Search

Background: The use of routinely collected health data for secondary research purposes is increasingly recognised as a methodology that advances medical research, improves patient outcomes, and guides policy. This secondary data, as found in electronic medical records (EMRs), can be optimised through conversion into a uniform data structure to enable analysis alongside other comparable health metric datasets. This can be achieved with the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM), which employs a standardised vocabulary to facilitate systematic analysis across various observational databases. The concept behind the OMOP-CDM is the conversion of data into a common format through the harmonisation of terminologies, vocabularies, and coding schemes within a unique repository. The OMOP model enhances research capacity through the development of shared analytic and prediction techniques; pharmacovigilance for the active surveillance of drug safety; and 'validation' analyses across multiple institutions across Australia, the United States, Europe, and the Asia Pacific. In this research, we aim to investigate the use of the open-source OMOP-CDM in the PATRON primary care data repository. Methods: We used standard structured query language (SQL) to construct, extract, transform, and load scripts to convert the data to the OMOP-CDM. The process of mapping distinct free-text terms extracted from various EMRs presented a substantial challenge, as many terms could not be automatically matched to standard vocabularies through direct text comparison. This resulted in a number of terms that required manual assignment. To address this issue, we implemented a strategy where our clinical mappers were instructed to focus only on terms that appeared with sufficient frequency. We established a specific threshold value for each domain, ensuring that more than 95% of all records were linked to an approved vocabulary like SNOMED once appropriate mapping was completed. To assess the data quality of the resultant OMOP dataset we utilised the OHDSI Data Quality Dashboard (DQD) to evaluate the plausibility, conformity, and comprehensiveness of the data in the PATRON repository according to the Kahn framework. Results: Across three primary care EMR systems we converted data on 2.03 million active patients to version 5.4 of the OMOP common data model. The DQD assessment involved a total of 3,570 individual evaluations. Each evaluation compared the outcome against a predefined threshold. A 'FAIL' occurred when the percentage of non-compliant rows exceeded the specified threshold value. In this assessment of the primary care OMOP database described here, we achieved an overall pass rate of 97%. Conclusion: The OMOP CDM's widespread international use, support, and training provides a well-established pathway for data standardisation in collaborative research. Its compatibility allows the sharing of analysis packages across local and international research groups, which facilitates rapid and reproducible data comparisons. A suite of open-source tools, including the OHDSI Data Quality Dashboard (Version 1.4.1), supports the model. Its simplicity and standards-based approach facilitates adoption and integration into existing data processes. [ABSTRACT FROM AUTHOR]

Objectives: The use of cannabis-based medicine (CBM) as a therapeutic has surged in Australia over the past 5 years. Historically, the United Nations Single Convention on Narcotic Drugs (1961) prohibited cannabis use in Europe, the USA, the UK and Australia, leading to legislative resistance and limited preclinical data on CBM. Existing safety monitoring systems for CBM are poorly structured and do not integrate well into the workflows of busy health professionals. As a result, postmarketing surveillance is inconsistent. This review aims to evaluate international systems for monitoring CBM side effects and adverse events., Design: To undertake a scoping review with a systematic approach, we used the Population, Intervention, Comparison, Outcome (PICO) framework to develop keyword elements, and two search queries to maximise search sensitivity and specificity., Data Sources: Search queries were entered into Embase and Scopus for peer-reviewed literature, and additional searches for grey literature were conducted on 23 June 2023., Eligibility Criteria: We included 54 full-text articles in the review: 39 from peer-reviewed searches, 8 from grey literature and 7 from citations of relevant texts., Data Extraction and Synthesis: Our search yielded two main forms of monitoring systems: databases and registries. Out of the 24 monitoring systems identified, there were 10 databases and 14 registries, with databases often created by regulatory