Healthcare Reimbursement Models
Executive Summary
Key Takeaways
- ✓ DRG-based, fee schedule, per-diem, and case rate reimbursement each calculate payment through a genuinely different mechanic, and a provider's model should represent each method actually in use rather than one blended average rate.
- ✓ Under DRG-based payment, revenue is largely fixed per case regardless of length of stay, meaning a longer stay increases cost without a corresponding revenue increase, the opposite relationship from per-diem payment.
- ✓ Per-diem reimbursement pays a fixed rate per day, so revenue scales with length of stay directly, requiring a materially different sensitivity analysis than DRG-based payment.
- ✓ A provider paid under multiple reimbursement methods across different payers or service lines should model each method's mechanic separately, since the revenue sensitivity to volume, acuity, and length of stay differs fundamentally between them.
Objective¶
This guide covers how to model the mechanics of the distinct reimbursement structures healthcare providers are paid under, within Healthcare Financial Modelling, extending the payer-rate concepts introduced in Payer Mix into the specific payment mechanics each method applies.
DRG-Based Payment¶
Diagnosis-related-group (DRG) payment pays a largely fixed amount per case based on diagnosis and case mix complexity, regardless of the actual length of stay or resources consumed within that episode. This creates a direct structural relationship the model should represent explicitly: a longer stay increases cost without a corresponding revenue increase, meaning DRG-based revenue is far more sensitive to case volume and complexity than to length of stay.
Fee Schedule Payment¶
Fee schedule payment reimburses each itemised service or procedure at a defined rate, so revenue scales directly with the specific services delivered rather than a single episode-based payment. This structure most closely resembles a traditional fee-for-service mechanic and should be modelled at the service-item level where volume and mix data support it.
Per-Diem Payment¶
Per-diem reimbursement pays a fixed rate per day of stay, so revenue scales directly with length of stay, the opposite relationship from DRG-based payment. A model covering a per-diem-reimbursed population should apply length-of-stay sensitivity analysis with the expectation that a longer stay increases both cost and revenue, rather than the DRG assumption that a longer stay increases cost alone.
Case Rate Payment¶
A case rate is a negotiated, typically payer-specific fixed payment for a defined episode or procedure, mechanically similar to DRG-based payment (fixed per case) but set through direct negotiation rather than a standardised diagnosis-based classification, and often covering a differently defined episode of care than a public payer's DRG system.
Why Blending Reimbursement Methods Misrepresents Revenue Sensitivity¶
A provider paid under multiple reimbursement methods across different payers or service lines should model each method's mechanic separately in Revenue Cycle Modelling, since revenue sensitivity to volume, acuity, and length of stay differs fundamentally between them. Blending DRG-based, per-diem, and fee schedule revenue into a single average reimbursement rate conceals which specific payment mechanic is driving revenue and removes the model's ability to correctly project the financial impact of a length-of-stay or case mix change, which affects each method differently.
Common Construction Pitfalls¶
Single blended reimbursement rate. Applying one average rate across payment methods with fundamentally different revenue-to-length-of-stay relationships misrepresents the provider's true sensitivity to operational changes.
DRG revenue tied to length of stay. Modelling DRG-based revenue as if it scales with length of stay, rather than being largely fixed per case, overstates the revenue benefit of longer stays under this payment method.
Per-diem revenue treated as fixed per case. Applying DRG-style fixed-per-case logic to a per-diem-reimbursed population understates the actual revenue sensitivity to length of stay.
Recommended Practices¶
- Model each reimbursement method actually in use, rather than one blended average rate.
- Apply length-of-stay sensitivity analysis appropriate to each payment method's actual mechanic.
- Track the revenue mix across reimbursement methods explicitly where a provider operates under more than one.
Continue Reading¶
Related Pillars¶
Related Technical Guides¶
Related Glossary¶
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Frequently Asked Questions
What is DRG-based reimbursement, and how does it affect the revenue-cost relationship?
Diagnosis-related-group (DRG) payment pays a largely fixed amount per case based on the diagnosis and case complexity, regardless of the actual length of stay or resources consumed. This means a longer stay increases cost without a corresponding revenue increase, creating a direct financial incentive tension between clinical necessity and cost efficiency that the model should represent explicitly.
How does per-diem reimbursement differ from DRG-based payment?
Per-diem reimbursement pays a fixed rate per day of stay, so revenue scales directly with length of stay, the opposite relationship from DRG-based payment, where revenue is largely fixed regardless of stay length. A model should apply materially different length-of-stay sensitivity analysis depending on which method applies.
What is a case rate, and how does it differ from a DRG payment?
A case rate is a negotiated, typically payer-specific fixed payment for a defined episode or procedure, similar in mechanic to DRG-based payment (fixed per case) but set through direct negotiation rather than a standardised diagnosis-based classification system, and often covering a broader or differently defined episode of care.
Why shouldn't different reimbursement methods be blended into one average rate?
Because each method creates a fundamentally different revenue sensitivity to volume, acuity, and length of stay. Blending them into a single average rate conceals which specific payment mechanic is driving revenue and removes the model's ability to correctly project the impact of a length-of-stay or case mix change on revenue.
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Healthcare Financial Modelling
Healthcare financial modelling is the discipline of modelling a healthcare provider's revenue, cost, and capital structure from its clinical and operational drivers, patient volume, case mix, payer mix, and clinical staffing and equipment, rather than the generic market-price and headcount-growth drivers used in most corporate models. This page is the hub for the Knowledge Centre's healthcare and life sciences financial modelling content: how a hospital or provider operating model is structured, how the revenue cycle converts gross charges into collected cash, how service line and cost models are built, and how sector-specific business models, occupancy dynamics, and governance practice apply as this domain expands to cover the full range of healthcare and life sciences sub-sectors.
Case Mix Index (CMI)
Case mix index (CMI) is a single weighted-average figure representing the clinical complexity and expected resource intensity of a hospital or service line's patient population over a given period, derived from the relative weight assigned to each treated case under a diagnosis-related-group or similar classification system. A rising CMI generally reflects a shift toward higher-acuity, higher-resource cases and, all else equal, increases both expected reimbursement and expected cost per case. CMI is one of the most consequential single assumptions in a hospital financial model, since it directly scales reimbursement-rate revenue independent of any change in total patient volume.
Payer Mix
Payer mix is the distribution of a healthcare provider's patient volume, and more importantly its revenue, across payer categories such as government programmes, commercial insurance, managed care, and self-pay patients. Because each payer category reimburses the same clinical service at a materially different rate, payer mix is one of the primary determinants of a healthcare provider's realised revenue per case, independent of both volume and case mix index. A financial model that assumes a single blended reimbursement rate across all patients, rather than modelling payer mix explicitly, understates its sensitivity to a shift in that mix.
Revenue Cycle Modelling
The revenue cycle module translates gross billed charges into net patient service revenue and, ultimately, collected cash, through contractual allowances, claims denial and resubmission, and the resulting accounts receivable balance. This guide covers how to build that module: the gross-to-net waterfall, how denial and collection assumptions should be sourced and tested, and how days in accounts receivable feeds the working capital forecast.
Insurance Mix Modelling
Insurance mix modelling is the technical discipline of forecasting how a provider's payer composition, government, commercial, managed care, and self-pay, evolves over time and translating that composition into a blended revenue and collection outcome. This guide covers how to build a payer mix projection from historical trend and market data, how to test payer concentration and downside shift risk, and how payer mix should connect to the reimbursement method and collection performance assumptions used elsewhere in the model.