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Managed Care Decomposition Analysis MCDA

Managed Care Decomposition Analysis MCDA. Comparative Reimbursement Analysis and Contract Optimization. Introduction.

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Managed Care Decomposition Analysis MCDA

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  1. Managed Care Decomposition AnalysisMCDA Comparative Reimbursement Analysis and Contract Optimization

  2. Introduction In today’s Managed Care environment, expected reimbursement is a function of Managed Care Organization (MCO) specific rules that are executed at the patient-level based on each patient’s characteristics as defined in the MCO’s contract. The goal of Managed Care Decomposition Analysis (MCDA) is to clearly define and quantify this expected reimbursement process in terms of patient characteristics (master attributes) and expected reimbursement (reimbursement attributes) so that the healthcare executive may identify and potentially optimize net income within existing managed care contract parameters.

  3. Marketing Product Lines Clinical Product Lines MarketSpace ChargeMaster Hospital Patient Population Shift to Managed Care MCO brings in New Patients and Proposed Contract Predicted MCPL’s MCOContract Master MCO Contract Accepted (Payor Specific) Inherent MCPL’s

  4. How Contracts Are Interrelated: MCO Contract Master Patient Characteristics Reimbursement Characteristics What are the MCPL’s defined by the contracts? How are the MCPL’s reimbursed? A patient or patient group can have more than one reimbursement possibility based on characteristics. A patient or patient group can have more than one characteristic.

  5. Contract Negotiation Predicted Patients Offered Contract Rules Predicted Reimbursement

  6. Contract Monitoring Actual Patients Contract Rules Expected Reimbursement

  7. MCO Contract Master Patient Characteristics or MCPL’s Reimbursement Characteristics • Percent of Charges • Per Diem • Time Sensitive Per Diem • Discharge Amount • Line Item Amount • DRG • UB-92 REV Code • CPT-4 Code • ICD-9-CM Code • Covered Charges How much? What?

  8. Managed Care Decomposition Analysis MCO Contract Master Actual Patients MCDA Data Base Contract Rules Patient Characteristics Reimbursement Characteristics Managed Care Product Lines Expected Reimbursement Reimbursement Attributes Master Attributes How is it being purchased? What is being purchased?

  9. Managed Care Decomposition Analysis Contract 1 Contract 3 Contract 2 Contract n Hospital Contract Management System MCO Contract Master MCDA defines this as . . . Patient Characteristics Reimbursement Characteristics 1. Define what is currently happening 2. Define alternative reimbursement scenarios from MCO Contract Master that, if implemented, could increase net income 3. Extract all patient characteristics as defined in MCO Contract Master and identify potential net income opportunities based on these characteristics

  10. Example: Payor Decomposition Analysis

  11. Master Attribute

  12. Reimbursement Attribute Master Attribute

  13. Reimbursement Attribute

  14. Reimbursement Attributes

  15. Managed Care Decomposition Analysis The OSI Standardization process allows MCDA encoded hospitals to be aggregated into a Managed Care Data Repository for future comparative analyses. . . . . MCDA Hospital n MCDA Hospital 3 MCDA Hospital 1 MCDA Hospital 2 OSI Attribute Encoder Managed Care Data Repository Managed Care Product Lines Standard Reimbursement Attributes Standard Master Attributes Standard Payors

  16. Management Care Decomposition AnalysisBenefits • The identification and definition of MCPL’s based on the current expected reimbursement • environment. • The quantification and ranking of expected reimbursement incidents by Master Attribute • and payor. • The identification and quantification of alternative reimbursement scenarios by Master • Attribute. • The compilation of a detailed Master Attribute catalog outlining the various reimbursement • scenarios that are possible based on standard payor and associated Reimbursement Attribute. • . • The creation of an MCDA database that can serve as a basis for expected reimbursement • simulations and budgeting. • The identification of statistically relevant clinical correlation's between existing Standard • Master Attributes.

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