Thursday, 16 April 2020
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PATH's Bill & Melinda Gates Foundation funded Introducing Digital Immunization information systems: Exchange and Learning from Vietnam (IDEAL-Vietnam) project is very excited to announce the release of their second case study: 


This case study deep dives into lessons learned from Vietnam of a successful scale-up of an electronic immunization registry (EIR) from pilot to nationwide application. Successful scale-up is not an easy feat, and the process of moving from small- to large-scale operations in Vietnam was due in part to from-the-start planning, key partnerships, government commitment, and sustained collaboration. The webinar will highlight key facilitators and barriers, and focus on important partnerships that catalyzed the success of the scale-up process. 

You can find regularly updated project documents and further information about this project on our homepage (

Please do not hesitate to reach out to [email protected] for questions or comments on this case study or the IDEAL-VN project. 

Thanks for interesting entry. Can you share the study methdology and findings supporting the impact changes (e.g. time to produce the report, changes in vacciantion coverage, etc). I would like to consider this data for inclusion into a systematic review.

3 years ago

After reviewing the lessons learned from Vietnam national EIR document, it's far from calling it a successful scale-up. Training all health workers on how to use EIR is not the same as successfully scaling EIR system. Some points to consider from the current status of implementation of EIR system in Vietnam:

1) Health workers are still using paper-based and EIR systems in parallel, which means data is not accurate and complete in EIR system, and Government is still relying on manually generated monthly reports, compared to EIR generated monthly reports. There is no real value brought from EIR data yet.

2) There is no technical support at the commune level, to mitigate any technical issues quickly. Technical issues happen daily, and if there is no technical support at the district/commune level, health workers will give up on using the system, as it is not available for them to use.

3) There is no annual budget from the Government to procure laptops, mobile devices for health workers, to enter directly immunisation data to EIR. Which means if the device is not working, health workers need to use papers, and one cannot successfuly transition to paperless work.

4) There is no process for supervision, monitoring and evaluation of data quality and data use, which means data accuracy and data completeness will get worse over time. 

5) Data accuracy and data completeness is very low, and it is getting worse.


One should consider and claim successful national scale-up of EIR when there is successful operations of EIR system. Some points to consider:

1) Health workers are only using EIR system and current paper forms are retired, and there is no duplication of efforts or double entry at the facility level

2) There is available and effective proactive and reactive technical support at the district/commune level, to fix technical problems in less than 1 hour

3) There is an annual budget allocated for replacing old/broken/stolen laptops, mobile devices, computers at facility level

4) There are resource available and effective processes are established for supervision, monitoring and evaluation of data quality and data use. 

5) When data quality is high for at least 90-95% of health facilities, and health workers, commune, district, province and national level stakeholders trust and use the data for improvement actions. Data accuracy should be above 90-95%, in order to be trustworthy. 

I definitely miss some other points here for establishing successful EIR system at a national level, but these five points are critical ones. Let's do our home work properly and keep learning how to make EIRs successful.

Thanks Rustam for this insightful remarks. My impression is that this is rather a controversial area resulting from patchy (when not contradictory evidence). This relative lack of evidence may be delaying the scale up of effective interventions as well as accelerating the setting up of ineffective (and may be harmful) ones. May I take this platform to propose an open dialogue with explicit rules of the game about what works and what doesn't, in terms of HIS (maybe not resitricted to immunisation)? Any interest?

Géraldine Nemrod
updated the category from Data to Data — 3 weeks ago
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