Compilation shows US Veterans Administration spent the most at $16B
Clinical laboratory leaders and pathologists will be interested in which hospital systems are making the largest investments in electronic health record (EHR) technologies. Especially considering laboratory information systems (LIS) must interface with these platforms and require extensive reworking when hospitals change their EHRs. For example, hospitals moving to the Epic Systems EHR often require their laboratories to implement the Epic Beaker LIS as well.
According to information sourced by Becker’s Hospital Review, the top 16 hospital systems each spent $500 million or more on EHRs, adding, however, that the information is “not an exhaustive list.”
Number three on the list is Kaiser Permanente which operates multiple hospitals within its nine healthcare networks across the United States serving 12.5 million members. For that reason, its total investment in EHR technology represents a much larger number of hospitals than the other health systems on the list.
Of the 16 providers on the list, 12 installed EHRs provided by Epic Systems of Verona, Wis. Four of the providers implemented EHRs from Oracle Health (formerly Cerner), North Kansas City, Mo., and Meditech of Westwood, Mass.
“Looking forward, there are many advantages in terms of investing in the future and how we will be aligned with technologies including digital and AI applications,” said pathologist Angelique W. Levi, MD (above), vice chair and director of pathology reference services at Yale School of Medicine, in a news release following a site visit to Geisinger Diagnostic Medicine Institute in Danville, Pa., to see Epic Beaker in operation at Geisinger’s clinical laboratory. “But what we gain immediately—having all the patient information accessible in one place in a linked and integrated fashion—is very important.” (Photo copyright: Yale School of Medicine.)
Provider, EHR, Investment
Becker’s list below shows the total amount invested by the 16 healthcare systems was approximately $38.32 billion. The average EHR implementation cost is $2.39 billion for a large healthcare provider.
Becker’s stated they assembled this list from public sources and that there may be other EHR/hospital contracts with a total cost that also would make the list. It is not common to see a list of what hospitals actually spend to acquire and deploy a new EHR.
Epic added 153 hospitals to its client base in 2023. Epic’s EHR competitors—Oracle and Meditech—both experienced declines in client retention rate, Healthcare IT News reported based on the KLAS data.
“Both current and prospective large organization customers are drawn to Epic because they see the vendor as a consistently high performer that provides strong healthcare IT [information technology], quality relationships, and the opportunity to streamline workflows and improve clinicians’ satisfaction,” Healthcare IT News said of the KLAS report’s findings.
In a blog post, authors of the KLAS report explained that in 2023 Oracle added specialty hospital clients and Meditech “saw several new sales” which included healthcare systems and independent providers.
In the next few years, the industry is “ripe for disruption. Another vendor could come in and turn everything on its head,” the KLAS blog article concluded. “Even those who choose Epic want to have more competitive options to choose from.”
Preparing for an LIS Change
Clinical laboratory leaders who may be transitioning their LIS during a new EHR installation may learn from colleagues who completed such an implementation.
Angelique Levi, MD, vice chair and director of pathology reference services at Yale School of Medicine, who was part of the pathology team, noted that one challenge for labs is addressing “information that’s from many different places when we’re talking about cancer care, prognostic testing, and diagnostics.
“It’s become much more complicated to manage all those data points,” she continued. “Without being on an integrated and aligned system, you’re getting pieces of information from different places, but not the ability to have linked and integrated reports in one spot.”
EHR implementations are among the most labor-intensive, expensive projects undertaken by hospitals. Therefore, it is crucial that clinical laboratory and pathology leaders research and learn why an EHR (and possibly LIS) change is needed, what is expected, and when results will be received.
One goal of these new functions is to streamline physician workflows. However, these new EHRs may interface differently with clinical laboratory information systems
Artificial intelligence (AI) developers are making great contributions in clinical laboratory, pathology, radiology, and other areas of healthcare. Now, Electronic Health Record (EHR) developers are looking into ways to incorporate a new type of AI—called “Generative AI”—into their EHR products to assist physicians with time-consuming and repetitive administrative tasks and help them focus on patient-centered care.
