A 2017 study by Trust for America’s Health declared Public Health funding a national crisis. It highlighted the need for Public Health entities to “address gaps in critical infrastructure and update outdated systems and technologies.”
In December of 2019, Congress stepped in to help by introducing the Public Health Infrastructure Modernization Act of 2019. The bill allocated $500M for Public Health data and technology improvements and authorized entities to update and improve their data collection methods.
Then, in December 2019, the COVID-19 pandemic entered the picture.
Now, public health’s technology gaps are glaring. Health systems are being flooded with data. Many health information exchanges (HIEs) don’t have the IT capacity to handle the rise in demand, nor do they have the interoperability capabilities to capitalize on the data in a meaningful way.
Which is causing HIEs to adopt a cloud-first strategy. Here are three challenges the cloud is currently solving for HIEs.
Traditional HIE technology stacks are incredibly expensive – oftentimes in the millions per year for the full stack. This is a significant portion of most HIE budgets, which makes it difficult for HIEs to invest in growth.
However, a cloud-based model allows HIEs to throw away expensive hardware and much of the technology stack, significantly alleviating pressures on HIE bottom lines. In fact, our cloud-native interoperability solutions are saving HIEs around 90% on their technology stacks, giving them back valuable resources they can instead invest in growing their capabilities.
2. Data Interoperability
Data interoperability has always been limited and challenging. Besides the inconsistencies in encoding systems and data that make interoperability difficult, the integration engines designed to ingest the data are finicky and prone to error. They reject a lot of data if it isn’t a perfect match, and just getting the data into the environment can take months.
With cloud-native data interoperability solutions, HIEs can spin up new environments in a matter of days. They can train and leverage machine learning models that can help uncover deeper insights. They can also use tools like Amazon Comprehend Medical to quickly find valuable information in unstructured text like clinical notes, improve attribution, and increase interoperability.
As the COVID-19 pandemic increases momentum, there’s pressure for HIEs to scale and manage the data quickly. Using traditional hardware, scaling an interoperability program could take between six and eighteen months – which is time we don’t have.
The move to the cloud is allowing HIEs to scale their data interoperability programs in minutes. They’re swiftly standing up massive data lakes, deploying sophisticated data ingestion platforms, and providing data scientists with access to rich sets of healthcare data. They’re analyzing the data, tracking the disease, implementing policies that are mitigating the spread of the disease, and saving lives in real time.
The Emergence of Next-Gen HIEs
As the pandemic rapidly grows and evolves, many HIEs are turning to public clouds like Amazon Web Services (AWS) to meet their digital needs. This move is allowing HIEs to be more effective, offer more strategic solutions, and become real-time responders in the fight against the pandemic.
Even after the pandemic is over, the implications for Public Health are immense. With the agility and capabilities gained, HIEs will be able to upscale their contribution to the healthcare ecosystem, dramatically reduce costs, and increase the scope and impact of healthcare data interoperability.
If you’re an IT professional at a healthcare organization looking to quickly spin up a COVID-19 data interoperability program, reach out to us. We are currently working with some of the hardest hit states and would love to talk to you and see if we can help. Schedule a free consultation today.