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What Is Interoperability? (+Barriers to Achieving It)

Sumayya Mahin
Sumayya Mahin  |  November 26, 2019

Interoperability. That’s not a word that rolls off the tongue easily.

So you might already be wondering what it is. But in the health IT industry, healthcare professionals already know.

What is interoperability?  

What exactly is interoperability? Let's discuss. 

This way, any healthcare professional from anywhere in the world can access the patient’s records and provide care and treatment without delay. Though it may sound all rosy and good, there are some barriers to achieving interoperability. In this article, we will be talking about those barriers and how to overcome them. 

Before actually getting into the barriers, it is worth understanding interoperability and the different levels in interoperability first to see how barriers can actually arise. 

1. Data interoperability by level

There are three levels of interoperability: Structural, Foundational, and Semantic. Each of these levels have their capabilities and uses in the modern healthcare industry. Hospitals and clinics assume different levels of interoperability depending on the information, the data to be shared, and the patient’s condition.

2. Data deployment depending on the deployment type

There are two kinds of interoperability based on the deployment category: cloud-based deployment and on-premise interoperability. Through cloud-based interoperability, the users can utilize the same management tools and software with a number of other cloud computing platforms and providers.

On-premise interoperability is mainly used by large hospitals when they have huge sets of data and they share it with different departments of the hospital. This way, the doctors can avail information about the patient without having anyone providing them physically. On-premise interoperability can definitely save a lot of time and energy, and provide better deliverance. 

3. Data on an application level

Data interoperability on the basis of the application here means collecting and sharing data while a diagnosis is made. Apart from EHR software, clinicians have begun to use technologically upgraded healthcare interoperability software that would considerably reduce errors while the diagnosis is made. Early diagnosis can reduce mortality rates. A huge repository of data is thus being disseminated at the diagnosis stage so they can be shared as people get diagnosed at the initial stage. 

TIP: See how electronic health records software functions and how the technology has made great advances in recent times. 

See the Easiest-to-Use EHR Software →

Interoperability at the application level extends to not just the diagnosis level, but at the treatment level too. There is considerable growth in the treatment segment because of the increase in the prevalence of chronic diseases, and the number of patients seeking treatment for chronic diseases has increased as well.

4. Data interoperability through the right model

When data is shared on the basis of a centralized model, there is a higher level of protection because once the healthcare professionals share the data in a particular repository, it can be seen by other professionals or repositories only when they send in the request and permission is granted. This would prevent unauthorized sharing of data, and can prevent data breaches to a great extent. 

The hybrid model was also in great demand because it had several benefits associated with it. Hybrid interoperable software can really cut down operational costs. A major difference that this model has with the centralized model is that you don’t have to create a separate consolidated data center, and this helps in preventing time delays.

5. Data interoperability by end-user

The end-user mentioned here is most definitely the patient. And with the growing occurrence of chronic diseases, patient admissions are also increasing. More patient admissions means more data and this calls for better and highly effective interoperability solutions. The number of surgeries is also increasing because the number of chronic illnesses has increased, and this would lead to consequent generation of patient data; data that must be used appropriately.

interoperability graphic

6. Region-wise increase in data interoperability

The government initiatives in the North American healthcare sector are allowing a robust growth of data interoperability in that area. The government is also spending well for the effective use of EHR and for the quick, effective and safe data exchange across all channels and healthcare departments. This has escalated the growth of a particular region when compared to the others.

The Asia Pacific (consisting of India, Japan, China, Australia, South Korea, Bangladesh, Nepal, North Korea, etc.) healthcare data interoperability market is also seeing immense growth, and the governments in these countries are also increasing their expenditure to ensure secure healthcare facilities, including pharmacies. 

Related: Learn how artificial intelligence is being used in the healthcare field in 2020, and what ways this affects data sharing and security.

Related content: AI in Healthcare →

Challenges in achieving interoperability

Keeping the aforementioned points in mind, let’s have a look at the challenges in achieving interoperability.

1. There is a huge influx of data

As the number of data sources increases, so will the amount of data that’s coming in. And this would increase when more patients are using smart devices and wearables. The huge influx of patient-generated health data comes from elderly patients, patients with chronic conditions, in-hospital patients, from wellness programs and even from remote patient monitoring systems.

All the levels of interoperability that we mentioned above come into practice here. But the problem is that all this information requires several layers of interoperability, and also involves semantic interoperability and syntactic interoperability. And there could also be social, cultural, economic and even policy barriers to interoperability. So when the influx of data is huge, then it would be difficult to clear them all and collect relevant data.

2. More partners, more complicated relationships

The more partnerships you form, the more complicated it becomes to manage them. For example, if a huge hospital system acquires smaller hospitals, then aligning the IT systems could be a tough job. These IT systems may have to combat a number of tasks in order to make the data interoperable, including scheduling, and even sometimes converting the paper records.

Often when acquisition happens, this part is often neglected, leading to time-consuming jobs by the IT people. In order to ensure that the end-user or the patient doesn't suffer as a result of the acquisitions, the hospital systems must conduct a thorough audit and then make an interoperability game plan. Make a reasonable timetable to move the data and make it interoperable so the healthcare professionals and the patients would benefit from it. 

