< + > Why Public Health Data Needs to Modernize

The following is a guest article by Keith Boone, Standards Guru and Enterprise Architect at Audacious Inquiry, a PointClickCare Company

The complexity, volume, and interoperability requirements of healthcare data have grown so much over the past decade that they’re outstripping the capabilities of the legacy software systems that manage the information.

Public health agencies have done a remarkable job of operating and maintaining their current systems, some of which date back three decades, but the need to modernize becomes more apparent every day.

This is evident as the public sector lags private industry in its adoption of new data handling interfaces, specifically, the transition from HL7 V2 and CDA health data standards to FHIR (Fast Healthcare Interoperability Resources). Ironically, the push for FHIR is being driven by the public sector, namely, the Federal government, which is mandating the adoption of FHIR-based APIs for healthcare data exchange. Private healthcare organizations, including health plans, are also moving to FHIR.

The reasons for the transition are clear. FHIR is superior to HL7 V2 in multiple ways. The web-based FHIR offers standardized APIs, is easier to integrate with modern applications, including mobile and cloud-based apps, and overall is more flexible and adaptable to a fast-changing healthcare landscape. 

Continued reliance on legacy systems is problematic for a number of reasons. A lack of interoperability among systems can leave critical data in silos and unavailable. In the case of a public health emergency, this can cause delayed responses and an inability to accurately assess and address the crisis.

In addition, these legacy systems lack the sophisticated analytical capabilities required to advance public health initiatives such as population health, transitioning to value-based care, identifying health inequities, and addressing social determinants of health.

Then there is cost. Keeping decades-old, HL7 V2-based interfaces – operating and modifying them to do things they were never designed for – is expensive and requires constant attention from IT departments. At some point, it becomes untenable.

It’s clear that if healthcare is to achieve its interoperability goals, it must upgrade its technology.

However, public health agencies face several barriers to modernization, in addition to cost. Public health data is still being driven into HL7 V2 formats by legacy regulations and standards, even as the Centers for Disease Control and Prevention and the Assistant Secretary for Technology Policy push for FHIR.

Also, converting HL7 V2 and CDA to FHIR is neither simple nor easy. Integration and interface engines require complex and painstaking mapping from legacy to modern standards. Integrating via platform-as-a-service is difficult and costly. While federal funding sources for the work do exist, healthcare budgets are under stress, which makes it imperative that health agencies handle the modernization as efficiently as possible.

Agencies reluctant to abandon the reliable HL7 V2 standards can take comfort in the fact that it will take years to transition completely to FHIR, and both will be required for the foreseeable future.

Public health agencies don’t have to switch everything immediately from HL7 V2 and CDA to FHIR, but those that have not yet started should at least begin planning. Agencies that make the move sooner rather than later will be better positioned to meet the growing demands on public health data.

Agencies can make modernization faster and easier by finding an expert partner who can help them accomplish it with minimal disruption while producing optimal results. This sort of collaboration can eliminate context switching between systems to access data, avoid complex integrations across multiple systems using different data formats, and aggregate and merge datasets across data sources in different formats without manual intervention.

Those modernized agencies and the people they serve will benefit from improved efficiency and streamlined processes, enhanced data quality for informed decision making, and increased collaboration with other agencies and the private sector.