Background

Drug utilization research (DUR) explores how societies use medicines, bridging pharmacoepidemiology and health services research. It aims to understand, evaluate, and improve medication prescribing, dispensing, and consumption. Key objectives include designing interventions to enhance these processes and informing healthcare decisions [1,2,3].

DUR draws data from various points along the pharmaceutical chain, including procurement, retail sales, pharmaceutical or medical billing, prescriptions, dispensing, drug disposal, pharmacy and health records, and pharmacovigilance. In high-income countries, Electronic Health Records (EHR) are widely used to provide information on drug utilization and health outcomes. However, low- and middle-income countries (LMICs) often lack EHR or have nascent systems [4, 5]. Additionally, the parallel pharmaceutical distribution systems that serve the public and private healthcare sectors in LMICs result in a lack of comprehensive national data on the consumption of medications. Despite pharmaceutical sales data enabling DUR and cross-national comparisons [6,7,8], public sector data remains scarce.

Mexico, trailing only Brazil, stands as Latin America’s second-largest pharmaceutical hub [9]. The nation’s health landscape features three main sectors or sub-systems: social security, other public services, and private services [10]. The social security health subsystem provides healthcare to formally employed workers and their families through various insurance schemes including the Mexican Social Security Institute (IMSS), which as of 2019 covered 37.5% of the population; the Institute of Social Security of State Workers (ISSSTE), which covered 6.5% of the population; [11] and other minor institutions for the national oil company, marine, and army employees (PEMEX, SEMAR, and SEDENA). Each social security scheme provides free health services and medications at the point of care. The second tier, primarily for informal workers, is provided by the Ministry of Health (MoH), at the national and subnational (state) levels. These services were largely overseen by the Popular Health Insurance (SPS), covering 42.7% of the population in 2019. However, SPS’s dissolution in 2020 led to ongoing restructuring efforts [12]. Lastly, Mexico has a large private sector, paid mainly out-of-pocket, which accounted for 43.2% of all outpatient consultations in 2019 [11, 13].

Health sector fragmentation in Mexico has led to disparities in drug access, prescription trends, and personal drug expenses across its three subsystems. MoH facility users face regular drug shortages, while private healthcare users face more prescriptions and greater out-of-pocket expenses [13, 14]. Addressing these disparities requires a thorough understanding of DUR within Mexico’s context.

The limited scope of DUR in Mexico stems from a lack of awareness or access to relevant drug utilization databases. The International Society of Pharmacoepidemiology has supported initiatives in Latin America to address these challenges [15, 16] from which this study departs. This study aims to develop an inventory of electronic data sources available in Mexico for DUR, outlining their characteristics, strengths, and limitations.

Methods

Study design and expert assessment

From March to December 2019, a team of ten experts embarked on a comprehensive assessment of both public and private electronic databases to develop a detailed DUR data catalog for Mexico. The selection of databases was informed by the collective expertise of the research team, coupled with an exhaustive search across academic, private, and governmental websites. Recognizing the impact of healthcare reforms in 2019 and the subsequent changes in governmental health institutions and websites, annual assessments were conducted from 2020 to 2024 to ensure the catalog’s relevancy and accuracy.

Literature review for identifying data sources

A literature review was conducted using MEDLINE/PubMed to identify Mexican-specific electronic data sources that were used in published DUR studies between January 2000 and July 2023 in Spanish and English. The search strategy included a combination of Medical Subject Headings (MeSH) terms: “Drug Utilization”, “Pharmacoepidemiology”, “Drug Prescriptions”, “Medication Errors”, “Self Medication”, “Prescription Drugs”, “Drugs, Essential”, “Drugs, Generic”, “Nonprescription Drugs”, and “Pharmacovigilance”. To capture relevant articles not yet indexed with these MeSH terms, we also included equivalent keywords and variants in the title or abstract, such as “drug utilization,” “pharmacoepidemiology,” “prescription,” “medication error,” “self-medication,” “essential medicine,” “generic drug,” “over-the-counter drug,” “non-prescription drug,” “adverse drug reaction,” “drug safety,” “health policy,” “drug policy,” and “medicine access.” The search was focused on studies related to Mexico, identified through MeSH tagging, mentions in the title or abstract, or author affiliations. The results were independently reviewed by two of the investigators, and disagreements were resolved by a third reviewer. Table 1 outlines the inclusion and exclusion criteria used in our literature review.

