How to Improve Data Quality in Healthcare?

Contrary to the common idea the more complex software solutions are used by the healthcare organizations the more problems they may have to face in terms of data quality they gather. And healthcare is among the industries where poor data quality is the number one issue that requires major improvement as the stakes are too high.

The lack of reliable data security measures and strategies results in inaccurate information without appropriate protection. Complete and accurate data is a vital component of the complex healthcare system. Otherwise, organizations will not be able to deliver high-quality care to their patients.

Methods to Improve Data Quality

Integrated Data Analytics

Every time you need to fill in possible healthcare data quality gaps, you will also need to understand the importance of integrated data analytics.

The medical data set should include the following three points:

1. Capture. At this stage, staff or automated systems deliver necessary data to electronic health record (EHR). The data confirms that a particular event has happened (returned lab results or an encounter). Clinicians enter all results accurately.
2. Structure. This is the process of storing captured information. Keep in mind that all data should be kept in a proper format. Make sure it is delivered on time to the right place, and keep an eye on the correct values, as well as EHR platform configurations and settings.
3. Transfer. At this stage, you need to extract data and deliver it from storage to a back-end database connection. In other words, you need to make a conclusion based on previous health records. Here, clinicians should use key factors, in addition to an efficient transport mechanism, that will ensure the quality of outgoing data.

Use tools to qualify and quantify collected data

If there are no tools or metrics to measure a particular set of data, you will never be able to improve it. There are advanced methods to generate, store, and evaluate the data in a healthcare organization, and using them could be beneficial for the patient care, but only a structured, comprehensive and holistic approach to the health data collected across various sources would ensure the better service.

Manage the process, not the staff

Whenever you need to improve care quality, you need to manage the process; you don’t, necessarily, need to manage the nurses and physicians. Organizations need to provide education programs to inform staff on how to use specific tools, methods, and techniques that appear in the healthcare marketplace.

On-time data delivery in the right format

If the medical facility wants to manage care delivery process, it definitely needs accurate and visible data. Moreover, that data should be delivered on time in the proper format, and to the right location. The key to success is to get the health information into the right hands. In other words, it should be processed by responsible clinicians ready to handle the task.

Smart Cogs in Healthcare

Smart cogs are clinicians on the front-line responsible for the process of delivering care to the patients. These individuals should not only be intelligent and experienced but also highly educated. Clinicians are supposed to be committed to always improve the quality of their inputs to the healthcare data.

The majority of clinicians have a clear understanding of the role that new technologies and data collection tools play in today’s healthcare industry. They need to consider the importance of a data-driven approach for the whole digital health system. The only thing they need is the right support, training and other ways to learn about the possibilities they have and the tools they can use to advance own professionalism together with the level of the provided service. This is where organizations could and should help their staff on a regular basis.