Industry reports show that 59% to 78% of physician practices are using an electronic health record (EHR) in 2016.1,2 Despite this widespread adoption, health IT is just beginning to connect the 400+ different EHR systems to help address the need for better informed patient care. With insurers, government entities and new legislation, such as the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA), calling for more transparency regarding the cost and quality of care, the focus has shifted from looking at the relatively simple metric of EHR adoption to the more complex measurement of the degree to which EHR systems can share health information in a meaningful way through interoperability.
The most exciting part of advancing interoperability is that health data no longer will be siloed in practices and hospitals, but instead will become available to help inform value-based care delivery, help improve patient outcomes, and help provide doctors with insights that support clinical decision making. For example, with interoperable systems, providers can access salient health information about their patients outside of his or her practice’s own clinical record. If a patient was recently hospitalized, the provider seeing that patient will have access to the health information from that visit, including diagnoses, prescribed medications, tests and results, and appropriate follow up as part of that patient’s care plan.
Although there is agreement that the free flow of clinical information between systems is essential, the steps needed to bring this vision to fruition and measure its success are still being debated. Many believe that the problem is that disparate systems are not interoperable or are not interoperable enough. This narrow view overlooks the more immediate issue of not having industry and regulatory alignment on the definition of interoperability and how to measure its progress. To move interoperability forward, health IT organizations and regulatory bodies need to align on three things:
- How do we objectively define interoperability?
- What lessons can we take from how we currently define and measure interoperability?
- Given what we have learned, how can we measure meaningful interoperability as we look to the future?
Defining interoperability
The way technology is defined matters. For example, “interoperability” and “health information exchange (HIE)” are terms that often are used interchangeably. However, they are not the same thing. HIEs are a prerequisite for interoperability and constitute a vital part of modernizing our healthcare system, but they do not define interoperability.3
It is easy for disconnects to happen when discussing interoperability because there is no alignment on a universal definition. According to MACRA, interoperability is defined as “the ability for two or more disparate health technologies to exchange clinical information and to use that information under a standard set of guidelines to coordinate patient care, ultimately improving patient outcomes.”4
Under this definition, interoperability has two components:
- The exchange of information between two or more systems.
- The ability of those systems to use the information exchanged to improve the coordination of patient care.
This is meaningful to the health IT industry because it defines interoperability without getting lost in the concepts of standardization, integration cooperation, and technical specifications. The value of having an objective, consensus definition cannot be overemphasized, as it gives health IT professionals a tangible goal to achieve and a way to evaluate current and future states of interoperability. However, the definition under MACRA falls short of encompassing all that interoperability is and what we truly want it to be — it will need to continue to evolve symbiotically with technology and with learnings from use cases.
Key takeaways on how we measure interoperability now
Standards are key to achieving shared interoperability goals. Today there are multiple standards development organizations (SDOs) such as HL7, ASTM, and others working to develop universal standards needed to support health IT interoperability. As outlined by the EHR Association (EHRA), through the combined efforts of SDOs and other working groups, the EHRA has established:5
- Data and terminology standards that allow concepts to be expressed in a common language. For example, assigning codes to particular medications so that they can be consistently referenced and understood across systems. Terminology standards in common use include SNOMED (conditions), LOINC (results), DICOM (imaging), and RxNorm (medications).
- Content standards that package information for consistent consumption so that it is machine readable. Common standards include HL7 V2, CCDA, QRDA, FHIR, X12 5010, and NCPDP Script.
- Data transport standards that include Direct, IHE XDR/XDS/XCA, and RESTful services.
- Governance and policy standards that provide a model for which two organizations agree to exchange data.
These have helped EHR systems undergo rapid standardization, primarily through their inclusion in Meaningful Use (MU) Stage 2 certification, which defined a common data set for all summary of care records. Sharing this data is mandated for providers participating in MU and other quality reporting programs and include patient names and demographic information, vital signs, encounter diagnoses and immunizations.6
As a result, we measure interoperability today in terms of volume of these types of data being exchanged between systems.
What we have learned is that this way of measuring places the burden of advancing interoperability squarely on the shoulders of providers. It is a draconian approach that mandates what doctors must do to meet arbitrary reporting requirements instead of enabling them to do the necessary things that will better inform their clinical decision making. For example, providers must check boxes such as race or smoking status, regardless of whether it is relevant to the patient’s visit, or risk a negative adjustment on their Medicare Part B payments. Additionally, they are required to share educational materials electronically with their patients, even if it is not the optimal or preferred method for patients to receive those materials.
The way we currently measure interoperability is not sustainable over the long term for providers, especially those in small private practices. Practices already spend $40,000 per doctor per year—$15.4 billion nationwide— on collecting and reporting quality measures to Medicare, payers and others.7 The inclusion of interoperability measures as part of providers’ reporting requirements, particularly on datasets of limited clinical relevance, only increases the burden and costs for these providers in delivering care to their patients.
This is the paradox of 21st century medicine: Despite having more data to help providers gain insights to better inform their patient care, the quality of the care experience has actually decreased because of the administrative burdens placed on providers and the resulting erosion of the provider-patient relationship.
Practicing medicine is both a science and an art, recognizing that each patient is an individual requiring personalized care. When providers must spend more time looking at a screen than speaking with their patients, this relationship is seriously impacted. The most important lesson learned is that the way we measure interoperability has a direct impact on the health of human relationships at the point of care.
How we can meaningfully measure interoperability in the future
In the near term, we should recognize that interoperability is already happening and should continue to measure its progress by leveraging present MU metrics and other reporting requirements grounded in quality programs. While these may not be ideal, they have the advantage of being established measurements that will not introduce additional reporting requirements for providers.
Of course, there are many domains of interoperability outside the scope of quality reporting that could be used in the near-term and that do not generally increase the burdens on providers, including:8
- sending e-prescriptions,
- incoming lab and imaging results,
- sending to immunization registries,
- sending reportable labs to public health, and
- reporting syndromic surveillance data to public health agencies.
A critical, but less tangible, measure of interoperability is how much time a provider can save in finding salient health information from across disparate health systems that they then can use to better inform their clinical decision-making. If we are increasing the amount of time a provider is spending in front of a screen instead of with his or her patient, we are heading in the wrong direction.
Ultimately, the way we measure interoperability determines what it becomes. Looking ahead, rather than trying to develop measures for the many ways interoperability can occur, it is more beneficial to understand the clinical and business needs driving interoperability. This will allow us to better understand how interoperability can help improve the care delivery process and ultimately, help achieve better patient outcomes.
References
- SK&A, Physician Office Usage of Electronic Healthcare Records Software, February 2016.
- HIMSS, 2016 HIMSS Analytics Outpatient EHR Study, July 2016.
- HealthITBuzz, Interoperability vs. Health Information Exchange: Setting the Record Straight, January 2016.
- HealthIT Interoperability, ONC Issues RFI on Defining Interoperability Under MACRA, April 2016.
- HIMMS, Interoperability FAQs (July 2017).
- HealthITBuzz, Meaningful Use Stage 2: A Giant Leap in Data Exchange, August 2012.
- Medscape, Quality Reporting Costs $40,000 per Physician per Year, March 2016.
- EHRA, Attention: RFI Regarding Assessing Interoperability for MACRA, June 2016.