Last Updated | June 7, 2024
Due to the massive influx of complex data, the healthcare industry faces significant data analytics and management challenges. Without the right tools, healthcare organizations struggle to extract meaningful insights from this data, hindering their ability to improve patient care and organizational efficiency. Healthcare data becomes meaningful only when analyzed using advanced data analytics tools.
Data analysis in healthcare is crucial in understanding what sickens people and better-understanding illnesses. Healthcare innovation can be attributed to health data analytics, which gives doctors and researchers essential insights into diseases and their prevention. Leveraging data analytics in healthcare industry is imperative to improving treatment for various medical conditions.
What Is Data Analytics In Healthcare?
Data analytics in the healthcare industry revolutionizes the collection, processing, and analysis of complex healthcare data, empowering healthcare practitioners to make informed decisions. This automation has a profound impact, driving significant reductions in medical costs, personalized treatment, patient behavior analysis, and health plan data analytics.
Healthcare analytics data plays a crucial role in this process. As one of the most complex data sets generated in any industry, data analytics in medicine includes real-time vital signs, telemedicine records, and electronic healthcare records (EHR).
Each patient generates vast data, which must be stored, structured, and analyzed to provide holistic healthcare treatment. Additionally, strict government regulations require healthcare organizations to ensure the secure storage and handling of this data during big data analytics.
Advanced analytics in healthcare offers organizations the tools to meet these regulatory requirements while delivering high-quality healthcare services to patients. According to one Mckinsey and Co. report, hospitals using medical device data analytics in healthcare result in up to 30% cost savings over five years. This trend indicates that data analytics and healthcare are transforming the healthcare industry, influencing its clinical, operational, administrative, and financial aspects.
The Role of Data Analytics In the Healthcare Industry
The role of data analytics in healthcare is crucial for improving patient care and organizational efficiency. It involves collecting data from various organizational departments to create a central, structured data repository. A central data store helps the hospital consolidate essential doctor, patient, financial, administrative, and operational data in one place instead of in different locations.
Real-world benefits of a centralized data repository are seen when AI models analyze data sets to extract healthcare insights. Having data in one place allows the model to access all the data it needs to conclude, making AI medical diagnosis a reality instead of a pipe dream. Additionally, the benefits of data analytics in healthcare enable healthcare practitioners to offer better-quality services to patients by adopting a holistic treatment approach and providing personalized healthcare services.
Analytics and healthcare are deeply rooted in their potential to help organizations stay competitive. Healthcare organizations need advanced software and tools to transform complex data into insightful information, such as AI healthcare data analytical solutions. This technology enables them to maintain a highly structured data repository with AI data interoperability, facilitating well-informed decision-making for improved efficiency and quality of services.
With data and analytics in healthcare, healthcare professionals become comfortable using the technology and can better understand their services by receiving detailed and structured patient information. Understanding the importance of data analysis in healthcare enables them to offer personalized, holistic, and precise disease treatments, ultimately improving patient outcomes.
- Disease Prediction and Prevention
- Care Coordination
- Customer Service
- Financial Risk Management
- Fraud & Abuse Detection
The Importance of Big Data Analytics In Healthcare Industry
Due to a better understanding of the importance of data analytics in healthcare, the industry has undergone a significant transformation in the form of:
- Shifting from a volume-based business to a value-added business that maximizes patient experience through personalized services.
- Placing doctors, physicians, and staff under constant pressure to deliver high-quality, value-added services with better outcomes
- Healthcare organizations compete to offer patients more valuable and affordable services, impacting the industry’s financial structure.
Data analysis in healthcare plays a crucial role in this transformation, benefiting:
- Patients
- Healthcare organizations
- Insurance companies
- Governmental bodies
Additionally, healthcare insurance companies are adopting value-based, data-driven payments instead of traditional fee-for-service models, leveraging Electronic Medical Records (EMRs) to provide insurers with more customized and effective services.
Applications Of Data Analytics In Healthcare For Practitioners
Here are different examples of the use of analytics in healthcare. Each example shows how far healthcare has come thanks to the availability and analysis of healthcare data.
Disease Prediction and Prevention
Advanced analytics in healthcare plays a crucial role in disease prediction and prevention. It leverages machine learning capabilities to analyze historical patient records and identify patterns in severe diseases. This enables doctors and physicians to take preventive measures, minimize complications, and improve patient outcomes.
Care Coordination
Data analytics and healthcare provide real-time insights that give doctors a second chance to save patients’ lives in emergencies. Beyond emergency care, the technology helps caregivers care for patients better and sends alerts about patient health, enhancing overall care coordination.
Customer Service
Health data analytics significantly impacts customer service in healthcare by offering structured and filtered data. This enables healthcare practitioners to personalize treatment, streamline billing and payment processes, and provide a seamless healthcare experience thanks to data analysis in healthcare.
Financial Risk Management
Data analytics backed by artificial intelligence (AI) helps healthcare organizations manage financial risks such as unpaid bills, underutilized records, and lower reimbursements. Predictive analytics can determine accounts owed payments, identify unpaid bills, and identify insurance coverage to improve cash flow.
