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How to find patient insights with data-driven healthcare technology

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Healthcare is increasingly becoming data-driven in its nature, real-time in its speed, and consumer-centric in its focus. As access to more technology and data increases, quality of care and outcomes will improve, and patient engagement is expected to rise as individuals take a more active role in managing their healthcare. For health plans and providers, this shift demands a deep working knowledge of how to find patient insights with data-driven healthcare – and how to leverage those insights to inform positive action.

This blog covers:

- The role of technology in achieving data-driven healthcare
- Strategies to better identify patient insights
- Using patient insights to inform behavior at the point of care

Leveraging technology to achieve data-driven healthcare

Creating a truly accessible and complete patient health record that tells the full patient story is far from an easy proposition, as healthcare data exists in disparate forms across the healthcare continuum – disconnected from itself from the get-go and difficult to piece together to determine the next best step in patient care.

For the past decade, payers, hospitals, and other providers have undertaken a significant effort to combine provider clinical data with non-clinical or administrative payer data, as well as patient data from pharmacies, labs, and other disparate sources.

However, true healthcare interoperability and data aggregation is still a work in progress for many organizations. Those leading the way are making significant investments in data technologies and partnering with companies that can acquire and cleanly integrate clinical data to drive greater transparency, care continuity, and clinical quality outcomes for their members.

As healthcare organizations continue to invest in and develop technologies to bridge these data silos, patients benefit from greater transparency, better encounters, and ideally, stronger health outcomes.

Additionally, the combination of all this disparate data requires organizations to employ sophisticated data management practices, particularly in the areas of patient and provider matching and linking, anonymization and tokenization where needed, and the use of more fluid data models. Interest has also grown in leveraging Natural Language Processing (NLP) and Machine Learning (ML) to analyze massive amounts of data to drive curated care interactions.

How to find patient insights in a sea of data

Between the various data sources and the many forms of technology available to help make sense of patient data, it’s challenging for healthcare organizations to obtain actionable insights in a timely, efficient manner. Claims data, prescription data, EHR data, and reporting data must all be aggregated, normalized, secured, and then analyzed in order to be valuable.

While the efforts mentioned above are helping healthcare organizations move the needle in achieving data-driven healthcare, the best way to identify rich patient insights is to get access to as much data as possible. Having one source of detailed, secure data in a single authorized location takes the heavy lifting out of data utilization. With real-time access to longitudinally linkable data, authorized providers can turn the strain of sifting through silos into an easy, seamless process.

The path to finding patient insights doesn’t have to be reinvented for every patient or across different settings. Instead, with technology such as DataStream, providers across the continuum of care can uncover valuable patient health history, prescription information, claims data, and more – all within seconds.

Using patient insights to inform action at the point of care

Data has the potential to drive better patient-provider interactions, increase transparency, and enable providers to spend more time on assessing patient options and delivering care instead of searching for key patient insights. Patient insights can potentially promote disease prevention, drive better health outcomes, and increase patient satisfaction rates – but all of this comes down to having access to the right data at the right time.

Without real-world data readily available at the point of care, organizations will not have the holistic patient views necessary to create significant progress in health outcomes.