Healthcare Data Exchange Roadblocks: The Struggle Is Real

Accurate, timely, and accessible data has never been a given in healthcare. Other industries get this. Retailers, financial institutions, and tech companies are masters at this. Healthcare still lags behind. It’s not a new story, but healthcare data exchange roadblocks are more glaring during a pandemic.

The big question is, what are we—the entire healthcare ecosystem—willing to do about it?

Healthcare Data Exchange Struggles

Having a full picture of a patient’s medical records is vital to effective treatment and continuity of care. Being able to exchange data internally and externally has implications as well. That’s especially true in the case of data sharing for COVID-19 tracing. 

While it seems, this would be easy. It’s not. The struggle, as they say, is real. This is what we know:

• 30% of healthcare organizations still report challenges with healthcare data exchange with other providers.
• 52% of hospitals can’t use patient data from external sources because their EHRs don’t support these workflows.
• 20% of patient records are duplicates, which impacts the ability to establish accuracy in case history.

Why Is This Disconnect So Pervasive?

It’s a question that doesn’t have a single answer. The reality is that accessibility, portability, and interoperability are all critical issues. We knew they existed. They are just getting a bigger spotlight because of the new interoperability rule and the pandemic.

The problems include not having standardization in interoperability, privacy concerns, and data integrity concerns. Is it so hard to get systems to communicate with each other? Other industries do this well. Healthcare falters here, but there is hope on the horizon.

Improving Healthcare Data Exchange: Fundamental Action Items

Here’s what providers, payers, and stakeholders can do.

Invest in data management infrastructure

One issue is matching. Even within the same system, it can be problematic. Variability in technology and processes derail these efforts. By strengthening the foundation, you can work to eliminate failures in matching. Algorithms could support better matching, too. 

Next is the accuracy issue. A lot of data is unusable for analysis in healthcare. That’s because it has quality issues. Think about all the opportunities providers and payers are missing here. To circumvent this issue, we need to address it. Doing so would include data validation, data normalization, and data cleaning, which would require a robust healthcare data management strategy.

Remove backlogs internally

Another issue is the inability to exchange information due to internal delays. IT staff doesn’t have the bandwidth to create exchange protocols. So, data remains in silos. If you can’t even exchange data between your different health information systems, externally sharing it becomes an even larger hurdle.

Instead, healthcare entities should look for outside support to make this happen quicker. If you can bridge the gap with experts in the field, there are benefits for all.

Streamline and aggregate outside sources

Another problem is being unable to import external data. That’s data from other providers, pharmacies, or payers. It could enrich the patient record. To make it happen, you must have a workflow to bring the data in, clean it, format it, and augment existing files with it. 

This process isn’t new—it’s just not been standard in healthcare. You again look to outside expertise for this. With data enrichment, you would have a much more holistic view of a patient’s health history. 

Now Is the Time to Get Exchange Right

Data exchange has always been a roadblock. A pandemic makes it that much more urgent. By working together, we can all play our part in closing the gap in data exchange. It has the potential to revolutionize care and manage population health.

We’re here to help. As healthcare data experts, we know the struggles, and we have a solution. Check out our data sharing capabilities today.