Table 1 Inclusion and exclusion criteria for the literature review
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Eligibility criteria for database inclusion

A database was considered eligible for inclusion if it provided information on any aspect of drug use along the drug use chain, including procurement (sales, purchases, and stocks), prescription, patient use, adverse events, and drug disposal in Mexico. The candidate database was also required to offer DUR-related information at the population level. This criterion led to the exclusion of data sources from individual healthcare providers or facilities due to the limited generalizability of their data. We included databases regardless of type, incorporating administrative databases (e.g., health insurance databases) and those used for healthcare purposes (e.g., EHR databases) or for monitoring population health (e.g., national surveys). Among DUR-related publications, only original research articles that included databases that met the eligibility criteria were included.

Screening process for data sources

The expert network used a meticulous screening process, working in pairs and independently, to evaluate potential data sources, resulting in a final inventory of DUR data sources. Collaboratively, the team assessed each database’s characteristics, including contained information, timeliness, and potential access, strengths and limitations for research and decision-making.

Data collection and analysis

The data collection and analysis process were guided by a checklist developed by the European Drug Utilization Research Group [16], which included the following elements:

  • Data Source Name.

  • Database Administrator: Categories included public administration, public health insurer, private health insurer, market research owner, and others.

  • Data Accessibility: This ranged from publicly available to restricted access (protocol-only access; dependent on legislation; limited to specific institutions) and included unclear or inaccessible data.

  • Healthcare Setting: This encompassed hospital settings, ambulatory/primary care, or both.

  • Coverage: Detailed the years covered, geographic scope (national, state, municipality, or other), and population demographics.

  • Data Aggregation: This involved the level of data aggregation, whether individual-level or aggregated.

  • Health Sector Coverage: Included public, private, or both sectors.

This checklist was supplemented with additional details concerning the strengths and limitations of each database. Finally, we mapped all data sources along the drug-use chain and across the various healthcare sub-systems, providing a comprehensive overview of the DUR landscape in Mexico.

Results

Data sources screening and selection

Figure 1 presents a flowchart outlining the selection process of data sources. In the initial search conducted in 2019 across websites, 27 potentially relevant data sources were identified. Over the subsequent years, 7 additional databases were identified, resulting in a total of 34 data sources that were screened. Following the removal of duplicates (n = 2), irrelevant (n = 8) and unavailable data sources due to government changes (n = 4), a final selection of 20 databases met the eligibility criteria for inclusion in the analysis. The literature search initially yielded 1,530 articles using the predefined search strategy. After applying inclusion and exclusion criteria, only 18 articles remained, in which 6 databases meeting our eligibility criteria were identified. Notably, these 6 databases had been previously identified by experts through website search.

  • Table 2 categorizes the identified databases based on their position in the pharmaceutical supply chain and the health sector.

  • Table 3 details each database’s data accessibility, geographical granularity, type of data aggregation, and related publications.

Fig. 1
figure 1

Flowchart of data sources identification and selection

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Table 2 Selected data sources by the healthcare subsystem coverage and position in the pharmaceutical supply chain
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Table 3 Detailed description of identified databases
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Procurement data sources

Retail sales: Market research firms, notably IQVIA, collects retail sales data relevant to DUR. IQVIA utilizes national sample surveys along the pharmaceutical sales distribution chain (e.g., from manufacturers to wholesalers or wholesalers to retailers) to gather information on medicine prices and sales volumes [17]. However, their coverage is limited to the private sector in Mexico, and access is typically restricted to those with approved research protocols.

IQVIA data have been used to compare antibiotic consumption in Mexico and various Latin American countries [8], to evaluate the impact of policy interventions designed to improve the use of antibiotics [18,19,20]and the unintended consequences of such policies [21]. These data have also been used to report and compare antibiotic consumption worldwide [7], and also to evaluate the consumption of antihypertensive drugs consumption in Mexico [22]. IQVIA’s databases are not publicly accessible. Some researchers have managed free access through well-framed research protocols submitted to the company [19]. A major drawback is that the IQVIA surveys only cover the private sector in Mexico.

Public Acquisition: Five databases were identified.

