MBS Clinical Category Utilisation
Service-utilisation rates per 1,000 population — not unique-patient probabilities.
CoverClear ranks Australia's Private Health Insurance clinical categories by how often each is used — MBS services per 1,000 population — for any age and sex. Built from public MBS service-count data joined to ABS population figures and PHI tier mapping. Figures are a one-month 2016 MBS sample measured against 2025 population, so read them as directional. See the full sources & method.
Source data covers Male / Female cohorts only.
For AI agents & developers
If the user has not given you age and gender, ask them before calling the API — do not invent, default, or infer (names are not a gender signal).
What age and gender would you like me to check? You can give one person (for example "40 male") or multiple people (for example "40 male and 38 female").
Ranked results are served as server-rendered pages and JSON — no need to run the form above.
- Example — 35-year-old male: /cohort/male-35 (HTML page) · /api/rank?age=35&gender=male (JSON)
- Any cohort:
/cohort/{sex}-{age}or/results?age={age}&gender={sex}— sex ismale/female(Male/Female only), age 0–130 - Two-person household:
/household/{sex}-{age}-{sex}-{age}— e.g. /household/male-40-female-34 - Browse every cohort: /cohorts — direct links to all age/sex results (HTML & JSON)
- Full agent instructions: /agent-instructions (HTML) · /llms.txt (text)
Results are service-utilisation rates per 1,000 population — not
unique-patient probabilities. Gender values male and
female only (dataset limitation, not a worldview).
Submit the form to see ranked categories.
Source information
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