Cloud Computing in Healthcare

The global healthcare cloud computing market is expected to reach $35 billion by 2022, increasing by 11.6% each year, according to BCCResearch. COVID-19 pandemic pushed healthcare organizations and medical institutions to adopt cloud computing services for ensuring remote patient care at a large scale. 

Keep reading this article to find out what advantages of cloud computing in healthcare are already actively utilized in the industry and what future of cloud computing in healthcare is to expect in the next few years.

Cloud computing is a technology that enables storing, accessing, and processing data ‘in a cloud’ from any device instead of using your local hardware capacities. It allows to quickly deliver content on high-loaded platforms and create apps that may be accessed from any type of user device on the web.

As an outsourcing dotnet development Dataxdev is here to share our experience with cloud technologies in the healthcare industry through the article below.

The use of cloud computing in healthcare can be represented in such simple things as a telemedicine app that runs in a cloud, or it can be as complex cloud-based IT infrastructure that unites healthcare establishments, pharma companies, suppliers, insurance companies, and patients.

Healthcare establishments can store and exchange valuable data like electronic healthcare records, physician notes, staff schedules in the cloud and access it when the data is needed. Cloud storage is beneficial in terms of service costs: providers charge clients only for actual usage of cloud computing and never upfront.

In-establishment IoT cloud apps can help with remote patient monitoring by hospital staff. IoT devices can even assist patients with changing their body positions or adjusting beds or wheelchairs to patients’ ongoing needs. IoT-based cloud apps can also be used for home patient care providing doctors with precise health indicators monitoring information. 

This type of apps powered with AI is popular in medical diagnostics.

Distribution model of cloud computing can be splitted in three categories: IaaS, PaaS, SaaS. A great example of the combination of these services is Amazon Web Services (AWS).

Infrastructure as a service (IaaS) — cloud vendor delivers IT infrastructure with the operating system that allows users to manage all business resources through the cloud. Clients deploy their own apps on this tech basis. The more legacy systems become outdated, the more IaaS grow their popularity meeting the demand for legacy systems modernization and cloud migration services. One of the brightest examples can be Microsoft Azure.

Platform as a service (PaaS) — PaaS providers deliver clients their infrastructure and platform that serves as a virtual software development environment. It provides developers with in-built software components, SDKs, or high-level API integrations to speed up the development process with ready tools. AWS Elastic Beanstalk is a PaaS part of its cloud computing services.

Software as a service (SaaS)— these applications are delivered over the internet on a subscription basis instead of software you pay for and download on the front end. SaaS apps run on a provider’s remote servers and have gained popularity among business owners due to the speed and low costs of their development and maintenance in the cloud, as in this case, programmers don't need to build separate app versions for each type of device. Users love SaaS apps at least for saving space at their device storage.

The deployment model depends on cloud ownership and accessibility.

Private cloud can be accessed only by a particular client or employees of an established legal entity. Healthcare organizations tend to use private clouds as they want to have all possible control over the storage environment to ensure HIPAA compliance with no help from other vendors. Private cloud also has more customization options to offer. Private cloud is more expensive than public cloud due to the demand for local hardware.

Public cloud is available for usage by a wide general audience on the web. Public clouds are flexible in scalability. Large healthcare institutions frequently use public clouds to test new environments before extended migration projects.

Hybrid cloud provides its owner with tools for access level control based on pre-established parameters. This perfect mix of on-premise resources and cloud tools helps healthcare vendors achieve security compliance and smooth workflow migrations.

Cloud technologies create advantages for both doctors and patients. Cloud-based apps help manage diagnostic and treatment processes on different stages — during a hospital stay and remotely.

Cloud computing enabled the processing of an enormous amount of data per short unit of time. It revolutionized telehealth solutions and IoT-based cloud computing applications in healthcare. SaaS healthcare apps can leverage real-time patient data from different sources simultaneously. This way, comparing heart rate indicators from smartwatches with a patient’s heart disease history in his or her healthcare records, a cloud app can notify doctors and patients about the possible risks or even advise preventive measures. 

