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Empowering FHIR

Fast Healthcare Interoperability Resources (FHIR®) is celebrating 10 years of development and use. This is partially due to the people at the non-profit Health Level Seven International (HL7®), who created an incredible tool for interoperability by applying lessons learned from earlier efforts and successfully convening broad stakeholder participation. In terms of healthcare data standards, FHIR is still the relatively new kid on the block. 

Before FHIR, organizations found it notoriously difficult and brittle to achieve interoperability because proprietary systems across multiple vendor organizations stored healthcare data and effectively locked it behind those systems. Therefore, achieving interoperability was notoriously difficult and brittle. Fast forward to today, and FHIR has enjoyed a widespread adoption from a global community of health leaders, as well as recent requirements of the Centers for Medicare & Medicaid Services (CMS) and the Office of the National Coordinator for Health Information Technology (ONC). 

Why is data interoperability needed in healthcare?

A short answer would be to empower patients, increase the quality of care, and reduce information silos. But it would be helpful to step back and consider some drivers propelling us forward.  

Thanks to sources like electronic health records (EHR), personal fitness applications, and home test kits, the growth rate of health-related data is growing substantially faster than other industries. Researchers estimate approximately 30% of the world’s data volume is generated by the healthcare industry.However, as data about our health piles up—the healthcare industry and patients should collectively understand a lot more than we used to about the human body, disease, and health outcomes. But having a lot of data is not enough.  

Patients, providers, and payers must be aware of the quality of data they have access to. Beyond that, they must also understand what it means, and act on that understanding. While challenges are more acute in the United States because of its fragmented system of care, they exist globally. According to a report conducted by the Commonwealth Fund, the U.S. has the lowest life expectancy at birth, the highest death rates for avoidable or treatable conditions, and the highest rate of people with multiple chronic conditions.2

The healthcare system will continue to face challenges as more people with chronic diseases age into Medicare every year. Currently, an estimated 61.5 million people living in the United Stats are enrolled in Medicare3. 86% of them have one or more chronic conditions.4 

This number will continue on an upward trajectory with two-thirds of the world’s population expected to be over the age of 60 by 2050.

The growing complexity of providing comprehensive care has been a driving force behind enhanced medical research and documentation. However, researchers found that practices that implemented EHRs saw an increase in stress.6 The cumbersome process of data entry, government regulations, and lack of autonomy, among other variables, have led to a rise in practitioner burnout. Today, research shows nearly two-thirds of healthcare professionals are experiencing at least one symptom of burnout.7  This will lead to an increase in demand while the industry is heading for a decrease in supply.  

There’s no doubt that patients will directly feel the impact. Caregivers and health plans will also feel the burden. Middle-aged adults will have no other choice but to step in and act as caregivers in increasing numbers. In fact, a study done by the Centers for Disease Control and Prevention (CDC) found that 22.3% of adults reported providing care for or assistance to a friend or family member in the past 30 days.Alongside the ability for health plans and providers to leverage clinical data as a strategic asset, providing patients and their loved ones with reliable healthcare data is becoming more and more critical for delivering quality care and improved outcomes. 

In this regard, health plans can play a significant role by developing a long-term data strategy centered around high-quality and interoperable clinical data assets, providing support for caregivers, and other non-traditional clinical data consumers. This includes family caregivers who may lack the medical expertise required to comprehend the intricate coding variations that constitute raw clinical data assets from EHRs. Non-traditional clinical data consumers will need reliable and comprehensive data, including reference ranges and meaningful descriptions, with the help of technology. 

Although current technology-based solutions to improve data quality and interoperability may not prioritize non-traditional clinical data consumer needs at the moment, it’s essential to pivot towards a consumer-focused approach for the future. AI can play a critical role in this convergence of supply (access to high-quality FHIR data) and demand (the shift of daily care responsibilities away from medical professionals). While AI will never replace human medical professionals, it can assist non-medical professionals in managing care between medical encounters. By creating a comprehensive data strategy that prioritizes data quality and interoperability, healthcare organizations can lay the groundwork for success. To learn how clinical data can be a powerful, strategic asset, download Availity’s 2023 Clinical Data Integration Buyer’s Guide.