  • The IMSS Purchases (“Compras IMSS”) website became public in 2011 detailing IMSS procurement activities, including medicine purchases and healthcare expenditures. From 2012 to 2018 “Compras IMSS” also coordinated the consolidated purchases (and published related data) for the SPS and other national and sub-national public health institutions and high-specialty hospitals. Data on consolidated purchases was open to the public, however, this system was interrupted post-2019 health reforms [23] and from 2025 it will be substituted by a new system organized by the MoHFootnote 1. “Compras IMSS” was regarded as a relevant source for drug pricing and procurement research in Latin America [24]. The database is accessible now via the Observatory of Mexican Information and National Health Innovation platform (OMINIS) Footnote 2.

  • The IMSS Pharmacy Module (SAI-FARMACIA) provides information on medicine purchase orders, the storage and supply of medicines, prescription information and dispensing, but is not publicly accessible.

  • ISSSTE’s Supply Control Board, a public system since 2012, offers detailed information on medicines and other healthcare supplies of the ISSSTE National Distribution Centre including medicine stocks. There is information on more than 900 medicines from each ISSSTE health facility and central storage, including information on insufficient stocks. The database also has information on the cost per unit of each drug and the expected coverage of the central warehouse stock based on average consumption. This publicly accessible database has been used in the ISSSTE Public Procurement Review [25]. Following recent changes in national medicines procurement, the database is now retrievable from the OMINIS platform.

  • The ISSSTE’s Drug Supply System (SIAM) is an internal database, which has been used to control medicines stock, including the storage of medicines, exchanges, and returns, thereby preventing shortages of medicines in the health facilities and has recently been linked to EHR databases.

  • MoH’s System of Administration, Logistics, and Surveillance of Antiretroviral Drugs (SALVAR) [26]launched in 2011, has national coverage and tracks antiretroviral purchases and prescriptions for patients previously covered by SPS. The initial function of this data source was to manage antiretroviral drug purchases; the SALVAR system was later transformed into a tool for monitoring patients’ health. The SALVAR database has been used to explore the purchasing and prescription practices of antiretroviral medicines [27] and to describe the distribution of AIDS-related mortality in Mexico [28].

Finally, because the medicines procurement process is a public transaction, obtaining data from the databases mentioned above is possible through the National Institute of Transparency, Access to Information, and Protection of Personal Data (INAI), an autonomous constitutional body that seeks to guarantee access to public information [29]. Data requested directly to INAI has been used on a procurement analysis for cancer medicines [30].

Prescription data sources

Twelve databases, including SALVAR, were identified for prescription data analysis, providing comprehensive information on medication prescribing patterns across various health institutions.

  • Key databases such as the IMSS Information System of Family Medicine Consultations (SIMF) and the Information System of Outpatient Specialty Consultations in Secondary and Tertiary-level Hospitals (SICEH) offer rich data, albeit with restricted access to specific research projects.

  • Since 2003, the IMSS Information System of Family Medicine Consultations (SIMF) has collected information from EHR for primary care. including data on patient medical history, reasons for consultation codified according to the Tenth Revision of the International Classification of Diseases (ICD-10), physical examinations, laboratory test orders, and complete electronic prescriptions (names of prescribed medicines, doses, and duration). All IMSS databases are hosted on the IMSS server with IP addresses located in the IMSS intranet, and the access is restricted to IMSS researchers with research projects registered and approved by the IMSS Research and Ethics Committees. IMSS researchers have used the SIMF database on DUR studies focused primarily on healthcare quality including the quality of prescriptions for patients with chronic diseases (e.g., diabetes, hypertension, and osteoarthritis) and infections [31,32,33,34,35].

  • The Information System of Outpatient Specialty Consultations in Secondary and Tertiary-level Hospitals (SICEH), launched in 2006, collects information from IMSS EHR for ambulatory care provided in hospitals. EHR are currently required in family medicine and specialty consultations.

Databases from other social security institutions (ISSSTE, PEMEX, SEDENA, and SEMAR,) provide in-depth prescription data within their operational scope.

  • In the ISSSTE, the database of the Program for the Standardization of Prescription of High Specialty Medications (PEPMAE). is a restricted prescription control system that manages 22 high-cost drugs for treating multiple sclerosis and hemophilia. All high-specialty medications should be prescribed through the Platform of the Control System for Prescriptions (SICOR). This program began in 2013 at the León Regional Hospital and was subsequently implemented in six other ISSSTE regional hospitals [36]. The PEPMAE is available exclusively to researchers in this medical institution because it provides EHR and prescription histories at the individual level.

