Completeness
Flag missing height, weight, BMI date, diagnosis intent, Member ID, PBM route, comorbidity answers, lifestyle evidence, previous therapy, contraindication response, or continuation outcome before the request reaches clinician review.
Weight management
GLP-1 prior auths improve when eligibility evidence is complete before submission.
Foresight helps telemedicine teams collect the right BMI, comorbidity, lifestyle-trial, diagnosis, formulary, and continuation evidence before a GLP-1 request reaches clinician review.
BMI + formulary
Why it matters
The highest-leverage GLP-1 improvement is usually not a clever appeal letter. It is asking the missing questions early: obesity versus diabetes indication, BMI history, weight-related comorbidities, prior lifestyle trial, contraindications, formulary route, and continuation outcomes.
Higher first-pass readiness
Fewer avoidable resubmissions
Cleaner audit trail for each request
Workflow checks
Evidence to catch before work leaves the queue.
Operating workflow
Rules-first automation with human review where it counts.
- Initial BMI, current BMI, and BMI >=30 or >=27 with documented weight-related comorbidity where required
- Comorbidity intake for hypertension, dyslipidemia, obstructive sleep apnea, type 2 diabetes, cardiovascular disease, kidney disease, and other payer-recognized criteria
- Lifestyle-trial, contraindication, previous therapy, and diagnosis-intent evidence before the packet is drafted
- Plan benefit route, formulary exclusions, step therapy, and initial-auth versus reauthorization criteria
Collect structured intake answers before the visit so the clinician is not asked to reconstruct payer criteria later.
Build payer-specific checklists that separate obesity, diabetes, cardiovascular, sleep-apnea, and continuation-use logic.
Assemble chart evidence into a human-readable packet and gate AI-drafted answers behind clinician sign-off.
Track authorization expiration and continuation evidence, including weight change and adherence, before reauthorization is due.
Automation fit
Inspect the actual artifacts.
Foresight checks whether required evidence is present, whether records contradict each other, and whether the available facts look approvable under payer criteria before submission.
Contradictions
Compare EHR diagnoses, BMI Z-codes, medication history, lab evidence, questionnaire answers, and selected benefit route so a diabetes history, obesity indication, contraindication answer, or formulary alternative does not conflict with the packet.
Payer approvability
Evaluate obesity, diabetes, cardiovascular-risk, step-therapy, exclusion, and reauthorization criteria by payer, then route only the uncertain or clinically sensitive exceptions for human sign-off.
Common leakage points
The work Foresight is built to surface early.
Missing comorbidity documentation
Diagnosis intent mismatched to the drug and plan benefit
Lifestyle-trial or previous-therapy evidence added only after denial
Late reauthorization without continuation outcomes
Workflow risk audit
Map the risk surface.
A useful audit scores concrete workflow gaps: missing evidence, contradictory records, payer criteria risk, and follow-through after submission.
Required evidence present
Whether the claim, PA, or appeal has the basic identifiers and clinical anchors needed before work leaves the queue.
Chart contradictions
Where the EHR, notes, questionnaire, inventory, pharmacy response, and billing record point to different answers.
Payer approvability
Whether the available evidence appears to satisfy payer criteria before the submission creates AR or appeal work.
Follow-through
Whether approvals, denials, paper EOBs, portal messages, corrected claims, and deposits resolve cleanly after submission.
GLP-1
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