Why does data quality matter for FHIR?

FHIR combines three powerful concepts: small document/resource size, a query-able API, and extensibility. Together, these aspects aim to revolutionize how people in all roles interact with healthcare data.

However, healthcare data is uniquely complex. This ranges from administrative data, such as claims, to clinical data, which includes patient charts documented in EHRs. While FHIR covers all facets of data, clinical data is arguably the most important. This is because it contains rich information about an individual’s health journey and includes precise indicators that are not always present in other data sources. 

Clinical data, in raw form, often contains inconsistent or missing codes and duplicate entries. This is due to the lack of standardization caused by non-conformant codes, redundancies, and other systemic data quality issues. Data quality issues in this area will only grow more complex.

There is significant variability in how EHRs code and represent values with the lack of data standardization. This can lead to essential data being either incomplete or absent. 

Furthermore, most EHRs assume the consumer of the data is a medical professional who understands jargon and can fill in the gaps. Unfortunately, this assumption is not true for EHR users that increasingly include administrative staff, patients, and even computers/AI.  

Healthcare institutions also have their own unique way of documenting patient information. For example, one clinician might document a flu shot in the EHR’s procedures section while another might use a narrative note. This lack of standardization can lead to gaps in care and decision making based on fragmented information. Other factors, like licensing code systems and the need for abbreviations, sometimes conflict across specialties. The result is that there is little conformity in clinical data. 

Certainly, FHIR addresses all these problems, right? Well, it does move the bar significantly by providing standard structure and requiring consistency in terminology via code systems in specific places. However, if the original data was coded in the EHR in another code system, then there needs to be logic to crosswalk to the one specified by FHIR. But what if there is no code, only a description? If the original data was recorded in a nonstandard way, the resulting FHIR data is often flawed. This lack of standardization makes it difficult for public health departments, for example, to determine appropriate responses. For example, there are wide discrepancies in both the code and descriptions of COVID-19 test results. So, if a developer writes an app that pulls FHIR data to check for COVID-19 care recommendations, their app could populate erroneous information.

Example of the wide variation in test data from labs 

There are over 40 ways that a negative COVID-19 result is coded within these tests, not to mention the hundreds of ways the test itself is coded. 

Example of coding variation across multiple EHRs 

Below is an example of the wide variation in how a hemoglobin A1c (HbA1c) test might be documented. For analytics, this data should map to a single LOINC code (LOINC 4548-4) and description. 

FHIR Alone is Not Enough

FHIR addresses some of these issues by sharing data in a standard structure, but it does not address how systems represent and interpret the meaning of data within a given context. Fixing the semantics is key to making it actionable. Many of the remaining problems can be solved by applying some simple rules to the data. When codes are available but semantically incorrect, these rules can crosswalk the codes from one coding system to another. They can also use text descriptions to look up codes. For example, a “systolic blood pressure” description maps easily to a code and even implies the units of measure.

At the same time, you can tag the data with meaningful metadata that helps improve its usability. For example, suppose you label all opioids as such during this process. In that case, downstream systems can consistently and accurately report on Morphine Milligram Equivalence (MME) or similar drug classes or even broader clinically relevant contextual knowledge. You can apply other rules to the data to reorganize it by intent. For example, finding future-dated procedures and moving them to a plan of care. You can also fix duplicated data. It requires certain complex logic, often supported by the metadata found earlier. For example, metadata about the classification of a condition can be used to understand its chronic nature.

At Availity, we coined the phrase Upcycling Data™ to refer to our automated API, and cloud-based solution for generating high-quality, interoperable data assets.  

