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OpenMRS Evidence Hub

OpenMRS Evidence Hub

Help us improve our Evidence Hub! Have you written a published paper about OpenMRS? Know of one that's not listed here? Add it!

 

  1. Decide if you want to contribute just a few times or regularly.

    1. If you just want to contribute right away: You can use this search query on Google Scholar to start finding publications that mention OpenMRS. You are welcome to use other academic search tools instead (such as PubMed); the reason we recommend Google Scholar is we find that this helps us discover mentions from LMIC-based authors whose work may not otherwise appear in academic search tools that favor journals from higher-income settings.

    2. If you want to regularly contribute: Sign up for Google Scholar alerts to your inbox at https://scholar.google.com/scholar_alerts 3. Use the search term “openmrs”. This ensures that you will get an email alert for any article that mentions “openmrs” or a similar term. Then when you receive automated email alerts, review the email. (Sometimes it is a false-alarm - e.g. sometimes you’ll get alerts for a totally unrelated system called “openMS”. You can ignore these.)

  2. Review the publication: If the alert looks like it really involves OpenMRS, open up the publication and see if it looks like it is from a legitimate source (such as a formal journal, reputable conference, or other trusted source like a Ministry of Health or implementing organization). Then, see if the article actually mentions anything of substance about OpenMRS. For example, if the article only mentions OpenMRS as a source in a footnote, this is not sufficient to be added to our Evidence page. The article should contribute some interesting knowledge to the OpenMRS community of implementers, developers, or researchers. Sometimes the article might be about some particular disease research, or open source processes, or eHealth leadership, or even cybersecurity practices.

  3. Add to the Wiki page following the table template.

    • The most important part here is the “Themes” so that people can quickly find articles of interest to them, or at least, proof that OpenMRS has had impact in multiple areas. (For example, in the past there was a myth that OpenMRS was only for HIV care (incorrect!), so it was important for us to show articles from other disease areas, such as Oncology, Endocrinology, and more.)

    • Use APA formatting (guidelines here, free generator here), as this is often the formatting standard that healthcare researchers expect, and thus communicates professionalism.

  4. Bonus: If you thought the article had an extra interesting quote or general finding, share that quote or note in the table for easy reference!

This page is our online repository of the many studies conducted exploring OpenMRS. Collectively, these studies provide strong evidence for a variety of use cases: the impact of EMR use on care, secondary data use for site or regional or global program guidelines improvement, and the community open source model. The OpenMRS Community maintains the OpenMRS Evidence Base and adds new studies as they are discovered.

Over 4,050 publications are noted online involving OpenMRS - search query here.

Note

This page began in August 2023. We are communally updating this with the thousands of articles published on OpenMRS, strongly prioritizing recent articles from within the last few years.

Category

Citation

APA formatting preferred

Year

Country

Reference Key

URL

Misc. Notes

Category

Citation

APA formatting preferred

Year

Country

Reference Key

URL

Misc. Notes

HIV, KPs

Ensuring Equitable Access to Quality HIV Care for Key Populations in Complex Sociocultural Settings: Lessons from Nigeria

Abdulsamad Salihu, Ibrahim Jahun, David Olusegun Oyedeji, Wole Fajemisin, Omokhudu Idogho, Samira Shehu, Jennifer Anyanti

2025

Nigeria

Salihu 2025

https://doi.org/10.1101/2025.01.19.25320786

 

TB Tuberculosis

Sharifov, R., Nabirova, D., Tilloeva, Z. et al. TB treatment delays and associated risk factors in Dushanbe, Tajikistan, 2019–2021. BMC Infect Dis 24, 1398 (2024).

2024

Tajikistan

Sharifov 2024

 

https://doi.org/10.1186/s12879-024-10265-8

 

Data Interpretation


Nanyonga, S., Medina, P. B., Kozlakidis, Z., Garcia, D. L., Ivanova, D., & Katsaounis, P. (2024). Proliferation, ingestion, and interpretation of health data in low- and middle-income countries (LMICs). In Z. Kozlakidis, A. Muradyan, & K. Sargsyan (Eds.), Digitalization of medicine in low- and middle-income countries (Sustainable Development Goals Series). Springer. https://doi.org/10.1007/978-3-031-62332-5_25

2024

Global

Nanyonga 2024

https://link.springer.com/chapter/10.1007/978-3-031-62332-5_25

This Book Chapter shows how digital health initiatives like OpenMRS are progressing from pilot stages to scalable, integrated healthcare solutions, emphasizing the importance of data proliferation, ingestion, and interpretation for sustainable impact.

Process Optimization

Implementation models

Innovation

Avagyan, A., Minasyan, E., Khachatryan, H., & Gevorgyan, S. (2024). Possible process optimization: Innovative digital health implementation models. In Z. Kozlakidis, A. Muradyan, & K. Sargsyan (Eds.), Digitalization of medicine in low- and middle-income countries (Sustainable Development Goals Series). Springer. https://doi.org/10.1007/978-3-031-62332-5_10

2024

Global

Avagyan 2024

https://link.springer.com/chapter/10.1007/978-3-031-62332-5_10

 

Interoperability

Cyber Security

FHIR

Anantharaman, P., Shapiro, R., Varadharaju, V., & Locasto, M. E. (2024). A study of interoperability in electronic health record software. In Proceedings of the 2024 Workshop on Cybersecurity in Healthcare (HealthSec ’24) (pp. 8). ACM. https://doi.org/10.1145/3689942.3694743

2024

Global

Anantharaman 2024

PDF

FHIR Garden, a tool designed to compare FHIR implementations in EMRs including OpenMRS, identifying parser discrepancies and highlighting vulnerabilities that could impact patient data security.

COVID 19

Remote Health Monitoring

 

Musheghyan, L., Harutyunyan, N., Sikder, A., Reid, M., Zhao, D., Lulejian, A., Dickhoner, J., Andonian, N., Aslanyan, L., Petrosyan, V., Sargsyan, Z., Shekherdimian, S., Dorian, A., & Espinoza, J. (2024). Managing patients with COVID-19 in Armenia using a remote monitoring system: Descriptive study. *JMIR Public Health and Surveillance, 10*, e57703. https://doi.org/10.2196/57703

2024

Armenia

Musheghyan 2024

https://publichealth.jmir.org/2024/1/e57703

This study highlights the effective use of an OpenMRS based system for a remote monitoring and home-based oxygen therapy program (COVID@home) in Armenia, showcasing its potential in resource-limited settings.

Implementation

Clinical Decision-Making

Impact

Bouh, M. M., Hossain, F., Paul, P., et al. (2024). The impact of limited access to digital health records on doctors and their willingness to adopt electronic health record systems. Digital Health, 10. https://doi.org/10.1177/20552076241281626

2024

Bangladesh

Bouh 2024

https://journals.sagepub.com/doi/10.1177/20552076241281626

The study investigates the challenges Bangladeshi doctors face due to limited access to digital health records, affecting their workload and clinical decision-making. It also highlights the impact and efficiency brought in by some OpenMRS-based implementations

Implementation

Uwambajimana, E., Rugirangoga, P., Musabyimana, E., et al. (2024, August 25). Assessment of the use of electronic medical records system and barriers in Rwanda (Version 1) Preprint. Research Square. https://doi.org/10.21203/rs.3.rs-4763866/v1

2024

Rwanda

Uwambajimana 2024