Evolving to a utility infrastructure model for enhanced data management

This is the second of three articles, powered by CHIME Digital Health Insights and sponsored by Philips Healthcare, exploring how AI can help improve patient outcomes and operational efficiencies by addressing the challenges of data overload and fragmented systems in healthcare provider organizations. 

It’s common to hear health system CIOs say they want to get out of the data center business. On-premises data infrastructure is expensive to manage and maintain, and it can’t scale to meet growing demand for data to drive better clinical and operational decision-making. It retains the data silos that make it difficult to extract data and use it effectively.

Today’s health systems need a more agile approach to managing data. One consideration is a utility infrastructure, which couples interoperable platforms and standard data models with robust security and governance. The utility infrastructure model can help organizations provide open, real-time, and appropriate access to data while making data storage more efficient and cost effective.

Cloud Enablement: Promise and Challenges

Organizations migrating data to the cloud benefit from the ability to deploy storage and compute resources quickly, without the cost and complexity of installing physical hardware. IT teams can spend less time setting up storage systems and more time optimizing data for its intended use cases.

At the same time, organizations need assurance their cloud partners will protect sensitive data through services such as encryption, access controls, threat detection and response. At a minimum, they need partners who sign HIPAA Business Associate Agreements; HITRUST certification and SOC 2 attestation to demonstrate a commitment to security and compliance.

Equally important, but often less discussed, is how a technology partner has adopted the cloud. Vendors that embrace a cloud-first mentality have purpose-built solutions to leverage the cloud’s scalability, flexibility, and support for automation. They also let organizations move data and workloads to suit their needs without locking them into rigid contracts. Vendors with cloud-enabled or other niche offerings, on the other hand, often host legacy systems in the cloud. This may reduce operational costs, but it doesn’t make the most of cloud capabilities.

Beyond the Cloud: Building a Comprehensive Utility Infrastructure

A healthcare data utility infrastructure views data like water or electricity – something that should be readily available to any entity granted access to it. Open access fosters innovation throughout the healthcare ecosystem, particularly among entities that previously haven’t collaborated.

One key component of data utility infrastructure, the interoperable platform, has the cloud at its core. The cloud enables previously disparate entities to share data seamlessly in real-time. Two additional components are necessary. Standardized data models put data in a recognized format that all entities can use, while strong security protocols ensure the right users can access the right data at the right time.

Another consideration is AI’s role in optimizing and improving data management. Analysis of where data is stored, how it’s used, and where bottlenecks occur in accessing, processing, or uploading data (among other factors) can help get data to key stakeholders faster – and offer a clear demonstration of data utility infrastructure’s value proposition.

Breaking the Cost Barrier: Strategies for Affordable Data Management

Amid the advantages of cloud services, vendors must be mindful of healthcare’s limited capacity to invest in large-scale technology initiatives. It’s imperative to consider practical strategies to make data management more affordable.

One option is using open-source technologies for tasks such as data standardization, automated data management optimization, or cloud provisioning, as they can be more cost-effective than proprietary solutions. Another is establishing a comprehensive data governance framework to dictate where data is stored and how it’s accessed. This reduces redundancy, as data isn’t duplicated across multiple locations, and allows organizations to store data in the optimal environment.

Vendors should also calculate and pinpoint the cost savings achieved through improved operational efficiency. After all, the time data scientists spend reformatting data adds up; so, too, does the time clinicians spend searching for a single imaging file.

The Road Ahead: Building the Healthcare Data Utility of the Future

It will take a collaborative effort among providers, vendors, and policymakers to ultimately create the data utility of the future. While the technology infrastructure is in place today, no single entity can define standardized data models, establish robust interoperability frameworks, or dictate an ethical and responsible data governance practice.

As the industry is already hard at work to advance data and interoperability standards, Part 3 of this series will take a closer look at data governance in an area of real-time data availability.

Read article one, Breaking Down the Walls: Liquidating Data Silos for Enhanced Insight Extraction.

About Philips

Royal Philips is a leading global health technology company focused on improving people’s health and well-being through meaningful innovation, employing about 74,000 employees in over 100 countries. Our mission is to provide or partner with others for meaningful innovation across all care settings for precision diagnosis, treatment, and recovery, supported by seamless data flow and with one consistent belief: there’s always a way to make life better. For more information, please visit https://www.philips.com/global.