How Upcycled Data and Clinical Data Repositories Help

Availity’s automated data transformation engine, Availity Fusion, produces Upcycled Data. It normalizes to national standards, deduplicates, consolidates into a longitudinal health record, and packages for flexible deployment at scale. It can process an average-sized continuity of care document (CCD) in less than a second. Someone converts that data to high-quality FHIR data, which powers multiple downstream systems. You only need to do this work once. It can then be stored in a clinical data repository (CDR), forming the basis of a high-quality longitudinal health record. Even in situations where different display output is required, you can standardize the data semantically in the CDR, or upcycle it, ensuring that downstream display logic can rely on consistent representations. This dramatically reduces the complexity of the translation process. 

That’s where Smile Digital Health comes in. FHIR sets standards and definitions for data structure, data access, identity management, tracking updates, and more. Smile Digital Health holds recognition worldwide as the preeminent FHIR server. As the reference implementation of FHIR in Java, Smile Digital Health provides the most robust implementation of the FHIR specifications. 

Smile Digital Health’s platform recognizes all the benefits of FHIR alongside myriad of industry-leading data-sharing features such as a FHIR Gateway, MDM, security and consent management, federated IAM, etc., in a single solution. In coordination, these features underpin a Health Data Fabric. The combination of quality Upcycled Data in a Health Data Fabric empowers health enterprises to provide genuine coordinated care. Equally exciting is the ability to focus on modernizing healthcare and innovation to recognize true business value. On the other hand, if the first uses of FHIR rely on sub-par data, there is a chance of failure. This is not because FHIR is flawed but because the data quality, comprehensiveness, and access methods have issues.

The story will be completely different with Upcycled Data and a best-of-breed. The most meaningful data can be made available at scale. The positive outcomes are too numerous to count. They will help FHIR become the foundation of a modernized, future-oriented health system. FHIR, in conjunction with the Patient Access API, is a game changer. The data is now available through public endpoints in an open, structured, and normalized format. Leading FHIR vendors such as Smile Digital Health are CMS and ONC compliant, in addition to providing: 

  • Multiple security layers and subscriptions in an Event Driven Architecture. 
  • Provenance, FHIR operations, CQL, support for automatically loading and validating against unlimited Implementation Guides (IGs).

Effectively providing futureproofing against forthcoming Da Vinci IGs and CMS and ONC mandates, SMART on FHIR support, real-world high performance at web scale, as well as a host of other benefits collectively allow for the enterprise to transition to rapid interoperability with ad hoc connectivity to other certified FHIR systems. For Smile Digital Health customers, this translates to increasingly lower-cost implementations and maintenance, faster go-lives, and ROI recognition. 

Conclusion

As we see in many other industries, sharing data through open standards and APIs unlocks innovation. Activities that we can only dream of today become the reality of tomorrow. With FHIR, healthcare is truly on the eve of tomorrow. Rapid and increasingly seamless interoperability has only as much value as the quality of the data. Ultimately, the success of FHIR will depend on how effortlessly networks can exchange data. The best implementations of FHIR will mean nothing if plagued by data interoperability issues.

Bringing high-quality, Upcycled Data together with a best-of-breed CDR such as Smile Digital Health’s open-standards FHIR platform will enable users to enjoy a single architecture that optimizes the value of their data assets – interconnected within the ecosystem of their peers. This can be game-changing and opens the possibility of truly addressing the challenges for healthcare. Reliable data quality in healthcare is good for one and all. How will your organization adapt and recognize the transformative value of this new reality? 

References

“Healthcare’s Data Tsunami.” Brunswickhttps://www.brunswickgroup.com/healthcare-data-i20729/#:~:text=As%20a%20result%2C%20approximately%2030,health%20data%20will%20be%2036%25.&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;/p&amp;amp;amp;gt;&amp;amp;lt;/p&amp;amp;gt;&amp;lt;/p&amp;gt;&lt;/p&gt;</p>

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