Build robust digital clinical trials with real-world data using no code
All your health information in one place
Simple and free daily symptom tracker
From ingestion and aggregation of raw data, to standardization and harmonization of disparate data types
Standardize & classify healthcare codes and concepts
Enrich & transform patient data to optimize your workflow
Compute hierarchical condition category (HCC) risk adjustment profiles
Privacy-preserving record linking across data sources and use cases
Securely match patient records in 2 simple steps
Reference guides, tutorials, and tools to develop your own participant experiences with the MyDataHelps APIs and SDKs
Reference guides, tutorials, and resources for using MyDataHelps Designer
Reference guides, tutorials, and tools for using the Orchestrate APIs
Manage your developer account and explore the Orchestrate APIs
Case studies, blogs, and white papers
Journal articles from partners leveraging CareEvolution’s platform
Webinars, conferences, and product educational resources
News articles and press releases
How we protect your data
Explore examples to get an idea of what’s possible with decentralized clinical trials and research
Collect high-quality data, fast—save your time and budget
You’ve made a transformational move. Investing in a powerful cloud platform like Snowflake, Databricks, Amazon HealthLake, or Google Cloud for Healthcare is a critical step toward a future powered by data. Your teams are poised to unlock transformative insights, streamline operations, and fundamentally improve how you manage member health and risk.
But many forward-thinking leaders like you encounter a hidden, frustrating paradox: the incredible potential of the cloud platform now feels stalled. Your analytics teams are struggling to get trustworthy insights, your data engineers and scientists are spending more time trying to ingest, assemble and clean data than building analytical models, and the promises made to the enterprise businesses who funded the project, fall short of expectations. They are left thinking ‘we spend all of this money to move our data to the cloud but I see no difference in my business outcomes’.
If this sounds familiar, you’re not alone. This isn’t a failure of your cloud strategy. It’s a sign of a hidden, final-mile challenge that many of the most innovative health systems, payers and payviders are now learning to solve: the data itself isn’t ready for the platform.
Your organization’s data with decades of clinical records, claims, and financial information is an invaluable asset. It represents your history and holds the key to your future. The challenge is that this data was created for different purposes, in different systems, using different standards. It was never designed to be seamlessly aggregated and analyzed in a modern cloud environment.
Simply lifting and shifting this raw data into a sophisticated platform is like putting unrefined crude oil into a Formula 1 race car. The engine is world-class, but it can’t perform without the right fuel. The result is stalled projects and a frustrating gap between your investment and commitments to your business partners.
To truly capitalize on your cloud investment, crucial work happens before the data lands in your analytics environment. It needs to be efficiently ingested, meticulously cleaned, enriched, and standardized into a single, cohesive format that your platform can leverage.
This is where a dedicated data readiness strategy becomes essential. By focusing on creating a high quality, harmonized longitudinal patient record, you create a “single source of truth” for every member from all data sources. This process involves:
a multitude of patient data from a multitude of sources.
inconsistent and fragmented data from each source.
the incoming data to the correct patient.
and harmonizing the data to create a 360-degree view of each patient.
the data into your formats that support your use cases, from flat files, PDFs to FHIR, the gold standard for modern healthcare data exchange.
When you feed your cloud platform a clean, standardized, and enriched data stream, you empower it to do what it does best: generate reliable insights, identify care gaps, predict risk with more accuracy, and power the AI-driven initiatives you’ve envisioned.
It’s understandable to be cautious about adding another step to your data flow, especially if you’ve had mixed results with vendors in the past, which most have. However, a data orchestration layer isn’t an extra burden; it’s the missing link to achieving your data cloud strategy.
By preparing your data with a partner like CareEvolution®, you ensure you have a clean, reliable data asset that is completely cloud-agnostic. Whether you’re on Snowflake today and exploring Databricks tomorrow, your foundational data remains consistent, powerful, and ready. This gives you the ultimate flexibility to enable the best features of each cloud solution, ensuring your data strategy is truly future-proof.
Leading healthcare organizations are learning that the key to unlocking the cloud’s value isn’t just about choosing the right platform, it’s about feeding it the right data.
Your cloud strategy is more than just a technology decision; it’s a business transformation initiative. To achieve the transformative results you expect, you must address the foundational issue of data quality.
Investing in a solution to clean, enrich, and standardize your clinical and financial data into a longitudinal FHIR record is not an optional “add-on.” It is the critical first step to ensuring the success of your cloud adoption journey. By prioritizing data quality, you will empower your organization to:
If you are navigating this challenge and want to explore what a practical data readiness strategy might look like for your organization, we’re here to help.
Let’s have a conversation about closing the gap between your platform’s potential and your current reality.
Let’s get technical. Learn more from our reference guides, tutorials, and tools for using the Orchestrate APIs.
The Orchestrate APIs liberate, aggregate, standardize, enrich, and transform data to power patient-centric use cases.
