Healthcare fraud detection relies on complex algorithms to detect outliers in claims data, but ICD-10 may challenge these algorithms and render them less efficient, according to EHR Intelligence.
The most common types of fraud, according to the National Healthcare Anti-Fraud Association, involve billing for services not provided, upcharging for services rendered, providing false diagnoses, overbilling a co-pay and accepting kickbacks.
Since ICD-10 is a new way of producing data, the algorithms may temporarily struggle to correctly interpret data. This could allow more undetected fraud to slip through than normal.
Though a real solution will take time, the AMA now recommends payors increase the timeliness of payments, make the rules for editing medical claims more transparent and reverse the trend of denying claims.
More Articles on Coding, Billing and Collections:
Two St. Louis Hospitals Approved for CMS Bundled Payment Programs
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Population Health Will Require More Accurate Illness Documentation
The most common types of fraud, according to the National Healthcare Anti-Fraud Association, involve billing for services not provided, upcharging for services rendered, providing false diagnoses, overbilling a co-pay and accepting kickbacks.
Since ICD-10 is a new way of producing data, the algorithms may temporarily struggle to correctly interpret data. This could allow more undetected fraud to slip through than normal.
Though a real solution will take time, the AMA now recommends payors increase the timeliness of payments, make the rules for editing medical claims more transparent and reverse the trend of denying claims.
More Articles on Coding, Billing and Collections:
Two St. Louis Hospitals Approved for CMS Bundled Payment Programs
Physicians Remain Reluctant to Embrace ICD-10
Population Health Will Require More Accurate Illness Documentation