While best known for our healthcare technology, InterSystems is a global leader in interoperability across multiple industries. One goal common to all of them is achieving the level data liquidity needed to unlock simultaneous breakthroughs in quality and efficiency. However, unique attributes of clinical data and healthcare data management pose additional challenges.
In particular, clinical data must be integrated with operational and financial data that have long been managed in separate siloes, as well as with clinical data from other sources. Healthcare leaders charged with unlocking the power of clinical data to improve quality, care management, and consumer experience must ensure their data strategy addresses each of the following considerations:
How is information from disparate data sets and streams accurately matched to your individual members or patients?
At the risk of stating the obvious, there is no universal identifier for US patients or health plan members. Healthcare organizations must integrate data from multiple systems with dueling formats for capturing patient information, which often leads to duplicate records and data gaps that can undercut quality and productivity. According to Black Book Research, 35% of all denied claims result from inaccurate patient identification or information.
To overcome this challenge, we recommend an enterprise master person index that can draw upon a wide array of referential data, uses both deterministic and probabilistic logic to match records, and includes automated tuning tools to adjust algorithms for your organization’s unique needs. Visit InterSystems EMPI to learn more about these criteria and how our solution addresses them.
How do all your legacy systems, from quality to care management to claims administration, talk to each other electronically?
Healthcare cannot afford to wait on industry-wide adoption of FHIR to integrate clinical and administrative data. While FHIR is the right goal, we are still in the early stages of this migration. The systems embedded in most organizations “speak” in multiple formats and standards, and upgrading or swapping out these complex, costly systems will be a decade-plus endeavor. Additionally, there is variation in how FHIR standards are being implemented in each organization and system, and the Implementation Guides published by the HL7 Da Vinci Project continue to evolve.
To overcome this challenge, data stacks at healthcare organizations must include a powerful data transformation engine. Your engine must support FHIR, HL7 v2, DICOM, and IHE profiles; parse and pressure test incoming data feeds; and process high volumes of data in disparate standards and formats in real-time. View InterSystems Health Connect to learn more about these criteria and how our solution addresses them.
How do you ensure information ingested from data streams for a specific purpose is readily available for multiple use cases?
At the root of many care siloes plaguing healthcare are persistent data siloes. Even successful data integration efforts all too often focus on narrow use cases, forcing other departments and functions to recapture and normalize overlapping data elements relevant to challenges they are working address. The end result is a lose-lose. Valuable information in data streams not relevant to an immediate use case is left on the cutting-room floor, while ancillary data that could have meaningfully informed a critical decision is not considered.
To overcome this challenge, a comprehensive, healthcare-specific data model should anchor all components of your data integration strategy. The model must include fields to store all data elements relevant to your larger enterprise in formats that others can readily utilize. View InterSystems HealthShare Unified Care Record to learn more about this criteria and how our solution addresses them.
The potential for data integration to transform how we deliver care is enormous. To achieve this promise, we must rethink a number of longstanding data practices unique to our industry.
