Common Reasons Data May Appear Inaccurate

Jiro Health sources data from a national claims database and third-party provider registries. Because this data flows through multiple external systems before reaching the platform, there are a few common reasons why what you see in Jiro may not match your expectations or your own records.

Claims Data Lag

Claims data is not updated in real time. There is an inherent gap between when a service occurs and when it appears in Jiro. For specific lag windows by claim type, see Time & Refresh Cadence.

What you might see:

  • Recent months showing little or no data
  • Metrics that appear lower than expected because recent care has not yet been processed
  • Differences between your Jiro data and other systems you use that reflect more current activity

For the most complete view of your practice patterns, focus on time periods that ended at least six months ago.

Claims Coverage and Missing Fields

Jiro's claims database is broad but not exhaustive. It covers approximately 60–70% of U.S. medical encounters and 50–60% of pharmacy encounters in any given year. Not all payers participate, and patients with coverage but no observed claims in a given period are not represented.

Certain financial fields are only available for closed claims. Blank or null values for fields like payment amounts or patient costs are expected for open claims and do not indicate a display error.

What you might see:

  • Lower total patient counts than expected in Metrics
  • Missing values for payment amounts or patient costs

Incomplete or Missing Pharmacy Data

Pharmacy claims rely on National Drug Code (NDC) mappings to link prescriptions to drug classes, generic versus brand designations, and adherence calculations. NDC databases have gaps, and some prescriptions may not map correctly. Out-of-pocket payers are not represented in pharmacy claims.

What you might see:

  • Generic vs. Brand Share Metrics appearing lower than expected
  • Certain drug classes or prescriptions absent from Metrics
  • Medication Adherence Rates that look unusual

Referral Matching Limitations

Referral data in Jiro is inferred from claims patterns — specifically, by matching a "from" claim to a "to" claim. If one side of a referral was not billed under your NPI, or if the receiving provider does not generate a matching claims record, the referral may not appear.

What you might see:

  • Referral counts lower than expected
  • Certain providers or facilities not appearing in your referral network
  • Transit times missing for specific referral pathways

NPI Profile and Data

NPI registry data is self-reported. Not all providers update their information regularly, and some fields — including addresses, specialty codes, and practice locations — may lag behind real-world changes. If a claim was billed under a different NPI, those encounters may not be attributed to your account.

Metrics are calculated against the patients attributed to your NPI. A relatively small attributed panel can make individual Metric values appear more extreme than they would in a larger cohort.

What you might see:

  • Fewer patients than expected in a Metric
  • Spotlights that seem extreme or unrepresentative of your practice
  • Missing encounters compared to your internal records
  • Referral patterns that do not reflect your actual activity

Patient Exclusions

Certain patients are excluded from Metric calculations by design. For example, patients who passed away or were hospitalized during the measurement period may be excluded to ensure Metrics reflect appropriate care standards.

What you might see:

  • A smaller denominator than expected for a given Metric
  • Metrics that differ from a manual calculation
  • Cohort breakdowns that do not sum to your total patient count

Troubleshooting

Issue

What to Do
My data looks significantly off or wrong Review the drill-down view for the Metric's definition and exclusions before assuming an error.
My data from last month looks incomplete Claims take 30–90 days to be fully processed. Check back in a few weeks.
A Metric I expect to see is missing Some Metrics are specialty-specific. Confirm your specialty is set correctly in your profile.
My peer comparisons do not match my expectations Review your profile to confirm your specialty is accurately set, as peer groups are built from specialty groupings.
My referral data does not match what I expect Referral data is inferred from claims patterns and is best used as a directional indicator rather than a complete record.
My Medication Adherence or Generic Share Metrics look off This may reflect NDC mapping gaps. Flag the Metric using the in-app feedback button.
I have questions about my data accuracy Use the in-app feedback button to describe the Metric or data point in question.

Frequently Asked Questions

Why does my data from last month look incomplete? Claims take time to be submitted, processed, and finalized. Data from the most recent 30–90 days is often still accumulating. Check back in a few weeks and the picture will typically fill in.

My data looks way off. What should I do? Start by checking the "N" value on the Metric and reviewing the drill-down for the Metric's definition and patient exclusions. If something still looks wrong, use the in-app feedback button to report it with as much detail as possible.

Can Jiro correct 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 some Metrics update while others stay the same? Different Metrics refresh on different cadences depending on the claims data they rely on. Pharmacy-based Metrics typically refresh faster than those based on inpatient or specialist claims.

Is this data used for credentialing or performance evaluations? No. Data in Jiro is for your personal clinical use only. It is not shared with employers, insurers, or credentialing bodies.

Why is my "N" so 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 narrow patient population, or when some patients were excluded based on the Metric's defined criteria.

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Version History

Updated: April 17, 2026

Reviewed by: Claude, Help Scout Docs Reviewer

Approved by: [Name, Title]

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