What AI helps with occupational health (K3) medical check-ups in Indonesia?
MCU CoPilot turns mapped labs, vitals, audiometry, spirometry, vision, and other structured findings into draft MCU reports for doctor review. It can organize findings and propose a fitness-to-work result for an authorized physician to review, correct, and approve; the doctor remains responsible.
From source data to follow-up
MCU CoPilot works with supported structured inputs or institution-verified integrations. We check your formats, field mappings and reporting rules before setup.
Read the full explanationAI prepares a structured report draft. Doctors verify the source evidence, make corrections and approve the report before release.
Read the full explanationReviewed reports and clinician-confirmed plans can continue into Care Loop for follow-up. The next appointment is coordinated and confirmed through your institution’s booking workflow.
Read the full explanationOccupational-health MCU programs combine structured findings from multiple examination categories across many workers. Reconciling those inputs, preparing individual clinical drafts, and producing aggregate program summaries creates repetitive work. MCU CoPilot uses institution-mapped structured data to prepare a draft report, group findings, surface abnormalities, and propose a fitness-to-work result for clinical review.
The occupational physician reviews the source findings, corrects the draft as authorized, and approves the clinical outcome. The product does not replace that decision. Individual clinical reports remain limited to the patient and other verified, authorized clinical recipients. Employer sponsorship does not make the employer a default recipient; any employer-facing output must be explicitly authorized, purpose-limited, and minimum necessary, such as an approved fitness outcome or aggregate de-identified summary.
Supported categories can include laboratory results, vitals, vision, audiometry, spirometry, and other configured examinations; the exact fields, mapping, workflow, recipients, and integrations depend on the institution's implementation. Clinical judgment stays with clinicians; the AI does not diagnose or sign.