Provisional drug overdose deaths (state, monthly)
CDC National Center for Health Statistics (VSRR)
In a RepVector build, this dataset quantifies clinical need and utilisation across the population.
| Year | Month (12-mo ending) | Substance indicator | 12-month-ending deaths | % of records complete |
|---|---|---|---|---|
| 2,026 | March | Psychostimulants with abuse potential (T43.6) | 108 | 100% |
| 2,026 | March | Natural & semi-synthetic opioids (T40.2) | 70 | 100% |
| 2,026 | March | Synthetic opioids, excl. methadone (T40.4) | 104 | 100% |
| 2,026 | March | Percent with drugs specified | 95.203 | 100% |
| 2,026 | March | Opioids (T40.0-T40.4,T40.6) | 161 | 100% |
| 2,026 | March | Natural & semi-synthetic opioids, incl. methadone (T40.2, T4 | 74 | 100% |
| 2,026 | March | Number of Drug Overdose Deaths | 271 | 100% |
| 2,026 | March | Cocaine (T40.5) | 12 | 100% |
What this dataset is
Monthly provisional counts of drug-overdose deaths by state and substance category (opioids, cocaine, psychostimulants and more), released faster than final vital-statistics data so recent trends are visible before the annual figures are final. State-level only. It is published by CDC National Center for Health Statistics (VSRR) and can be queried at state level, refreshed monthly. Each row is a period observation, so results show direction and rate of change rather than a single snapshot.
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 Provisional drug overdose deaths (state, monthly) 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 CDC National Center for Health Statistics (VSRR) line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If CDC National Center for Health Statistics (VSRR) 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 |
|---|---|---|
| Year | year | number |
| Month (12-mo ending) | month | string |
| Substance indicator | indicator | string |
| 12-month-ending deaths | deaths | number |
| % of records complete | percentComplete | percent |
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 Provisional drug overdose deaths (state, monthly):
Other health datasets
Common questions
What does Provisional drug overdose deaths (state, monthly) contain?
Monthly provisional counts of drug-overdose deaths by state and substance category (opioids, cocaine, psychostimulants and more), released faster than final vital-statistics data so recent trends are visible before the annual figures are final. State-level only. It is published by CDC National Center for Health Statistics (VSRR) at state grain.
How often is it refreshed?
CDC National Center for Health Statistics (VSRR) publishes on a monthly cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.
Do I need an account to use it?
No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.
Build the list for one county and see whether the names are right.
Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.
3 free runs — no card required.