Three strategies for health data interoperability success

This year can and should be the year of health data interoperability. It has become an imperative for the effective and efficient delivery of high-quality healthcare.

Government and commercial health organizations realize that being data driven leads to better decisions and more impactful outcomes. It is critical for quality care, and is directly dependent on the interoperability of health data.

While many healthcare organizations are committed to improving interoperability, progress has often stalled for a variety of reasons. For example, although standards adoption by electronic medical records systems vendors is rising, many systems remain difficult to interoperate. There’s also a need for greater interoperability of privacy and data protection frameworks. 

The stakes are high for healthcare data

These reasons pale in comparison, however, when the effectiveness of treatment in critical situations is paramount to sustainment and quality of life. Healthcare organizations don’t exist to pick market winners or inhibit healthcare delivery. Rather, their objective is to keep people healthy and provide high-quality care.

To fulfill this mission and meet emerging public health-related challenges, healthcare organizations need to prioritize data modernization focused on combining data from multiple sources in a standardized, secure and streamlined fashion. They also need new types of solutions and analytical capabilities so they can swiftly access, interconnect and analyze varied health data sources.

Achieving these objectives requires interoperability to enable data-driven solutions and provide the ability to assemble and analyze vast quantities of data and share it with multiple parties securely. A wide-ranging communications protocol called Fast Healthcare Interoperability Resources (HL7® FHIR®)^[1] can make all of that possible. FHIR offers numerous benefits over existing standards and contains transport mechanisms, content standards and resources.

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Take the first steps to success

Although this undertaking may seem daunting, here are three strategic steps that will prepare your organization to move forward: 

1. Treat this effort as a wider customer experience (CX) strategy grounded in a set of human centered design (HCD) principles, intending to improve overall customer service. Ensure the strategy is integrated in an agile fashion with digital transformation and organizational change efforts. Measure improvements by channel and overall. The initiatives should contain updates to the operating model. Define business event processes that cover all lines of business within the operating model and include customer journeys within those business lines. Organize business events in a journey
   map format with input from the field employees and customers.
2. Take an enterprise-wide data view with a modernization perspective that includes data governance, an associated framework, enterprise data strategy, data policies and standards, and tactical initiatives aimed at removing barriers to data sharing in a streamlined, virtualized fashion. Formulate the framework as a set of maturity models and KPIs with the goal of improving data stewardship programs, data architecture, data standards and data quality. As always, data privacy and security are essential for trust in healthcare. Timely and secure access, integration and appropriate use of health data across the patient experience are keys to achieving coordinated and connected health.
3. Leverage intelligent automation capabilities to put in place state-of-the-art algorithms, tuned to the business domain, to offer tailored artificial intelligence/machine learning (AI/ML) solutions to transform business processes. A use-case based approach enables targeted application of advanced analytics, natural language processing, ML, robotic process automation and application programming interface (API) integration.  

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Embrace a holistic approach

Resist any suggestions that a bolt-on FHIR tool would add interoperability capability to the existing ecosystem. Delaying to undertake a holistic approach, that includes people, process and technology, will only make demographically driven challenges worse. 

For example, the baby-boomer generation’s growing use of healthcare is swelling the data load, and their demand for better, faster data-driven answers heightens the urgency for interoperability. At the same time, gen Z and millennial cohorts bring their ever-higher expectations for data accessibility and utility, few of which health organizations can meet without transformation. 

We typically see a fragmented approach when senior managers are reluctant to embrace a broader strategy. This leaves individual leaders addressing whatever limited interoperability aspects that they can control.

Fragmented approaches put more pressure on an already-strained environment, with many subtle touchpoints that create process confusion and defects that elude detection.

The antidote is a holistic approach that includes a coordinated change management effort, which:

• Allows organizations to address population health activities identified via surveys and trends
• Enables data availability for digital health-related activities
• Provides precision medicine activity support including tailored therapies, coordination of care across multiple teams, reduction of waste due to streamlining, and reduction of wait times
• Enables the adoption of an event-driven architecture that makes the organization more responsive

As you begin, it also is worth considering at a high level the technologies your interoperability project will entail, including API gateways, data governance platforms and analytics solution sets. 

Now is the time to recommit to a successful interoperability effort, designed to deliver an array of CX satisfaction, security, innovation and efficiency benefits. For more information on how you can help lead your organization’s successful healthcare data interoperability effort, contact me.

Learn more about how CGI is empowering healthcare organizations to optimize operations and improve patient outcomes through the responsible use of AI 

^[1]HL7® FHIR is a standard for healthcare data exchange (https://www.hl7.org/fhir/index.html), published by HL7. HL7 is the not-for-profit, ANSI-accredited standards-developing organization dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing and retrieval of electronic health information that supports clinical practice and the management, delivery and evaluation of health services.