Code review
AuraScore 89/100

Clinical Data Pipeline Code Review Plan

Plan a structured review of clinical data ingestion pipelines for FHIR conformance, PHI isolation, and throughput.

Use this template when preparing pull request assessments for ETL scripts transforming raw EHR data into standardized clinical formats. It helps teams identify data integrity risks and compliance gaps prior to deployment.

Template

Role: Principal Clinical Software Architect specializing in health interoperability and regulatory data governance.

Context

  • Repository under review: {{pipeline_repo_name}}
  • Upstream clinical payload: {{source_data_format}}
  • Standardized target format: {{target_fhir_version}}
  • Data privacy and masking protocol: {{phi_handling_protocol}}
  • Performance baseline: {{throughput_target_rps}}
  • Delivery schedule: {{review_timeframe}}

Task

Generate a structured code review execution plan that guides engineering teams through assessing clinical ingestion logic, schema mapping consistency, and data protection controls before release.

Method

  1. Map out the end-to-end data transformation path from {{source_data_format}} to {{target_fhir_version}} across all changed modules.
  2. Define inspection checks for PHI de-identification and secret storage against {{phi_handling_protocol}}.
  3. Identify high-risk serialization, deserialization, and schema validation routines vulnerable to parsing exceptions.
  4. Formulate deterministic test review criteria to catch silent data truncation and data type coercion errors.
  5. Evaluate concurrency handling, batching mechanisms, and stream buffering to guarantee {{throughput_target_rps}}.
  6. Establish line-by-line review assignments across parser logic, error queues, and audit logging layers.
  7. Synthesize findings into prioritized remediation work items with measurable acceptance gates.

Constraints

  • MUST flag any unencrypted logging or raw payload dumping as a critical blocking issue.
  • MUST NOT approve code that skips schema validation for malformed inputs.
  • All review tasks must fit within {{review_timeframe}}.
  • Keep recommendations actionable with concrete code-level patterns.

Output format

Provide a markdown document with the following exact headers:

  1. Executive Review Objective (max 100 words)
  2. Inspection Phase Matrix (table containing Phase, Target Components, Review Technique, and Owner)
  3. Critical Healthcare Quality Checks (4 to 6 numbered compliance and mapping verification steps)
  4. Risk-Weighted Approval Criteria (bulleted list of release gates)

Self-review

  • Ensure every verification step specifically addresses {{source_data_format}} or {{target_fhir_version}}.
  • Verify that PHI isolation requirements from {{phi_handling_protocol}} are directly reflected in the matrix.
  • Check that the total generated response is comprehensive, practical, and strictly adheres to the output format.
AuraScore breakdown
89/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification14/14 · Strong

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency7/10 · Adequate

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

developers
developers-code-review
healthcare-life-sciences
fhir
phi
clinical-data