
Hospital pre-authorisation - private health fund Patient: Rowan Achterberg Hospital number: H0772145 Health fund: Coastline Mutual Health Member number: 77310482 MBS item: 49518 Requested procedure: Total knee replacement, right Outcome: approved for 4 days length of stay; excess of $500 applies. — Fund pre-authorisation with patient, hospital number, member number, MBS item and approved decision (85)

Should not match

unrelated generic text without domain phrases — No relevant topic phrases present
placeholder value 12345 — Random text should not match topic-specific regex
patient biometric — Generic word pair from old broad template should not match
Policy guidance: this procedure explains how prior authorization requests are collected, stored and shared, who may access them and how long they are kept. Staff should read the privacy section before completing any form. It contains no details about any individual. — Policy/guidance text naming the topic without any populated record (65 discovery at most)
Prior authorization request form Patient name: ____________________ Date of birth: ____________________ Member ID: ____________________ Requested service: ____________________ Diagnosis code: ____________________ Signature: ____________ Date: __/__/____ — Blank form with unpopulated labelled fields (placeholder guard keeps it below 75)
Training: this session explains when a prior authorization is required, how coverage determination timelines work and how providers lodge an appeal if a request is denied. — News/training prose about the topic without a populated record (65 discovery at most)

Known false positives

Medical terminology in health education materials, research publications, clinical guidelines, or public health documents without patient-specific data. Mitigation: Require corroborative evidence keywords confirming patient context. Look for co-occurrence with patient identifiers such as medical record numbers or dates of birth.
General wellness and fitness content using medical vocabulary without constituting protected health information. Mitigation: Layer with patient identifier patterns or healthcare-specific document structure detection to distinguish clinical records from general health content.