Healthcare AI is a trending topic. Have you ever tried to retrieve your medical records? Between the HIPAA release forms, wait times, forgotten requests and antiquated transfer methods, it is nearly impossible. There’s no uniform system for medical providers to share information. Insurance plans struggle to obtain clinical data from providers, providers struggle to access plans’ member claims dataand healthcare vendors struggle to access data from both sides, even when an agreement has been reached, due to technological obstacles.
With CMS’s big push around electronic health record (EHR) interoperability in 2010 as part of its Meaningful Use rule, industry experts predicted a paradigm shift. However, because Meaningful Use didn’t provide incentives around data sharing or clear standards, the companies designing and implementing the new systems had no reason to make their platforms more user-friendly. The new rules should’ve set the stage for longitudinal healthcare records that can exist across ecosystems. Instead plans and providers are generating a ton of isolatedelectronic healthcare data – more than 1.2 billion clinical documents in the US each and every year.
Now imagine you’re trying to take population health information and use it to solve healthcare’s biggest problems. Data scientists want access to this information in order to build artificial intelligence (AI) tools to improve healthcare outcomes and determine the best treatment options for people facing healthcare challenges.
Why Didn’t Digital Transformation Help?
Who wouldn’t want easier access to more data to improve patient care and business operations? Before cloud-based systems gained widespread adoption, healthcare information was stored in on-premises, siloed repositories that could only be accessed by people within the organization. Doctors’ offices had walls of file folders. This reinforced the behavior that patient or member data housed by a healthcare entity is “owned” by that entity—and that the “owner” therefore controls who can access that data. Additionally, given the ambiguous HIPAA guidelines around patient privacy and security, healthcare organizations feared legal repercussions for granting access to the information.
EHRs were supposed to change this siloed approach to data storage and patient data. This means we still have a problem accessing data —but instead of physical filing cabinets or servers, we have localized digital systems that don’t integrate with other platforms and are difficult to access.
The Government Attempt to Encourage Interoperability
In 2019, two government healthcare agencies,CMS and OHS, proposed regulations that are putting increasing pressure on healthcare technology vendors, payers and providers to move toward interoperability.A variety of proposals have been made to promote interoperability, with varying levels of technical specificity around implementation and penalties for perpetuating the status quo.
CMS’s Interoperability and Patient Access Proposed Rule
This proposed rule, put forth by the Center for Medicare and Medicaid Services (CMS) in February 2019, promotes data sharing between healthcare entities and with patients. Here are the key components of the proposed rule:
- MyEHealthDataInitiative / Blue Button 2.0 API: Makes patient claims data available via consumer apps using HL7/FHIR. Implementation is already happening for Medicare fee-for-service claims; this rule would extend the work to Medicare Advantage, Medicaid and CHIP data in the future.
- Health Information Exchange and Care Coordination Across Payers: Requires participation in a data exchange network for payers across all government plans (Medicare/MA/Medicaid/CHIP/QHPs).
- API Access to Published Provider Directory Data: Requires all Medicare, MA, CHIP and Medicaid payers to share their provider directory data publicly via an API.
- Trusted Exchange Network: Requires all payers in CMS programs to share data through a trusted exchange network so information can flow securely and privately between plans and providers throughout the healthcare system.
This proposed rule, put forth by the Office of the National Coordinator for Health Information Technology (ONC), implements certain aspects of the 21st Century C**** Act and introduces new requirements to promote seamless and secure access, exchange and use of electronic health information (EHI). A few of the key provisions of this proposed rule include:
- Information Blocking: Mandates secure data sharing between covered entities (payers, providersand vendors) for all reasonable and necessary healthcare activities. Organizations who continue to block information will be subject to $1 million fines or more.
- Adoption of the United States Core Data for Interoperability (USCDI) Standard: Establishes a set of data classes and constituent data elements that would be required to be exchanged in support of interoperability nationwide.
- EHI Export: Enables the export of EHI for a single patient upon request and supports the export of EHI when a health care provider chooses to transition or migrate information to another health IT system.
- APIs: New HL7 and FHIR API requirements are designed to support services that give access to data for individual patients and multiple patients.
These technical parameters would help to open up medical records to more integration, making research and healthcare ecosystem cooperation more plausible. Even still, there’s debate around implementation timelines and requirements. The original dream of interoperability is still alive, but more rule reform would be needed to open up anonymized data for AI advancements.
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Interoperability Benefits for Healthcare AI
Increased interoperability has the potential to benefit any organization using AI techniques to analyze data at scale, but more cooperation is needed to realize the full potential of AI techniques. In order to be successful, AI techniques need billions and billions of data points. To glean population-level healthcare treatment insights, researchers need representative samples of patient treatments and outcomes. This requires more healthcare record sharing.
New APIs and exchange networks will make it easier for approved healthcare entities to access data from other organizations within the industry. Standardized data classes and elements will simplify the process of cleaning, labeling and running models on existing healthcare datasets, allowing AI models to be deployed faster.
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Paired with regulatory changes around data use, governance, privacy and security to ensure organizations can use all this newly-accessible data in the appropriate ways, and advancements in AI, a new frontier of medical knowledge is on the horizon. The next few years of interoperability improvements will be pivotal in paving the way for AI advancement and adoption, which opens the door to improve patient outcomes and solve for some of our greatest healthcare challenges.
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