WHO supports a quality data system through the Operational Research and Structured Training Initiative in Sierra Leone – Sierra Leone

Sierra Leone is among the other low- and middle-income countries with public health programs that are ‘data rich but information poor’, implying that a lot of data is generated at the country level, but the full potential of it. Using this data to inform improvements in public health is rarely achieved.

Antimicrobial resistance (AMR) is a global public health challenge with the potential to kill up to 10 million people per year by 2050 and cost the global economy up to $ 100,000 billion. AMR makes standard treatments ineffective and allows infections to persist and spread to others.

Aware of these disturbing statistics, the Operations Research and Structured Training Initiative (SORT IT) seeks to make countries ‘rich in data, information and action’, thereby helping to improve healthcare delivery and outcomes. .

WHO HQ and the Sierra Leone Country Office, in collaboration with the Ministry of Health and Sanitation, organized the Sierra Leone SORT National IT Training for Ministry of Health staff and of Sanitation, the Ministry of Agriculture and Forestry and the Environmental Protection Agency, with a view to a health approach. The training took place in Bo district and in the capital Freetown. The objective of the training is to strengthen the capacity of participants to write operational research protocols and to better understand the collection and analysis of quality data.

Dr Ibrahim Franklyn Kamara, SORT IT Fellow and member of the WHO Infection Prevention and Control (IPC) team highlighted the importance of these trainings:

“Sierra Leone, like many other parts of the world, has limited data on AMR, antimicrobial consumption and / or use, making it difficult to prioritize interventions that will reduce the burden of AMR in the community. country. As emerging and re-emerging infectious disease outbreaks become more frequent, we need to better prepare to prevent the silent AMR epidemic. Dr Kamara said.

At the end of these trainings, it is expected that 16 priority projects of Operational Research (OR) (4 regional participants and 12 national) and many other researchers have been trained on OR. The SORT IT program helps its fellows to become future OR leaders; build a community of practice on AMR; an extended SORT IT partnership base; publications; policy / issue briefing notes; and the integration of OR activities into national strategic plans.

“Completing 2 modules of a 4-module course gave me valuable insight into operations research, research protocol development, and quality data collection and analysis. As a SORT IT Fellow, I am happy to participate in the first cohort of Sierra Leone’s national SORT IT training, says Dr Kamara.

Bobson Derrick Fofanah, WHO Infection Prevention and Control Officer, explained what SORT computer training means to him:

“At SORT IT, we are guided to undergo training and conduct our research simultaneously. In Sierra Leone National SORT IT Modules 1 and 2, I was able to use my research project and acquire the practical skills needed to write a study protocol and ensure quality data capture and analysis. I feel privileged to be part of this initiative ”, declared FOFANAH.

“Of the 12 SORT IT participants from Sierra Leone, six chose their research topic around IPC; and I think the reasons for this are universal acceptance with evidence that an effective IPC implementation is a practical and cost-effective approach to preventing healthcare associated infections (HAIs) and leads to a reduction by 2/3 of the frequency of RAM, ”added Fofanah.

SORT IT has been successfully extended to 90 countries over 8 years (with approximately 800 participants) and has addressed topics such as multidrug-resistant tuberculosis, malaria, maternal and child health, epidemics and emergencies. The approach has proven to be adaptable to various geographic contexts, thematic areas and research methodologies. About 85% of participants publish in peer-reviewed journals and 69% of studies report an impact on policy and practice. This model is now suitable for combating RAM.

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