EHRs are the systems of record for the United States healthcare system and, increasingly, the entire world. In the United States, close to 100% of physician practices use EHRs. The adoption of EHRs has spiked significantly over in the last 10 years due to federal incentives called Meaningful Use that were a part of the HITECH Act.
The problem facing healthcare transformers today is that EHRs were built for the current episodic healthcare system, not the rapidly emerging future continuous healthcare system. Transformation in healthcare is slow due to a multitude of reasons, but EHR data integration, EHR interoperability, and open data standards is a few of those reasons.
Healthcare is changing rapidly
However, transformation is happening, and it is being driven by the demands of patients and clinicians in the form of digital health. As the healthcare industry finds itself constrained by legacy software built for pay-for-service models, it looks to shifting certain clinical workflows outside the EHR in order to appease newer value-based care models. An explosion of digital health products outside the EHR has subsequently filled the void.
Market data has proven the case over the last several years. According to a research study from firm Rockhealth, 2018 venture investment in digital health is set to approach $7 billion, compared to $1.2 billion in 2011. Almost every conceivable corner of the care continuum has had entrepreneurs and intrapreneurs attempt to bring innovation and change: telehealth, care coordination, secure messaging, genetics, diagnostics, scheduling, supply chain, bundled payments, durable medical equipment, physical therapy, clinician note dictation, benefit management, clinical trials, medical adherence, and dozens more categories.
The monolithic EHRs of today are being unbundled by focused companies that have built modern digital health applications founded on the cloud; we are moving from one company, the EHR, delivering everything in an episodic, fee-for-service world to a pay-for-quality world with best-of-breed digital health products. Those digital health applications are built to transform an isolated problem and optimize the patient and provider experience to the standards all patients and clinicians expected in today’s digital world. This unbundling of the EHR is a painful process as EHRs battle to maintain their stronghold on the enterprise but are not well suited to be data platforms for modern applications.
More than ever, data matters, and those new digital health products are too often locked out of adoption due to poor data interoperability with EHRs.
In order for regulated organizations like health systems to take advantage of the cloud, they must adopt new digital products whose data is being stored, computed, and transmitted outside the on-premises legacy software, like the EHR. Existing market conditions combined with legacy technology debt is forcing a strategy dilemma and compliance crisis that must be solved: adopt new products and manage more risk, or maintain the status quo and fall further behind?
The future is data-driven healthcare
Healthcare data today predominantly resides in EHRs and is considered clinical data. That data is used for direct clinical decision making, oftentimes manually by providers, and for billing for episodic care. This model of data use and storage is not compatible with a future based on quality, continuous care, precision medicine, and new partnerships. The future of healthcare requires informed decisions not just on clinical care and billing, but on risk and prevention.
The future is data driven healthcare. The data used to drive care will come from multiple sources — 1) clinical (EHRs), 2) IoT, 3) genomics, and 4) images. Combining this data, and indexing the data on individuals, is the key to machine learning, which is a generic and more broad term for precision medicine. It is the key to answering new questions, developing new drugs, and enabling new partnerships across the spectrum of healthcare.
Data driven healthcare is a far reach from where we are today with data in silos and best case data usage based on historical, not real-time, data and targeted at populations, not individuals. The chasm between today’s episodic, non-integrated healthcare and data driven healthcare needs a bridge; there is not going to be magical leap from one side to another or a day when things change in an instant. That bridge is why interoperability matters today.
Don’t let the last mile be your weakest link
Interoperable infrastructure is a prerequisite for interoperable data. This matters because locked-up data is increasingly useless. One way to interpret healthcare’s terrible interoperability record is by examining how woefully behind the industry is with API-driven and microservices-based cloud architectures.
Now, the compliance of data integration on the cloud is more complicated than on-premises integrations because, by nature, the data is flowing in and across shared resources and networks. The increase of integrations inherently increases compliance breadth as well.
Considering the additional risk of data access, mitigating that risk cannot be accomplished without proper security. Also, the fragmented nature of digital applications and the lack of standardization on cloud and data platforms means that no decent market solutions exist to solve the problem. Successful strategies require flexible data integration tools that support different forms of data access.