What is the importance Of Data Quality in Healthcare?

Writen by Ravi Reddy

January 8, 2021

Advances in technology have revolutionized the way healthcare providers operate. Although there are multiple benefits associated with being able to access and share data, not all data is created equal. To ensure the best possible outcomes, healthcare companies must ensure that they utilize high-quality data. In this guide, we’ll discuss the importance of data quality, offering advice to help businesses recognize good data and implement effective data management techniques.

What does data quality management mean?

Quality control is an integral aspect of overseeing the production and distribution of safe, effective, useful products that meet customer expectations. Data quality management is slightly different, but it is a similar concept. Healthcare companies have access to a vast amount of data today, but not all of it will be relevant or reliable. Data quality management involves using procedures, technology and tools to monitor the quality of data and ensure that sources are verified. Effective data quality management covers integrating reliable data sources, verifying information, working with and sharing sensitive data with trusted recipients and implementing systems, which protect customers

Why is data quality management so important in healthcare?

Data quality management should be a priority for any organization that analyzes, handles and shares data, but it is particularly critical for healthcare companies. The sensitive nature of the data means that it is protected and governed by stringent rules and regulations. It’s also crucial to understand the impact accessing that data has on the individual. It’s not just essential for healthcare and insurance providers to be aware of rules related to compliance. It’s also vital to recognize that accessing reports and records has consequences for the individual and the treatment they receive. 
There are several benefits to prioritizing
data quality for healthcare providers. As well as ensuring HIPAA compliance, improving patient outcomes and protecting sensitive data, companies can also:

  • Accelerate existing ways of working and boost efficiency and accuracy
  • Improve learning to facilitate better decision-making and new policies and procedures
  • Enhance patient safety
  • Identify relevant trends and patterns
  • Monitor and evaluate services to highlight weaknesses and build on strengths
  • Plan for the future

What are the consequences of using poor quality data?

Utilizing poor quality data can have far-ranging implications for providers, employees and customers and patients. The consequences of failing to prioritize data quality include:

  • Delays and patient frustrations: a lack of accuracy can result in delays and growing patient frustration. In extreme cases, errors or inaccuracies can even put patients at risk of receiving inappropriate treatment. 
  • Employee morale: if employees are working with inaccurate, poor quality data, this could contribute to low morale and widespread mistrust. Your team may resort to using manual techniques, which will be less efficient and more time-consuming. The risk of making mistakes will also increase.
  • Reduced efficiency: having access to high-quality data should improve efficiency and outcomes for employees and patients significantly. In contrast, poor quality data can reduce efficiency and create backlogs and bottlenecks. This is likely to impact customer service and job satisfaction for employees.
  • Policy-making: data can be incredibly valuable for policy-makers, but this is not the case when handling unreliable data. If data quality is poor, this could have a negative impact on policy-making.

What constitutes effective data quality management?

Healthcare providers can enjoy several benefits from implementing effective data quality management protocols and procedures. Signs of a good data quality control strategy include:

  • A structured process: it is important that any data that enters the system, particularly through manual data entry, goes through a structured process to ensure that it can be validated. If there is a lack of structure, the risk of inaccurate, poor quality data penetrating the system will increase.
  • Data formatting and validation: formatting data, utilizing structures and tried and tested processes and validating data will improve efficiency and prevent errors, such as duplication. It’s essential not only to validate the structure of the data, but also more advanced features that can be identified by the system.
  • Security, collaboration and cohesion: one of the most significant advantages of using modern technology to access and evaluate data is the ability to work together and share relevant data with other providers, insurance companies and medical experts or departments. To do this effectively, it is critical to ensure that you can collaborate securely and work cohesively. The system should be watertight to ensure that your organization is fully compliant and prevent sensitive information from ending up in the wrong hands.
  • Continuous monitoring and scalability: there is always a threat to data security, and technology advances at a rapid pace. This means that it is vital to monitor data continuously, to keep an eye out for suspicious behavior or activity and to move with the times. Continual monitoring allows for threats to be detected and addressed swiftly.
  • Understanding the entire data life cycle: healthcare providers must always be aware of changes in regulations or policies, which govern access to data. Guidelines change, and this can affect how you deal with data at different points in the life cycle.
  • Aligning policies with key performance objectives: there is scope for healthcare providers to make significant improvements to services and outcomes using high-quality data.

When drawing up policies, it’s beneficial to align procedures with key performance objectives. You can use the data you have to boost efficiency, create stronger relationships with customers, improve patient outcomes and highlight and eliminate operational weaknesses, for example.  


High-quality data is incredibly valuable for healthcare companies and providers looking to ensure their patients and clients receive the best possible standards of care and customer service. If your organization provides health services, it’s crucial to ensure you have procedures and policies in place to monitor and manage data quality. Having access to good data will enable you to run an efficient company, meet customer expectations, boost employee morale and facilitate effective decision-making in the future.

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