Earlier this year, I wrote a post about difficulties in the language of healthcare IT, focusing on the seemingly small, but meaningfully vast difference between two very important words in healthcare IT: interoperability and intraoperability.
Unfortunately for our industry, there is no shortage of these confusing and often misused false cognates. Our latest case: data exchange and data aggregation. 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 Practice: Data Exchange
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.
Again, 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. And 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.
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. Data exchange is highly valuable in specific instances, but in many cases people are mistaking data exchange as the foundation for what they are trying to do with value-based care: analyze and inform the care of a population.
In Practice: Data Aggregation
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 through large amounts of it simultaneously to create insights, trends, and predictions.
Data aggregation is the foundation for the transformation 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. This can improve health outcomes and reduce costs.
Aggregation allows you to take data and transform it from transactional to informative. Armed with aggregated data, a physician can then turn it into a prediction (If “A” happens, then “B” is likely to follow) and ultimately, and most importantly, a prescription (if a patient is experiencing “A”, do “B” to get “C” outcome). Data from a single patient, while helpful for that single moment in time, won’t allow you to discern this kind of important, transformational intelligence.
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, purposes, 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.