With 70% of health IT professionals reporting their organizations have adopted cloud computing solutions, and another 20% expressing their desire to migrate to the cloud in the next two years, it’s safe to say that cloud computing in healthcare is in full swing.
And for good reason. The cloud is enabling healthcare to solve long standing challenges that were not possible previously – or at least would’ve been prohibitively expensive – using traditional computing solutions. And the cloud is enabling this at a rapid scale and pace.
What are the biggest benefits of cloud computing for healthcare organizations?
Here are the top nine.
Providing high-quality care requires patient records to be readily available, discoverable, and understandable. A huge challenge in healthcare is that data are often locked up across disparate systems and stored in varied formats, making them incompatible for sharing information, creating data silos.
When providers can’t access patient records, they’re forced to rely on patients to provide accurate information on their medical history, but patients often miss important details, which hinders care quality.
But with cloud computing, data are stored in a centralized location and made available to anyone with a network connection to the system. Cloud is open source and data are generally stored in common languages like JSON, XML, HL7, and FHIR, enabling systems to communicate with each other so clinicians can access longitudinal data on their patients.
Analytics on large datasets can provide a wealth of information for driving standards of care. Unfortunately healthcare data is incredibly heterogenous, so analyzing large amounts of healthcare data requires a lot of manual work to transform it and get it ready for analysis. Because of this, a lot of valuable data is left untouched and unused.
Cloud Service Providers (CSPs) offer a wealth of services that can help remove the manual work around preparing and analyzing data, like extract, transform, and load (ETL) services that can transform raw data into a single format and data integration services that make it easier to discover, prepare, move, and integrate data from multiple sources.
Traditionally, artificial intelligence (AI) and machine learning (ML) solutions were incredibly complex and expensive to implement. Only organizations with a ton of capital to burn were able to invest in this technology. Today, thanks to CSPs like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, this technology has been made available to anyone with an internet connection.
With the power of AI at their fingertips, healthcare organizations are able to solve previously unsolvable challenges. For one, healthcare payers can use ML models to identify at-risk patients – 5% of patients are consuming nearly 50% of the medical spend. This can trigger proactive interventions, like reminders for medical screenings to help improve the health of these patients before they end up in the emergency room.
On the provider side, AI is being used to diagnose ailments sooner, like recognizing breast cancer in early stages in CT scans, which significantly increases the chance of survival. As for genomic organizations, they’re building solutions that can identify patients who are at high risk of diseases like Alzheimer’s, which can help drive preventative care that slows the progression of the disease.
More than ever, healthcare CIOs are being expected to leverage technology in order to streamline care processes and simplify the journey for the patient. In the words of one healthcare CIO, “The best check-in process is no check-in at all.”
Hospitals are expected to offer contactless patient intake services, online appointment scheduling, telehealth, self-service payment tools, digital consent management, remote patient monitoring, and other solutions that improve convenience for the patient. And all of these applications are infinitely easier to manage, upgrade, and scale when hosted on the cloud.
Healthcare generates an enormous amount of unstructured data. Compared with industries like financial services, which tends to work with a lot of structured data, healthcare produces a vast array of unstructured data, like written notes, discharge summaries, lab reports, consent forms, and medical imaging data from MRI scans and CT scans, and so forth. Unstructured data takes up far more space than structured data and are incredibly expensive to store by comparison.
To further complicate things, the Health Information Portability and Accountability Act (HIPAA) requires medical data to be stored for a minimum of seven years. The penalties for mismanaging this can be costly. So what do healthcare providers do? Usually, they don’t delete anything.
Historical data storage becomes a huge expense for hospitals. But with the cloud they can use services like Amazon S3 Deep Archive and store a terabyte of data for just a buck and a penny a month. Plus, when hospital facilities space is freed up from hardware storage, that space can be repurposed toward providing more healthcare services.
There’s a big push in healthcare to switch from a fee-for-service reimbursement model to a value-based reimbursement model. The fee-for-service model means providers get reimbursed by payers solely based on the costs of the services provided. The problem with this is that it incentivizes providers to administer more tests and more expensive solutions than may actually be needed to achieve the best health outcomes. Alternatively, value-based care rewards providers based on the quality of care given, instead of quantity, and incentivizes them to provide the most effective care while also managing costs.
The move to value-based care (VBC) is an important step toward improving healthcare outcomes, but in reality it’s not achievable in many cases today. A report from 2023 found that only 46% of primary care physicians received payments through VBC models.
Determining VBC metrics is a data exercise, requiring interoperability between disparate electronic health records (EHR) systems, sophisticated data analysis, and ML modeling. As we discussed earlier, these are incredibly difficult things to achieve using traditional infrastructure. But with the cloud, the ability to move toward a more value-based reimbursement system is made possible.
Medical practitioners need to take detailed notes to assist with present and future care. One challenge is that clinicians often spend far too much time inputting notes into the system, which can result in overly long visits, long wait times for patients, and can reduce the number of patients served in a given time. This is especially problematic in emergency care situations, where mortality rates can increase with long wait times in some cases.
Solutions from CSPs are changing that. Microsoft and Epic recently announced the release of the Nuance® Dragon® Ambient eXperience™ Express (DAX Express™) solution for Epic EHR. Dax, a generative AI solution, allows clinicians to draft clinical notes automatically, reducing hours of work to mere seconds and enabling them to spend more time with patients and less time typing up notes.
The public cloud is more secure than on-premise data centers because cloud security is a shared responsibility with the CSP. So many of the tasks that are required to secure traditional infrastructure, like securing the hardware itself and patching, configuring, and managing access of the physical hosts, is provided out-of-the-box by the CSP. And you can bet they accomplish these tasks better than you ever could! CSPs compete for the best talent and pay top dollar for the best tools, as delivering good security is part of their business model.
But there’s one caveat. Although cloud infrastructure security is among the best in the world, organizations still have to secure the data they put in the cloud themselves. They must limit access, encrypt data, enable authentication, create roles, rotate keys, and employ other best practices around data security to keep hackers out. A common mistake is that some companies assume the CSP is managing all the security protocols, and they neglect to keep up their end of the bargain which is why so many data breaches can be attributed to simple access management failures and misconfigurations.
The cloud can be configured for high availability quickly and easily, when compared to traditional infrastructure. You can leverage multiple data centers in multiple locations as easily as you can software. You can implement load balancing to distribute traffic evenly across multiple servers to help ensure your application remains available even if some instances become unavailable. You can set up auto scaling to automatically add or remove resources based on demand so your application can handle traffic variation. You can set up automatic backups and backup your data to different regions, in case one region experiences a catastrophic disaster. All of this can be done in a matter of days. This wouldn’t be impossible to do on premise, but it would take years to deploy and management would be prohibitively complex.
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Wrap Up
Whether your organization is trying to create innovative new applications or just wants to simplify medical record systems management, the cloud offer healthcare organizations the scalability, agility, and cost efficiency to meet modern healthcare needs.
To learn more about why your healthcare organization should consider going all in on cloud, read the free eBook, The Business Case for Public Cloud in Healthcare.
Or schedule a free consultation with a healthcare cloud expert today to learn how cloud managed services can help you achieve your cloud goals.