Datica Blog

March 29, 2019

5 Keys To Simplifying Interoperability In Healthcare

Dave Levin, MD

Co-Founder and Former Chief Medical Officer

While the health IT sector has made a big impact in terms of facilitating cooperation between electronic health records (EHRs), it still has a way to go with regard to simplifying healthcare interoperability. A research study showed that only about 30 percent of hospitals have implemented the four basic functions required for interoperability: data gathering, data reception, data distribution, and data integration. However, issues still remain even when a healthcare facility is performing reasonably on these four vital metrics.

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Below, we’ll take a look at five keys to simplifying interoperability in healthcare.

1. Wider Adoption of Data Standards

According to a Government Accountability Office (GAO) report on healthcare interoperability, although the standards for digital exchange of data do exist between EHR systems, these standards are inadequate to achieve true interoperability. HL7 has gained widespread adoption, yet room for interpretation means that there’s significant variance in how these standards are implemented. FHIR, a newer specification developed by HL7, makes some strides yet shares some of the same concerns that exist with the HL7 standards. For instance, vendors may not implement all FHIR APIs, or they may not implement the complete APIs – either scenario prevents true interoperability.

The foundational key to simplifying healthcare data interoperability is a wider adoption of data standards. A large number of healthcare organizations and vendors still continue to work within the outdated concept of data ownership instead of sharing patient information. Some forward-looking organizations are ready to share, but lack the capabilities necessary for doing so. The goal must be to shift from isolated data and participate in the industry process of building an interoperable healthcare ecosystem. The recently published draft rules by ONC & CMS that promote FHIR and encourage the free flow of clinical data are a significant step in this direction.

2. Choosing the Right Health Information Technologies

The second key is to choose the best technology that helps bring multiple data sources on to a unified platform. Healthcare organizations that continue to use inefficient or outdated technologies for data integration are going to find it difficult to make the transition.

Their tech interface might be incompatible with the cutting-edge cloud technologies, or they may discover that their system simply does not support the modern data formats. These issues are common and require a reliable and advanced solution, such as Integrate’s proven API solution, which offers turnkey integration across EHRs.

3. Improving EHR Integration for Better Point of Care Solutions

EHR integration is one of the most important use cases in healthcare interoperability. Health IT solutions will be most effective if they can be delivered to clinicians (who are using the EHR) right at the point of care. Interoperability can avoid the need for a clinician to work with diverse interfaces to obtain the data they need.

According to health IT experts, doctors are far more likely to modify their treatment protocols if they are provided with relevant substantiating data right at the point of care (as against receiving the same data in a process improvement group meet).

4. Bringing More Uniformity in State Privacy Laws

The process of healthcare interoperability can go to the next level if there is more harmony between the rules and regulations related to healthcare data privacy. To achieve nationwide interoperability for the best possible patient care, providers in one state should be in a position to exchange vital health information with providers in another state.

In the absence of such uniformity of laws, one hurdle is that providers in an “opt-in” state could be reluctant to exchange health data with the providers in an “opt-out” state (in absence of an assurance that the patients have given their explicit consent for data sharing). The complexities further increase in the case of mental health patients or for more sensitive patient data such as HIV status. The risk of an inadvertent violation of privacy laws is higher in such cases. Although this abundant caution may be appreciable, it can hinder healthcare data interoperability, making it harder for providers to leverage the benefits of health data exchange to deliver better care.

5. Augmenting Patient Matching Capabilities

Healthcare interoperability gets further complicated if the patient matching technologies are not up to the mark. With unreliable patient matching systems, even if the healthcare providers manage to streamline other issues, they would still fall short of their objectives if the data is not attributed to the appropriate patients on the other side.

In addition to building advanced and reliable patient matching technologies, a national patient identifier system could be a game-changer in this area.  AHIMA notes that achieving patient matching capabilities can help to improve the quality patient care, yet acknowledges that roadblocks to effective patient matching exist. One study also revealed that half of health IT managers routinely sort out duplicate patient records, and 72 percent do so on a weekly basis, which increases the costs. Small and mid-sized medical practices can cut down their costs of maintaining and managing patient records with a robust system for healthcare interoperability.

Interoperability is not a goal, but a journey that requires a collaborative environment around healthcare technology infrastructure, data standards, and permissions, among other things. To simplify healthcare data exchange, health IT vendors and providers should work closely with support from governmental agencies to make continual progress on this path to true interoperability.

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