Of course, to achieve this level of ‘application smartness’, developers should also apply AI and machine learning technologies. However, cloud computing technologies are the reason why today we can process and share all these volumes of data in such a fast manner.

Cloud healthcare infrastructure is usually powered by various data sources depending on departments, divisions, partnership programs, and patients as key data generators and providers. However, this data can be enriched through integrations with third-party data platforms to get more external information, for example, to identify the frequency of patterns in diagnostics of some disease among a certain segment of patients in a given region. 

Using cloud-based apps, users of different levels can see the full picture of healthcare efficiency in business operations or patient successes.

Medical data analytics solutions are one of the good examples of applications of cloud computing in healthcare. Patient data is a priceless digital asset, whether it is structured or not. Using BI tools and machine learning algorithms to process these datasets, hospitals, and clinic owners may predict seasonal facilities load or probability of epidemic outburst. Deep and complex patient analytics also helps doctors create more efficient treatment plans and make dynamic adjustments based on real-time data changes.

Before medical cloud computing, all patient health records were uselessly stored within establishments, and now they are available for utilization in medical research. The medical data on patterns and correlations in the states of health of patients with the same symptoms or diseases helps deliver diagnostic and treatment insights. At the same time, sensitive pieces of data that uncover the real person behind medical history remain securely encrypted and anonymized.

Thanks to cloud computing, applications in healthcare anticipative services turn from the utopian concept of predictive medicine to practical reality. Predictive analytics in medical cases may scan patients' health condition monitoring, taking into account their medical history, ongoing treatment plan, and external statistics of patients with similar health indicators to forecast risks and emergencies. These analytical conclusions may be sent to doctors and caregivers so they could adjust cure plans to avoid worst-case scenarios.

If a forecasting analytics tool is combined with wearable devices and IoT-based cloud medical apps, risk alerts may trigger automatically executed action like calling an ambulance with pre-diagnostic assumption. Even some smartwatches can save a human life if it's powered by a cloud computing app.

Lucrative opportunities for significant expenses reduction are in-built in the very nature of cloud computing technology. Cloud services don't charge healthcare management upfront, either for storage space or actual 'computing'. You only pay for what you use. It means that by building cloud IT infrastructure, medical institutions save costs that otherwise would be spent on expensive hardware and its support within the in-house IT department (that not every healthcare provider even has).

The other cost-effective benefit of using cloud computing for building healthcare app is its flexibility in development options. Cloud-based apps can be launched through a web browser and shouldn't be downloaded to users' devices. It saves providers a lot of money that could be spent on native mobile development. Cloud-based solutions are also easily scalable and resilient. Cloud computing keeps performance indicators high no matter how fast your app's user base grows.

Cloud storage of electronic healthcare records helps to ensure optimal conditions for coordinated actions towards patient treatment and preventive measures. Each representative of medical staff who has interacted with given patient updates its EHR information that can be accessible and visible for all medical specialists who work with this patient. There's no more need for additional requests and wasting time waiting for a response.

The medical data interoperability principle is also boosted by using cloud computing in the healthcare industry. Cloud computing serves to create high-level connectivity between the medical Internet of Things. Cloud medical apps can collect and analyze data from different sources and devices and are used as a platform for 'communication' and 'decision-making' if their programs are automated.

Cloud computing is continuing to revolutionize the way of patient monitoring and healthcare delivery. Thanks to the comparatively low costs of using cloud IT infrastructure, many healthcare providers may easily adapt to the cloud environment and build their own cross-platform applications.

High abilities to store, analyze and exchange enormous volumes of data provide healthcare institutions with 360-degree visibility on in-establishment and remote patient care. Applying AI & machine learning algorithms to the power of cloud computing technology, it's possible to receive highly precise medical forecasts or in-depth disease cause analysis.

Partner up with Dataxdev to catch up with the lucrative opportunities that cloud computing technologies offer to the healthcare industry!