The Government of Accountability Office in its report to the Government found that hospitals face three primary challenges when they have to implement evidence-based patient safety practices, including limitations with sharing, integrating, and analyzing data.
It is difficult for hospitals to gather health data for identifying the adverse events and decide which evidence-based practices to use and ensure that the staff in the hospital constantly implements these practices.
The first challenge that hospital officials reported was they are difficult to secure health details about adverse events. It is a resource-consuming method as the healthcare staff members need to collect data from different analytics systems and then integrate all data together.
Several hospital officials are of the opinion that securing data on adverse health needs an investment of considerable resources and time in Electronic Health Record systems and vendors. Hospitals might have to hire and manage different vendors of carrying out various data-related tasks.
Challenges with Data in Healthcare
By nature, big data is quite complex and requires healthcare organizations to take a closer look at the approaches to collect, store, analyze, and present the data to business partners, staff members, and patients.
Here are some of the top challenges with data in healthcare.
Data comes from somewhere. However, unfortunately for some healthcare providers, it does not always come from somewhere with incredible data governance habits. Capturing data that is complete, clean, accurate, and formatted in the right manner for use in multiple systems is an ongoing battle for healthcare organizations.
Healthcare organizations are largely familiar with the importance of cleanliness in the operating room and cleaning, but they might not be aware of the importance to clean their data. Dirty data can easily derail a big analytics project. Data cleaning is important to make sure that data sets are correct, accurate, relevant, and consistent, and aren’t corrupted.
Front-line healthcare workers hardly think about where the data is being stored. However, it is a critical security, cost, and performance problem in the IT department. With the growth in healthcare data, some providers are now unable to manage the impact and cost of on-premise data centers. This has led to the popularity of cloud storage. Almost 90% of the healthcare organizations are using the cloud-based health-IT infrastructure.
Data security is of primary importance when it comes to healthcare organizations. From malware to phishing attacks, healthcare data is subject to a large number of vulnerabilities. The HIPPA Security Rule has laid down a long list of technical safeguards. However, even the most robustly secured data center can be taken down.
Healthcare data isn’t static. Most elements will need updates to be relevant and current. In certain datasets, the updates might occur every few seconds. So, it can be challenging for healthcare organizations to consistently monitor their data sets. They have to make sure that they aren’t creating redundant records when updating a single element.
Some healthcare providers operate in a vacuum, and only a few patients receive their care in one location. Thus, it is important to share data with external partners. Data interoperability is an ongoing concern for all healthcare organizations.
What is Data Lake?
A Data Lake is a central storage repository holding big data from various sources in a granular and raw format. It can store all types of data. So, healthcare organizations can store data in a more flexible format. While storing data, the technology associates it with metadata tags and identifiers for faster revival.
With healthcare data growing at the rate of 48% every year, healthcare providers have to improve analytic capabilities for translating data into actionable insights and make an informed decision.
How can Data lake Help in Bringing About a Change?
A Data Lake offers a strong data architecture with a uniform location for reducing silos across the healthcare enterprise. It enables effective cross-data analytics and incorporates internal data sources for mining and analysis by data science teams and clinical departments.
With structure-focused insights, healthcare organizations can further advance accountable care initiatives, create a new domain of data science to uncover patterns and correlations, and make discoveries for improving patient care.
AI Data Lakes in healthcare can also integrate details from wearables, the appliances that are developed on the basis of the Internet of Things. Healthcare organizations can use advanced analytics for using data generated by the devices for reducing unnecessary readmissions and complications in hospitals.
Data Lakes is a reliable and flexible platform. It offers ample new opportunities for finding trends and helping caregivers to create a continuous and data-driven environment.
The role of data lakes in healthcare organizations is to simplify the management, storage, and analysis of big data through data integration in real-time from various sources.
Advantages of Data Lake in Healthcare
AI Data Lakes in healthcare comes with some significant benefits. Let’s take a look at them.
Real-Time and Comprehensive Patient Insights: Real-time data streaming can deliver a more current and complete parent profile and journey maps for enabling the patient-care team to know how to treat the patient.
Clinical Data from the Largest HER Network in the Nation: It can convert data from over two hundred thousand clinician EHR, into usable and structured data, leveraging FHIR-based models. This helps in supporting the data exchange for clinical trials using the API constructs.
Scalable Data Model to Cater to Your Needs: Highly extensible and scalable data model with a wide range of output based on client requirement, including exportable data extracts, user-friendly dashboards, query tools, and APIs support an extensive array of business use cases that is aimed to improve operational efficiency, delivery, and financial performance.
Industry-Leading Expertise in Clinical Data Integration: With Data Lakes, you can get clinical data validation edits with deep industry subject matter expertise and risk adjustment program compliance.
Complete Data Management: Using a scalable and secure infrastructure for integrating, validating, and normalizingthe data types.
How Data Lakes on Cloud Help the Insurance Sector?
Over 50% of the healthcare professionals don’t trust data and report low-levels of self-service when it comes to making data-driven decisions.
The insurance sector has a data swamp. One claim can have multiple data points for analyzing and interpreting. So, healthcare CIOs are using the cloud-first strategy for new workloads and applications with 47% using patient data predictive analytics. Moving Data Lake to the cloud promises to provide a different customer experience. It makes data processing cost-effective and faster.
According to Gartner, by 2021, public cloud vendors will process over 35% of the IT workloads of healthcare providers. The cloud lets you pay as per the data nodes used in the cluster.
How can ResolveData Help Create the Best Data Lakes Solutions?
ResolveData actualizes data to drive transformational healthcare. With Resolve, you can drive smarter and data-driven decisions just by capitalizing on the broader variety of data. It offers multi-vendor software support. Our experts offer the foundation to create, manage, and efficiently use Data Lake. The company offers a range of integrated technologies for supporting today’s data science and machine learning better, be it on-premises or on the cloud. Using Data Lake, you can tap into unstructured data for generating insights from real-time analysis. The role of data lakes in healthcare is very significant.
In case you are interested, you can easily schedule a no-cost call with an experienced ResolveData expert and learn more about the solutions.