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The latest version of our premiere medical claim-scrubbing software makes sure you submit only correct and compliant codes to the payers. It helps you reduce submitting time and cost and increase revenue.
Improve your ability to code and bill correctly with MDCodeWizard claim-scrubber
One of the main benefits of our medical claim-scrubber is that it helps users select more precise codes by applying the many built-in rules. Our software helps eliminate coding oversights and ensures accurate coding. It also ensures that submitted claims meet all nationally-accepted coding guidelines. Frequently, this results in less denials and a higher reimbursement level.
Another benefit of MDCodeWizard code scrubber is the cross-walk feature which automatically matches the ICD diagnosis codes with appropriate CPT/HCPCS codes within your encounter thus showing the medical necessity for procedures performed. Very often it is difficult for the medical records staff to find the CPT code that accurately corresponds to ICD-9 coding. Staff members may spend valuable time flipping from one book to the other, searching indexes, only to select matching codes with mixed results. With MDCodeWizard claim scrubber errors stemming from mismatched codes have been virtually eliminated, and the time to match codes has been significantly reduced.
Another big plus, according to the users, are timely upgrades. Medical records departments estimate reimbursements increase because they are now sure the diagnosis is being coded accurately all the time, leading to the highest reimbursement level allowable for each case. The time to code a typical patient record has also been reduced by 10% and as a result the physicians are getting proper reimbursement for their services.
MDCodeWizard's claim-scrubber can substantially increase reimbursements by simplifying the coding process, helping to identify overlooked diagnoses and alerting coders to possible missing procedures. Studies have shown that 15% to 20% of cases marked for review are re-coded for higher reimbursement. Factors such as patient gender, age, diagnoses, procedures and discharge status are used to fine tune the data.
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