EHR interoperability and how to achieve it

EHR interoperability and how to achieve it

April 7, 2021

Blog

EHR interoperability and how to achieve it

Healthcare Analyst

EHR appeared back in 2009, and since then the talks about interoperability in EHR software development have been in the air. Though at first providers perceived interoperability as an innate EHR feature, the bitter practical experience proved that this assumption was far-fetched. Ensuring interoperability has always been a separate intensive effort demanded from medical providers in the first place. Has the situation improved? Unfortunately, it has not, and the COVID-19 pandemic has exposed the poignant issue once again.

In March 2020, Black Book Market Research ran a series of interoperability surveys that offered insights into providers’ and consumers’ experiences regarding EHRs amidst the pandemic:

health info sharing

As we can see, in the times when an effective EHR was more needed than ever, the tool failed to be of help to both doctors and patients. Surprisingly, the reason for such a devastating performance was still an insufficient interoperability.

What is EHR interoperability?

Interoperability is the ability of disparate systems to exchange a variety of data. Apart from EHR, it covers lab systems, imaging solutions, healthcare information exchange software, tools for practice management, and more. But how does it work? Here’s how the Healthcare Information and Management Systems Society (HIMSS) defines it:

Interoperability describes the extent to which systems and devices can exchange data, and interpret that shared data. For two systems to be interoperable, they must be able to exchange data and subsequently present that data such that it can be understood by a user.

Healthcare Information and Management Systems Society (HIMSS)

Thus, just being able to receive EHR data doesn’t make a tool interoperable. Apart from obtaining this data, it should be able to present it to a user in an understandable way. This peculiarity hints at diverse types of interoperability, or its levels.

Types of interoperability

HIMSS defined the types of interoperability in healthcare back in 2013. First of all, HIMSS specialists carefully articulated the Society’s functions: access to health data and data integration into the system, health information exchange, and joint care coordination with practitioners regardless of their location. This analysis helped them define three levels of interoperability:

  • Functional interoperability is the basic level. It allows sending data between systems without its interpretation. For example, when a patient is discharged from the hospital, they receive a health summary in PDF.
  • Structural interoperability is the intermediate level that involves a certain share of interpretation. Structural interoperability is a system’s ability to send and receive information without altering its meaning and purpose. To ensure this ability, a system should interpret information at the level of data fields, which requires both sending and receiving systems to follow accepted data standards.

E-prescription is a vivid example of this interoperability level. It ensures that a drugstore computer shows what was received from a medical provider’s system without any changes, as the two systems apply the same standards to common prescription elements, such as dosage, route, the name of the medicine, and more.

  • Semantic interoperability is the most advanced level. It’s the ability of digital health systems to not only exchange and structure data correctly but also to interpret it. This is possible due to data codification, including vocabulary. Semantic interoperability lets providers exchange patients’ health data with other providers who might employ different EHR systems. It helps improve care quality, safety, and efficiency.

Unfortunately, for now, the majority of providers across the US have only reached the structural interoperability level. Hospitals and health systems can utilize existing health data standards to achieve lower levels of interoperability and set a solid foundation for future improvements in health data exchange.

However, insufficient interoperability became a major care deterrent during the pandemic outbreak across the US.

What’s the problem?

In March 2020, at the onset of the pandemic, experts from the Duke University tried to evaluate the EHR system readiness to manage the crisis. They came to some disturbing conclusions.

First of all, the lack of homogeneity in major EHR systems could complicate the work of clinicians:

One is the lack of a cohesive data model for patients in most electronic health records that allows clinicians to start with a patient and trace back to their signs, symptoms, and diagnostic tests.

Erich Senin Huang

MD, Co-Director of Duke Forge and Assistant Dean for Biomedical Informatics, Duke University

Truth be told, EHR vendors tried to improve the situation by rolling out numerous updates for their tools. However, the majority of EHR systems are very complex, with many functions intertwined, which renders trouble-free updates virtually impossible. For providers, this is a long and costly process, which may only make matters worse.

Duke University researchers detected yet another alarming feature of modern EHR systems. It’s their inability to serve as population health management software amidst the crisis:

Tracking dozens of patients in an electronic health record system is feasible in many health care systems, but current capabilities are unlikely to scale to hundreds or thousands.

Eric D. Perakslis

PhD, Rubenstein fellow, Duke University

Besides, several interoperability challenges have been there from the start:

  • Lack of a patient identification standard accepted nationwide (NPID) that would assist with patient matching, lowering the rate of repeat tests and delayed care instances.
  • Insufficient data sharing among payers. Insurance companies store loads of diverse data, and yet they are reluctant to share it with providers.
  • Integration costs. To ensure quality care, providers employ a range of IT solutions. To yield the benefits, providers need to achieve seamless integration of disparate systems, including EHRs. This is a hefty investment that only large healthcare networks can afford.
  • Lack of efficient EHR-to-EHR communication. Ironically, the relevant tools are there. They are HL7 and FHIR standards. Moreover, top EHR vendors support them. However, this doesn’t mean each of their EHR implementations follows this pattern.

