key: cord-0766434-2pv1au2l
authors: O’Grady, Thomas J.; Tesoriero, James M.; Yuan, Yingchao; Grisham, Thomas M.; Seo, Seung Jun; Gonzalez, Charles J.; Morne, Johanne E.
title: Evaluation of Trends in Preexposure Prophylaxis Prescriptions During the First 6 Months of the COVID-19 Pandemic in New York State
date: 2022-03-28
journal: JAMA Netw Open
DOI: 10.1001/jamanetworkopen.2022.4065
sha: 5286c8809196347e32f96dabc1c38c1dbad106a2
doc_id: 766434
cord_uid: 2pv1au2l

This cohort study uses time-series models to estimate preexposure prophylaxis prescription trends during the first 6 months of the COVID-19 pandemic in New York State in 2020.

De-identified PrEP prescription data in NYS from 10/20/2018 to 9/27/2020 were extracted from Symphony Health IDV® by applying a validated PrEP algorithm. This longitudinal data source contains adjudicated prescription, medical, and hospital claims from across the United States for all payment types. Patients were included in the dataset for this analysis based on NYS residence and prescription criteria. The data extracted were then converted into weekly PrEP 

This study was deemed by institutional policy to be exempt research, satisfying the Code of Federal Regulations Protection of Human Subjects exemption criterion 45 CFR 46.101(b) Category (4): Research involving the collection or study of existing data, documents, records, pathological specimens, or diagnostic specimens, if these sources are publicly available or if the information is recorded by the investigator in such a manner that subjects cannot be identified, directly or through identifiers linked to the subjects. See https://www.hhs.gov/ohrp/sites/default/files/ohrp/policy/ohrpregulations.pdf

Evaluation of Algorithms Used for PrEP Surveillance Using a Reference Population

Intervention Analysis with Applications to Economic and Environmental Problems

Evolving forecasting classifications and applications in health forecasting