Prior authorization decisions combine patient, coverage, provider, service, policy, and clinical evidence data. A defect in any one domain can lead to rework, an incorrect requirement, or an unsupported submission.
Define quality in workflow terms
Completeness alone is not enough. Data must also be correct, timely, consistent, uniquely identified, and fit for the criterion being evaluated.
Create checks at intake and again before submission because coverage, orders, and clinical information can change during the case.
- Resolve patient and coverage identity.
- Validate codes and terminology systems.
- Evaluate status and effective dates.
- Preserve source and transformation history.
- Surface conflicts instead of overwriting them.
Assign ownership by data domain
Clinical, registration, pharmacy, payer, and interface teams may own different inputs. Route defects to the team able to correct the source rather than repeatedly patching downstream copies.
Track recurring failures by source system and field to prioritize remediation.
Make uncertainty visible
Represent unknown, absent, stale, and conflicting values differently. These states drive different next actions and should not collapse into a blank field.
Monitor how data quality affects manual touches, pends, denials, and turnaround. That connects technical cleanup to operational value.