ECAPEvidence Completeness Audit Platform

Evidence Completeness Audit Platform

Confidence begins with complete evidence.

ECAP evaluates whether published clinical findings sufficiently represent what was established, measured, and committed to in the underlying study record.

The platform is being developed to assess reporting completeness before evidence is relied upon in scientific, regulatory, healthcare, or computational decision contexts.

Patent pending
NSF I-Corps
NSF SBIR · Phase I proposal invitation
Active R&D

The Evidentiary Gap

A publication may not fully represent the underlying study record.

Published clinical evidence is often relied upon as the accessible representation of a study, yet that representation may be incomplete.

Established appraisal methodologies assess study design and methodological quality, but they do not determine whether the published literature completely and consistently reflects the underlying study record.

ECAP establishes evidence completeness as a record-level standard for evaluating published clinical evidence.

Evidence completeness

The construct at the center of the ECAP research program.

Evidence completeness is the extent to which the available evidentiary record sufficiently represents the information required for a defined scientific, regulatory, or healthcare use.

Completeness is decision-specific rather than exhaustive: the same evidence may be sufficient for one use and insufficient for another.

A record-level characteristic

Evidence completeness complements study-level appraisal by evaluating the evidentiary record as a whole.

Decision-specific sufficiency

Sufficiency is interpreted relative to intended use and decision context.

ECAP
Evidence Completeness Audit Platform

The platform

Evaluating completeness across the clinical evidence record.

ECAP is being developed to evaluate whether published clinical evidence sufficiently and consistently represents the underlying study record.

The platform is intended to surface material gaps, inconsistencies, and limitations that may affect how confidently the published evidence can be interpreted or relied upon.

ECAP complements established scientific appraisal by adding a record-level evaluation of evidentiary completeness.

The objective is to determine whether the published evidence is sufficiently complete for its intended use.

Potential applications

Decision environments where evidence completeness can affect interpretation and reliance.

Regulatory Review

Examining whether the published evidentiary record is sufficiently complete for scientific and regulatory interpretation.

Coverage & Reimbursement

Characterizing evidentiary sufficiency for coverage, formulary, and reimbursement decisions.

Evidence Synthesis

Assessing record-level completeness alongside conventional retrieval and study-level appraisal.

Clinical AI Assurance

Evaluating whether the clinical evidence supporting development, testing, governance, or assurance is sufficiently complete for its intended use.

Program milestones

Active research and validation

ECAP is advancing through technical validation, structured customer discovery, and expert review.

Intellectual Property

Patent Pending

ECAP is the subject of a pending patent application.

National Science Foundation I-Corps

Structured Customer Discovery

Commercial hypotheses are being tested through structured stakeholder interviews.

National Science Foundation SBIR

Phase I Proposal Invitation

InterConnect Techs has been invited to submit a full Phase I proposal for merit review.

The invitation does not constitute an endorsement, funding commitment, award, or affiliation by the National Science Foundation.

Project Leadership

Research Direction & Governance

ECAP is directed by JoVonna Grayson-Kirkland, Principal Investigator, drawing on nearly two decades of leadership across audit programs, enterprise quality systems, regulatory process improvement, and FDA-regulated operations.

The platform is being advanced as an interdisciplinary research initiative spanning clinical evidence, biostatistics, and technical development.