  • PEMEX developed two integral systems—SIAH and SIAF—tailored for hospital administration and pharmacy management, respectively. These systems ensure restricted accessibility, limiting entry to the institutional network for specific medical and pharmacy staff. The SIAH database has been used in a study of long COVID [37].

  • The SEDENA introduced the Digital Health System SDS in 2018, offering digital healthcare accessible solely within its institutional network, which supports the medical staff in multiple areas, from outpatient care to surgical services, and operates across various regional levels. SDS is available in multiple medical facilities, ensuring efficient, comprehensive patient care for military personnel, retirees, and their beneficiaries [38].

  • SEMAR implemented the Electronic Clinical Record System SICOHOSP that records comprehensive medical data, spanning outpatient visits, emergencies, hospitalizations, and surgical procedures across 35 medical units, using the ICD-10, and it also holds an administrative module for medicines inventory control [39].

These systems, uniquely tailored to their respective institutions, operate within their restricted institutional networks to elevate medical standards and patient care, but an analysis of DUR has not been published in the scientific literature.

Apart from data sources of social security institutions, there are other data sources related to prescription within MoH healthcare units.

  • The National Health Information System under the MoH Directorate General of Health Information holds diverse databases. One of them is the medical emergencies database (Urgencias), which provides information on patient care in the public sector’s emergency rooms. The system provides information from patients and hospital units and dates are included since 2008. Patient data comprises emergency type, treated conditions, medical procedures, and administered medications. The database was recently used in a study on non-steroidal anti-inflammatory drugs [40].

  • The MoH SPS insurance, active until 2019, included a package of 66 high-cost interventions for conditions with potentially catastrophic financial consequences for families. Treatment for covered conditions was delivered in specialty units and financed by the Fund for the Protection Against Catastrophic Expenditure (FPGC); high-cost interventions covered were cancers, lysosomal diseases, and hepatitis C, among others [41]. Reimbursement for medicines from specialty hospitals are included in the FPGC databases with information on patient’s demographics, diagnosis and treatment, and refunded amount. The FPGC database contains data from 2005 to 2016, while data for 2017 and 2018 is only available on Excel files, upon request to the National Institute of Public Health (INSP). No publications were identified using this database.

Finally, two databases provide valuable information on prescription across diverse healthcare institutions.

  • The Citizen Observatory for Access to Medicines and Health Supplies (OCAMIS) has recently created a database using data obtained through INAI. This database contains information on medicines prescribed by public health services including IMSS, ISSSTE, and MoH state health services. It gathers information on medicines prescribed in ambulatory and hospital services weekly, from 2017 to 2024. Additionally, it identifies whether the prescribed medicines have been filled or not at the point of care. Up to date, only prescriptions for a limited number of medicines can be visualized on their website, as the database is still under construction. OCAMIS is hosted by the National Autonomous University of Mexico, UNAM [42].

  • The National Health and Nutrition Survey (ENSANUT) [43] is a survey designed to represent the national population, conducted every 6 years since 2000, and yearly since 2020. This survey follows a cross-sectional, representative probabilistic regional approach and is designed by area of residence. The user module spotlights a random sample of those who recently received primary healthcare, either in public or private facilities. It logs the number of prescribed medicines, usage instructions, and whether patients obtained them at the point of care. The database also contains information on medicine expenditures [44]. Various studies have used ENSANUT for medicine access research [45, 46] and to assess the pharmaceutical use in diseases like diabetes and hypertension [47]. While all data is web-accessible, the INSP, which holds ownership, requires users to obtain login credentials.

Pharmacovigilance

Two pharmacovigilance databases were identified: IMSS’s Pharmacovigilance System (SIFAVI) and the MoH adoption of WHO’s VigiFlow system, enhancing data collection and reporting capabilities.

  • The Pharmacovigilance System of IMSS (SIFAVI), launched in 2006, contains individual and aggregate data on notifications of suspected adverse drug reactions and allows searches for notifications of adverse drug reactions for specific periods and medicines. IMSS-SIFAVI, like all IMSS databases, provides information that can be summarized and reported at the health facility, administrative delegation (35 delegations), and national levels. Currently, IMSS safety data must be reported to the health authority through the National Pharmacovigilance Center.

