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How SiftMed Simplifies Medical Reviews for MVA Cases
Motor Vehicle Accident (MVA) cases are some of the most challenging records in the medicolegal world. Independent medical evaluators (IMEs) , legal professionals , insurance adjusters all rely on the same dense, disorganized documents but each needs clear, defensible insights to make informed decisions. Reviewing these files manually often feels like searching for answers in a two thousand-page haystack. SiftMed changes that. Our AI-powered platform streamlines the entire med
Erica Chant
23 hours ago3 min read


What To Consider When Using AI In Your Workflow
Artificial intelligence is becoming increasingly integrated into medical review workflows, offering new efficiencies and improvements. We see reviewers ask smart, practical questions about using AI in their processes - and that caution is both appropriate and necessary.
Erica Chant
1 day ago3 min read


The Hidden Traps in Medical Record Review - and 5 Ways to Avoid Them
Reviewing a 2,000-page medical file shouldn’t feel impossible — but for many professionals, it does. From duplicate documents to unreadable handwriting, there are hidden traps that slow reviews and increase errors. Discover the five most common pitfalls in medical record review — and how tools like SiftMed help you avoid them for faster, more accurate results.
Erica Chant
Oct 142 min read


Workflow Transformation
Discover how Olivia and Raquel streamlined their medical record review process from days to hours - improving accuracy, saving time, and making medical file review more efficient than ever.
Kelsey Lomond
Oct 13 min read


How AI in Medical Reviews Supports Experts - Without Replacing Them
Discover how AI in medical reviews reduces admin burden, improves efficiency, and supports clinicians without replacing human expertise.
Erica Chant
Sep 114 min read


Using AI to Stay Ahead of the Curve
Learn how Nicole uses SiftMed to stay ahead of the curve.
Kelsey Lomond
Jul 123 min read
Focus on the facts that matter.
Simply upload a medical file and let SiftMed find the facts you need.
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