Data Analytics in Healthcare

By Data-Core Systems | December 29, 2022

The healthcare industry is a diverse collection of information with the most important goal; the health and well-being of humans. Healthcare data comes from multiple departments and software systems, such as electronic health records (EHRs). Depending on the type of data, the formats also vary. Patients’ medical information can be stored as electronic health records of text and numerical data, while images are used for information such as x-rays.

With the data residing across multiple platforms, there is more room for inconsistencies and errors. Taking full advantage of the wide range of stored information poses a challenge when these factors are taken into account:

1.       Privacy issues: Organizations keep private and secured medical information. This means that there is a lot of concern over safeguarding the data, and companies need to take precaution to make sure that the patient’s information is kept private.

2.       Regulations: Organizations need to comply with certain rules for how to handle the information. Additionally, regulatory requirements are always changing. The amount of information an organization needs to disclose to the public varies from year to year, and with healthcare policies becoming more transparent, it adds to the challenge of keeping up with government regulations.

3.       Complex data: Clinical data can be more complex and unpredictable, especially with new research, discoveries and new or updated patient records coming in often. Since the data comes from many sources, improving data quality is challenging. It is important to be able to put all the data into a standardized format to better understand and analyze.

Organized medical data can help health professionals study disease trends for faster diagnosis and treatment, as well as reduce medical errors such as wrong prescriptions and operation mistakes. Additionally, it ensures the long-term safety of the organization. With the introduction of new drugs and medical practices, safety issues can arise, damaging the organization’s reputation. Identifying these problems early or even better, beforehand can help the company long term.

Health records play a role in how clinical data is stored and organized. EHRs contain clinical data of the overall health of the patient. This includes medical’s history, laboratory test results, immunizations, and allergies. With EHRs, health professionals can share information with other organizations, which allows for records from all clinicians and hospitals to be saved in one software.

With modern techniques in data wrangling, machine learning and data visualization, the healthcare industry can:

1.       Improve patient care: With more structured information, various treatment plans can be easily accessed and compared. Clinicians can notice certain patterns in a patient’s health for faster diagnosis and correct prescriptions.

2.       Support new innovations: The introduction of new drugs comes with safety risks. Data wrangling can help properly evaluate the risks of certain drugs and make sure they align with the FDA’s guidelines. In the long run, it avoids any controversy with the public and boosts the company’s reputation.

Increased productivity: Productivity is increased because of more efficiency with bills and medical refills. It is easier to prescribe the right medication, as well as creates a faster and more organized process for handling costs.