Navigating healthcare digitalization and its impact on the patient journey

• While data-driven healthcare can positively impact patient care, disconnected and incompatible systems, and data continue to be a major challenge in the healthcare sector
• Siloed information and cybersecurity risks are significant hurdles preventing healthcare organizations from sharing critical patient information that can delay clinical decisions
• Before implementing novel digital health technologies and advancing a new infrastructure into existing health systems, technologies need to be secure and improve operational efficiency and personnel productivity

As healthcare organizations adopt data-driven approaches, such as machine learning and artificial intelligence, the healthcare industry faces challenges and opportunities in implementing digital transformation. Data-driven approaches have the power to improve the operational efficiency of processes and dramatically impact the patient journey. At the same time, healthcare organizations must overcome numerous barriers, including siloed healthcare data sets, technology integration barriers, and interoperability difficulties.

According to a recent survey from the Harvard Business Review, 94% of healthcare professionals believe data-driven healthcare can offer new opportunities and more personalized approaches. However, almost half of those surveyed believe that one of the major hurdles to digital transformation in healthcare is disconnected and/or incompatible systems and data.¹

At this year’s Healthcare Information and Management Systems Society (HIMSS) Global Health Conference & Exhibition, Dr. David McClintock, Jina Forys, and Dr. David Vawdrey, with host Moritz Hartmann, shared insights on to build a foundation for data-driven practices in healthcare, address lab operational efficiency, and transform the compendium of digital information into personalized care strategies.

Digital infrastructure and data analytics enable healthcare organizations to provide novel clinical insights and decision support. Before implementing these advanced innovations, it is critical to highlight how these digital technologies will lead to positive outcomes for all stakeholders involved, from patients to clinicians and healthcare personnel, and be implemented safely and efficiently.

On the panel, Dr. Vawdrey pointed to the need to create technologies that augment human productivity, enabling healthcare professionals to work “more effectively, more efficiently, more affordably, with better overall outcomes for the entire system.” Ms. Forys added, “We have a lot of data flowing in and out of the laboratory. How can we make our internal operations more efficient, and provide data to clinicians so that it’s more actionable for them to use that information?”

Concerning data safety, Mr. Hartmann commented that cybersecurity is “a very foundational concern.” As a response, Dr. Vawdrey emphasized the need for improving healthcare data security, especially with the growth of horizontal and vertical integration of data between health systems and outside parties, saying that the industry needs to “work together in that ecosystem to provide the best and safest healthcare to facilitate overall health in all of our communities.”

A significant challenge when building a foundation for data-driven practices is handling siloed data sets, which is information that can only be used and analyzed by single departments or within a single healthcare system. Electronic health records (EHRs), which have become more commonplace in the last two decades, are a prime example of siloed data due to the difficulty in sharing this patient information between health organizations. This can lead to unnecessary delays in clinical decision-making. “We’ve built up these individual siloes of our own EHRs, and really haven’t built roads in between,” commented Dr. McClintock.

Additionally, analytical tools like AI-based algorithms or large language models could also be siloed, and locked away, only to be used by one healthcare system. This is becoming a major challenge in improving patient care because these valuable tools can rarely be used outside of the originating organization.

To address siloed data and tools, we need to improve interoperability, says Dr. McClintock. “We don’t have good ways of exchanging data, from a very simple thing of knowing whether or not you’re doing those same lab tests from one institution to another. We don’t have a good standardized way of making sure everybody’s using the right things.” To that end, healthcare leaders must emphasize the importance of standardizing digital infrastructure, ensuring efficient sharing procedures and interoperability, which could lead to better patient care.

In addition to finding standardized methods for sharing data and technologies, the panel discussed how best to bring new solutions into current legacy systems. Firstly, evaluating whether a new solution or novel technology will significantly change the patient experience is essential. If the ultimate goal is to get results faster to a patient, for example, a healthcare organization needs to closely evaluate whether or not the new digital solution is the best answer.

Dr. McClintock commented that rather than rushing to implement the newest systems, an older yet validated point-of-care test could help provide the best care. Speaking on this issue he asked rhetorically, “Are you going to break certain things that may be working really well right now?”

Along the same lines, Dr. McClintock said that when building novel AI models and implementing new algorithms into clinical laboratories, health leaders must develop a clear pathway to translating them into clinical practice. He emphasized that one must keep in mind all the steps within the process, including cybersecurity and regulatory procedures: “When you think about building out these digital solutions in clinical practice, you have to begin to think about how to build a roadmap.”

Speakers on the panel agreed that part of implementing a new digital infrastructure into legacy systems is to bring employees and personnel along the journey. While the digital automation process may accelerate as more data is being produced, it does not necessarily mean that human labor is altogether replaced. Rather, there will be a shift in the types of work being done. “The lab analyzers do not run themselves. There are still people that do that work,” said Ms. Forys.

When it comes to healthcare digitalization leaders must emphasize the importance of interoperability and trust in digital solutions, whilst finding ways to standardize digital infrastructure so that the sharing of data and technologies is both rapid and efficient. Prioritizing investments and building collaborations that focus on high-quality, rapid, and secure results for patients will optimize data access and workflows, support clinical staff, and create solutions that can be easily integrated into existing systems.

It is important to acknowledge that new technologies, including AI, can facilitate care, but careful consideration and implementation are necessary to avoid potential pitfalls. Streamlining the transition to a digital ecosystem is therefore critical to overcoming barriers to healthcare access and subsequent patient care. Healthcare digitalization is crucial in this context.