Healthcare organizations are moving toward digital transformation.
Healthcare organizations have moved to the next level in their data evolution. They recognize that the goal of making all data actionable isn’t attainable – yet. That is because many healthcare organizations are stuck in an interoperability quicksand that thwarts their goal of creating a single source of truth for integrated data.
Global IT consulting firm Gartner recently published its “3 Best Practices to Reset Healthcare Organizations’ Data and Analytics Strategy.” This research will help organizations operationalize three data best practices to set the baseline for true healthcare digital transformation.
Healthcare organizations are stuck in an interoperability quicksand that thwarts their goal of creating a single source of truth for integrated data.”
Gartner’s three data best practices
The issue of whether data is trustworthy is the critical baseline for quality care. Healthcare’s patchwork of legacy and digital platforms creates a challenging ecosystem that must be tamed to extract value from the data captured. Data integration and curation is an area of increasing investment by healthcare organizations. Many of these organizations are investing in data and analytics microservices as an overlay to orchestrate the omnichannel data architectures that make up the modern healthcare digital economy.
Comprehensive data integrators like ibi, a TIBCO company, can automate the capture, standardization, and democratization of multiple data sources to create that elusive single source of truth for healthcare organizations. Then artificial intelligence (AI)-enabled analytics can identify trends for study, workflow changes, better security, and improved consumer health.
Gartner calls these types of services “a data curation and enrichment hub,” suggesting these solutions are a necessity to “progressively replace legacy ways of moving data from source to target and enable digital transformation.”1
This solutions-driven approach requires three data best practices to truly enable healthcare digital transformation.
- Use next-gen smart data tech: Invest in the data services layer by using next-generation smart data technologies. This should include automating the integration of data processes, providing agile governance, coordinating access and compliance, and more.
- Build AI into a value-added service: Build AI into a value-added service for the organization by emphasizing human culture and business use cases that drive adoption. The idea is that the AI isn’t intended to replace human encounters but to provide decision support and analytics that increase the accuracy and effectiveness of care delivery.
- Enable adaptive data governance and DataOps: Improve enterprise agility with adaptive data governance and DataOps. DataOps as a data analytics strategy requires IT teams to collaborate with data consumers across the organization. The goal is to allow the data to be used across the healthcare continuum by improving how organizations build and manage their data pipelines.
Gartner points out that “many health systems are stuck in the world of compliance and quality reporting.”2 But dashboards and reporting are just the first iterations of data and analytics strategies. Healthcare digital transformation requires an evolution beyond formal data models and strict processes and structures. These methodologies still have a place in clinical care, but the next generation of the new healthcare digital economy requires a more mature model with advanced analytics and data sciences that modernize data governance and the tools healthcare uses to get the job done.
1, 2. Craft, Laura. “3 Best Practices to Reset Healthcare Organizations’ Data and Analytics Strategy,” Gartner, August 2020.