How software can enable efficient vaccine distribution
After the Pfizer and Moderna COVID-19 vaccines received the stamp of approval, the US faced the immense challenge of quickly building a nationwide logistics network and standing up more than 50,000 vaccination centers. Unfortunately, significant missteps have slowed this vital effort, including 20 million missing COVID-19 vaccine doses, reports of thousands of unused doses, canceled vaccinations due to shortages, and a series of other issues.
It’s clear that our healthcare industry needs more effective tracking of vaccine distribution and delivery to meet current needs, to later roll out COVID-19 variant boosters, and to prepare for future pandemics.
Making vaccine distribution and delivery run smoothly requires accurate, real-time information about all aspects of the distribution network. This information can help guide federal and state health agencies, healthcare providers, and other groups that work together as a joint operation to implement vaccine delivery. Key questions that this real-time information can answer include:
⦁ Where are all the vaccine shipments right now?
⦁ What is the shortfall in vaccines at each centre?
⦁ How many people are waiting for vaccines at each centre?
⦁ How many qualified medical personnel are available at each centre?
⦁ Which centres have the most urgent needs and need immediate attention?
⦁ Is vaccine distribution underserving certain regions or population groups?
Given the unique and highly dynamic nature of this challenge, the healthcare industry needs information processing technologies that are fast enough to generate this information, able to digest data streams from millions of data sources, and agile enough to adapt to evolving needs. A powerful new software technique, called “in-memory computing,” has recently emerged with the ability to meet these requirements. It offers managers an important tool for boosting their situational awareness as they identify and tackle problems in vaccine distribution.
Fast-changing data analysis
In-memory computing software is designed to track and analyse large volumes of fast-changing data in real-time. It can then aggregate results within seconds to give managers a complete visual picture of how a logistics network for vaccine distribution is performing. This enables managers to immediately spot emerging problems, such as a vaccine shortfall in a particular region, and take steps to remedy the situation.
In-memory computing software can simultaneously examine messages from thousands of vaccination centres, update each centre's status, and immediately evaluate which centre are most in need of assistance.
To make all this possible, in-memory computing software can maintain a component, called a “real-time digital twin,” for each vaccination centre to keep track of key status information about the center. As it receives periodic messages from personnel at the centre, it updates its information and looks for problems. For example, it can track the real-time supply of vaccines, current demand (number of waiting recipients), the number of people vaccinated, the availability of trained personnel to perform injections, and much more.
With this information, it can quickly compute the current vaccine shortfall. Application software that runs in a real-time digital twin can be quickly written to analyse a single vaccination centre and then deployed to simultaneously track thousands of centres. This technique can also be applied to vaccine shipments to keep track of their location, condition, and destination.
The in-memory computing software platform continuously aggregates status information maintained by thousands of real-time digital twins to provide managers with an overarching view of key statistics for the complete network of 50,000+ vaccination centres.
For example, it can aggregate the shortfall in vaccine doses by region to quickly pinpoint which regions have the greatest immediate needs. This allows managers to determine where vaccine shipments should be directed to balance overall distribution.
To address the current COVID-19 pandemic and prepare for future ones, it is vital that managers have immediate access to the information they need to ensure timely and efficient delivery of life-saving vaccinations. Because of its ability to analyse fast-changing data scale, in-memory computing software using real-time digital twins has the potential to meet this need.
This technology is agile; it can be quickly deployed and updated as requirements evolve. By providing a key missing piece of the logistics puzzle faced by managers at both the national and state level, it can help unlock the logjam in vaccine distribution to meet this daunting challenge.
Skin Analytics wins NHSX award for AI skin cancer tool
An artificial intelligence-driven tool that identifies skin cancers has received an award from NHSX, the NHS England and Department of Health and Social Care's initiative to bring technology into the UK's national health system.
NHSX has granted the Artificial Intelligence in Health and Care Award to DERM, an AI solution that can identify 11 types of skin lesion.
Developed by Skin Analytics, DERM analyses images of skin lesions using algorithms. Within primary care, Skin Analytics will be used as an additional tool to help doctors with their decision making.
In secondary care, it enables AI telehealth hubs to support dermatologists with triage, directing patients to the right next step. This will help speed up diagnosis, and patients with benign skin lesions can be identified earlier, redirecting them away from dermatology departments that are at full capacity due to the COVID-19 backlog.
Cancer Research has called the impact of the pandemic on cancer services "devastating", with a 42% drop in the number of people starting cancer treatment after screening.
DERM is already in use at University Hospitals Birmingham and Mid and South Essex Health & Care Partnership, where it has led to a significant reduction in unnecessary referrals to hospital.
Now NHSX have granted it the Phase 4 AI in Health and Care Award, making DERM available to clinicians across the country. Overall this award makes £140 million available over four years to accelerate the use of artificial intelligence technologies which meet the aims of the NHS Long Term Plan.
Dr Lucy Thomas, Consultant Dermatologist at Chelsea & Westminster Hospital, said: “Skin Analytics’ receipt of this award is great news for the NHS and dermatology departments. It will allow us to gather real-world data to demonstrate the benefits of AI on patient pathways and workforce challenges.
"Like many services, dermatology has severe backlogs due to the COVID-19 pandemic. This award couldn't have come at a better time to aid recovery and give us more time with the patients most in need of our help.”