Care Coordination, Data Integration, Value-based Care

How data can be used to improve care delivery

From meaningful use to meaningful data integration

Randy Coughlan, MBA, Director of Population Health

Have you ever wondered why you can go to just about any ATM in the country and withdraw money from your bank account, but you can’t easily access your medical history when you see a doctor outside your health system? There have even been stories of people who have gone to a specialist that is located across the street from their primary care doctor, but the specialist can’t access the patient’s medical records because the doctors use different electronical medical record (EMR) systems. In this day of technological advances, it’s incredibly frustrating that some of the most commonly used tools for transmitting medical records are CD-ROMs and fax machines.

It's complicated...

As is often the case in healthcare, “it’s complicated” is a common justification for the status quo. While this is undoubtedly true, most would agree that it shouldn’t be so difficult for patients to access and share their medical information. Of course, the right policies and protections must be in place to ensure medical information is used in a HIPAA-compliant manner, but this should not serve as an excuse for preventing the flow of important data.

While empowering patients to have more control over their medical information is incredibly important, and this is where the industry is heading, we should also expect provider organizations to use this information for the patient’s benefit. After all, what is the point of collecting all this information if it is not ultimately used to improve the patient experience and health outcomes?

Electronic medical records (EMRs)

The past two decades have seen virtually all providers move from paper records to electronic records; however, actually using this information effectively has proven much more challenging than initially expected. One of the main reasons for this is because EMR systems have not been able to easily “talk to each other”, resulting in massive data silos, both between and within organizations. If you can’t see the full picture of what’s going on, or it’s out of date by the time the data is pulled together, it significantly limits how effectively data can be used. 

Most advanced healthcare organizations are aggregating data from multiple sources so they have a full picture of healthcare needs at both the patient level as well as the population level – these data sources typically include medical and pharmacy claims, clinical (EMR) data and real-time ADT (admit, discharge, and transfer) feeds. This allows organizations to identify trends across populations (e.g., use of ER for problems that could be solved in an urgent care setting or through better engagement with their PCP), and then develop programs and outreach strategies to address them. In addition, having a comprehensive, up-to-date view of a patient’s situation enables interventions at the appropriate time to encourage the patient to get the right care at the right place. Equipping providers with this information at the point of care has the added benefit of reducing duplicative testing, which saves costs.

Provider incentives and value-based agreements

Another key factor explaining data integration challenges is the incentive structure. In a fee-for-service environment, there is not a strong incentive for provider organizations to dedicate the time and resources necessary to turning disparate data into actionable strategies and interventions that can reduce the cost of care or improve outcomes. This incentive misalignment has resulted in widespread adoption of EMRs so that providers could demonstrate “meaningful use” of this technology1 and receive incentive payments, but it has not resulted in widespread interoperability or data integration to improve care delivery.

To address these shortcomings, a new crop of regulations has been issued to spur information exchange between payers, providers and patients.2 In addition, other forces are converging to accelerate meaningful data integration in healthcare – namely, (1) the transition to value-based care, (2) technological advances to support data integration at scale, and (3) coalescence around new data exchange standards such as FHIR.

Under value-based care agreements, provider organizations are accountable for the quality and cost of care for a designated population. If they can implement data-driven strategies and interventions that improve quality and cost, they are able to share in these cost-savings. This better aligns incentives so that provider organizations can invest in the resources and tools required for data integration, which is a foundational capability for understanding the specific needs of and managing a population.

Data integration infrastructure

So, what are the resources and tools required for data integration? Because healthcare data is notoriously fragmented and messy, it has often required teams of clinical and IT experts to aggregate, normalize and cleanse data – and that’s before even figuring out what to do with it. Fortunately, after grappling with these challenges for many years, tech companies have been making progress in developing solutions to automate this work as much as possible. This means provider organizations can focus on doing what they do best – taking care of patients – while partnering with tech companies to integrate data so that it is comprehensive, understandable, and actionable.

This is not to say that it’s “quick and easy” today for provider organizations to leverage data in a meaningful way – it still requires significant time and effort. However, with the industry moving to common standards such as FHIR and data exchange methods such as application program interfaces (APIs), the hope is that this will allow data connections to be established in a faster way and at a lower cost. This should also make it easier for smaller provider organizations to “plug-in” and exchange data to better manage their patient populations. 

It’s an exciting time in healthcare – finally the technologies, stakeholders, and incentive structures are aligning to create new care models that can significantly improve the patient experience and reduce costs. Data will play a key role in this next evolution of healthcare, and those organizations that are able to effectively integrate and translate data into meaningful applications will lead the way.

1 - Public Health Data Interoperability. CDC.

2 - Policies and Technology for Interoperability and Burden Reduction. CMS.

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