3. Staff workflows could be a problem

You can think of interoperability as having two different layers: one layer would be the data layer, and the other, the workflow layer. Problems with workflows can hinder interoperability. Actually, workflow interoperability is one layer above data interoperability, and it is much more difficult to achieve. Sharing data is one thing, but sharing the workflow of another organization and using that information to coordinate it with the internal workflow of another organization is critical. 

Once that happens seamlessly, because there would be both speed and quality, the patient can move from one clinic to another or from a clinic to a rehabilitation center and back (each would require a different aspect of patient care) seamlessly. Creating automatic workflows is one answer to this, and once the workflows move from one organization to the partner organization, progress can be fast.

There is great progress with the data layer, and once this problem with the workflow layer is completely eradicated, there would be a rapid exchange of information and output.

4. Not all payers are happy to participate

The Centers for Medicare and Medicaid Services (CMS) issued a new rule on February 22, 2019, concerning the many programs that CMS manages. According to the rule, patients can access their health information on interoperable forms.

The patient’s health information, including their health plans and providers, complete with history of illnesses will all be shared. The payers here, mostly insurance providers that offer QHPs or Qualified Health Plans, have massive information about patients that would be really helpful to the providers.

But so far, they have been slow in cooperating with the healthcare providers, and some of them do not want to share their data at all. That has to change. Hopefully, with the new rules, there will be a change in that soon. Once that happens the payers would have to maintain open APIs to enable third-party applications to quickly retrieve patient health data (with approval from patients, of course) and adjudicated claims data, clinical data, provider directory data and so on.

5. Lack of proper standards

There is no doubt that there should be standardization in health IT standards, and even the stakeholders agree on that but it is the way these standards are interpreted and enforced that makes all the difference. There are various interoperability standards that stand as a challenge to interoperability advancement. The ecosystem is so different in today’s healthcare industry. You can see a patient at the clinic, hospital, in hospices and even through online consultation. So care is happening in multiple venues. If there is a lack of interoperability standards, then it makes data exchange difficult or limited. 

This can be solved by having a network where the healthcare exchange between all providers and organizations that promote interoperability uses software that’s already embedded into the provider’s EHR system. This will cut out the standardization problems and facilitate exchanges. However, following the same standards is still a limiting factor, but that should be cleared with time.

6. Mismatched patient records can be a real hindrance

One of the biggest barriers in interoperability is the inability to match the patient with the records. Errors could happen at any point, right when the patient fills out his forms to the point of care. It is obvious that one small error can really bring the whole thing down and because there are no actual people, once it goes through different systems, the errors may not even be detected.

Inaccuracies, inconsistencies and incomplete forms can pose real problems in actual matching. This makes comparing a particular patient’s information across other health records a tough task. Following certain common practices for identifying demographic data, developing a public-private collaboration effort and sharing best practices are a few ways in which these discrepancies can be avoided.

7. Enforcing standards for industry-wide interoperability measurement

There are new interoperability movement initiatives springing up every now and then. Government agencies need some kind of uniform method to measure the progress of these initiatives. This would help in the assessment of health IT interoperability in a consistent way. But sometimes, interoperability measurement standards can vary among the stakeholders too. And some of the older measurements can also pose confusion.

Some of these are Health Level 7 standards, International Classification of Disease, Digital Imaging and Communications in Medicine (DICOM), OpenEHR, CEN/ISO EN13606 and so on. Healthcare institutes do not always conform to a single standard, and the use of more than one standard can definitely lead to serious errors.

One way to overcome this problem would be having a uniform measurement framework - Interoperability Standards Measurement Framework. Through this framework, the industry’s activities in implementing interoperability standards would be analyzed, and measured in detail. This would help track the progress on a national scale.

Through this framework, the healthcare IT professionals/companies are required to report the following: the percentage of end-users following a particular standard, what are the number of transactions that happen according to these particular standards and after implementation, record the conformation and customization of those standards.

Conclusion

The main aim of interoperability is to bring together everyone related to healthcare sectors. This can be started by encouraging the medical professionals to use common medical terminology while creating patient health records (so there won’t be mismatches), coordinating the stakeholders in the medical industry because they really do have to collaborate on creating policies and standards in enforcing interoperability, and cut out the staff workflow issues completely.

It is imperative for all healthcare facilities to adopt interoperability because that’s the only way in which they can reach their goal: provide comprehensive diagnosis, treatment and care to the patient. Having patient data at their fingertips would enable healthcare professionals to provide healthcare without delays. And since the data comes in through various levels as mentioned above, those factors have to be considered as well.

Just like there are two sides to a coin, if there are several advantages to achieving interoperability among healthcare systems, the barriers that we mentioned above will also have to be considered. A huge change in this scenario will also come if the hospitals and clinics begin to consider the patient's medical records as not their own property, but that of the patients. 

Curious, and want to keep learning? Discover more about healthcare operations software and fulfill your thirst for knowledge. 

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Sumayya Mahin
Author

Sumayya Mahin

Sumayya Mahin is a digital marketer and technical writer for Cabot Technology Solutions who is passionate about exploring and writing about innovation, technology, and digital marketing trends.