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Participants discuss temperature data and what it implies for maintaining cold chain equipment.
How do you gain insight into the performance of cold chain equipment and its ability to keep vaccines within the ideal temperature range? By gathering vaccine cold chain equipment manufacturers and technicians and temperature data analysts in the same room.
During a side session at the TechNet Conference this October, in collaboration with New Horizons, PATH, VillageReach, CHAI, and eHealth Africa, we invited participants working with cold chain equipment and temperature monitoring to help us find ways to use temperature data to inform cold chain equipment maintenance. With new technology, real-time temperature data are more widely available, providing insight into the performance of the equipment and its ability to keep vaccines in the ideal range. This is essential to ensure that vaccines do not lose potency and protect those who receive them from vaccine-preventable diseases.
While data are regularly collected, it is not clear how or how often they are used. We thought the data could be used in a more proactive and predictive way to support equipment maintenance and management.
Before the session, we gathered and anonymized temperature data from multiple countries and types of devices—remote temperature monitoring devices and data loggers such as 30-day temperature recorders and different cold chain equipment makes and models. We challenged the 60 participants to hypothesize what the data were telling us about the cold chain equipment. For example:
The temperature data were analyzed from a programmatic and a technology perspective, including discussions that fluctuations in data could be due to the door being held open for monthly shipments of commodities, or that the fan needed to be cleaned. It was an opportunity for everyone in the room to find out more about cold chain equipment, what temperature data tell us, and to start thinking about how to translate these data into insights and action.
Session participants could only do so much to discern the maintenance and repair actions the equipment needed. Without cold chain technicians (who unfortunately were not at the conference) to confirm, we were still missing a critical piece of the puzzle.
This gathering was one step in thinking about practical use cases for temperature data. Once we are able to convene all critical staff, we can create a practical “cheat sheet” or diagnostic toolkit that provides recommended actions for technicians to maintain and prioritize cold chain equipment and can help with longer-term planning for cold chain equipment needs. To maximize data use opportunities, we can explore the use of machine learning and predictive analytics to optimize repair routes, order spare parts, and provide remote guidance for basic maintenance. All of this will help cold chain technicians and supply chain and immunization program managers make more informed decisions.
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