  • For the past two decades, Mexico’s Federal Commission for Sanitary Risks (COFEPRIS) has managed the national pharmacovigilance program, collecting data initially on paper and later electronically through a short-lived database called NotiReporta [48]. In 2019, COFEPRIS adopted the World Health Organization’s (WHO) VigiFlow system. This platform not only boosts data collection at hospitals and institutions but also streamlines reporting for a more robust analysis [49]. VigiFlow safeguards individual case reports while feeding into the WHO’s global VigiBase. Submitted information is visible only to authorized personnel because the data storage is encrypted and protected. Each reporting institution has access to its own information in Vigiflow, but only COFEPRIS has access to national data. Plus, the eReporting module allows for real-time safety reports from consumers, healthcare professionals, and pharmaceutical companies. This goldmine of data is then shared between pharmaceutical companies and government programs, optimizing their evaluation.

Drug disposal

The National System of Management of Waste of Containers and Medicines (SINGREM), part of the Ibero-American Network of Post-Consumption Programs of Medicines (REDIPPM) [50], offers unique insights into medicine disposal patterns, though its data is not widely accessible. SINGREM was created in 2008 by the Mexican pharmaceutical industry and annually collects and destroys tons of unwanted medicines. Around 5% of this collection undergoes analysis, yielding stats on discarded medication amount, private versus public sourcing, expiration, and intactness. These figures offer a unique lens into medicine consumption through waste [50]. SINGREM’s online stats span only 2010–2017 [51], it is not publicly available, and access procedures are ambiguous. We identified a study that leverages SINGREM examining antibiotic disposal patterns from 2016 to 2019, notably surrounding the 2017 earthquake [52]; and a published study that analyzed unused medications collected in SINGREM’s containers in Mexico City during 2019 [53].

Discussion

Our research has identified various electronic data sources that have potential for DUR in Mexico. This comprehensive perspective is crucial in understanding the intricacies of Mexico’s healthcare system, characterized by a blend of public and private sectors, also common in other Latin-American countries [54].

Notably, most data sources pertinent to DUR are owned by social security institutions, such as IMSS and ISSSTE. The IMSS has been instrumental in various research efforts, especially those focusing on the quality of care. Its extensive data on local medicine usage provides opportunities for detailed analysis by specialization [31,32,33,34,35]. ISSSTE’s databases are promising for evaluating prescribing patterns, dispensing, and overall medical costs [36].

However, the need for more data sources from MoH and private services poses challenges in conducting a comprehensive national-level DUR, thus hindering evidence-informed decision-making and cross-national comparisons. This issue is not unique to Mexico and has also been observed in other Latin American countries as well. The Pharmacoepidemiological Research on Outcomes of Therapeutics (PROTECT) by a European Consortium, highlighted the benefits of cross-national comparisons and showed the opportunities for enhancement in Europe’s healthcare systems [55]. Furthermore, a comparison of Mexico’s MoH databases, such as the SALVAR database and emergency room prescription records, with Argentina’s databases on medicine use among the uninsured, confirms the notable difference in the organizational structure of health data and lack of standardization between countries [56], which might limit their comparison.

The adoption of EHR in Mexico is growing, offering new opportunities for DUR. However, EHR usage in Mexico is highly variable across health sub-systems. While the IMSS has fully implemented a nationwide EHR system for family medicine consultations (SIMF), EHR deployment within MoH facilities varies substantially by state, ranging from full coverage in some states (such as Colima), to a complete absence in others [57]. In the private sector, adoption is more heterogeneous, with some institutions using proprietary systems. Access to EHR data, particularly outside major social insurance institutions, is invaluable for revealing detailed drug usage patterns and identifying previously overlooked areas. While high-income countries often rely on extensive administrative health data, Latin American countries, including Mexico, predominantly depend on primary data collection or third-party sources like IQVIA. It’s important to recognize the limitations of these sources, mainly since IQVIA’s data predominantly reflects the private healthcare sector [17].

The rich data reservoir of IMSS Purchases and ISSSTE’s supply database remain underutilized for DUR purposes. Post-2019 health reforms have further complicated their accessibility; however, these administrative databases are retrievable from the OMINIS platform which might offer an opportunity for research. It is yet to be seen if the new MoH system for consolidated purchases allows publicly access. With programs such as the National Plan against Antimicrobial Resistance emphasizing antimicrobial consumption studies, the timeliness and relevance of tapping into such sources could not be more evident [58].

