With the global market for electronic health records expected to exceed $22 billion by the end of this year, healthcare providers are shifting their focus on big data analytics and cloud computing to improve patient health information management.
Healthcare information systems will benefit from a universal framework that offers the highest level of sharing, amalgamation, and interoperability of patient health data among healthcare providers and patients. The cloud and big data can be intertwined effectively to achieve this objective.
Modern healthcare information technology has the potential to empower care delivery organizations to digitize, electronically move, and store patient health data across the world in a matter of seconds. Although cloud and big data hold great potential for the healthcare industry, going the cloud way still presents a challenge for the industry, although this is inevitable.
So let’s look at the major roadblocks the industry currently faces.
Electronic medical records are too centralized. The present-day electronic medical records (EMR) are highly centralized. With each healthcare provider owning a local EMR system, collecting the medical information of patients whose records are dispersed among different healthcare providers is a big challenge. The need of the hour is to have a universal patient health information infrastructure in place that allows timely and safe access of all required patient health information.
The healthcare industry generates huge amounts of data. If the healthcare industry wants to become cost-effective, speedier and more efficient, it should create a revolution in healthcare information systems to optimally utilize the massive data (structured, semi-structured, unstructured) it generates every day.
Traditional database tools make it difficult to analyze huge amounts of data. So, there is a need for a universal healthcare data management system that is used by large pools of care delivery organizations, which interact with each other and patients to generate, consume, store, share, and utilize patient health data in a secure manner.
Secure global authentication is a key challenge. Keeping in mind the huge data sets to be handled on a daily basis in a domain as big as healthcare, traditional physical, face-to-face verification might become impossible after a period of time. This creates a need for an encrypted data access and storage solution within the networked healthcare system that authenticates individuals and care delivery organizations to access patient health information in a secure manner. The challenge will be to integrate a tamperproof electronic identification and authentication system to prevent illegal data access and preserve data integrity.
How Cloud and Big Data Can Help
Let’s talk about cloud first.
Cloud inevitably will cut down the cost of an electronic health record. The cloud environment brings users, including patients, care delivery organization, doctors, and researchers, on to a common, low-cost platform. This sort of resource pooling optimizes use of cloud’s computing and storage capabilities.
Cloud provides broader access and is accessible anytime, anywhere. This helps users overcome problems of limited bandwidth and portability issues that are part and parcel of traditional IT infrastructure.
The scalable nature of the cloud means that, unlike the legacy model, customized offerings can be looped in without substantially increasing cost.
Cloud computing combined with mobile will increase EHR portability. While mobile will make data access portable, cloud will help the mobile platform overcome its problem of limited bandwidth in data processing and storage. Cloud-based mobile apps will play an important role in speeding up the portability of EHR cloud.
Cloud service providers will play a significant role in cloud security. They will authenticate healthcare providers, practitioners, and patients at different levels of privilege and permissions to securely access EHRs and retrieve crucial patient health information. They can deploy two healthcare cloud models based on the levels of data sharing among different care delivery organizations, patients, and practitioners within the domain of the cloud. The models are as follows:
Private healthcare cloud. A single-entity care delivery organization will own the cloud. It can be on or off premise, with the same capability in terms of security and patient information protection as an EMR system run by a care delivery organization.
Community healthcare cloud. In this model, several care delivery organizations support a specific community with shared interests. It is managed by care delivery organizations and can exist on or off company premises.
Moving ahead, we can segregate cloud healthcare offerings even further, based on the following types of services:
Software-as-service (SaaS). EHRs are hosted as a service, and the applications are available through a web browser to patients, doctors, and healthcare providers. There is no need to install records on personal computers or hand-held devices. Because multiple users can split the cost of software licenses, maintenance and upgrade expenses can be kept within budget. This makes it more affordable to a large group of users.
Platform-as-a-Service (PaaS). This development platform will enable healthcare providers to play a more active role by allowing them to design, develop, and test healthcare applications in addition to deploying them. This could be used in collaborative healthcare projects in which team members are dispersed across different geographical locations.
Infrastructure as a Service (IaaS). Healthcare providers can use third-party hosted hardware, software, servers, storage, and other infrastructure components based on their increasing/decreasing resource demand. This virtual use of the hardware does away with the need for investing in actual hardware and is available on a pay-per-use model.
Cloud Enables Faster, Better Big Data Management
Digital healthcare data, which totaled 500 petabytes in 2012, is expected to reach 25,000 petabytes in 2020. As cloud computing will ease global healthcare management, big data will cuts costs through predictive analysis of this vast data. Because traditional data management tools will not be able to store, process, or analyze the huge data sets, proper management of big data is unthinkable without cloud computing.
How predictive Analysis of Big Data will Help Healthcare?
Health care data is growing at an exponential rate in both size and complexity. Data mining with traditional tools is insufficient. Newer tools and technologies are needed to handle data within a tolerable timeframe. A breakthrough algorithm is the need of the hour to quickly mine data in the following ways:
- Capture patient behavioral data through social media communications and build insights based on this data.
- Efficiently trawl a sea of medical imaging data and extract potentially useful information.
- Accumulate information from various clinical reports as part of predictive analysis.
- Understand unstructured clinical data in the right manner.
Of the more than $2 trillion spent on healthcare annually in the United States, billions are wasted on unnecessary treatments, tests, and the like – $750 billion in 2009 alone, according to a report by the Institute of Medicine, the health arm of the National Academy of Sciences. Predictive analysis of big data can help identify patients at risk, get patients the treatment they need, and limit the number of hospitalizations and the related costs.
The biggest challenge to cloud enablement of the healthcare system will be compliance with HIPAA, which mandates a strict authentication of patient health information system to prevent its misuse. With people still wary of cloud’s security, it might delay, but not prevent, the paradigm shift of electronic health records from legacy to cloud. This inevitable shift will change the way patient health information is managed.
Stan Roach is the Chief Customer Officer at Agiliron, which offers inventory software for small business. He has more than 30 years of experience. with a track record of launching several B2C and B2B software products. Follow Agiliron on Twitter.
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