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Three Use Cases of Data Integration in Modern Healthcare

Three Use Cases of Data Integration in Modern Healthcare

Modern healthcare systems are adopting new technologies with agility to deliver the best-quality patient experiences. However, healthcare data has not benefited from the same forward-thinking approach. In fact, analyzing sensitive healthcare data is a challenge for the majority of healthcare organizations.

Even the majority of tech-driven companies can struggle to achieve efficient healthcare data integration, which ultimately sabotages their ability to address and meet patient needs and requirements. A typical healthcare integration system provides access to in-house data but may not do a great job consolidating diverse sources and delivering unified data to end users. 

With the right solutions, healthcare units can support data-driven decisions and improve the quality of frontline care with a better healthcare data integration strategy. 

Why Healthcare Data Integration is Important?

Data integration consolidates data from different sources into a unified set to facilitate better business intelligence. For example, healthcare integration technologies can extract data from myriad electronic health record (EHR) systems and store it into one comprehensive data source – providing practitioners will all the information they require to deliver high-quality accurate, standardized care. 

The amount of healthcare data streams waiting to be used is huge. With every visit, healthcare providers gather patients’ personal information and medical history, which they can leverage to recognize effective preventative strategies, eliminate inefficiencies, and reduce costs. 

Improved data integration can lead to complete and unified patient information, resulting in better care and experiences. 

Modern data integration solutions have many use cases that can help healthcare units function and deliver — in a positive way. This blog highlights three such healthcare data integration use cases in detail. Let’s take a look.

Three Use Cases of Data Integration for Healthcare 

Deploying data integration can highlight data gaps and increase accessibility among doctors, patients, and third-party service providers. Through a unified patient view, one can deliver many healthcare use cases:

1. Response to a Crisis

Healthcare systems need a high-level view of what is happening within their hospitals. However, when proper systems to effectively integrate data from different sources are not present, leaders often struggle to manage critical situations effectively. 

Healthcare providers can use data integration solutions to consolidate information from different sources and consolidate it in a single database. So, in times of crisis, healthcare professionals can access the information to give an adequate response on time. 

2. Drug Discovery 

The development of drugs is not a straightforward process. It takes a significant amount of time, research, and monetary investment before a new drug can be launched. Statistical reports indicate that the cost of bringing a drug to market is $1.3 billion on average. 

Data integration can empower researchers to access information from various datasets and use it to advance drug development and target validation. Drug developers can access data from trusted, diverse datasets. They can use this information to build on already existing research and avoid the costly mistakes that previous developers made. 

3. Diagnostic Accuracy

Diagnosis is a central part of a patient’s care cycle as it determines the quality of treatment. If not done properly, it can amount to a great deal of error. Research indicates that diagnostic errors have attributed to 80,000 deaths in the US every year. While data exists to run tests and inform diagnostics accurately, results are heavily undermined by ineffective data integration.

With a modern healthcare data integration approach with AI and ML capabilities, health units can easily gain access to data and holistic views of patients and deploy treatments accordingly. Instead of primarily relying on their own records, practitioners can build diagnostics informed by the complete history of a patient. A comprehensive view can also enable them to draw links between fundamentally different symptoms, provide an accurate diagnosis, and administer appropriate treatment and care.