Answer honestly: What if your cell phone plan only allowed calls from people who had the same carrier as you? Or, what if your bank could only see certain transactions from just one store, so it couldn’t flag any other activity? Or, when you check your weather app, you could only see weather updates in one small region and nowhere else? Hard to imagine, isn’t it?

All EHRs should be interoperable, but the reality is that obtaining that data in a usable and readable format is difficult. So now imagine that you could access your banking information, but only on an iPhone. Or you could only check the weather if you downloaded software on your iPhone that allowed you to read the weather in bits and pieces.

For many years, the healthcare industry has faced the challenge of fragmented data in isolated departments and systems. Simultaneously, nowadays there’s also a swirl of data in disorganized systems, different formats, poor interoperability and integration between health systems.

With fragmented data, and much of it disorganized, organizations are facing the task of accessing information that is reliable, clean and easy to understand. Here are three aspects to look for when considering how to approach harnessing your data.

Smarter data aggregation for greater interoperability

Organizations not only need a solution that aggregates patient data, but that data needs to be reliable, comprehensive and usable, and clinicians need to have confidence in using that data to make accurate decisions. Data aggregation is defined by the process of organizing and compiling large amounts of data from multiple sources into a single, unified set. Using data interoperability and analytical solutions, data aggregation can be smarter and more unified, making critical patient data easy to read and understand.

Organizations not only need a solution that aggregates patient data, but that data needs to be reliable, comprehensive and usable, and clinicians need to have confidence in using that data to make accurate decisions.

Data-driven insights for patient care

Accessing important patient data means better care outcomes for the patient. With real-time predictable analytics, clinicians are given a bigger picture of the patient so they can provide accurate and more patient-informed care. Harnessing the data and real-time insights, providers can identify and visualize the gaps in care to manage patients more efficiently. With higher-risk patients, clinicians can monitor trending of patient data and history, from any care setting, to proactively intervene and create care plans to improve patient outcomes. Patients are mobile, so venues of care may be in many different places. Patient portals are not interoperable, so patients may think they have data, but it may only be for one certain area like immunizations. Further, more complicated patients may see multiple providers and specialists, which means that certain records may only be available in one space, leaving the family provider in the dark about lab results, immunizations, medication or more.

Bulk data and risk stratification

With the ability to reliably aggregate data, patient care isn’t the only benefit. Bulk data aggregation offers multiple data uses that aid in risk stratification, which enables clinicians and healthcare workers to give their patients the best care possible. With greater information available, utilizing bulk data can help visualize and share data within clinical workflows. Information for clinical research, clinical registry and administrative information, reporting analytics and much more is easily accessible and within reach.

Bringing it all together

It’s imperative for organizations to have the right data readily accessible and easy to understand. I know that Altera is keeping these trends at the forefront of our minds while working with clients and developing solutions to meet these needs. The dbMotion™ Solution is how we’re doing that. The overload and disorganization of data is overwhelming, and dbMotion enables the ease of data sharing and aggregating for organizations. Learn more here.