IQVIA applied its Patient Finder tool to detect undiagnosed transthyretin cardiac amyloidosis (ATTR-CM) by analyzing structured and free-text EHR data. Among 19,500+ patients screened, the ML-enabled model flagged 53 high-risk cases, leading to four confirmed diagnoses. By identifying patterns such as pacemaker use, heart failure symptoms, and comorbidities, the solution reduced misdiagnosis risk and revealed otherwise hidden patients. This systematic, data-driven approach enhanced early detection, guided physician outreach, and created new opportunities for timely interventions, directly improving patient access to needed care.

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