Purpose: There is increasing recognition of the importance of transparency and reproducibility in scientific research. This study aimed to quantify the extent to which programming code is publicly shared in pharmacoepidemiology, and to develop a set of recommendations on this topic. Methods: We conducted a literature review identifying all studies published in “Pharmacoepidemiology and Drug Safety” (PDS) between 2017 and 2022, Data was extracted on the frequency and types of programming code shared, and other key open science practices (clinical codelist sharing, data sharing, study pre-registration, and use of reporting guidelines). We developed six recommendations for investigators who choose to share to programming code and gathered feedback from members of the International Society of Pharmacoepidemiology (ISPE). Results: Programming code sharing by articles published in PDS ranged from 2.4% in 2017 to 13.4% in 2022. It was more prevalent among articles with a methodological focus, simulation studies, and papers which also shared record-level data. We recommend that reporting of open science practices, including code sharing, is standardised to enable continued monitoring. When sharing programming code, we recommend the use of permanent digital identifiers, appropriate licenses, and, where possible, adherence to good software practices around the provision of metadata and documentation, computational reproducibility, and data privacy. Conclusion: Programming code sharing is rare but increasing in pharmacoepidemiology studies published in Pharmacoepidemiology and Drug Safety. We recommend improved and consistent reporting of code sharing, and adherence to good programming practices in order to maximize the utility of code when this is shared.

Purpose To validate Covid-19 information records in The Pharmacoepidemiological Research Database for Public Health System (BIFAP), commonly used for pharmacoepidemiological research in Spain. Methods The recorded Covid-19 cases in primary care (PC) or positive test registries (gold-standard) were identified among vaccinated patients against SARS-CoV-2 infection of any age. They were matched with unvaccinated controls by birth year, vaccination date, region, and sex, between December 2020-October 2021. The sensitivity (SE), specificity (SP), positive (PPV), negative (NPV) predictive values, and date accurateness were estimated for PC by vaccination status and age brands. Results Among 21,702 patients with positive tests and 20,866 with recorded Covid-19 diagnoses, the SE, SP, PPV, and NPV were, respectively, 79.98%, 99.95%, 80.24% and 99.94% among vaccinated, and 78.67%, 99.96%, 84.51% and 99.94% among controls. For those aged ≥70 years old, SE (71.15-72.85%) was lower while PPV (84.68-88.04%) was higher compared to <70 years old participants. 94.12% of the total true positive cases (N=17,191) were recorded within ±5 days from the date of the test result. Conclusions PC Covid-19 diagnosis recorded in BIFAP showed high validation parameters. SE was similar and PPV was slightly lower among vaccinated than unvaccinated controls. Correction of vaccines effectiveness estimates by such misclassification is recommended. Data shows the influence of age. Among the elderly, Covid-19 diagnosis was less recorded but when recorded is more accurate than among younger patients. These findings permit the design of informed algorithms for performing Covid-19-related research.