In 2019, researchers from the Center for Connected Medicine (Pittsburgh, PA) ran a survey looking into the types of interoperability established across the US:

While the interviewed providers were content with their data sharing practices with payers, patients, and pharma (structural interoperability), only a third of them reported advancements in data sharing with other health systems (semantic interoperability).

Judging by the concerns the Duke University researchers shared not long ago, the situation seems to be stuck. So is there a way to improve EHR interoperability? Luckily, there are a couple of them.

How to improve EHR interoperability

A few technologies promise interoperability improvements, from cloud-based to blockchain EHRs. We’ll consider how each of them may assist with enabling full-scale interoperability.

Moving to the cloud

Cloud technologies have already settled comfortably in the healthcare industry, so EHR migration to the cloud is in high demand right now. For providers, a cloud EHR helps reduce overbearing costs they have to endure by offering a pay-as-you-go model.

What’s more, the cloud environment allows providers to take the security burden off their shoulders, at least in part. The majority of cloud EHR vendors offer round-the-clock support and expert cybersecurity services to keep PHI protected at all times.

However, it should be noted that the advantages above apply only to public and hybrid clouds. If providers decide to go for a private cloud, they have to be aware of the hefty cost and the need for a professional in-house IT team to manage the solution.

Unfortunately, cloud environments are not completely free from interoperability issues either:

Right now, interoperability is being done on an ad-hoc basis. What we need are some government regulations around cloud. The technology is there for interoperability, we just need to decide on some standards.

 

Zeus Kerravala

Founder and Principal Analyst, ZK Research

Without the standards, cloud environments can’t “communicate” efficiently. Besides, the lack of standards may hamper data sharing between different cloud tools.

Adopting a blockchain EHR

EHRs can be a good starting point for implementing blockchain in healthcare. This decentralized ledger technology may help provide enhanced EHR security and accessibility to both medical professionals and consumers.

This is how a blockchain EHR works:

blockchain workflow

Blockchain can also make a positive impact on semantic interoperability. With blockchain, there’s no need to ensure costly integrations across different EHR systems. The only thing required to get access to one's records is a private key. This may enable access to health records for any medical professional and from any location, providing they have valid credentials.

This seems to be a “dream come true” situation, so why hasn’t the industry switched to this EHR system model altogether?

With a blockchain EHR system in place, patients become full-scale masters of their data. It’s them who grant access to their health information to providers, not vice versa, as it’s always been. In this context, consumers are left to fight off cybercriminals and malicious actors on their own. As a result, they may fall victim to some advanced fraud schemes like social engineering.

Besides, with patients becoming protagonists of their healthcare journey, providers will need to learn many new skills, from blockchain operation to marketing and advertising. After all, they’ll have to find ways to persuade consumers to become their clients and share their personal health data with them. A bit off the beaten track, isn’t it?

How to measure EHR interoperability?

Measuring interoperability is a complex effort that may require extra time and effort from providers. Well-aware of the accompanying challenges, in 2016, the Office of the National Coordinator for Health Information Technology (ONC) addressed providers asking for comments regarding interoperability measurement.

ONC specialists developed a sort of rapid interoperability assessment framework that only looks at two critical data sets:

  • Share of providers who electronically perform the four basic operations related to interoperability: sending, receiving, finding (querying), and integrating information from external sources.
  • Share of providers who use the information they get from other providers and clinical decision-making sources for reporting.

This data allows researchers and healthcare officials to evaluate structural and semantic interoperability rapidly.

For providers, the simple framework may work for self-assessment. They just need to reformulate the measurements into questions: e.g., “Do we send, receive, query, and integrate information from external sources?”

To measure interoperability comprehensively, HIMSS Interoperability cooperated with the HIE Committee and worked out eight measuring factors. They allow evaluating all the three levels of interoperability within a healthcare system:

  1. Basic transactions. This factor describes the ability of two systems to exchange data and the ability of the receiver to use the information without difficulties. It is measured in terms of volume and transaction type (send—receive, query—use, and find—integrate).
  2. Partners/stakeholders within a network. Here data exchange is considered at individual and population levels (provider to provider vs. provider to registries).
  3. Standards applied. This factor includes message types and standards that enable the receiver to recognize and process data.
  4. Profile-dependent transactions under diverse implementation guidelines, Integrating the Healthcare Enterprise (IHE), and more.
  5. User specifics, e.g. size, location, specialty, etc. to understand the settings that host interoperable transaction
  6. Transaction time frame, e.g. real-time or delayed.
  7. Transaction volume for all technology types involved and network-reported trend data. Having examined how the seven factors above fit their healthcare system, providers may rate their interoperability scope and efficiency and identify the gaps.
  8. Future plans for scaling up transactions.

At this point, providers may develop some strategies for bridging those gaps and advancing towards semantic interoperability with more healthcare systems if needed.

On a final note

Healthcare interoperability is a complex matter for the modern healthcare industry, intended to allow seamless sharing of patient data and improvement of care coordination and clinical decision-making.

While functional and structural interoperability is already there, semantic one is yet to be achieved. Still, there is a powerful facilitator around. It’s the honest cooperation of stakeholders involved in the improvement effort, from clinicians to insurance companies and EHR vendors. Without this multi-faceted cooperation, semantic interoperability can hardly be achieved.