Help improve insights from health data

A shift is happening in the way health organizations are thinking about their data and analytic technology needs. According to a new IDC Market Spotlight, instead of traditional “bottom-up” approaches, in which the needs of individual service lines and functions drive technology decisions, health plan analytics are beginning to take a “top-down” approach. This approach uses data platform architecture to break down data silos and better meet the needs of the entire enterprise.

In my experience, many healthcare providers are taking similar approaches to health plans. They are recognizing that targeting opportunities to improve operational effectiveness and clinical quality require transformation that should be driven from the top and enabled from the bottom.

You might ask – why is a top-down approach so important? I’ve seen that in the “wild” (e.g., within our clients’ enterprises), re-use is challenged with “bottom-up” approaches, and in my opinion, it is exemplified in two key ways:

1. Multiple point solutions being leveraged, integrated via point-to-point means. Health organizations commonly have multiple point technology solutions that focus on specific aspects of their mission, such as understanding claims cost drivers, understanding physician network performance or stratifying populations. These solutions are routinely integrated via point-to-point means, which can add functional integration challenges when cross-solution re-use is needed.
2. There’s wide variation on the leverage of data interoperability standards. Many do not consider interoperability standards and common data models, such as Fast Healthcare Interoperability Resource (FHIR), HL7, U.S. Core Data for Interoperability (USCDI), and the Observational Medical Outcomes Partnership (OMOP) Common Data Model. And when they are leveraged, they’re not leveraged consistently. This can exacerbate the data liquidity challenges when re-use is needed.

Net: I believe bottom-up approaches can result in challenges enabling re-use and leveraging data cross-solution, as well as duplication of cost and effort for solution integration and data curation. With limited integration and interoperability, these data silos are not easy to leverage to benefit the rest of the enterprise.

Read more from IDC: Foundational Data Platforms Improve Payer Interoperability

In my experience, health organizations are investing in aggregating and leveraging their data. It takes great skill and solid governance to combine multiple disparate sources and make them analytically ready in a timely, cost-effective manner.

IDC Research Director Jeff Rivkin contends that health plans must destroy data silos by, “…using a data platform that addresses operational and analytic needs while combining clinical and administrative data in an open, canonical way…The ‘data platform’ is now the go-to approach to integration.”

I agree that integrating data across sources may help health organizations create a single source of truth for enterprise data that can be used for analytics and business processes. With this resource, they may be better able to uncover new and valuable insights that can potentially help improve their ability to manage risk and create operational value. Ultimately, insights from a single source of truth may help health organizations navigate the industry’s transition from fee-for-services to outcome-based healthcare delivery.

As health organizations look to improve insights from data, they should look for partners that focus on and are committed to embracing health data interoperability standards, such as HL7 and FHIR. It’s important to have a partner that can help guide the effective use and application of these standards to help these health organizations solve challenges, such as point-of-care decision support, real-world data for life science protocols, and management decision support for quality and operational performance.