Unlocking siloed data and other takeaways from HIMSS 2023

Last week we had the privilege of joining thousands of other industry innovators in Chicago for the annual HIMSS conference. We presented live demonstrations highlighting interoperability use cases and thought leadership on data wealth management solutions, and how FHIR and patient-mediated data can elevate research and public health initiatives.

We heard from research experts about the expansion and evolution of decentralized clinical trials and from machine learning experts about the continued discovery of AI’s role in healthcare technology and patient care. Some of the most exciting conversations included the future of healthcare data interoperability, the potential for making data more accessible to patients, and unlocking a deeper and broader set of insights for providers and innovators.

Below are some of our takeaways from an engaging week at HIMSS.

General interoperability takeaways:

TEFCA and QHINs are coming. It’s going to make the data liquidity pipe bigger. Most companies are ill-prepared to make the data they have ‘usable’, and the increase in data liquidity will put more stress on data usability.
The government is doing its job to mandate the availability of data. Vendors are fulfilling that mandate. Now the challenge is to figure out how to use the data to improve care, which could save billions of dollars in unnecessary costs.
Patients are working to generate and manage their own health information. We need to work respectfully with them as willing participants. Making consolidated records usable has the potential to impact population level health.
“Patients don’t need to be able to read the complex codes and jargon in a medical record. We need to make it easy for patients to review, understand and share their data.” – Nilesh Shah, Clinical Team Lead Office of Connected Care, Patient Care Services, Veterans Health Administration
Data sharing is interoperability table stakes; the bigger win is helping patients receive the best care they need. It starts with trusted, accurate data.
The current demand for interoperability is largely based on individual business use cases. An expansion of interoperability throughout the healthcare system can create innovation in clinical services, administrative workflows, and population and public health. We are just scratching the surface of the opportunities before us.

Data Wealth Management with Benjamin Berk, MD MS&E

With increase in data accessibility, data enhancement is only becoming more critical. To get value out of the emerging wealth of healthcare data, we need to be able to convert and aggregate it to a common format. We must also standardize to reference codes and classify terminology so the data is useful for analytics and applications.
With the availability of APIs (Application Programming Interfaces), the decision of ‘build vs. buy’ is becoming a false dichotomy. We now have APIs enabling users to maintain transparency and control in the data pipeline, allowing them to benefit from the experience and expertise of those who build the functionality at scale.

The Expanding Role of FHIR and Patient-Mediated Data in Research and Public Health

Panel Discussion with Ballista Technology Group, Healthjump, and CareEvolution

The Cures Act of 2016 and Patient Access APIs has led to adoption of FHIR standards and consumer-controlled sharing of significant new sources of healthcare data (patient-mediated exchange), beyond claims and EHR, which is enhancing clinical and research use cases.
Availability does not guarantee reliability or useability:
1. The growing number of FHIR implementations has created wide variability in the completeness, quality, and consistency of coding, making it difficult to rely on FHIR data in its raw form.
2. Challenges around matching patients across sources, aggregating data from differing coding systems, or combining data from claims and clinical resources frequently delay projects and limit insights.
Organizations can overcome these challenges through data enhancements, including:
- Linking patient records across multiple FHIR sources to create a single lifetime patient record for each individual,
- Mapping data to reference terminologies and combining data sources,
  Aggregating data stored in claims and clinical FHIR resources to gain insights into both individual patients and populations
- Making this information digestible and easy for patients to understand by building consumer-friendly visualizations.
One standard does not fit all purposes; choosing the standard that best supports the use case is critical:
- FHIR is well-suited for sending data between applications but requires downstream transformations to extract insights.
- Transformation of FHIR to a tabular format such as OMOP may be useful to accelerate research using a data model and standard terminologies tailored to analytics as well as support for several off the shelf tools.
- HL7 and CCDA are still quite prevalent and may be the best way to access the broadest set of resources which can then be transformed and aggregated for analytics.