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A case mix simulation decision support system model for negotiating hospital rates.

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Hospitals need strategic financial planning due to prospective payment systems. A new model aids managers in case mix planning and pricing by projecting patient volumes and revenues for different case types.

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Area of Science:

  • Health Services Management
  • Health Economics
  • Hospital Administration

Background:

  • Prospective payment systems (PPS) link hospital revenue to patient diagnoses, shifting focus from services rendered to case mix.
  • Effective financial planning and pricing strategies are crucial for hospitals operating under PPS.

Purpose of the Study:

  • To present a case-based financial planning model for managerial decision-making in hospital strategic planning.
  • To assist hospitals in optimizing case mix and pricing strategies within a PPS environment.

Main Methods:

  • Developed a computerized model treating hospitals as manufacturers of discharged patients.
  • Grouped diagnoses by payor and treatment costs into meaningful case types for analysis.
  • Aggregated diagnostic and treatment costs to model the hospital production process.

Main Results:

  • The model projects patient volumes, prices, and contribution margins for each case type.
  • It calculates the total contribution to hospital overhead based on projected case mix.
  • Testing with a hypothetical scenario demonstrated its utility as a decision-making aid.

Conclusions:

  • The model shows potential for aiding strategic case mix planning and case-type pricing in hospitals.
  • Further development is needed to address identified model shortcomings.