Neil v. Secretary of Health and Human Services
Opinion
In the United States Court of Federal Claims
OFFICE OF SPECIAL MASTERS
No. 18-0159V Filed: March 8, 2019
UNPUBLISHED
AMI NEIL,
Petitioner, v. Special Processing Unit (SPU);
Damages Decision Based on Proffer; SECRETARY OF HEALTH AND Influenza (Flu) Vaccine; Shoulder HUMAN SERVICES, Injury Related to Vaccine
Administration (SIRVA) Respondent.
Jeffrey S. Pop, Jeffrey S. Pop & Associates, Beverly Hills, CA, for petitioner. Ryan Daniel Pyles, U.S. Department of Justice, Washington, DC, for respondent.
DECISION AWARDING DAMAGES1
Dorsey, Chief Special Master:
On January 31, 2018, petitioner filed a petition for compensation under the National Vaccine Injury Compensation Program, 42 U.S.C. §300aa-10, et seq.,2 (the “Vaccine Act”). Petitioner alleges that she suffered a shoulder injury related to vaccine administration (“SIRVA”) as a result of an influenza vaccination received on September 17, 2016. Petition at 1. The case was assigned to the Special Processing Unit of the Office of Special Masters.
On March 8, 2019, a ruling on entitlement was issued, finding petitioner entitled to compensation for SIRVA. On March 7, 2019, respondent filed a combined Rule 4 report/proffer on award of compensation (“Rule 4/Proffer”) indicating petitioner should be awarded $85,000.00. Proffer at 3. In the Proffer, respondent represented that petitioner agrees with the proffered award. Based on the record as a whole, the undersigned finds that petitioner is entitled to an award as stated in the Proffer. Id.
Pursuant to the terms stated in the Proffer, the undersigned awards petitioner a lump sum payment of $85,000.00 in the form of a check payable to petitioner, Ami Neil. This amount represents compensation for all damages that would be available under § 15(a).
The clerk of the court is directed to enter judgment in accordance with this decision.3 IT IS SO ORDERED. s/Nora Beth Dorsey Nora Beth Dorsey Chief Special Master
Case-law data current through September 30, 2026. Source: CourtListener bulk data.