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Reinventing the way revenue cycle collections is done.
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Improve Fiscal PerformanceUtilizing Self Pay ModelingJune 21, 2011
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Introduction iSolutions IQ
Patient Data
Equifax Credit Data
CollectionData
iSolutions Platform
Four Phase R2
Validation
Zip+4 Census Data
Substantiate
Credit data validation
Collection data validation
Verify
Patient historical data
Zip+4 census data
Custom Hospital Specific Scoring and Analytical Model
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Patient ID Provides current credit header address, phone number,
employer Updated data returned to hospital eliminating mail returns Equifax and First Search databases updated in real time
Charity Validation Customized to meet hospital’s charity guidelines Specialized Medically Indigent module Consistent system takes the subjectivity out of the process Reduces FTE administrative costs by over 50%
Payment Analysis by Segment Segmentation of accounts by predictability of payment Payment predictor based on household’s financial profile Empirical collectability benchmarks for each segment based on
workflow modifications
iSolutions IQ Platform
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Maximum Payment Estimation Analyzes patient’s financial profile providing recommended
threshold for payment Accurate estimate of what the patient “really” can afford Eliminates guesswork of high/low balance collection strategy
Fraud Alert Immediately identifies fraudulent use of PHI Provides systematic process supporting compliance of “Red
Flag Rule”
Behavioral Analysis – Customized Modeling 360 degree financial analysis of entire household Cascading algorithm delivers most accurate results Custom set up based on geo-demographic multivariate
statistical analysis
iSolutions IQ Platform
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Charity Determination
iSolutions PlatformiSolutions Platform
Patient data delivered in batch or real time
Segmentation analysis performed utilizing a four step validation process
Household income and dependant estimation evaluated for charity determination
Accounts are prioritized by charity designation and propensity of payment catagories
Automatically calculates sliding scale and financial assistance discounts
Patient data delivered in batch or real time
Segmentation analysis performed utilizing a four step validation process
Household income and dependant estimation evaluated for charity determination
Accounts are prioritized by charity designation and propensity of payment catagories
Automatically calculates sliding scale and financial assistance discounts
OrIntegration Real Time HL7
Batch Placement Secure FTP
iSolutions IQInformatics
Platform
CreditReport
Zip+4Census
Demographics15 Million Accounts
Patient Accounting System
Med. AbilityPropensity
High AbilityPropensity
Charity Validation
Unlikely Propensity
Low AbilityPropensity
Needs More Data
Analysis
Income Estimator
Estimate Household
Maximum PaymentEstimate
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Charity Care Prediction
iSolutions IQ Platform analyzes household dependents at the Zip+4 level (7 to 9 homes) and estimated household annual income to determine charity validation per the FPG
Income verification factors include: monthly obligations, mortgage amount, available credit, credit card
balances, auto loans, revolving credit, average cost for rental, food cost, utilities cost, transportation cost, communication cost
Stated patient Income is validated to ensure accuracy
Proprietary income estimator validates census & credit data
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Tested algorithm ensures accurate charity prediction
All income estimations verified through Equifax credit
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Charity CalculatorConsistent & Accurate Validation
Provides a single data sheet which validates charity per your hospital’s guideline
Utilizes stated or estimated income
Estimated income is based on Zip+4 census data plus validation factoring against the patient’s credit file
*Reduce the risk of collecting from charity qualified patients
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Work Flow Optimization
Qualify & Process
Maximum Resources
Modified Work Flow
Accelerate to Bad debt
Skip Trace & Process
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Maximum Payment Estimator
Validate Stated Income via Credit Report
Estimated Income Baseline from Zip+4 Census Bureau Report
Validated via Credit Report
Income Estimation
Estimation of Assets via Credit History
Open Lines of Credit Available
Estimated Cost of Living in Geo-Demographic Area
Financial Profile
12 month Total Patient Can Pay Without Financial Duress
Total Payment
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Measurable Results from Presumptive Charity Policy and Self-Pay Stratification
Reduced placements of self pay accounts to collection agencies by nearly 50% within first six months
Reduced FTE allocation for follow up on self pay accounts by 25%
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Increased cash receipts on self pay accounts by over 22% during first 90 days
Case Study
Reallocated 60% of FTE staff previously assigned to charity care application processing4
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Reporting
Charity, 153
High, 412
Medium, 125
Low, 60
Unlikely, 460
Need More Data, 102 No Data, 3
Breakdown by Number of Accounts Charity
High
Medium
Low
Unlikely
Need More Data
No Data
Charity, 12%
High, 31%
Medium, 9%
Low, 5%
Unlikely, 35%
Need More Data, 8%No Data, 0%
Breakdown by Number of Accounts in Percentage Charity
High
Medium
Low
Unlikely
Need More Data
No Data
DATE
Analysis Prepared for XXXXXXXXX
iSolutions Self Pay Analytics PlatformCharity Analysis based on 200% of the FPG
XXXXXX Location (800) 866-6228
Breakdown by Number & Balance of Accounts
PPI Count Balance
Charity 153 107,100.00
High 412 288,400.00
Medium 125 87,500.00
Low 60 42,000.00
Unlikely 460 322,000.00
Need More Data 102 71,400.00
No Data 3 2,100.00
Total 1,315 920,500.00
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Charity, 107,100.00
High, 288,400.00
Medium, 87,500.00
Low, 42,000.00
Unlikely, 322,000.00 Need More Data,
71,400.00 No Data, 2,100.00
Breakdown by Balance of Accounts Charity
High
Medium
Low
Unlikely
Need More Data
No Data
Charity, 12%
High, 31%
Medium, 9%
Low, 5%
Unlikely, 35%Need More Data, 8%
No Data, 0%
Breakdown by Balance of Accounts in Percentage Charity
High
Medium
Low
Unlikely
Need More Data
No Data
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Thank You
Phil C. SolomonChief ROI OfficeriSolutions IQ [email protected]
Do You Have Any Questions?
