Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
3 pending office actions • 2 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready
Experian Health Inc. has 3 pending office actions in the Computing & Software technology area. These actions are assigned to 3 distinct examiners. The matters are distributed across 2 distinct art units, indicating some technical variety within the company's software-related filings. This structure suggests that at least 2 of the applications are technically similar enough to be reviewed within the same art unit, while the 3rd falls into a different category.
CHANG, EDWARD is the busiest examiner for the portfolio. This examiner is managing 1 busiest examiner pending office action. Each of the 3 pending actions is being handled by a different examiner. This ratio of actions to examiners ensures a decentralized review process. However, with only 2 distinct art units involved, the company may still encounter some consistency in departmental standards. Practitioners must manage 3 separate examiner relationships while accounting for the procedural nuances of 2 different art units. This profile highlights a balance between examiner diversity and technical concentration.
Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 1 (33%) |
| §101 + other | 1 (33%) |
| Double-patenting only | 1 (33%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| CHANG, EDWARD | 1 | 63.1% | +32.2% |
| HICKS, AUSTIN JAMES | 1 | 75.0% | +25.8% |
| GAW, MARK H | 1 | 49.8% | +59.7% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18761156 | ESTIMATE ACCURACY SCORING MODEL | GAW, MARK H | 209d overdue |
| 18985626 | SYSTEMS AND METHODS FOR AN ARTIFICIAL INTELLIGENCE/MACHINE LEARNING MEDICAL CLAIMS PLATFORM | HICKS, AUSTIN JAMES | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18761156 | ESTIMATE ACCURACY SCORING MODEL | GAW, MARK H | 209d overdue |
| 19215981 | AUTOMATIC DATA SEGMENTATION SYSTEM | CHANG, EDWARD | — |
| 18985626 | SYSTEMS AND METHODS FOR AN ARTIFICIAL INTELLIGENCE/MACHINE LEARNING MEDICAL CLAIMS PLATFORM | HICKS, AUSTIN JAMES | — |
| Art Unit | Apps |
|---|---|
| 2142 | 1 |
| 3693 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19215981 | AUTOMATIC DATA SEGMENTATION SYSTEM | CHANG, EDWARD | — | DP | Non-Final OA | — | Pending | May 22, 2025 |
| 18985626 | SYSTEMS AND METHODS FOR AN ARTIFICIAL INTELLIGENCE/MACHINE LEARNING MEDICAL CLAIMS PLATFORM | HICKS, AUSTIN JAMES | 2142 | §101§103 | Non-Final OA | — | Pending | Dec 18, 2024 |
| 18761156 | ESTIMATE ACCURACY SCORING MODEL | GAW, MARK H | 3693 | §101 | Non-Final OA | 209d overdue | Pending | Jul 01, 2024 |
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