Health plans

What is preventing healthcare plans from becoming more interoperable? Technical preparation


Lack of technical readiness, from legacy technologies to data silos, continues to prevent healthcare plans from achieving the promise of interoperability. It also creates obstacles to innovation.

These are challenges that payers must overcome before the next phase of interoperability takes effect: the widespread adoption of application programming interfaces (APIs) such as Fast Healthcare Interoperability Resources (FHIR), which will empower consumers the ability to access their health data with the touch of a smart phone.

Break down barriers to technical preparation

More than six months after the new interoperability rules took effect, healthcare plans are still struggling to develop a cohesive business data strategy and infrastructure. This makes it difficult to develop a single source of truth that can help identify limb risk, fill gaps in care for people with chronic illnesses, or even determine the quality of care limbs receive, whether virtually or in person.

Additionally, many plans struggle to derive actionable insights from the data they collect. As a result, 62% of health plan managers say improving AI and machine learning capabilities and driving their adoption are “extremely high priorities” for their organization.

These lapses in technical readiness will become even more apparent in January 2023, when the Centers for Medicare & Medicaid Services begin requiring some payers to implement FHIR-based APIs that:

  • Give patients the ability to access complaints and encounter data as well as pending and active prior authorization decisions
  • Make supplier directories accessible to the public
  • Allow patients to request that certain clinical data be exchanged with other payers

Such changes could have a big impact on the member’s experience, given the barriers members typically face in obtaining their health information. Today, around 40% of patients have to go to a healthcare professional’s office or hospital to get copies of medical records or imaging tests. While 66% of consumers have access to a patient portal, only 18% of those surveyed have ever been able to receive digital records through the portal.

Closing the preparation gaps

How can healthcare plans move from emerging technical readiness to a state where they can not only comply with API standards, but also use APIs to fuel internal workflows? Here are three approaches to consider.

Break down internal and external data silos. Delivering on the promise of healthcare interoperability requires that all key stakeholders have access to connected data. Yet even within healthcare plans, data silos between departments and divisions are not uncommon. For example, data silos between pharmacy and medical benefit management limit the ability of health plans to get a complete view of the cost drivers for a specific population. When health plans integrate data from these divisions, the effects on health outcomes and costs are dramatic: less than integrating health insurance and drug plans.

Leaders of an Appalachian Health Plan found the organization could more effectively bolster star rating performance under Medicare Advantage by ensuring performance is tracked in one place. This meant breaking down information silos so team members could more effectively leverage data analytics to identify critical gaps in care and work together to identify strategies for improvement. Custom dashboards tracked the plan’s efforts. The impact? It became one of 110 Medicare Advantage plans to achieve 4-star status for 2021.

Developing secure and accurate reference datasets for patients and providers is critical to breaking down data silos. With continuous governance, master data management technology can enable a faster path to interoperability. Additionally, leveraging standards to streamline and govern patient clinical data enables semantic translation of clinical data between vendors and generates value in AI use cases requiring rich data sets.

Harness the power of cloud-based analytics. Increasingly, healthcare plans are leveraging cloud computing to make sense of disparate types of data, from the social determinants of health data and medical records, to pharmacy and laboratory information, in order to make sense of it. ‘obtain a longitudinal view of the limbs. Relying on cloud-based analytics enables healthcare plans to overcome analytic challenges associated with legacy technologies by accessing AI and machine learning software through cloud platforms. This eliminates the challenges associated with fragmented and siled data. It also provides a more detailed understanding of the actions needed to improve results and reduce risk.

An industry survey shows that 78% of healthcare organizations have integrated cloud computing into their operations, and 20% plan to invest in the cloud. Meanwhile, nearly half of health plan managers surveyed say their organization has an innovation lab dedicated to AI and machine learning to support adoption across the board. business.

Smaller health plans can migrate to the cloud by leveraging the infrastructure and applications of cloud providers through a platform-as-a-service model.

Build capacity to prevent fraud, waste and abuse. Although some industry groups fear that the new interoperability rules endanger patient privacy, such concerns should not be a barrier to innovation. Instead, as the health insurance industry faces a growing risk of cybersecurity threats from the pandemic, with Fitch Ratings reporting a significant increase in insurance claims linked to ransomware attacks, the plans health care providers should double their defense against cybersecurity. One recommendation is to implement a zero-trust security model that requires all users to be authenticated, authorized, and continuously validated before accessing health plan applications and data.

82% of health plans also create rules and ratings that automatically detect potential fraud schemes, according to a survey. These include the development of logic-based rules for specific types of complaints as well as user-defined rules that proactively flag complaints with specific procedure codes and modifiers for review. Some plans choose to apply rules and scoring to specific populations, such as Medicaid managed care.

Major healthcare plans rely on AI to detect suspicious activity, such as impossible day billing and cases where simple encounters have been coded to appear more complex. While only 12% of health plans surveyed have made this decision, 83% plan to invest in AI for the prevention of fraud, waste and abuse.

Invest in a prospective approach

While interoperability is a driver for the adoption of digital health among health plans, organizations need to strengthen their technical readiness for large-scale data sharing and analysis to establish a solid foundation for the transformation. Developing a cohesive strategy for data capture, analysis and protection, supported by strong internal collaboration and a commitment to innovation, is a great place to start.

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