Healthcare providers and payers are generating more data than ever. Approximately 30% of the world’s data volume is generated by the healthcare industry. By 2025, that number is predicted to reach 36%, which is faster than manufacturing, financial services, media, and entertainment. But payers and providers often fail to use all that available data while making care management decisions aimed at improving outcomes, enhancing the patient experience, and reducing costs.
Moreover, this huge volume of data is siloed and often disconnected from one system to the next. The true value of healthcare data can only be achieved by integrating it from every source be it clinical or non-clinical. It’s difficult to aggregate healthcare data due to non-standardized data formats, stringent regulations, and a huge influx of data from different sources such as EHRs, claims, wearable devices, and many more.
Data aggregation is the process of bringing data together from disparate sources to provide users, analysts, and developers with a unified patient view. The core purpose is to make data easily accessible for all stakeholders to consume and process. It is a complex process, and making improvements in this area requires patience, commitment, and out-of-the-box thinking.
However, if done strategically, data integration and aggregation can propel transparency and coordination between internal users such as PCPs, and care teams as well as external users such as patients.
Benefits of Data Aggregation
As an example, you received a request to pull together all medications prescribed, connected home health data, CT scans, and accompanying radiology reports for any patient older than 45 who had undergone surgery within the last two years. This is a typical request for health data managers.
The request could come from physicians, clinical researchers, or data scientists, but with today’s systems, it can take weeks or even months for health systems to query multiple data stores that don’t speak the same language, extract the data files, and work to unify them in batches for analysis. By centrally aggregating data, healthcare organizations can achieve:
Health systems need clean and curated data at the right time and the right place, especially in emergency cases where time is of the essence. Strategic data aggregation enables the speedy transmission of useful medical data. For example, it can help identify risk factors and speed up diagnosis. Increasingly, these days providers consult only a patient's Electronic Health Record (EHR), which consolidates limited health and medical data. But without data aggregation, EHRs can miss critical data from sources such as claims, pharma, etc. which is necessary to view a patient’s longitudinal care journey.
Integrating data enables better evidence-based decision making, leading to better health outcomes. That’s crucial when it comes to delivering care outcomes at scale, i.e., for the population at mass. Error and duplication of data can change the course of a care journey.
On the other hand, accurate information derived from high-quality data can enable providers to better manage timely and required treatments, payers to facilitate timely reimbursements, and patients to become active participants and empowers them to engage in their care journeys.
Aggregation can enable the automation of business processes and more efficient use of resources for reduced costs. From facility operations to clinical treatments, healthcare institutions can measure the care they deliver, analyze their data, and use data insights to make improvements or changes.
Recently, CMS put Social Determinants of Health (SDoH) in the spotlight to advance health equity across the care continuum. The relevancy of SDoH is gaining momentum as non-clinical factors—age, gender, ethnicity, neighborhood, or income level—outside a healthcare setting affect the care outcomes. Quality data aggregation pushes providers to collect SDoH data and integrate it with care journeys to achieve better care outcomes.
System-Wide Access During Emergencies
The COVID-19 pandemic dramatically showed the need for system-wide access to data in a crisis. In response to the pandemic, there was coordination across international borders of massive amounts of data, such as infection rates, strategy planning research, hospital, medical staffing, and pharmaceutical research. This wouldn’t have been possible without accurate data collection from multiple sources, aggregation into one unified view, and sharing of information with stakeholders as a single source of truth.
Data Aggregation Drives Integrated Healthcare Systems
The care journey is becoming complex with multiple touchpoints such as patients asking about services or appointments, care teams such as PCPs, specialists, etc. coordinating with each other, follow-up engagement with patients, and the list goes on. Each of these touchpoints requires accurate and comprehensive integrated data to make the right decision. This lays the true foundation for integrated systems which consists of multiple point solutions that address specific, targeted aspects of the care experience.
By using healthcare industry codes, medical systems can automatically map local data to standards with integrated, normalized data sets. Therefore, a well-established data integration solution should be able to aggregate data from disparate sources and make information compliant with the standards of codification. Moreover, we need a user-friendly and meaningful way of data representation. A medical dashboard can be a good example of such a front-end interface.
Due to its undeniable impact for providers, payers, and patients, data can no longer be locked in silos. With modern IT solutions on the rise, efficient data integration and aggregation are becoming more critical than ever before to effectively reap the benefits of in-depth insights that can unleash the power of data. Healthcare leaders are putting massive efforts into bringing together the right mix of technology for data integration. But, there are certain challenges that every health system faces while implementing such solutions. More on that in my next blog.