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TissueQA matched to an existing eligibility workflow
A high-volume tissue bank processing multiple tissue types needed TissueQA fitted to their specific SOPs and review stages, without requiring medical directors to change how they work.
The context
Large tissue banks operate at a scale that amplifies the cost of every inefficiency in the eligibility review workflow. This organization processes musculoskeletal tissue, cardiovascular tissue, and skin across a high volume of donors. Their medical directors review eligibility determinations that require pulling findings from donor charts, serology reports, physical assessment records, and the organization's own SOPs, often across dozens of pages per case.
The challenge was not that the organization lacked a rigorous review process. They had one. The challenge was that the review relied on coordinators to compile and surface the relevant information, and the compilation step did not leave a structured record. A coordinator would work through a donor record, identify relevant findings, and present them to the medical director. The AI output and the human decision existed separately, or not at all in structured form.
The question this engagement explored: could TissueQA be configured to match the organization's specific eligibility SOPs and deliver a cited summary to the medical director, without disrupting how reviewers already work?
What we configured
The organization's eligibility criteria are their own. They reference external standards but their SOPs interpret and extend those standards in ways specific to their tissue types, donor populations, and processing methods. A generic TissueQA configuration would not reflect that.
The configuration mapped the organization's eligibility SOPs section by section, covering musculoskeletal, cardiovascular, and skin tissue types with separate matching rules where criteria diverge. Extraction fields were configured to pull the values their SOPs actually require, not a superset of all possible donor data points. PARTIAL flag thresholds were established to reflect their review standards: which gaps are escalation-required, which are acceptable with documentation, and which are disqualifying.
Citation links were connected so every finding in the TissueQA summary points to the specific source page in the donor chart or serology report. The existing review stages were preserved, with TissueQA positioned as a structured pre-summary that arrives before the medical director opens the full chart.
Capabilities deployed
- TissueQA donor record ingestion across multiple tissue type configurations
- SOP matching against the organization's specific eligibility criteria for musculoskeletal, cardiovascular, and skin tissue
- Citation links from every finding to the source document and page number
- PARTIAL flag surfacing for incomplete or ambiguous fields before the case reaches the medical director
- Reviewer override capture with the override reason recorded against the AI recommendation
- Medical director sign-off screen with AI summary, source citations, and electronic signature capture
- Audit trail recording AI output, coordinator review, and qualified human decision for every case
What the workflow now supports
The organization's medical directors receive a structured eligibility summary before opening the full donor chart. Every finding the summary contains has a citation. Partial or missing data is flagged explicitly rather than surfacing mid-review. Reviewer overrides are captured with the reason, creating a record of where the AI recommendation and the qualified human judgment diverged and why.
The configuration is theirs. Another tissue bank reviewing the same donor types with different SOPs would produce a different configuration. TissueQA does not normalize eligibility criteria across organizations. It runs each organization's own criteria against each case, and records the result alongside the human decision that follows.
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