Technology area: Transportation, E-Commerce & Mechanical Systems
8 pending office actions • 7 art units • 7 examiners • 0 of 8 (0%) have an AI response strategy ready • 11 patents granted in the last 365 days
Elevance Health Inc. is currently managing 8 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. This portfolio involves 7 distinct examiners and 7 distinct art units, showing a high level of variety in the technical review process. The presence of 7 distinct art units for 8 actions indicates that the company's filings are being evaluated across a broad spectrum of technologies, rather than being confined to a single specialized group.
The busiest examiner for this portfolio is ELSHAER, ALAAELDIN M, who is responsible for 2 pending office actions. With 7 distinct examiners in total, the workload is distributed such that most actions are being handled by individuals who only see one of the company's applications. This distribution suggests that the company must adapt its legal arguments to the preferences and styles of 7 different examiners. The variety of 7 distinct art units further emphasizes the need for a versatile prosecution strategy that can address the unique requirements of numerous technical fields within the 8 pending office actions.
Based on the USPTO statutory response window for each pending office action. 4 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 4 of the docket's apps have a known mailing date.
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 (12%) |
| §101 + other | 5 (62%) |
| §103 only | 1 (12%) |
| §112 only | 1 (12%) |
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 |
|---|---|---|---|
| ELSHAER, ALAAELDIN M | 2 | 35.7% | +29.8% |
| BARR, MARY EVANGELINE | 1 | 36.1% | +32.5% |
| SANGHERA, STEVEN G.S. | 1 | 30.3% | +29.7% |
| GO, JOHN PHILIP | 1 | 33.9% | +43.3% |
| ZHU, RICHARD Z | 1 | 69.3% | +15.5% |
| PAULS, JOHN A | 1 | 49.0% | +27.7% |
| HAYES, JONATHAN EDWARD | 1 | 36.3% | +23.5% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 6 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18986676 | SYSTEMS, METHODS AND INTERFACES FOR RESOURCE RESERVATION USING SMART CONTRACTS | ELSHAER, ALAAELDIN M | 58d overdue |
| 17237591 | Machine Learning Derived Multimorbidity Risk Scores for Generalizable Patient Populations | HAYES, JONATHAN EDWARD | 46d overdue |
| 18962869 | Cognitive Artificial Intelligence Platform for Physicians | GO, JOHN PHILIP | 45d overdue |
| 19040827 | Devices, Systems, and Methods for Generating and Providing Personalized Communications to Improve Adherence to Patient Treatment Plans | SANGHERA, STEVEN G.S. | — |
| 18986671 | SYSTEMS AND METHODS FOR COMPLIANCE PREDICTION | ELSHAER, ALAAELDIN M | — |
| 18939258 | Real-Time and Diagnostic Omnichannel Interaction Insights, Actions, and Management Using Machine Learning Models | ZHU, RICHARD Z | — |
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 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18986676 | SYSTEMS, METHODS AND INTERFACES FOR RESOURCE RESERVATION USING SMART CONTRACTS | ELSHAER, ALAAELDIN M | 58d overdue |
| 18587691 | Method and System for Predicting Medical Diagnoses Using Machine Learning without Patient Intervention | PAULS, JOHN A | 49d overdue |
| 17237591 | Machine Learning Derived Multimorbidity Risk Scores for Generalizable Patient Populations | HAYES, JONATHAN EDWARD | 46d overdue |
| 18962869 | Cognitive Artificial Intelligence Platform for Physicians | GO, JOHN PHILIP | 45d overdue |
| 19282259 | Systems and Methods for Predicting Outcomes Using Large Language Models | BARR, MARY EVANGELINE | — |
| 19040827 | Devices, Systems, and Methods for Generating and Providing Personalized Communications to Improve Adherence to Patient Treatment Plans | SANGHERA, STEVEN G.S. | — |
| 18986671 | SYSTEMS AND METHODS FOR COMPLIANCE PREDICTION | ELSHAER, ALAAELDIN M | — |
| 18939258 | Real-Time and Diagnostic Omnichannel Interaction Insights, Actions, and Management Using Machine Learning Models | ZHU, RICHARD Z | — |
| Art Unit | Apps |
|---|---|
| 3687 | 2 |
| 3682 | 1 |
| 3684 | 1 |
| 3681 | 1 |
| 2654 | 1 |
| 3683 | 1 |
| 1685 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19282259 | Systems and Methods for Predicting Outcomes Using Large Language Models | BARR, MARY EVANGELINE | 3682 | §103 | Non-Final OA | — | Pending | Jul 28, 2025 |
| 19040827 | Devices, Systems, and Methods for Generating and Providing Personalized Communications to Improve Adherence to Patient Treatment Plans | SANGHERA, STEVEN G.S. | 3684 | §101§112 | Final Rejection | — | Pending | Jan 29, 2025 |
| 18986676 | SYSTEMS, METHODS AND INTERFACES FOR RESOURCE RESERVATION USING SMART CONTRACTS | ELSHAER, ALAAELDIN M | 3687 | §101§103 | Final Rejection | 58d overdue | Pending | Dec 18, 2024 |
| 18986671 | SYSTEMS AND METHODS FOR COMPLIANCE PREDICTION | ELSHAER, ALAAELDIN M | 3687 | §101 | Final Rejection | — | Pending | Dec 18, 2024 |
| 18962869 | Cognitive Artificial Intelligence Platform for Physicians | GO, JOHN PHILIP | 3681 | §101§103 | Final Rejection | 45d overdue | Pending | Nov 27, 2024 |
| 18939258 | Real-Time and Diagnostic Omnichannel Interaction Insights, Actions, and Management Using Machine Learning Models | ZHU, RICHARD Z | 2654 | §101§103 | Non-Final OA | — | Pending | Nov 06, 2024 |
| 18587691 | Method and System for Predicting Medical Diagnoses Using Machine Learning without Patient Intervention | PAULS, JOHN A | 3683 | §112 | Non-Final OA | 49d overdue | Pending | Feb 26, 2024 |
| 17237591 | Machine Learning Derived Multimorbidity Risk Scores for Generalizable Patient Populations | HAYES, JONATHAN EDWARD | 1685 | §101§112 | Final Rejection | 46d overdue | Pending | Apr 22, 2021 |
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Start Free TrialElevance Health Inc. has 8 pending office actions as of October 2026, spread across 7 art units and 7 examiners.
Alaaeldin M Elshaer has the most, with 2 of Elevance Health Inc.'s pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.
