Healthcare

One of the Momentum applications to healthcare analytics is to determine the gap between the amount of revenue hospital/providers are entitled to and the amount of reimbursement eventually received.

Missed charges on patient invoices have a major impact on hospital systems’ results. The proposed system will analyze hospital data using latest big data technology and machine learning to identify revenue leakages and provide actionable insights.

Predictive and comparative analytics have the potential to drive improved value by determining areas where proactive steps can better support optimal revenue cycle performance.

The following healthcare analytics have been developed for various healthcare analytics organizations:

Insurance claim rejection/denial rates and their causal analysis

Causes of rejections/denial
Rejections by providers, service categories, employees who prepare bills, by period etc.

Analytics to determine un-collected revenues and underpayments

Causes of no collections/ underpayment
Analysis by various categories and factors that influence underpayment and non-collections

Analytics to determine Revenue at Risk (RAR)

Current and future risk of revenue and factors that influence that

Charge master analytics to determine invalid and outdated charges

Analyze to determine the last update date of each charge
Determine charges that are outdated
Code optimization

Missed charges due to services not coded but available elsewhere within the patient record

Determine services that are not coded but available elsewhere within patient records
Loss due to such non-coded services
Loss by providers, service categories etc

Revenue leakage due to non-payment of co-pays

Co-pay non-payment analysis by patient age group, service categories, providers
Revenue loss analysis

Revenue leakage due to write-offs

Write off analysis by service categories
Write off reason analysis

Other analytics

Missing Referral
Untimely Filing
Missing Authorization
Not a Covered Benefit
Ineligible on Date of Service

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Healthcare Analytics Solutions

Healthcare Analytics Solutions

Insurance claim rejection/denial rates and their causal analysis

Analytics to determine un-collected revenues and underpayments

Analytics to determine Revenue at Risk (RAR)

Charge master analytics to determine invalid and outdated charges

Healthcare Analytics Solutions

Missed charges due to services not coded but available elsewhere within the patient record

Revenue leakage due to non-payment of co-pays

Revenue leakage due to write-offs

Other analytics

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