Audit is a cutting edge, systematic approach that blends advanced analytics, AI, and clinical best practices to uncover missed opportunities in patient care. By scouring historical patient records - from structured lab results and imaging data to unstructured clinical notes - Audit delivers actionable insights that empower healthcare providers to elevate care quality, reduce errors, and enhance patient outcomes.
Consolidate information from disparate sources - structured data like prescriptions, ICD codes, lab results, imaging studies, and unstructured data such as clinical notes and discharge summaries - into one comprehensive system.
Ensure consistency across patient records by standardizing terminologies using established vocabularies such as ICD-10l SNOMED CT, and LOINC continuity.
Seamlessly integrate with your existing electronic medical records (EMRs) and hospital information systems, ensuring smooth data exchange and workflow continuity.
Embed evidence-based guidelines (USPSTF, AHA, etc.) to establish benchmarks for optimal care—such as timely follow-ups on abnormal lab results or recommended screening intervals.
Identify and monitor metrics like delayed diagnoses, omitted follow-ups, and deviations from best practices that signal potential missed opportunities.
Develop scoring systems to flag patients who might have benefited from earlier interventions, such as those at risk for cardiovascular events or diabetic complications.
Parse free-text clinical notes to extract crucial details like symptom descriptions, clinician impressions, and contextual cues. Detect subtle indications of patient status that might not be evident in structured data.
Recognize patterns correlated with adverse outcomes, highlighting when a clinical pathway deviated from established guidelines. Evaluate the timeline of care events to pinpoint delays or gaps—such as an abnormal test result not acted upon within the expected window.
Spot outliers in treatment timelines, lab follow-ups, or care transitions that suggest gaps in care.
Compare cohorts with favorable outcomes against those with complications to identify divergent care paths and root causes of missed opportunities.
Cross-reference patient care trajectories against clinical decision trees. For example, if a patient at risk for colorectal cancer wasn’t referred for screening per guidelines, Audit flags this deviation for review.
Access to easy-to-navigate interface displaying: Flagged Cases, Trend Analysis, and detailed timelines and insights for individual cases.
Generate periodic reports for quality improvement committees, summarizing common issues and providing actionable recommendations for systemic change.
Incorporate feedback directly from clinicians to validate flagged cases, refine algorithms, minimize false positives over time.
Regularly retrain machine learning models with updated data and clinician input to boost accuracy.
Utilize reinforcement learning to adjust detection thresholds and patterns as clinical guidelines evolve and new trends emerge.
Link Audit findings with patient outcomes, ensuring continuous improvement and the evolution of “missed opportunity” definitions.
Handle all patient information with the highest security standards in compliance with HIPAA and other relevant privacy laws.
Maintain an audit trail for every decision made by the tool, ensuring external reviewability and accountability.
Continuously monitor for and address any biases in data or algorithms to support equitable care delivery.
Audit is not just an auditing tool—it’s your partner in quality improvement. By turning historical data into actionable insights, Audit empowers you to identify missed opportunities, implement effective interventions, and ultimately, drive better patient outcomes.