authorities. Systems differed in methods of causality assessment, level of detail collected, terminology and affiliations., Results: Within the monitoring systems with enough published data for analysis, all except one remain active at the time of this review. VigiBase is the largest centralised monitoring system, receiving international case reports, however data heterogeneity persists., Conclusions: Our study emphasises the need for a centralised, consistent and accessible system for the postmarketing surveillance of side effects and adverse events associated with medicinal cannabis use., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The COVID-19 pandemic impacted mental health disorders, affecting both individuals with pre-existing conditions and those with no prior history. However, there is limited evidence regarding the pandemic's impact on mental health visits to primary care physicians. The International Consortium of Primary Care Big Data Researchers (INTRePID) explored primary care visit trends related to mental health conditions in Argentina, Australia, Canada, China, Norway, Peru, Singapore, Sweden, and the USA., Methods: We conducted an interrupted time series analysis in nine countries to examine changes in rates of monthly mental health visits to primary care settings from January 1st, 2018, to December 31st, 2021. Sub-group analysis considered service type (in-person/virtual) and six categories of mental health conditions (anxiety/depression, bipolar/schizophrenia/other psychotic disorders, sleep disorders, dementia, ADHD/eating disorders, and substance use disorder)., Findings: Mental health visit rates increased after the onset of the pandemic in most countries. In Argentina, Canada, China, Norway, Peru, and Singapore, this increase was immediate ranged from an incidence rate ratio of 1·118 [95% CI 1.053-1.187] to 2.240 [95% CI 2.057-2.439] when comparing the first month of pandemic with the pre-pandemic trend. Increases in the following months varied across countries. Anxiety/depression was the leading reason for mental health visits in most countries. Virtual visits were reported in Australia, Canada, Norway, Peru, Sweden, and the USA, accounting for up to 40% of the total mental health visits., Interpretation: Findings suggest an overall increase in mental health visits, driven largely by anxiety/depression. During the COVID-19 pandemic, many of the studied countries adopted virtual care in particular for mental health visits. Primary care plays a crucial role in addressing mental ill-health in times of crisis., Funding: Canadian Institutes of Health Research grant #173094 and the Rathlyn Foundation Primary Care EMR Research and Discovery Fund., Competing Interests: CL and AO receive a salary for research associate positions at the University of Toronto. JMW holds the position of Vice President Medical Affairs and is employed by the DARTNet Institute. SdeL serves as the director of the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) the primary care sentinel network and he receives funding from the UK Health Security Agency for this position. Seqirus and Roche provided a bursary for speaking. AstraZeneca provided a bursary to attend a European conference. Additionally, AstraZeneca, Sanofi, and Seqirus provided funding for Advisory Board membership. RSK has received payment from Qulturum Jönköping County for lectures and support from Region Uppsala to attend WONCA Sydney 2023. MSC-F is an Associate Professor at the Universidad Peruana Cayetano Heredia, and the Director of the Primary Health Care Research Center. Her salary is sourced from teaching, contracts and grants awarded to the university. She has received a grant from the National Council of Science and Technology of Peru. KT receives a Chair in Family and Community Medicine Research in Primary Care at UHN. She has received grants from the following organizations in the past 3 years: The Canadian Institutes of Health Research, Rathlyn Foundation Primary Care EMR Research and Discovery Fund, College of Family Physicians of Canada/Foundation for Advancing Family Medicine/CMA Foundation Heart and Stroke Foundation of Ontario, Department of Defense United States of America, St. Michael's Hospital Foundation, Ontario Health Data Platform First Movers Fund, Queen's University CSPC Research Initiation Grant, Diabetes Canada, Heart and Stroke Foundation and Brain Canada Heart-Brain IMPACT Award, CANSSI ICES Data Access Grant, North York General Hospital Exploration Fund, CFPC Janus Grant. Support for attending meetings is provided by the Rathlyn Foundation Primary Care EMR Research and Discovery Fund. None of the other authors have reported any other potential conflicts of interest., (© 2024 The Author(s).)