Common Reasons Data May Appear Inaccurate
- Claims Coverage & Missing Fields
- Incomplete or Missing Pharmacy Data
- Referral Matching Limitations
- NPI Profile & Data
- Patient Exclusions
- Frequently Asked Questions
- Important to Remember
- Related Articles
Data in Jiro can differ from your internal records for several reasons, and knowing them helps you judge which numbers to trust and which to check. This page covers coverage gaps, missing fields, matching limits, NPI attribution, and patient exclusions.
View the Time & Refresh Cadence page for specific lag windows by claim type. If a concern remains, report it through the help button with the Metric name, the date range, and the values you expected.
Claims Coverage & Missing Fields
Jiro's real-world data includes approximately 60–70% of U.S. medical encounters and 50–60% of pharmacy encounters in any given year. Coverage varies by payer participation.
A patient with insurance coverage does not appear in Jiro if no claims were submitted for that patient during a given period. Patient counts in Metrics can therefore be lower than your internal records.
Financial fields, such as payment amounts and patient costs, can be incomplete on both open and closed claims. Open medical claims carry a charge amount. Closed claims are allowed or paid. Closed claim financials are merged into the open record when duplicate records are combined.
Pharmacy claims use a different cost model: gross due, paid, and patient pay. Payment and cost values can be missing for recent or open claims.
Incomplete or Missing Pharmacy Data
Jiro links pharmacy claims to clinical information through National Drug Code (NDC) mappings. These mappings connect each NDC to a drug class, a generic or brand designation, and adherence calculations.
NDC databases have gaps. Some prescriptions map incorrectly. Patients who pay out of pocket do not appear in pharmacy claims.
How This Shows Up
Generic vs. Brand Share Metrics can appear lower than expected. Specific drug classes or prescriptions can be absent. Medication Adherence Rates can show unexpected values.
Referral Matching Limitations
Referral patterns in Jiro are directional. Jiro infers them by matching a claim from one provider (the referring provider) to a claim from another provider (the receiving provider).
A referral does not appear in Jiro in two cases: either provider has no claims record, or the referring claim was not billed under your NPI.
Expected Data Patterns
Referral counts can be lower than expected. Certain providers or facilities can be missing from your referral network. Transit times between referral initiation and completion can be missing for specific pathways.
NPI Profile & Data
NPI registry data is self-reported, and providers update it at varying intervals. Address, specialty code, and practice location fields can lag behind real-world changes.
If a claim was billed under an NPI other than the one associated with your Jiro account, those encounters are not attributed to you.
Metrics are calculated from patients attributed to your NPI. A smaller attributed patient panel can produce Metric values that look more extreme than they would in a larger cohort.
Impact on Your Metrics
Patient counts in Metrics can be lower than expected. Spotlights can highlight patterns that seem unrepresentative of your practice. Encounters in your internal records can be missing from Jiro. Referral patterns can differ from your actual referral behavior.
Patient Exclusions
Jiro excludes certain patients from Metric calculations by design. For example, patients who died during the measurement period or were hospitalized for specific conditions can be excluded. This keeps Metrics aligned with clinically appropriate care standards.
How This Affects Denominators
Metric denominators can be smaller than expected. Metrics can differ from manual calculations based on your internal data. Cohort breakdowns can fail to sum to your total patient count.
Frequently Asked Questions
Why does my data from last month look incomplete? Claims require time for submission, processing, and finalization. Data from the past six months (commercial) or nine or more months (Medicare/Medicaid) continues to accumulate. Check your Metrics after the relevant lag period has passed; data completeness typically improves significantly.
My data looks substantially different from my records. What should I do? First, review the "N" value on the Metric to see the number of patients included in the calculation. Then examine the drill-down view to confirm the Metric's definition and patient exclusion criteria. If a discrepancy remains, use the help button to report it with specific details: the Metric name, date range, and the values you expected.
Can Jiro correct NPI attribution errors? In some cases, yes. If you believe your NPI is misconfigured or that patients are missing from your attributed panel, contact support for investigation.
Why do different Metrics update on different schedules? Metrics refresh on different cadences depending on the claims data they depend on. Pharmacy-based Metrics typically refresh faster than Metrics based on inpatient or specialist claims.
Is my data in Jiro used for credentialing or performance evaluation? No. Data in Jiro is for your personal clinical and operational use only. It is not shared with employers, insurers, or credentialing bodies.
Why is the patient count ("N") low on some Metrics? The "N" reflects the number of patients included in a Metric's calculation. A low N is expected with a smaller panel, a specialized patient population, or when the Metric's defined exclusion criteria remove patients from the denominator.
Important to Remember
- Jiro's real-world data includes approximately 60–70% of U.S. medical encounters and 50–60% of pharmacy encounters in any given year.
- Encounters billed under an NPI other than the one tied to your Jiro account are not attributed to you.
- Data from the past six months (commercial) or nine or more months (Medicare/Medicaid) continues to accumulate.
- Jiro excludes certain patients from Metric calculations by design, so Metrics can differ from manual calculations based on your internal data.