Generative AI uses complex algorithms and statistical models to learn patterns from collected data. It then generates new content, including text, images, and audio/video information.
According to the federal Government Accountability Office (GAO), generative AI “has potential applications across a wide range of fields, including education, government, medicine, and law” and that “a research hospital is piloting a generative AI program to create responses to patient questions and reduce the administrative workload of healthcare providers.”
Reducing the workload on doctors and other medical personnel is a key goal of the EHR developers.
Generative AI uses deep learning neural networks modeled after the human brain comprised of layers of connected nodes that process data. It employs two neural networks: a generator [generative network] which creates new content, and a discriminator [discriminative network] which evaluates the quality of that content.
The collected information is entered into the network where each individual node processes the data and passes it on to the next layer. The last layer in the process produces the final output.
Many EHR companies are working toward adding generative AI into their platforms, including:
As our sister publication The Dark Report points out in its December 26 “Top 10 Biggest Lab Stories for 2023,” almost every product or service presented to a clinical laboratory or pathology group will soon include an AI-powered solution.
“We believe that generative AI has the potential of being a personal assistant for every doctor, and that’s what we’re working on,” Girish Navani (above), co-founder and CEO of eClinicalWorks, told EHRIntelligence. “It could save hours. You capture the essence of the entire conversation without touching a keyboard. It is transformational in how it works and how well it presents the information back to the provider.” Clinical laboratory information systems may also benefit from connecting with generative AI-based EHRs. (Photo copyright: eClinicalWorks.)
Generative AI Can Help with Physician Burnout
One of the beneficial features of generative AI is that it has the ability to “listen” to a doctor’s conversation with a patient while recording it and then produce clinical notes. The physician can then review, edit, and approve those notes to enter into the patient’s EHR record, thus streamlining administrative workflows.
“The clinician or support team essentially has to take all of the data points that they’ve got in their head and turn that into a narrative human response,” Phil Lindemann, Vice President of Data and Analytics at Epic, told EHRIntelligence. “Generative AI can draft a response that the clinician can then review, make changes as necessary, and then send to the patient.”
By streamlining and reducing workloads, EHRs that incorporate generative AI may help reduce physician burnout, which has been increasing since the COVID-19 pandemic.
“Language models have a huge potential in impacting almost every workflow,” Girish Navani, co-founder and CEO of eClinicalWorks, told EHRIntelligence. “Whether it’s reading information and summarizing it or creating the right type of contextual response, language models can help reduce cognitive load.”
Generative AI can also translate information into many different languages.
“Health systems spend a lot of time trying to make patient education and different things available in certain languages, but they’ll never have every language possible,” Lindemann said. “This technology can take human language, translate it at any reading level in any language, and have it understandable.”
MEDITECH is working on a generative AI project to simplify clinical documentation with an emphasis on hospital discharge summaries that can be very laborious and time-consuming for clinicians.
“Providers are asked to go in and review previous notes and results and try to bring that all together,” Helen Waters, Executive Vice President and COO of MEDITECH, told EHRIntelligence. “Generative AI can help auto-populate the discharge note by bringing in the discrete information that would be most relevant to substantiate that narrative and enable time savings for those clinicians.”
Many Applications for Generative AI in Healthcare
According to technology consulting and solutions firm XenonStack, generative AI has many potential applications in healthcare including:
The technology is currently in its early stages and does present challenges, such as lack of interpretability, the need for large datasets and more transparency, and ethical concerns, all of which will need to be addressed.
“We see it as a translation tool,” Lindemann told EHRIntelligence. “It’s not a panacea, but there’s going to be really valuable use cases, and the sooner the community can agree on that, the more useful the technology’s going to be.”
Since generative AI can be used to automate manual work processes, clinical laboratories and anatomic pathology groups should be alert to opportunities to interface their LISs with referring physicians’ EHRs. Such interfaces may enable the use of the generative AI functions to automate manual processes in both the doctors’ offices and the labs.
