Inpatient hospital discharges and payments by DRG
Centers for Medicare & Medicaid Services
In a RepVector build, this dataset quantifies clinical need and utilisation across the population.
| DRG | Discharges | Avg total payment | Avg Medicare payment | Avg submitted charge | Area |
|---|---|---|---|---|---|
| INTRACRANIAL HEMORRHAGE OR CEREBRAL INFARCTION WITH CC OR TP | 2,572 | $8,605 | $6,371 | $40,542 | Ohio |
| INTRACRANIAL HEMORRHAGE OR CEREBRAL INFARCTION WITH MCC | 2,157 | $16,369 | $13,521 | $68,742 | Ohio |
| SEIZURES WITHOUT MCC | 1,213 | $8,464 | $5,997 | $35,112 | Ohio |
| DEGENERATIVE NERVOUS SYSTEM DISORDERS WITHOUT MCC | 1,088 | $11,227 | $8,853 | $36,932 | Ohio |
| SEIZURES WITH MCC | 820 | $16,854 | $13,960 | $69,569 | Ohio |
| TRANSIENT ISCHEMIA WITHOUT THROMBOLYTIC | 775 | $6,583 | $4,804 | $31,636 | Ohio |
| CRANIOTOMY AND ENDOVASCULAR INTRACRANIAL PROCEDURES WITH MCC | 739 | $39,979 | $32,330 | $184,180 | Ohio |
| OTHER DISORDERS OF NERVOUS SYSTEM WITH CC | 663 | $8,836 | $6,673 | $36,536 | Ohio |
What this dataset is
Medicare inpatient discharge volume, average submitted charge, average total payment and average Medicare payment for each diagnosis-related group (DRG), by state and nationally. Shows what hospitals in a state actually treat, how often, and what it costs. It is published by Centers for Medicare & Medicaid Services and can be queried at state and nation level, refreshed annual. Each row is an aggregate statistic for a geography, so results describe a market as a whole rather than a single account.
Why it is useful
- Separates markets with real clinical demand from markets that only have supply.
- Grounds a territory case in published prevalence and utilisation instead of assumption.
- Highlights where need outruns available capacity — usually the fastest conversations.
Questions it helps answer
- Where is the underlying clinical need highest relative to available capacity?
- How does utilisation here compare with the state and national picture?
- Which measures are suppressed or unreported for this geography?
How different verticals use it
RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.
Prioritises territories where clinical need outruns available capacity.
Quantifies prevalence and utilisation behind a programme or referral case.
Informs risk and benefit design with published utilisation patterns.
Shows community health pressures that shape support-service demand.
How RepVector uses it
- You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at state runs without you knowing any codes.
- The planner selects Inpatient hospital discharges and payments by DRG only when your question matches what it actually reports. It is never included to pad a result.
- Returned rows are normalised into the shared metric layer, so figures from Centers for Medicare & Medicaid Services line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If Centers for Medicare & Medicaid Services suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
- The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.
What it does not tell you
- Aggregated and often suppressed at small geographies to protect privacy; gaps are reported rather than filled in.
| Field | Key | Type |
|---|---|---|
| DRG | drgDescription | string |
| Discharges | discharges | number |
| Avg total payment | avgTotalPayment | currency |
| Avg Medicare payment | avgMedicarePayment | currency |
| Avg submitted charge | avgCharge | currency |
| Area | area | geo |
| DRG code | drg | string |
How it fits with the rest of the catalog
Need data explains why a territory matters; provider and facility data explains who you visit once you get there. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to Inpatient hospital discharges and payments by DRG:
Other health datasets
Common questions
What is DRG reimbursement?
Medicare pays inpatient stays a fixed amount per diagnosis-related group rather than per service. This file reports the average payment actually made for each DRG.
Why is the submitted charge so much higher than the payment?
Charges are list prices almost nobody pays. The average total payment column is the money that actually changed hands.
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