Data analytics play a crucial role in numerous industries, including healthcare. Right now, healthcare data analytics are set to make a massive difference in the way medical professionals treat patients. By leveraging data analytics, healthcare centers can reduce costs, streamline administrative tasks, improve patient care quality, and even predict disease outbreaks.
As we move into the new decade, we need to assess and analyze how we can leverage data analytics to improve the healthcare industry. In its latest blog post, the data analytics experts at Iron Bridge will cover:
- A general overview of healthcare analytics
- Examples of data analytics in healthcare
- Five ways that healthcare analytics can transform how the healthcare industry functions for the better
Keep reading to learn how your company can leverage data analytics to improve patient outcomes and employee performance now.
What is Healthcare Data Analytics?
Let’s start by reviewing the basics of healthcare analytics and why organizations are planning to take a deeper dive into data analytics for 2021.
The concept of healthcare data analytics is simple. Data analytics platforms take large quantities of health-related information and consolidate it into a digital format before performing in-depth analysis. Users must closely analyze this data to gain useful insights from it. Managers can leverage healthcare data analytics on both a micro and macro level.
But when compared to other industries, healthcare analytics are the most complex out of all of them. This complexity can be partially attributed to electronic health records (EHRs), which often source data from multiple resources. EHRs must also comply with numerous federal regulations. As a result, healthcare providers need access to secure and connective data analytics solutions.
5 Ways That Data Analytics Improve the Healthcare System
Healthcare data analytics play a crucial role in the future of medicine.
Already, healthcare analytics is set to change the medical industry for the better. Currently, healthcare data analytics are used to:
- Increase patient engagement
- Determine staffing needs
- Prevent opioid abuse
- Identify people who are at risk of developing certain diseases
- Reduce human error
Let’s explore each topic further in the following sections.
1. Increase Patient Engagement
Health tracking devices like Fitbit and Apple iWatch have recently grown in popularity among consumers. These devices can track people’s heart rates, sleep patterns, steps, and even hydration levels. Patients who track their health through these devices are more incentivized to lead a healthier lifestyle. In turn, this can reduce future visits to the doctor.
2. Determine Staffing Needs
Finding the perfect balance of staff members can be challenging. You don’t want to understaff your team, as that can lead to burnout and poor patient outcomes. But you don’t want to overstaff either, as that can cause your organization to lose money.
To prevent staffing problems, hospitals are starting to use big data analytics to forecast admission rates up to 15 days in advance. This allows them to to predict the number of staff members accurately they’ll need for a particular shift. Adding extra staff members for days they predict will be busy, can successfully reduce wait times and improve patient outcomes.
3. Prevent Opioid Abuse
According to a 2019 report by the Centers for Disease Control (CDC), an average of 130 U.S. citizens die from an opioid dose every day. To help prevent further opioid abuse among more Americans, healthcare data analysts are starting to analyze insurance and pharmacy data from patients to determine their risk for opioid abuse.
4. Identify Patients Who Are at Risk of Developing Certain Diseases
Predictive data analytics are also currently being used to help treat chronic diseases. With the help of predictive data analytics, medical professionals can determine which patients are at a high risk of developing certain diseases and stage early interventions for them. When assessing different patients, data analysts must take their medical history, socio-economic status, and any comorbidities that put them at a high risk of developing these chronic diseases.
5. Reduce Human Error
A high number of health concerns and insurance mistakes stem from human error. For instance, a physician might prescribe the wrong medication or dosage to a patient. In fast-paced environments that require healthcare professionals to handle multiple patients at once, this risk is especially high. To reduce the chance of this happening, physicians can corroborate medication information with patient data on the fly. If they try to give an inaccurate prescription or dosage, the data system can also alert them to ensure that they aren’t accidentally making any errors.
Data analytics are poised to lead the healthcare industry into a better and brighter future. Iron Bridge is ready to help guide organizations into this promising future with its cutting-edge technology. From the Nuvola Hub to fhirstation, Iron Bridge’s state-of-the-art tech solutions can help different healthcare organizations stay connected and compliant with the latest health regulations. To learn more about our IT solutions, contact the team at Iron Bridge today!