10 Questions to Ask When Evaluating Clinical Data Assets

Whether it’s about gaining a competitive advantage, improving health outcomes, or reducing the total cost of care, health plans are building more holistic views of members’ interactions with the healthcare system. To do this, plans are investing in clinical data, which contains critical elements such as lab results and vital signs, to support use cases like the Healthcare Effectiveness Data and Information Set (HEDIS^®) quality measures, risk adjustment, prior authorization, utilization management, and care management.

However, in many cases this valuable data is either not in place or is not being properly utilized. To capitalize on the potential, health plans must take a proactive approach to gathering and optimizing clinical data. To help optimize your clinical data strategy, here are the top questions you should ask when evaluating clinical data assets.

1. How do I acquire clinical data, what are the key sources of clinical data?

There are several different ways in which clinical data is collected ranging from electronic health records (EHRs), health information exchanges (HIEs), and other clinical research data sets abstracted from medical records. These datasets have unique interactions with specific systems and processes, making them extremely valuable but challenging to access.

2. Where is my organization in our clinical data journey?

Several determinants shape your organization’s position in its clinical data journey. Evaluating these factors will play a crucial role in guiding future investments and leveraging clinical data to drive downstream value. Key considerations include: 

• Clinical data management infrastructure: Does your organization have a system in place for collecting, storing, and accessing clinical data?
• Data sharing: Is your organization actively sharing clinical data with other healthcare providers or organizations as needed to support patient care?
• Data quality: Is the clinical data your organization is collecting accurate and reliable?
• Data integration: Is clinical data being seamlessly integrated into clinical workflows, or is it siloed and difficult to access? How real-time is this process and how real-time does this need to be?
• Data analysis: Is your organization utilizing clinical data to drive decision-making and inform strategic planning?

3. Has your organization reviewed its data rights policies to foster clinical data sharing?

Reviewing data rights policies is important for health plans that want to foster clinical data sharing as it ensures compliance with regulatory requirements, facilitates collaboration and data-driven healthcare, increases access to data, and promotes patient-centered care.

4. How are organizations using clinical data today?

Market forces are compelling – and inspiring – health insurance providers to acquire digital clinical data and make it available to members and usable across the enterprise Centers for Medicare & Medicaid Services (CMS) mandates require government-sponsored plans to provide members access to their health data using the Health Level Seven International^® Fast Healthcare Interoperability Resources (FHIR^®) standard. Risk adjustment is more accurate with access to diagnoses and other clinical factors that don’t appear on claims. HEDIS scores and Star Ratings depend on clinical data such as test results and vital signs to identify and address care gaps.

5. What are the common issues found in trying to integrate clinical data?

Despite the need for and availability of clinical information in digital form, the reality is that raw data collected from EHRs, HIEs, labs and other sources can’t be seamlessly incorporated into analytics or real-time transactions. Poor data quality and the need to integrate data from multiple sources to complete each member’s health picture pose enormous challenges.

6. What will it cost to build vs buy clinical data improvement capabilities?

After acquiring clinical data, it must be integrated into data management systems and normalized, enriched and deduplicated for successful deployment across downstream applications. Using traditional approaches to handle vast magnitudes of clinical data is extremely complex, costly, inefficient, and limiting. Using the Operational Cost Avoidance Model, we estimate it could cost a mid-sized health plan up to $75 million for manual resources to perform data improvement functions.

7. What technologies do I need to invest in?

Our customers and partners are levering our automated data transformation engine, Availity Fusion™, to produce data that’s normalized to national standards, interoperable, deduplicated, consolidated into a longitudinal record, and available in fit-for-purpose data packages for flexible deployment at scale. Availity Fusion accelerates the usability of clinical data across many data enterprise organizations, including health plans, HIEs, and technology partners, as well as supports clinical data compliance with CMS.

8. What should I look for in a clinical data integration vendor?

The evolving healthcare marketplace and cloud-based technology landscape can make it challenging to find the right data solution. Based on extensive work with health plans across the industry, we’ve outlined critical features to look for in a clinical data integration and interoperability solution:

• Scalability: Possess the experience, capacity, and infrastructure needed to ingest and optimize multi-format health data loads of up to millions of data records and process and deliver in real-time.
• API-Driven Workflows: Continuously maintain and update flexible API-based technology to integrate and deploy data to the right place at the right time.
• Standards-Based & Transparency: Maintain and leverage industry standard terminologies when standardizing data to support semantic interoperability and seamless data exchange, avoiding “black box” approaches that perpetuate the use of non-standard coding and prevent adoption and trust of data downstream.
• Expansiveness of Features: Use case-oriented capabilities designed to meet clinical workflow needs and drive immediate value in customer environment.
• Ease of Deployment and Use: Fast, repeatable implementation and customer resources, including training, documentation, and best practices.
• Expertise: Clear thought leadership and applicable expertise in the domain area to ensure customer success and continuously drive innovation.

9. What are the potential risks of not leveraging clinical data or interoperability?

• In accurate or incomplete patient records: If clinical data is not being properly collected and managed, patient records may be inaccurate or incomplete, leading to suboptimal care decisions and potentially negative outcomes for patients.
• Increased costs: Without access to complete and accurate clinical data, healthcare providers may be forced to rely on more costly diagnostic tests or procedures to make treatment decisions. This can lead to increased costs for both healthcare providers and patients.
• Reduced efficiency: If clinical data is not easily accessible or integrated into clinical workflows, it can lead to reduced efficiency and productivity for healthcare providers. This can also lead to longer wait times for patients and increased frustration for both patients and providers.
• Poor patient outcomes: Without access to high-quality clinical data, healthcare providers may be less able to identify and address patient health issues, leading to poorer patient outcomes.
• Legal and regulatory risks: Failing to properly manage and use clinical data can also expose an organization to legal and regulatory risks, such as data breaches or non-compliance with relevant regulations.

10. How is the investment in clinical data an investment in innovation?

Investing in clinical data can be considered an investment in innovation because it can support the development and implementation of new technologies, processes, and approaches to healthcare delivery. Some specific ways that investing in clinical data can drive innovation include:

• Data-driven decision-making: By providing access to high-quality clinical data, organizations can use data analytics to identify trends and patterns that can inform the development of new treatments, care models, and policies.
• Telehealth and digital health: Investing in clinical data can support the development and implementation of telehealth and other digital health technologies, enabling remote patient monitoring and care delivery.
• Personalized medicine: Leveraging clinical data can help organizations develop personalized treatment plans for individual patients based on their specific needs and characteristics.
• Interoperability: Investing in clinical data interoperability can facilitate the sharing of data between healthcare providers and organizations, enabling more coordinated and seamless care delivery.
• Financial:

•    Clinical:

To learn more about how clinical data can be a powerful, strategic asset when it’s actionable, accessible, and prepared for use, download our 2023 Clinical Data Integration Buyer’s Guide.