The Real Cost Of Data Integration Failures In Healthcare

Data Integration

It’s no secret there is an incredible amount of data generated and used in healthcare services. Healthcare data comes from various sources, such as patient medical records, hospital records, lab results, and wearable devices that are part of the internet of things (IoT), among others. To derive meaningful insights from this data, however, companies in the healthcare sector need to properly manage and analyze it. That’s where many challenges can arise, and one of the most common is data integration failure. 

Data integration is the process of gathering data from disparate sources and using a data pipeline to bring it together into one cohesive, accessible view. Without effective data integration, healthcare enterprises struggle to keep their customers happy and get the most out of their business intelligence (BI) tools. Simply put, failing to properly integrate your data will cost you money. Here are some of the most common data integration challenges in healthcare and strategies for addressing them:

Data Integration Challenges in Healthcare

Lack of Standardization

Different data collection systems that healthcare organizations use often log data in different data formats. While that wouldn’t be an issue if they intend to keep that data separate, the lack of standardization does cause problems when they try to integrate the data. Healthcare systems often struggle to communicate with each other because there is no standard form for formatting and exchanging data from these sources. Even if all the data eventually ends up together in one place, there may be errors and duplicate data when it isn’t standardized beforehand. 

One clear solution to this problem is to establish shared standards for data storage and management in the healthcare industry. Using common standards would allow healthcare organizations to exchange information seamlessly between each other and their various internal systems. The Fast Healthcare Interoperability Resources (FHIR) standard is one example of these types of standards. 

On an individual level, these organizations can turn to certain data solutions that are equipped with advanced integration capabilities. They can connect disparate systems and seamlessly bring all your data together in one place — eliminating the standardization problem. 

Fragmented Data Collection Systems

Alongside the lack of standardization, having fragmented data collection systems is another top data integration issue for healthcare organizations. Businesses in the healthcare industry often suffer from isolating data into data silos only accessible to certain departments or teams. Data silos cause problems across industries, but they’re especially damaging in healthcare. 

For example, 83% of patients needed to provide duplicate health information at their medical appointments, leading to frustration and worse patient experiences. No one wants to answer the same questions over and over about their medical history. If healthcare data collection systems weren’t so fragmented, this wouldn’t happen as often. 

And when healthcare practices need to receive patient results from other practices, things can get even more complicated. Any systems that operate independently of each other and cannot properly communicate and coordinate will lead to issues integrating data. The first step in solving this problem is to break down data silos within each organization. Establishing common standards would also help fragmentation. 

Manual Entry

In the healthcare industry, healthcare professionals still input plenty of data manually into their organizations’ digital systems. This can lead to data inaccuracies or incomplete data — in other words, low data quality. If you’re basing decisions on the data you collect, low-quality data can be extremely costly, especially in a healthcare setting. And once you integrate that low-quality data with the rest of the higher-quality data you collect, you may face a compounding data quality problem. 

To address the issues that arise from manual entry, you can adopt a few different strategies. Increasing your use of automation in data entry can go a long way, as can improving the interoperability between the systems you use. Also make sure to have concise, straightforward processes for manually collecting data when necessary. The more standardized these processes are, the lower the chances of low-quality data. 

Security Concerns

Healthcare data generally contains extremely sensitive personal information. Cybercriminals can seek to exploit security weaknesses within healthcare organizations and gather this data for fraud or identity theft purposes. Because of this, companies in the healthcare industry need to be extremely careful about securing the healthcare data they handle. If they share that information with other appropriate healthcare organizations, the data needs to be encrypted and protected so only authorized parties may view it. 

Yet, these organizations must balance the very real need for comprehensive security with accessibility. Balancing these two (often opposing) aims is particularly difficult in terms of data integration. When you bring data from different sources together, you need a secure data pipeline to safely move the data to its final destination. It isn’t easy to securely transport data from disparate sources, though. Detailed security measures can help, as can a secure, well-managed data analysis platform

Why Data Integration Failure Matters

For enterprises in the healthcare industry, failing to properly integrate your data can come with significant costs. One estimate found that data integration problems collectively cost organizations in government health care over $300 billion each year. Another market report estimated that businesses could lose up to $500,000 or more annually due to integration concerns. That’s a lot of money that you don’t need to lose every year. 

Rather than devoting time, money, and effort to tackling these challenges one at a time, why not turn to a comprehensive solution? Live Earth is a real-time data streaming and analytics platform that can seamlessly connect disparate data sources in one user-friendly command center. You can aggregate and synchronize previously siloed data, so it’s all in one place and as useful to your organization as possible. Don’t let your healthcare enterprise fall prey to the costs of data integration failure. Schedule a demo of Live Earth to see how the platform can integrate your data and help you get more out of it than ever before.

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