Understanding Data Quality Risks & How They Affect Your Healthcare Business

When you think about the risks to your healthcare business, there are likely a lot of things that come to mind. However, one of the biggest threats to the well-being of a modern-day healthcare business is poor data quality. Data quality is actually a significant concern for leaders in the healthcare industry. Problems with data can hinder business goals, increase costs, and even affect your patients. Take a look at what you need to know about data quality risks as someone in the healthcare business.

Your First Step: Understanding That There Are Risks

One of the most significant problems with data risks in healthcare is not all healthcare business owners understand the risks and how common it is for a business to have problems because of them. Only 60 percent of those in the healthcare industry rank data as a serious matter when this should be listed as a serious matter to everyone. At least 61 percent say integrating clinical and business data is a significant challenge for their healthcare business, which shows how many data fallacies are likely committed.

The Inherent Risks of Inaccurate and Incomplete Data

Inaccurate or incomplete data can be a massive barrier of healthcare and even cause the demise of your healthcare business. The number one risk associated with incorrect or incomplete data is non-compliance with government regulations with as many as 34 percent of healthcare business owners having faced this issue because of data wrongs. A few of the other most common risks that are associated with inaccurate or incomplete data include:

• A loss of competitive edge due to lacking member retention
• A lack of enough data to drive new service or product developments
• Problems with interoperability that create a lack of support for the health of the population
• Missing real-time insights in clinical or treatment settings
• Significant profit losses due to fraud loss
• Inaccurate metrics and quality scores that lead to increased overhead costs

A Look at Where Problems with Data Originate

Data problems in healthcare can originate from different places. For example, data risks can start with improper input methods and poorly maintained hardware on a facility level. However, the majority of data problems originate in data silos. Data silos are proverbial storage places for data that are under the operation of one entity most of the time. In the healthcare business, the loads of data that is accumulated must be appropriately housed and data silos are the typical solution.

One of the most significant risks healthcare businesses face is not having access to the data in these silos as they should. This can happen because:

• Data gets stuck because it is only accessible by one department
• Data is improperly shared or cannot be shared at all
• Data cannot be leveraged across the entire enterprise
• Data gets lost because it is not adequately backed up outside of the data silo
• Data is compromised because it is improperly secured

Silos can and often are set up by a business owner who is trying to rightfully protect the information they take in, but the improper management of this data can pose a world of problems in both the short and long-term.

Changes to Make to Avoid Data Risks in Healthcare

Once you have armed yourself with knowledge about the data risks in the healthcare business, it is critical that you get proactive so your business can avoid those potential problems. You should first simplify data governance by limiting how many governing entities are in charge of or indirect control over your facility’s data. A few other things to do include:

• Optimize the analytics of your data
• Enable interoperability of your information
• Reduce operational overhead of your data

Working with a company that provides data management solutions and specializes in helping clients in the healthcare industry can usually help with these processes. Therefore, bringing in the help of an outside service to help you combat data risks is a logical business move.