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What We Were Thinking- 5 Bold Statements on Clinical Interoperability circa 2019

12/31/2019

It’s the time of year when we look back and reflect and make our predictions for the new year. In that spirit, we reviewed the articles our team wrote or contributed to over the past year to see what themes emerged and predict what we’d still be talking about in the year ahead.

5 bold statements emerged on the state of clinical data interoperability circa 2019. Our prediction? These will continue to be significant issues driving our work as a company as well as the industry at large.

Note: In this review we focus on contributions from our chief strategy officer and co-founder John D’Amore. John is our resident rock star when it comes to clinical data issues and how to address them. Ask him a question about clinical data quality, documentation standards, semantic interoperability, or federal regulations and he’ll likely have a very informed answer. He may even have “written the book” about it! (John is an editor on the HL7 C-CDA standard and has authored many peer reviewed studies on clinical data quality).

Here’s the lineup.

In January 2019, John wrote “Measuring the Promises of Interoperability” for Inside Digital Health. In that article he referenced research conducted in collaboration with the Department of Veterans Affairs and others (which received AMIA’s most distinguished paper award) that evaluated conformance and data quality from 52 EHRs. Here’s the first bold statement that emerged from that article.

#1 CLINICAL INFORMATION WILL CONTINUE TO BE DOCUMENTED WITH MASSIVE VARIATION.

“One of the most intriguing things revealed in the research is the massive variation among different EHRs displaying the same medical data. The C-CDA standard focuses primarily on machine-readable content, leaving the rendering of human-readable tables and lists up to individual EHR developers… As one example, 38 EHRs display the same three medications in radically different ways.”

In the same article he suggests a solution to deal with this systemic variation, generating the second bold statement:

#2 HEALTHCARE NEEDS A MIDDLE TIER ECOSYSTEM TO NORMALIZE MEDICAL DATA AND DELIVER SEMANTIC INTEROPERABILITY.

“Healthcare needs a second-tier ecosystem to normalize medical data,” he wrote. “This is like Google, which organizes the heterogenous ways content exists on the internet to make it searchable. In fact, Eric Schmidt said as much during his HIMSS 2018 keynote. This middle tier will deliver semantic interoperability and unlock digital uses we cannot even fathom today.”

Given that Google sources data from the public internet, and clinical data must be sourced from thousands of regulated EHRs and other clinical systems of record, functional interoperability in healthcare will require a new approach.

When HealthcareNOW Radio interviewed  John in March at HIMSS19 as part of their Highlights series, he shared his observations on two themes: why longitudinal patient data is the most valid for quality measurement and how clinical data is of increasing value to health plans. So, here are bold statements #3 and #4.

#3  QUALITY METRICS BEST REFLECT QUALITY OF CARE WHEN CALCULATED USING LONGITUDINAL PATIENT DATA.

Quality measurement doesn’t always reflect the quality of care a patient has received when it relies on data documented in a single EHR and from a single provider, he explained in the interview. “One of the exciting new use cases is the increasing use of clinical data for quality measurement, especially longitudinal data collected for the same patient who might have visited multiple providers, one that had Epic, another that had Cerner and another that had eClinicalworks or athenahealth. We are working with a number of qualified clinical data registries that collect data longitudinally and calculate quality measures, whether that be compliance for glucose control for diabetics, or blood pressure control for hypertensives.”

We hope to see this approach to quality measurement adopted to close the gap between quality metrics and quality of care, and mitigate concern that measurement is simply a reporting burden with little benefit. So, we will continue to advocate for this in 2020.

#4  PAYERS ARE GROWING MORE INTERESTED IN CLINICAL DATA TO HELP MANAGE MEMBER HEALTH.

Payers are seeing the value of clinical data for care management, he explained. “Another powerful use case is the increase in sharing data between payers, providers and HIEs. Now that most EHRs have implemented Meaningful Use Stage 3 we are seeing increasing use of clinical data by payers to calculate care gaps so members missing a colonoscopy or mammogram can be reminded to get tested.”

The healthcare insurance industry is morphing from simply paying for care to actively engaging with members and providers to improve member health. Access to clean, timely clinical data provides the foundation supporting this change. You’ll hear more from us about this and see the industry move towards more collaboration, we predict.

In November, John wrote Why 2020 Will (Continue to Be) the Year of Interoperability in Healthcare Business Today. This gets us to #5:

#5  FHIR WILL MAKE CLINICAL INFORMATION MORE AVAILABLE, BUT NOT NECESSARILY MORE USABLE.

Adoption of FHIR will be a great leap forward but will not be the panacea some believe. Quoting from the authors of a Deloitte Insights survey, John noted that “FHIR is only one piece of the interoperability solution….” He explained that “when information is returned as a result of a FHIR API request to an EHR, it’s not necessarily going to return data that can be immediately usable for the receiving software program. Each data source will speak different languages, or at least different dialects, for the foreseeable future. To stretch the language analogy: FHIR will make it possible to hear more of the people around you, but you won’t get a simultaneous translation to understand what’s being said.”

Our prediction for 2020? You’ll hear a lot more about this issue in the year to come as FHIR-based exchange becomes a reality.

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