In this blog post
The healthcare industry has more information than it can possibly make sense of, and it is likely that this data explosion will only continue to grow with time. The need of the hour is to not only make all this data available for use but to also put in place advanced systems and infrastructure that can fulfill rising data management and analysis needs. It would also be important to invest in the right resources to keep these systems and infrastructure working at optimal levels, and to be able to cull out information from this raw data using big data analytics.
So, what’s exactly behind the data overflow that we are seeing in the healthcare industry today? This can be majorly attributed to the fast and widespread adoption of technologies such as genomics, artificial intelligence, connected health, digital pathology, population health, and connected devices amongst others. The healthcare industry now has access to huge amounts of data that are coming from a variety of sources, including medical records and medical devices & instruments. Let us now put some data on the table before we move any further and discuss the challenges of this data explosion and how the modernization of data can help in overcoming most, if not all of those challenges.
According to IDC Healthcare, data in healthcare is growing at the rate of 48% every year. IDC also predicted that if all healthcare data were stored in digital format in the memory of tablets, the stack of tablets would reach about one-third of the total distance of the moon from the earth – this distance is approximately 82,000 miles. In 2013, the same figure was 5,500 miles – the rise is staggering. It is also expected that data coming from genomics is going to make its mark in the overall healthcare picture in the time to come. Genomics data is also expected to be amongst the most useful data sources in the next few years.
However, there is no use of these enormous amounts of data if healthcare organizations don’t have the right technology to make the most of it. What healthcare organizations need to do today is switch to modern healthcare technology and turn this huge data into actionable insights. They can then ultimately put this data through cognitive computing models to make data-driven, informed decisions.
Modernization of healthcare data can equip healthcare organizations to overcome these challenges. However, there is a bigger issue at hand that healthcare organizations first need to address and then work towards dealing with. Most of the data that we are talking about here is not present in the systems that most healthcare organizations use. This is why it goes unnoticed and this is why these organizations need improved data management capabilities, advanced IT infrastructure, and skilled people to make data simplify their route to transformation. Healthcare organizations need to take thoughtful measures to transition from their existing outdated & legacy technologies to new-age healthcare IT, in order to leverage insights from healthcare data and to stay ahead of the game.
This problem exists across the industry, emphasized by the findings of the HIMSS Analytics study. As few as half of the clinicians that participated in this study had IT infrastructure in place that provides them an integrated view of all the enterprise data coming in regularly. More than three-fourth of the participants had ‘medium’ or ‘high’ level of confidence in their system’s ability to support an integrated view of data. This problem is haunting the healthcare industry because many organizations are still stuck with standalone systems. They should be looking out for IT infrastructure with plug-and-play capabilities. It should be able to accumulate data from different sources and environments and provide an integrated and structured view of the same.
With the enormous amounts of data accessible to healthcare organizations, it is becoming increasingly difficult for them to manage all this information properly. For starters, they need to list down their data accessibility, storage, analysis, and sharing requirements. However, it’s easier said than done considering the amount, variety, and unstructured nature of data.
Data analysis across different data sources is another challenge that needs to be addressed and dealt with. If an organization wants to establish a relationship between information procured from different sources, such as medical images, clinical records, and others, it will be impossible since such data is trapped in medical system silos. A healthcare organization’s decision to move to a more advanced IT infrastructure and systems should be driven by the need to increase agility and reduce the time required to develop insights. Data management capabilities should be equally prioritized. It should be able to effectively handle growing amounts of data that has to be stored, analyzed, and managed without causing any disruption to operations. Such investments would help in improving data accessibility, business process efficiency, and reducing costs in the long run.
Here is a high-level look at some necessary elements of new-age healthcare IT infrastructure:
- An analytical platform that allows seamless integration of data
- Cost-effective, high-performing, and scalable data storage and computation solutions
- Simple and fast identification, mining, and analysis of unstructured data
- Flexible architecture to accommodate the dynamic needs of analytics applications
- Low-cost IT administration
- Protection and security of intellectual property and health information
- Tools to collaborate with teams across the world
The need for data modernization in healthcare can be summarized as follows. There are several drivers that mandate the modernization of data in the healthcare industry. The shift towards value-based care is amongst those and possibly, the biggest factor in healthcare today. With data modernization, healthcare organizations will be able to extract better insights from patient data and be able to make data-driven decisions to improve patient care outcomes. So, the need for patient insights is another important driver. Patient health data interoperability is another huge area of focus. With patient data in various silos spread across independent providers, systems, and health applications, it becomes impossible to have one cohesive body of information about patients and their health journeys. Hence, the interoperability of such data becomes critical to delivering quality care. And the first step towards that is data modernization.
If you are looking for a technology partner to help you modernize your Health IT infrastructure, Systems, and Data that would empower you to do a lot more with data that you have access to, look no further than GAVS Technologies! You can find more information about our healthcare offerings at https://www.gavstech.com/healthcare/.