Digital health information represents a health system’s greatest asset. It is also the healthcare industry’s greatest ongoing challenge.
Nearly a decade after the explosive rise in electronic health record (EHR) adoption, we are still making new discoveries about the enormous wealth of data we are generating every day. And we are still struggling to translate those findings into accessible, meaningful, and actionable tools for frontline clinicians while they are caring for patients.
As the healthcare industry continues to move toward financial incentives that demand more coordinated, cost-effective care, the status quo is no longer adequate. We must start adopting smarter, less labor-intensive techniques for engaging with health information and IT tools to produce better outcomes and reduce waste.
Surveying the current health IT landscape
We have come a long way since the early days of EHRs, but there is still much work to do before every technology user has the relevant precision insight they need to make proactive, informed, appropriate, collaborative decisions about patient care.
The health information exchange and data access landscapes remain somewhat stunted. According to the latest data from the Office of the National Coordinator, only 46 percent of hospitals met all four criteria for true interoperability: the ability to send, receive, find, and integrate key data elements to support clinical decision-making. Users reported significant issues with making good use of digital data. Even when data was available, half of hospitals could not integrate the information into the EHR. And if it’s in the EHR, it’s not presented in a useful or easily navigable format, leaving approximately a third of users unable to leverage the data in a meaningful way.
The downstream impacts of these gaps and barriers are significant. Providers may be unable to coordinate care or make informed treatment decisions. They may reorder tests and procedures unnecessarily, contributing to billions of dollars in waste and poor patient experiences. EHR usability, or the lack thereof, is also a major factor in provider burnout.
This is the third decade of the 21st century. This is unacceptable. We know we can and must do better.
Rethinking health information access
Many of the current strategies to improve health information access are rooted in document-based exchange, also known as query-based exchange, which may or may not result in easily accessible and usable data.
Oftentimes, making a request, sifting through the results, and synthesizing the data into a meaningful patient story can require significant time and manual effort. And this push-and-pull data exchange method might not even return the data providers are looking for. This generates too much work and cognitive load for an already overburdened and precious resource.
But what if there was a better way to make health information accessible at the point of care? What if we could achieve the goals of true transparent, helpful interoperability by having systems working smarter on data retrieval, integration, and understanding?
We know that it’s possible. More importantly, we know it’s possible without an expensive, disruptive rip-and-replace of existing health IT infrastructure.
Instead of requiring providers to actively query for the data they need and hope that the relevant data exchange partner has made the information available, we can deploy an omnipresent network of sensors embedded with relevant, authorized data exchange partners to instantly identify changes to patient records and act accordingly. With appropriate consent and robust security measures, these sensors can unobtrusively monitor activities on a patient’s profile, scan the relevant partners for new data related to that patient, and deliver impactful updates to providers in an easy-to-understand ribbon that is seamlessly presented within the existing EHR interface.
What does working smarter really look like?
We could continue to chip away at the barriers of document-based exchange in the same old way, or, with emerging technologies and advanced applied intelligence, we can leapfrog many of the existing obstacles to achieve better results more quickly and less expensively.
For example, let’s say Dr. Gomez is a primary care provider working with Mrs. Smith, an elderly patient with a history of chronic disease and multiple hospital events. With the traditional approach, Dr. Gomez would have to rely on the local hospital to make admission, discharge, and transfer alerts available to even be informed about Mrs. Smith’s recent inpatient stay.
Once she knows about the admission, she may have to actively request clinical documents from the hospital, the pharmacy, Mrs. Smith’s specialists, and the labs to understand what happened – and she may or may not receive a comprehensive record of the event.
If she does receive this data, it is still likely to be in a static format, such as a fax or scanned PDF. She will need to find where these documents are stored in her system and spend precious time reading through them, unable to easily search for the most pertinent information about Mrs. Smith’s recent procedures and new diagnoses. She will then have to take time and possibly conduct research to decide what to do next.
This is hard work for Dr. Gomez. It’s hard for her health information exchange partners, too. And it’s especially hard for Mrs. Smith, whose care might suffer as a result of insufficient access to information.
With a smarter, integrated, applied intelligence approach to health data access, Dr. Gomez does not need to do these steps. The system is now working for Dr. Gomez and Mrs. Smith, not the other way around. Just as it should be.
Simply opening up Mrs. Smith’s health records triggers a series of automated actions designed to identify any changes to data involving Mrs. Smith, funnel that data into a knowledge management hub, then analyze and present that data in a precise, prioritized, action-oriented manner as Dr. Gomez reviews the chart.
Not only is the information more readily available without additional effort, but it is thoughtfully displayed in a way that supports informed decision-making and proactive, evidence-based patient care while supporting the way Dr. Gomez wants to practice.
In essence, Dr. Gomez now has an automated, intelligent “personal assistant” to perform the hard work of data retrieval and synthesis. The personal assistant functions within her existing EHR environment without the need to log into additional tools. This smart technology has several benefits for Dr. Gomez and thousands of providers just like her.
First, she knows that incoming data will be displayed in a consistent, intuitive manner directly within her EHR, reducing the cognitive strain of skimming through poorly scanned copies of plain-text reports in unfamiliar formats.
Second, she can trust that the information presented is current, comprehensive, and as correct as possible.
And third, she can begin to use these precision insights to deploy proactive care plans that avoid unnecessary utilization, improve coordination of care, and foster better outcomes for her patients and practice.
With tools that take a smarter approach to health information access, the health system can achieve its ultimate goals of boosting outcomes and reducing waste while dramatically improving the experiences of both providers and patients.
Now is the time to break down the data siloes with creative, contextually aware, data-driven techniques that further the value of our health data assets and create a more intelligent environment for providers, patients, and the health system as a whole.