Healthcare Data Management: Three Principles of Using Data to Its Full Potential
U.S. healthcare is too expensive and inefficient, with undesirable variation in quality. Healthcare organizations need to begin treating data as a powerful asset and be willing to invest in a strategy for leveraging it in order to address these issues and realize the Triple Aim.
Douglas Laney, author of 3D Data Management: Controlling Data Volume, Velocity, and Variety, is now tackling Infonomics: the practice of information economics. In his 2017 book, Infonomics: How to Monetize, Manage, and Measure Information as an asset for competitive advantage, Laney provides detailed rationale as well as a thoughtful framework for treating information as a modern-day organization’s most valuable asset.
The Three Systems and Measuring, Managing, and Monetizing Data
Health Catalyst has been helping healthcare organizations measure, manage, and monetize data for more than a decade by using a three-systems approach for achieving meaningful, sustainable outcomes improvement. In this approach, best practice, analytics, and adoption are brought together to enable system-wide, sustained outcomes improvement. The framework asks, “What should we do,” “How are we doing,” and “How do we transform?”
The Three Ms of Infonomics invokes a similar three-component system for health systems to become information savvy. Laney’s book asks organizations to think about managing data (What data do we have?), measuring data (What is our data worth?), and monetizing data (How do we use data to transform?) With an investment in a robust data analytics program to measure data, powerful infrastructure in place for healthcare data management, and the right tools and resources in place to monetize data, healthcare organizations can begin to use their valuable data asset to its full potential in order to drive better health and financial outcomes for patients and providers.
Using Infonomics for Effective Healthcare Data Management
While most healthcare organizations have embraced the primacy of data to support evidence-based medicine and the emergence of value-based care, most have not yet made a commensurate investment to make sure they are getting the most out of that asset by putting in place a comprehensive strategy. This framework of Measuring Data, Managing Data, and Monetizing Data set forth by Laney is a helpful guide to leveraging data to its full potential.
How to Measure Data
1. Measuring Data is an organization’s willingness to invest in data as they would a valuable asset. How much data does the organization have? What is that data worth?
Data is everywhere in a healthcare organization. Data is constantly being generated throughout the system through the normal activities of conducting business and providing services – the billing system, EMR, prescription writing software, etc. Most healthcare systems recognize that much of this data has value, but many have failed to treat it as they would a tangible asset. For instance, all hospitals likely know exactly how many beds they have at any given time. They know how much a bed costs, and how much it would be to replace it. That same kind of rigor is not being invested into knowing how much data the hospital has or what the financial impact might be to replace that data. Laney points to the failure of modern accounting systems to provide the motivation or mechanisms to quantify the impact of their information assets.
Consider Allina Health’s Success Story: by undertaking a data-driven approach to healthcare, the health system was able realize $125 million in financial improvements in one year using analytics that leveraged their highly valuable asset–data. While it may not be necessary for healthcare organizations to put a specific dollar amount on just how much their data is worth, having a concept of the order of magnitude (hundreds of millions of dollars in the example above) can be helpful in driving organizations towards thinking about how much data they have, where it’s coming from, and how it could be used towards the bottom line, whether through saving money or improving care. Once health systems recognize the value of their data, they need to invest in caring for and maintaining that asset. This could mean investing in infrastructure such as a healthcare analytics platform to store and manage data, an information security program to protect data, cloud services to store data, or people and programs who can then convert that data into actionable insights.
Once the healthcare organization acknowledges the true value of their data, the next step is to manage that data by putting in place programs, software, and people to care for that asset.
How to Manage Data
2. Managing Data is an organization’s ability to track and inventory data like a physical asset. What data does the organization have?
Once health organizations have acknowledged the value of their data (measuring data), the next step is to determine where it’s coming from and how it is stored (managing data). Effective healthcare data management means understanding where the data is and the ability to get the data into some form where it can be appropriately managed. Revisiting the example of the hospital bed to help illustrate the difference in the way health systems treat physical assets, hospitals know how many beds they have, and they know where those beds are at any given time. They may even use RFID tags to track the movement of these beds. However, does that same hospital know the origination and location of all data in its ecosystem? They know what percentage of beds are in use at any given time – do they know how fully their data is being used across the organization?
In his book, Laney tackles both impediments and best practices for managing all forms of information assets. Health systems have many sources of data–some they carefully track and monitor and some they don’t, such as data from testing machines or data from RFID tags used to manage hospital beds. It is difficult to promote and control access to data without a healthcare data analytics platform in place.
Managing Data in a healthcare organization means having a data operating system in place that serves as the foundation for getting data under centralized control and ensuring its availability across the organization. With the Health Catalyst Data Operating System (DOS™) Solution, data is pulled in from a wide variety of source systems, providing a single control point where individual access rights can be granted. From there, the organization can establish data governance and track data lineage as data is enriched and spread to the edges of the organization. The organization knows what data they have, where it’s coming from, what it means, who has access, and how fully that access is being exercised. With the right management infrastructure in place, the organization is then in a position to monetize their data.
How to Monetize Data
3. Monetizing Data is an organization’s ability to leverage information assets. How does the organization use data?
A hospital knows how many beds they have (measure), where those beds are at any given time (manage), and how much they can bill for patients needing to stay in specific room types (monetize). Laney’s exploration of the monetization of data shows that this could take many forms. It could be taken literally in the ability to sell data, but in healthcare, the monetization of data is not just about money. It means improving the quality of care, improving patient experiences, lowering the cost of care that’s being delivered, discovering new revenue streams, improving the lives of care providers, or optimizing services.
In the case of Allina Health mentioned above, the combination of clinical, operational, and financial improvement projects resulted in a massive positive impact on the bottom line. Thirty million dollars of the realized $125 million impact came as the result of reducing unwanted clinical variation through a variety of improvement projects, including lowering heart failure readmissions, improving stroke care, improving outcomes for spinal conditions, and more.
Once the healthcare organization has the infrastructure in place to manage the data, they can then begin to utilize specific tools and programs to monetize their data. For Health Catalyst clients, they have DOS in place to manage their data, and then a suite of more than 70 applications and analysis tools on top of DOS to help them monetize their data. They can prevent harm to patients using Patient Safety Monitor™, reduce the cost of care using the Corus® Suite, which helps users understand the cost of care so that they know where to focus in order to cut costs, and improve population health using the Community Care advanced application to deliver quality data to healthcare providers and tell them how well they’re doing in treating populations, as well as identifying non-compliant patients so that they can be managed appropriately. These are just a few examples of the many ways Health Catalyst helps health systems monetize their data.
The Value of Healthcare Data Management
Since its inception in 2008, Health Catalyst has been treating data as a valuable asset and has been helping health systems do what Laney recommends: measure, manage, and monetize the value that data brings to the organization. Health systems are generating an incredible volume of data, and Health Catalyst is poised to help its partners leverage this data to its full potential with effective healthcare data management.
Would you like to learn more about this topic? Here are some articles we suggest:
- Cloud-Based Open-Platform Data Solutions: The Best Way to Meet Today’s Growing Health Data Demands
- In Healthcare Predictive Analytics, Big Data Is Sometimes a Big Mess
- 7 Essential Practices for Data Governance in Healthcare
- Hadoop in Healthcare: Getting More from Analytics
- The Case for Healthcare Data Literacy: It’s Not About Big Data
Would you like to use or share these concepts? Download this presentation highlighting the key main points.