Given the substantial (40%) portion of health spending that comes from out-of-pocket expenditures, emphasizing the role of private healthcare is crucial. ENSANUT, with its detailed data, is a valuable tool for analyzing drug use in the private sector and rural areas. Similar national health surveys in countries like Peru and Argentina could offer opportunities for cross-national comparisons [56, 59]. In addition to ENSANUT, diverse population cohorts that assess various health conditions and include consumption of medicines are available and have the potential to support DUR [60, 61].

Pharmacovigilance data, though collected for three decades, remains largely inaccessible for broader pharmacoepidemiological research. The National Pharmacovigilance Center has occasionally granted access for specific projects [62, 63], but there is an unclear process for broader access. The introduction of the VigiFlow platform to Latin American countries offers a possibility for institutional research enhancement, but access to national data continues limited.

Similarly, the SINGREM database has limited access and lacks a guideline and process to access it for research purposes. SINGREM, as part of the international network REDIPPM, opens avenues for comparing information across countries and offers insights into medication adherence, prescription patterns, and proper disposal practices, which can promote better environmental practices for the management of pharmaceutical waste.

This research primarily focused on national-level data sources. However, established subnational databases with EHR information, like Colima’s SAECCOL [64] and Mexico City’s SAMIH, indicate the presence of more such sources. Accessing prescribing data from IMSS, ISSSTE, and all state-level MOH clinics through the OCAMIS, provides an invaluable opportunity for DUR and decision-making across subsystems, and at the sub-national level. In a country without a universal healthcare system, understanding data at both the subsystem and subnational levels is essential, emphasizing the importance of population and drug coverage. Finally, other databases may still emerge, such as the COVID-19 open data set used to analyze the use of repurposed antimicrobials in hospitalized patients [65].

This study has its limitations. The criteria used potentially led to the overlooking of relevant, albeit smaller-scale, databases. Databases with ambiguous accessibility and acquisition requirements impeded the evaluation of DUR utility. Furthermore, the transformation of the health system from 2019 to 2024 led to transitional government websites, which hindered comprehensive exploration of some governmental databases.

Despite these limitations, this study provides a comprehensive evaluation by exploring both private and public databases, thus maximizing the chances of identifying all relevant electronic data sources for DUR in Mexico. The collaboration of specialists in DUR, pharmacoepidemiology, and health system research has strengthened the inclusion criteria and evaluation process. A review of literature further enhanced the accuracy of our database inventory.

The mapping of all data sources along the drug-use chain, coupled with the inclusion of other relevant sources like population surveys, provides a thorough overview of available data sources for DUR in Mexico. It is important to note that while this review focuses on mapping available data sources, each dataset may carry context-specific limitations, including the potential for sampling bias. This is particularly relevant for sources based on sample-based methodologies, such as commercial market data. A systematic evaluation of sampling risk across all data sources was beyond the scope of this study; however, researchers using these databases for drug utilization studies should carefully assess the representativeness and methodological underpinnings of each source when drawing conclusions. Additionally, acknowledging the limitations and coverage of these databases at both the population and drug levels is key to maintaining the validity of our results.

Based on our findings, we recommend improving the transparency and accessibility of both public and private data sources in Mexico. Policy initiatives should incorporate measures to facilitate access to government-sponsored databases for research purposes. This includes securing public funding to support DUR studies employing standardized research protocols, ensuring access to databases for approved proposals, and promoting the dissemination of research findings through official government platforms. Additionally, ensuring interoperability among EHR utilized within the public health sector, as well as integrating pharmacy data across different sectors, remains crucial. Finally, government-supported mechanisms should be established to evaluate and validate the representativeness of both governmental and commercial datasets.

This detailed inventory serves as a valuable resource for conducting DUR in Mexico, delineating available databases and extractable information, to reveal drug utilization patterns, trends, and outcomes. Recognizing the complexity of the Mexican health system, this study sheds light on the importance of understanding the coverage and limitations of data sources within the different healthcare sub-systems.

Conclusion

Identifying reliable sources of drug utilization information is essential for conducting research, and ultimately, drive evidence informed healthcare decision-making. In Mexico, valuable data could be found mainly in the databases of social security institutions which are not easily accessible. Accessible electronic data sources for DUR for non-social security institutions and the private sector were very limited. Notwithstanding the collection of pharmacovigilance data, it remains inaccessible for research purposes, which underscores the necessity for more open data policies. Finally, despite the availability of some publicly accessible databases in Mexico, they are still underused in published studies, highlighting the need to promote research on drug utilization in the country.