Table 8. Database information.

ID	Name	Description	Terms of Use	Terms and conditions for the access
CPRD	Clinical Practice Research Datalink	The Clinical Practice Research Datalink (CPRD) is a governmental, not-for-profit research service, jointly funded by the NHS National Institute for Health Research (NIHR) and the Medicines and Healthcare products Regulatory Agency (MHRA), a part of the Department of Health, United Kingdom (UK). CPRD consists of data collected from UK primary care for all ages. This includes conditions, observations, measurements, and procedures that the general practitioner is made aware of in additional to any prescriptions as prescribed by the general practitioner. In addition to primary care, there are also linked secondary care records for a small number of people. The major data elements contained within this database are outpatient prescriptions given by the general practitioner (coded with Multilex codes) and outpatient clinical, referral, immunization or test events that the general practitioner knows about (coded in Read or ICD10 or LOINC codes). The database also contains the patients’ year of births and any date of deaths.	1) Please allow for 2 weeks lead time for all publications using these results to go through internal review process. 2) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution.3) Our institution expects all authors to comply with all applicable personal data protection rules (such as the European Data Protection Regulation 2016/679, of April 27, 2016). 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://www.cprd.com/
CU-AMC HDC	U of Colorado Anschuz Medical Campus Health Data Compass (CU-AMC HDC)	Health Data Compass (HDC) is a multi-institutional data warehouse. HDC contains inpatient and outpatient electronic medical data including patient, encounter, diagnosis, procedures, medications, laboratory results from two electronic medical record systems (UCHealth and Children's Hospital of Colorado), state-level all-payers claims data, and the Colorado death registry. Acknowledgement statement: Supported by the Health Data Compass Data Warehouse project (healthdatacompass.org).	1) Please allow for 2 weeks lead time for all publications using these results to go through internal review process. 2) When using our results, you must always use this specific name when referring to our database. No other labels should be used in presenting our results. 3) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution. 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://www.healthdatacompass.org/
CUIMC	Columbia University Irving Medical Center	The clinical data warehouse of NewYork- Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY, based on its current and previous electronic health record systems, with data spanning over 30 years and including over 6 million patients	Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm. The results are specific to a study and should not be reused in other studies without review from our institution. For consistency, the Columbia database should be referred to as CUIMC.	https://www.cuimc.columbia.edu/ about-us/explore-cuimc/contact-cuimc gh13@columbia.edu
HealthVerity	HealthVerity	This HealthVerity derived data set contains de- identified patient information with an antibody and/or diagnostic test for COVID-19 linked to all available Medical Claims and Pharmacy Data from select private data providers participating in the HealthVerity marketplace.	1) Please allow for 2 weeks lead time for all publications using these results to go through internal review process. 2) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution.3) Our institution expects all authors to comply with all applicable personal data protection rules (such as the European Data Protection Regulation 2016/679, of April 27, 2016). 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://healthverity.com/license- healthcare-data-healthverity- marketplace/
HIRA	Health Insurance Review & Assessment Service	National claim data from a single insurance service from South Korea. It contains the observational medical records (including both inpatient and outpatient) of a patient while they are qualified to get the national medical insurance.	Review & Assessment service and the Ministry of Health and Welfare jointly release nationwide COVID- 19 patient’s de-identified data and do cooperation research together with the most prestigious academies and government organizations. Because raw data are owned in the organization so that cohort data are managed by result value sharing method with implementing analysis code without personal information leakage.	https://www.hira.or.kr/eng/main.do
IPCI	Integrated Primary Care Information	The Integrated Primary Care Information (IPCI) database is collected from EHR records of patients registered with 391 GPs throughout the Netherlands. The database contains records from approximately 2.6 million patients out of a Dutch population of 17M (8.2%) starting in 1996.	1) Results can only be used in the intent of a study that is approved by our governance board. Additional derived studies from large-scale analysis therefore require approval. 2) Inclusion of IPCI researchers is required for these derived studies to provide the proper context and interpretation of these results.	https://www.ipci.nl/
IQVIA-OpenClaims	IQVIA Open Claims	A United States database of open, pre-adjudicated claims from January 2013 to May 2020. Data are reported at anonymized patient level collected from office-based physicians and specialists via office management software and clearinghouse switch sources for the purpose of reimbursement. A subset of medical claims data have adjudicated claims.	Inclusion of IQVIA researchers is required in manuscripts using IQVIA data.	https://www.iqvia.com/solutions/real- world-evidence/real-world-data-and- insights
LPD-FRANCE	LPD FRANCE	LPD France is a computerised network of physicians including GPs who contribute to a centralised database of anonymised patient EMR. Currently, >1200 GPs from 400 practices are contributing to the database covering 7.8M patients in France. The database covers a time period from 1994 through the present. Observation time is defined by the first and last consultation dates. Drug information is derived from GP prescriptions. Drugs obtained over the counter by the patient outside the prescription system are not reported.	Inclusion of IQVIA researchers is required in manuscripts using IQVIA data.	https://www.iqvia.com/solutions/real- world-evidence/real-world-data-and- insights
