The Importance of Healthcare Data Cleansing and Validation

By Scott Mullins, Senior Director, Commercial Applications, Intalere and Executive Director, DataBay Resources

Many of the primary trends of the past several years continue to challenge hospitals and health systems. Many providers are continuing to develop and refine their Affordable Care Act (ACA) readiness strategies by exploring a variety of innovative reimbursement models and building infrastructure for population health management (PHM). All of these initiatives will depend on data.

Relevant, actionable data is the basic building block for an organization’s economic direction and also provides the facts and evidence needed both internally and externally to communicate the realities facing every stakeholder. Using the best data available and analytic tools, both in terms of spend and other areas, is the foundation to savings, improved bottom lines, improved clinical outcomes and efficient care delivery.

But more important than the amounts of data, is the quality of your data. Data can be virtually worthless to you if dirty, or not cleansed properly. Also referred to as data scrubbing, data cleansing is the process of detecting dirty data (data that is incorrect, out of date, redundant, incomplete or formatted incorrectly) and then removing and/or correcting the data.

Data cleansing is often necessary to bring consistency to different sets of data that have been merged from separate databases. Cleansing data involves consolidating data within a database by removing inconsistent data, removing duplicates and re-indexing existing data in order to achieve the most accurate and concise database. It can involve manual tasks or processes automated by special data quality tools. In many cases, these data quality tools need to be Health Insurance Portability and Accountability Act (HIPAA) and Federal Information Security Management Act (FISMA) compliant.

To get an idea of the importance of clean data, let’s review The Dallas-Fort Worth Hospital Council (DFWHC) Education and Research Foundation as an example. DFWHC is an organization comprised of nearly 90 hospitals in the north Texas region that are committed to becoming the community resource to create knowledge, insight and wisdom for the continuous improvement of healthcare.

To achieve this vision, the DFWHC Foundation began collecting data from its members 15 years ago and recording it into a regional database. With this data, the organization is able to identify and address disparities related to language, ethnicity, race, culture, gender, age, income, literacy, health, diseases and access to healthcare in the community. The DFWHC Foundation then helps transform this information into knowledge that can be used to create health programs that benefit the community.

With good, clean data, the DFWHC Foundation can make more accurate analyses and provide evidence-based support to regional health partnerships, community programs and various public health committees. And this knowledge can mean greater operational efficiencies, cost reductions and reduced risk in healthcare.

The enhanced role of data in the future of healthcare is a certainty. But to be truly effective and make the best decisions in terms of cost and quality, the investment in data cleansing and validation must be a leading component of every healthcare facility’s data program.

To learn more, read this success story on how Intalere subsidiary DataBay Resources helped DFWHC overcome their data challenges.

Leave a Reply

Your email address will not be published. Required fields are marked *