Digital transformation in the healthcare sector has created an abundance of public and private data, which can be strategically collected, organized, analyzed, and leveraged by providers to improve the experiences of their patients and/ or customers, as well as drive internal efficiency and cut costs. This is accomplished by integrating cutting-edge technologies, such as:
- Artificial intelligence (AI) and machine learning (ML) tools
- Cloud computing platforms
- Medical IoT devices
- Health information exchange (HIE) systems
- Blockchain networks
A growing number of hospitals, pharmacists, insurers, private practices, wellness companies, and other organizations in the healthcare space are adopting big data analytics tools and processes to better understand their business, its patients, and the surrounding market. Conversely, providers that avoid the benefits of harnessing internal and external data will continue to miss out on opportunities to improve their business and gain a competitive advantage in their niche.
Before we get into the key benefits, let’s define the different types of big data analytics, and how each is currently being applied by healthcare professionals today.
- Descriptive analysis: This involves examining and describing events that have already happened. For example, medical researchers were able to determine how contagious COVID-19 was based on the rate of positive tests among different populations.
- Diagnostic analysis: This approach focuses on discovering the cause or causes of an event. After collecting and analyzing a patient’s symptoms, AI technology can be used to diagnose the illness or injury.
- Predictive analysis: A common practice among businesses in all industries, predictive analytics involves collecting historical data, trends, and other helpful insights to make intelligent projections for the future—then adjusting organizational efforts and allocations based on those findings. In healthcare, researchers are analyzing COVID-19 data from the past two years to forecast the upcoming seasonal spread of the virus.
- Prescriptive analysis: This process aims to identify actions an organization can take to achieve a certain outcome. When implementing preventative treatment plans for patients, doctors will assess various types of clinical data, such as the patient’s pre-existing conditions and their family’s medical history, as well as relevant historical trends and insights within the medical field.
Of course, these are only a few high-level examples of how big data analytics is being used to modernize medical processes and experiences. There’s a wide range of advantages to intelligently utilizing data in healthcare—from saving lives to making life easier for patients or customers, to simply speeding up internal workflows and saving money.
Let’s dive deeper into the key benefits of data analytics in healthcare.
Superior patient experiences and outcomes
In general, data science helps medical professionals better understand their patients. There are many ways to learn about your patients’ wants, needs, and concerns—with the most obvious being to simply ask them directly. Healthcare providers will often send surveys to their patients to collect feedback after a checkup, surgery, or other procedure.
When it comes to digital products like your business’ marketing website, telehealth platform, or customer portal, collecting user data with software like Google Analytics is paramount. This allows you to see what’s working and what isn’t, so you can intelligently modify the front-end experience and exceed the expectations of various user types.
For a doctor looking to diagnose an illness, recommend treatment options, prescribe prescription medications, or all of the above, the advantage of having access to as much clinical data as possible cannot be overlooked. In addition to making in-person and virtual patient experiences faster, smoother, and more enjoyable, data-driven healthcare is helping people live happier, healthier lives.
With predictive modeling tools and processes, healthcare professionals can better anticipate patient outcomes. Analyzing micro- and macro-level data—like individual behavior and broader industry statistics—enables physicians to effectively evaluate the potential benefits and consequences of certain treatment plans, prescriptions, surgeries, and so on.
This process is currently being used by hospitals to determine the likelihood of a patient’s readmission. It’s also being used by mental health professionals to assess the risk of a patient inflicting harm on themselves or others.
Real-time updates and alerts
Beyond examining historical data to predict future outcomes, healthcare analytics technologies are also being leveraged to facilitate patient care in real time. Wearable devices that monitor a patient’s blood pressure, breathing rate, muscle activity, and so on are becoming increasingly popular among healthcare practices.
Using a combination of IoT, cloud computing, and AI technology, data from a patient’s wearable is sent to their doctor’s internal system, where it is then organized and analyzed by a bot—specifically trained to identify deviations and irregularities in inpatient data. If the bot notices something off, it will send an alert to the responsible healthcare provider, who can then review the data and act accordingly. This kind of data analytics is helping doctors provide patient care when it’s most needed, and get in front of life-threatening emergencies—such as heart attacks and drug overdoses—before they occur.
Healthcare is one of the most targeted industries when it comes to fraud, identity theft, and cyber attacks. Failure to comply with HIPAA standards and cybersecurity best practices can cause irreversible damage to your healthcare brand—meaning broken patient relationships, expensive government fines, and lost revenue.
Fortunately, AI- and ML-powered bots can be leveraged to spot fraudulent behavior before it makes an impact on your business. These bots compare real-time information against historical business data to identify patterns—and most importantly, deviations from those patterns—so that fraudsters are identified in a matter of seconds.
This technology is especially useful when managing online healthcare platforms, where users regularly provide sensitive information, such as their home address, personal medical history, credit card numbers, login credentials, and so on. An advanced healthcare analytics solution with fraud detection capabilities will automatically send an alert to system administrators if it notices an abnormally high number of logins, transactions, or requests from a single account.
High operational efficiency
We’ve established that collecting, managing, and analyzing clinical data from various sources is key to improving patient care, predicting patient outcomes, and protecting private information. But it’s also important to acknowledge the benefits of big data analytics from a strictly operational perspective.
With highly intelligent, well-integrated data analytics solutions, you can automate manual, time-consuming tasks—and put more resources toward higher-priority objectives, like communicating with patients and growing your business. For instance, rather than having an employee collect large volumes of data from disparate sources, you can deploy software that’s designed to automatically pull that information and compile it into a sophisticated, intuitive report.
Plus, predictive analytics solutions help you identify improvement opportunities within your organization. With internal business data, you can gain a better understanding of how long certain processes take, which parts of the process are creating roadblocks, and so on. This allows you to optimize internal workflows, lower operational costs, and increase revenue moving forward.
Partner with Codal to experience the benefits of data analytics in healthcare
When your healthcare organization is ready to embrace the power of big data analytics, where do you start? What custom solutions will need to be built? What changes must be made to your business's technological infrastructure? What third-party tools and databases will you need? And how will you effectively integrate these new technologies and processes into your current ecosystem?
As your digital transformation partner, Codal will design, develop, test, launch, and manage digital solutions that enable your business to maximize the value of internal and external healthcare data.
Over the past decade, we’ve worked with healthcare organizations in various niches to revamp their online presence, improve patient and customer experiences, and optimize internal workflows through data analytics. This often involves building out data visualization platforms, where information from public health records, internal web applications, third-party systems, and other sources can easily be accessed, analyzed, and reported—all from a centralized dashboard. Also, our team is well-versed in HIPAA compliance and other government regulations, so everything we build follows healthcare industry standards and best practices.
Interested in learning more about the benefits of big data analytics in healthcare, and how Codal can help transform your business? Get in touch with a member of our team today!