LPDItaly	IQVIA LPD Italy	LPD Italy is comprised of anonymised patient records collected from software used by GPs during an office visit to document patients’ clinical records. Data coverage includes over 2M patient records with at least one visit and 119.5M prescription orders across 900 GP practices. Dates of service include from 2004 through present. Observation time is defined by the first and last consultation dates. Drugs are captured as prescription records with product, quantity, dosing directions, strength, indication and date of consultation.	Inclusion of IQVIA researchers is required in manuscripts using IQVIA data.	https://www.iqvia.com/solutions/real- world-evidence/real-world-data-and- insights
OptumEhr	Optum© de-identified Electronic Health Record Dataset	Optum© de-identified Electronic Health Record Dataset is derived from dozens of healthcare provider organizations in the United States (that include more than 700 hospitals and 7,000 Clinics treating more than 103 million patients) receiving care in the United States. The medical record data includes clinical information, inclusive of prescriptions as prescribed and administered, lab results, vital signs, body measurements, diagnoses, procedures, and information derived from clinical Notes using Natural Language Processing (NLP).	1) Please allow for 2 weeks lead time for all publications using these results to go through internal review process. 2) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution.3) Our institution expects all authors to comply with all applicable personal data protection rules (such as the European Data Protection Regulation 2016/679, of April 27, 2016). 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://www.optum.com/business/solutions/life-sciences/real-world-data/ehr-data.html ?
SIDIAP	Information System for Research in Primary Care (SIDIAP)	The Information System for Research in Primary Care (SIDIAP; www.sidiap.org) is a primary care records database that covers approximatly 80% of the population of Catalonia, North-East Spain. Healthcare is universal and tax-payer funded in the region, and primary care physicians are gatekeepers for all care and responsible for repeat prescriptions.	1) When using our results, you must always use this specific name and this citation when referring to our database. No other labels should be used in presenting our results: Information System for Research in Primary Care (SIDIAP). 2) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution. 3) Our institution expects all authors to comply with all applicable personal data protection rules (such as the European Data Protection Regulation 2016/679, of April 27, 2016). 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://www.sidiap.org/index.php/en
STARR- OMOP	STARR-OMOP	STAnford medicine Research data Repository, a clinical data warehouse containing live Epic data from Stanford Health Care, the Stanford Children’s Hospital, the University Healthcare Alliance and Packard Children's Health Alliance clinics and other auxiliary data from Hospital applications such as radiology PACS. STARR platform is developed and operated by Stanford Medicine Research IT team and is made possible by Stanford School of Medicine Research Office. https://arxiv.org/abs/2003.10534	1) When using our results, you must always use this specific name and this citation when referring to our database. No other labels should be used in presenting our results. 2) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution. 3) Our institution expects all authors to comply with all applicable personal data protection rules 4) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm.	https://med.stanford.edu/starr-omop. html
VA-OMOP	Department of Veterans Affairs	VA OMOP data reflects the national Department of Veterans Affairs health care system, which is the largest integrated provider of medical and mental health services in the United States. Care is provided at 170 VA Medical Centers and 1,063 outpatient sites serving more than 9 million enrolled Veterans each year.	1) Please allow for 2 weeks lead time for all publications using these results to go through internal review process. 2) When using our results, you must always use this specific name and this citation when referring to our database. No other labels should be used in presenting our results. We would like to have the name and description of the database standardized.3) The results are considered fit-for-use and were generated for this specific protocol. Derivations from the intent of this protocol are not validated by our institution. 4) Our institution expects all authors to comply with all applicable personal data protection rules (such as the European Data Protection Regulation 2016/679, of April 27, 2016). 5) Our institution reserves the right to request to omit our results from a drafted publication if the findings could inflict reputational or institutional harm. In line with item 3, we would like to make sure that data created and validated with one use case in mind still fits for other use cases. We do not anticipate examples where data would produce such harm (outside of some data quality issue / need for retraction), but if that were the case, we would need to alert VA leadership and ensure the wording was objective. 6) We need to acknowledge our funding using language like: "This work was supported using resources and facilities of the Department of Veterans Affairs (VA) Informatics and Computing Infrastructure (VINCI), VA HSR RES 13–457." This can be shortened and arranged in the acknowledgement section with others. 7) We need a disclaimer such as: "The views expressed are those of the authors and do not necessarily represent the views or policy of the Department of Veterans Affairs or the United States Government." This can be shorted and combined with other institutions' disclaimers.	https://www.data.va.gov/