Automated business rules with the “SIFT” capability (i.e., capturing clinical meanings from non-discrete data) runs in the background and keys off the encounter, and reviews all clinical notes to create a comparable encounter that is matched with what was captured in the EMR.
Captures all clinical actions from patient visits, including Physician and other clinician notes, diagnosis, and orders which create billing codes associated with the encounter records.
Labor Costs Reduction
Errors are identified and flagged for human intervention, result is that initially 90% are automatically mapped correctly, moving toward 95% over time as the intelligent system learns from user corrections – typically can reduce quarterly labor of 5,000 user hours down to 50 user hours at cost savings of up to $2 million a year.
Revenue Cycle Management
Rules engine taps into the Revenue Cycle system looking for diagnosis codes and looks to optimize the revenue on the new corrected encounter record with the best billing codes, taking into account the quality metrics implications with changing codes and latest formularies.
Medical Billing Optimization
Rules engines looks for a match with the records and then fills in any missed events, procedures, diagnosis or codes, and identifies disease cohorts and tie to latest formularies, addressing the approximate $2 billion in lost revenues per year, or about $10 million per average healthcare provider group.
Works With Legacy
Highest Level Access To Largest
Hospitals and Provider Groups
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