Understanding Your Data Coverage
- What Coverage Means
- Coverage vs. Data Quality: What's the Difference?
- Your Coverage Tier
- How Coverage Affects Jiro Features
- Important to Remember
- Related Articles
Knowing how much of your clinical activity Jiro captures helps you read your metrics reliably and use Jiro's features with the right clinical context. Coverage is referenced in two ways across Jiro. Database coverage means Jiro accesses approximately 60–70% of U.S. medical claims nationally through data sources. Account coverage varies by user: it is the amount of your practice Jiro captures, based on your claims volume relative to your practice size.
What Coverage Means
Coverage is the proportion of your total claims that Jiro captures. It is expressed as a ratio of claims on file to total estimated claims generated. Your claims volume is not directly observable, so coverage is approximated using the encounter volume data you provide.
When your coverage is high, Jiro's data closely reflects your clinical activity. Lower coverage gives a more partial view of your practice. Coverage estimates improve as more real-world data is processed and as your newly available data is incorporated into Jiro's calculations. Data currently refreshes monthly.
Coverage vs. Data Quality: What's the Difference?
Data Quality measures whether the real-world data Jiro holds is complete and mature. It reflects delivery lag and how recently the data was processed.
Data Coverage measures what percentage of your total clinical activity is present in Jiro's real-world data. It reflects how much of your patient panel and clinical volume Jiro can access.
High data quality across Jiro's overall data can exist alongside low coverage of your individual data. Neither indicates inaccurate data. Each describes the scope and completeness of Jiro's measurement.
Your Coverage Tier
Jiro assigns your account to one of four coverage tiers based on the ratio of captured real-world data to your total estimated clinical volume. Your tier determines how your metrics and Jiro features behave. If you have questions about your tier, contact Jiro Support.
| Coverage Tier | What It Indicates | How Jiro Adjusts |
|---|---|---|
| No Data | No claims are on file for your NPI. This is common for residents and physicians who have recently joined. | Specialty-level benchmarks and comparisons are available. Individualized metrics are not displayed. Discover and Consult remain accessible using non-personalized data. |
| Low | Claims exist but represent a small portion of your estimated total volume. | Metrics and Discover cards draw on less specific data (specialty-level or location-level) rather than individual-level claims. |
| Medium | A meaningful portion of your claims is captured, but gaps remain. | Individualized metrics and Discover cards are available. Treat the metrics as a directional indicator of your practice. |
| High | Real-world data closely reflects your total clinical activity. | Metrics and Discover cards are fully individualized. |
How Coverage Affects Jiro Features
Your coverage tier determines how Jiro's features respond when surfacing personalized information. Each feature follows the same principle: specificity adjusts to the data available.
Practice - Spotlights
Spotlights appear based on the individual metrics you have data for.
Practice - Clinical Metrics
Each metric has its own calculation rules. Metric cards appear when you have enough data to form insights. Jiro shows "No data available" for a metric when your coverage is too low to calculate a reliable insight.
Practice - Financial Intelligence
Referral data often has naturally sparse coverage. Documented referrals are directional, relying on a "sending" and a "receiving" party.
Reimbursements draw on closed claims, which are subject to data lag. They show coverage patterns similar to your clinical metrics.
Denials reflect billed charges only. If you have partially denied claims, pending claims, or claims under appeal, you will see less data.
Encounter Coding does not include institutional or facility claims. It includes office and outpatient institutional claims only.
Research
Data coverage does not affect Research.
Consult
When your coverage is low, Consult responses may include inline caveats. These indicate that personalized clinical context is derived from limited real-world data.
Discover
Discover adjusts specificity based on your coverage. When your coverage is limited, cards present patterns at the specialty or location level rather than the individual practice level. This keeps them relevant to your clinical context.
Important to Remember
- Coverage is approximated from the encounter volume data you provide, because your claims volume is not directly observable.
- High data quality across Jiro's overall data can exist alongside low coverage of your individual data.
- Your coverage tier determines how metrics and Discover cards are individualized, and Medium tier metrics are a directional indicator.
- Data currently refreshes monthly.