Health Language Blog

The Significance of Normalizing Your Data to the Future of Healthcare

Posted on 01/24/13


On January 10, the Centers for Medicare and Medicaid Services (CMS) announced the formation of 106 new Accountable Care Organizations (ACOs), bringing the grand total to more than 250 ACOs. Comprised of physicians, hospitals and health systems, each of these ACOs must be able to exchange data on the designated population of Medicare patients included in the CMS program. What’s more, they need to be able to analyze the data to determine if they are meeting 33 distinct quality measures concerning care coordination, patient safety, preventive health services, at-risk populations, and patient/caregiver experience of care.

However, if the stakeholders in these ACOs aren’t all sharing and analyzing data that uses the same data terminologies, their success could be impacted. This is where data “normalization” comes in. It can greatly improve operational efficiencies and patient outcomes not just for ACOs, but for all healthcare providers and payers nationwide.

Data normalization is the foundation that enables apples-to-apples comparisons of information. As such, it is a first essential step toward the increasing use of evidence-based care protocols, population health management, HIEs, data warehousing, and other forward-looking initiatives.

Normalizing data includes adopting and mapping standardized code sets and terminologies such as ICD-9/ICD-10, SNOMED CT, LOINC, RxNorm and more. Normalization ensures data from across the continuum of care can be aggregated for an accurate picture of performance and patient outcomes over time. A collective ACO, for example, then has the freedom to combine data from its entire designated Medicare patient population to measure the organization’s performance against CMS quality measures.

Essentially, no matter your organization’s goals around ACOs, HIEs or other initiatives, normalizing clinical and financial data is an essential first step for integrated health systems, medical groups, and even solo physicians who want to ensure their data is consistent, accurate and useful. It is the keystone that will shape the emerging interconnected healthcare landscape. 

data normalization  

Topics: Meaningful use, ICD-10, HIE, Coding Challenges, Data Warehousing

About the Author

Dr. Brian Levy, MD is Vice President and Chief Medical Officer with Health Language, part of Wolters Kluwer Health. He holds an MD and BS from the University of Michigan. Go Blue!