Data Quality in Healthcare Can Make All the Difference

Healthcare Data collection problems

There are several issues that pose as barriers to effective data collection. 5 Reasons Healthcare Data is Unique and Difficult to Measure by Dan LeSueur outlines 5 of the most prevalent challenges in data quality in healthcare.

In healthcare, data quality is often difficult to assess. The same information can present in different formats which may not all transfer to the same end or data arrangement. For instance, Claims Data may record a broken ankle as a code while the medical record may have the same data only it is in the form of an x-ray image. Having data in a variety of forms without one single language can make it difficult to determine its fitness to serve its required purpose within the appropriate context. The challenge is not only collecting the data but sharing it throughout the healthcare system.

Healthcare data resides in more than one place

Because there is no universal data collection system in health care, it can be found in many different places. It may be collected and maintained in different IT systems, servers, or software like EHRs or it can be kept in different departments or other physical areas. Each of these places can also maintain the data in different forms, and not all of them electronic. There may be hard copy files, electronic files, images, video, and codes, all of which may not be easily translatable across the system.

Healthcare Uses Both Structured and Unstructured Data

Software for EHRs offers a platform for capturing data in a consistent, uniform way, but rarely does it work out that way. Tradition in the medical field when it comes to record keeping keeps the bent toward capturing data in the easiest way as opposed to the way that makes is easy to analyze and aggregate. This often involves paper files that never make it to a digital format. While EHRs open the door for standardized data, many health care providers are resistant to the change involved in adopting a universalized approach to documentation. Simply put, change is hard to implement across an industry as large and varied as healthcare.

Healthcare data is not defined consistently

Different doctors have different views on diagnostic procedures and criteria and even treatments for conditions. While some best practices in healthcare do exist, for the most part, there is a lot of differing information and inconsistent definitions that exist making it extremely difficult to standardize healthcare data. Health IT and EHRs can provide a standard language in certain cases, but that does not change different criteria and procedures that health practitioners utilize within their own practices. The fact that healthcare is constantly shifting as new research changes the face of the industry every day increases the difficulty and poses an ongoing challenge that is constantly shifting.

Healthcare data is complex

There is consistency in claims data due to its use over the long term. Clinical data from EHRs draws a bigger picture that claims data falls far short of yet it is extremely dense and complex. Scientists do not yet fully understand how the human brain or human body functions so to create standardized data that captures every nuance of a plethora of individual and interconnected systems creates a situation so complex that managing the related data is far more challenging that simply standardizing terms or processes. In truth, technology for identifying the data, capturing it, and sharing it will have to be far more sophisticated before it is fully viable.

Healthcare data is subject to frequent regulatory changes

As laws governing reporting requirements and regulatory actions constantly evolve and increase, the associated data also changes in form and function. With the onset of healthcare reform, the public will be privy to more transparency in the policies and procedures.

The Difficulty of Standardizing Healthcare Data Reports

Some of the biggest sources of unstandardized information are doctors, nurses, and others involved in diagnosing problems and writing up reports. Even where attempts are made to improve standardization, professionals often have to resort to writing in the details. This type of reporting, known as “free text,” doesn’t work well with databases and other such organizational tools. Computers rely on the ability to search for exact matches and exclude the rest, but when people write things in free text, they may use any number of terms and phrasings. This makes most of their reports unsearchable.

Data sharing problems

Data sharing is the other prong of the data quality in healthcare dilemma. Even when quality data is collected, there is no assurance that it will transfer across healthcare data portals and shared in a way that it is beneficial to all. While Health information technology (Health IT) could potentially improve both collections of healthcare data and sharing it, there would still have to be a consistent system such as an electronic health record (EHR) or a patient’s personal health record (PHR). This would require the entire chain and this includes specialists, hospitals, and even primary care to utilize the whole system.

Unfortunately, very few primary care doctors are using EHRs and even fewer are fully utilizing the EHR’s data capturing capabilities. Significant resources were allocated to the industry-wide adoption of EHR technology in the American Recovery and Reinvestment Act of 2009, development of the infrastructure that is required to fully support Health IT and implement it across healthcare entities will take time. Until then, healthcare data will continue to vary and sharing will not always be easy.