Unfortunately, there is no shortage of confusing and often misused false cognates for our industry. Our latest case: data aggregation and data exchange. These two words may seem very similar, but they have two very fundamentally different underlying meanings. Despite the difference, both are often used interchangeably. This has led to an industry-wide confusion about which is which, and which is more important.
At a high level, aggregation is about bringing many things together; exchange is about things passing from one entity to another. But beyond their definitions, the best way to differentiate these two terms is how they are used in practice and their impact on healthcare today.
In this article, we’ll dive into the difference between these two concepts and how you can use them to further positive patient outcomes. Let’s begin.
Data aggregation within the healthcare industry means taking many different pieces of data (health information, finances, lab results, etc.) and putting them all together in one place to create a single,unified data asset. With all the data in one place, one can then process large amounts of it simultaneously to create insights, trends, and predictions.
When integrated correctly, data aggregation can have transformative benefits on the healthcare sector as a whole, including:
By centralizing siloed data, aggregation allows you to take data and transform it from transactional to informative. Which, when completed over time, can improve health outcomes and reduce costs.
Data aggregation is necessary to transition from volume- to value-based care. It allows an organization to bring all their data together so that they can find things that they wouldn’t normally see in a single patient chart.
For example, a healthcare organization may be able to uncover the fact that all their patients who go to a particular specialist are receiving prescriptions for an older, costlier, and less effective drug than those who go to other specialists. If this organization were to evaluate each of those patients individually, the patients would appear to be receiving decent care, but when compared to their peer group as a whole, they fare worse than those receiving the newer, less costly treatment.
This type of analysis is an integral factor in improving the health of patient populations, and it can only happen if an organization is able to aggregate data. Once aggregated, problem areas can be identified and understood, and a healthcare system can then use that information to make better decisions.
When referring to data exchange within the healthcare ecosystem, we’re talking about requesting data from one place, packaging it up, and sending it somewhere else. It is a single, transactional experience. Electronic health information exchange (HIE), at its very basic definition, allows healthcare providers and patients to appropriately access and securely share a patient’s vital medical information electronically — improving the speed, quality, safety, and cost of patient care.
While data exchange can streamline the request/response process, it’s more akin to email (a leap above snail mail, for sure) than it is to the “big data analytics” that is proliferating across many industries, including healthcare.
However, when used securely and within a reliable software framework, data exchange can improve care coordination so that primary care physicians, patients, specialists, and hospitals can access and share patient information. This reduces the risks of errors, decreases costs related to duplication or missing data, and safeguards against unnecessary treatments.
At the same time, enhanced data exchange increases engagement on the patient side, thus promoting enhanced self-care management. With increased accessibility to portals, patients can begin to take a more active role in studying their medical history, analyzing their test results, and completing their treatment plans.
At its very basic functionality, when done right, data exchange allows for physicians to have a more complete medical record, which should allow them to better treat that patient. But it’s not as easy as it sounds.
On top of that, today’s standards are still fairly “lossy,” meaning that a good amount of valuable data from the medical record is lost during the technical process of extracting it, packaging it up, shipping it, unpacking it, and re-integrating it with the new medical record. It’s also worth mentioning that not every provider has the exchange infrastructure in place to support this transaction.
Data exchange is highly valuable in specific instances, but in many cases, people mistake data exchange as the foundation for what they are trying to do with value-based care: analyze and inform the care of a population.
Ultimately, both exchange and aggregation are important and should be used in tandem to make the best investments and succeed in value-based care. We just have to be careful not to confuse them, as they are truly different in meaning, purpose, and outcomes.
Arcadia enables data aggregation for healthcare providers and health plans by connecting more than 30 different EHRs and combining that with claims data to provide a full and complete picture of patient care. Without this data, it is nearly impossible to make informed decisions about the optimal care for a patient population (the cornerstone of value-based care). Technologies that can integrate and analyze data from multiple systems will be increasingly vital for healthcare organizations to improve care outcomes and drive financial performance.
Arcadia’s mission is to deploy data in service of healthier lives, and we partner with healthcare and life science organizations to empower everyone from the c-suite to the waiting room. From data aggregation to data exchange, let’s unearth insights and accelerate your team’s goals.