Fraud & Abuse
Health data analytics is essential in detecting and preventing fraud and abuse in healthcare. By identifying potential patterns of fraudulent activities, hospitals and healthcare organizations can avoid these issues, ensuring the integrity of their operations and improving the overall quality of services.
3 Aspects Of Data Analytics That Will Shape The Future Of Healthcare
Applications of Data Analytics in Healthcare for Patients
Population Health Management
The rise of data analytics technologies in healthcare, including machine learning, deep learning, artificial intelligence, and others, has led to the development of Population Health Management (PHM) services.
PHM has shifted healthcare services from treatment and response to prediction and prevention. Powerful predictive analytics can identify risk patterns for chronic diseases in patients at early stages, enabling healthcare practitioners to act in time and avoid complexities in later stages. Predictive analysis saves lives and helps lower treatment and cure costs for patients.
Health Tracking
The key to healthcare services is predicting health risks for patients before they become chronically ill. This can be achieved by implementing powerful data analytics technology with sufficient training data to train models.
These models can closely analyze medical records to identify critical patterns predicting potential disease risks, acting as a healthcare tracking system that offers faster and better services to patients.
With healthcare tracking technology, healthcare organizations can track patients’ vital statistics while developing preventive care methodologies for early treatment and cure. The technology also helps patients develop chronic illnesses by providing proper care at the right time.
Industry Advancement
Data analytics technology has enormous potential for developing Health Business Intelligence (BI) solutions in the future. It can analyze a massive amount of complex medical data to build the best treatment options personalized to a patient’s medical history.
Build vs Buy Data Analytics In Healthcare Industry – What you need to know.
So far, we’ve extensively covered the role of data analytics in healthcare. This section explains whether healthcare organizations should build their own data analytics solution or buy a pre-built one.
Build
Building a data analytics platform gives healthcare organizations extensive control over platform personalization and control. A custom-built analytics platform is built around the organization’s needs and required data structure. However, creating a custom data analytics platform is expensive because you must make a team with data scientists, engineers, and even healthcare IT professionals.
Buy
A pre-built data analytics solution will cost less upfront and hit the ground running after implementation. Pre-built solutions will vary because different vendors offer varying features and functions, making it essential for healthcare organizations to have precise data analysis requirements. However, it might be challenging to find the exact fit, and customization options will be limited.
Challenges
Despite the massive potential for business intelligence (BI) solutions in data analytics and healthcare, the industry is slow to adopt these technologies. One primary reason for this is the inherent complexity of implementing BI solutions. The complexities, including connectivity, security, integration, and implementation, are significant barriers to adopting BI solutions in healthcare.
Solution
Rather than building an in-house analytics solution, a more effective approach is to purchase a data analytics solution from a professional tech business. This allows for seamless integration with existing infrastructure, making it easier for healthcare organizations to implement and leverage the power of data analytics technologies.
Folio3 Offers Custom Healthcare Intelligence and Health Data Analytics
If you’re looking to leverage the benefits of big data analytics in healthcare, medical data analytics, and patient data analytics or use data analytics in healthcare, Folio3 is here to help.
With several years of experience in healthcare data analytics services, Folio3 Digital Health will help you take your dreams of healthcare data analytics and management and make them a reality. All Folio3 Digital Health products are FHIR and HIPAA-compliant, ensuring all essential data is always protected.
Our team of designers, developers, and testers will help you from ideation to deployment and maintenance, being there every step of the way.
Conclusion
Healthcare data analytics plays a vital role in the healthcare industry by enabling informed decision-making, improving patient outcomes, and enhancing operational efficiency. By leveraging advanced data analytics tools and techniques, healthcare providers can better understand patient needs, streamline clinical workflows, and reduce costs. This, in turn, contributes to improved patient satisfaction, better health outcomes, and more effective resource allocation.
As the healthcare landscape continues to evolve, the importance of data analytics in the industry will only grow. With the increasing availability of electronic health records, wearable devices, and other data sources, healthcare providers must be equipped to harness this data to drive meaningful change. By embracing healthcare data analytics, healthcare organizations can position themselves for long-term success, better serve their patients, and stay ahead of the curve in an ever-changing industry.
Frequently Asked Questions
How Does Data Analytics Help Healthcare?
The two main ways that data analytics in healthcare industry work include:
- Improving patient care, patient health data, and medical records analysis to find at-risk patients, predict potential health issues and create customized treatment plans.
- Using data analytics to reduce costs, improve efficiency, streamline day-to-day operations, and better resource allocation.
How Is Data Analytics Used in Healthcare?
- Doctors analyze patient data to assess their physical condition
- Hospitals to track patient readmission and use the findings to improve their numbers
- Insurance companies to create more accurate insurance pricing models
What Is the Impact of Data Analytics in Healthcare?
Using data analytics in healthcare allows healthcare organizations and professionals to create more personalized treatment plans, reduce healthcare costs, and improve patient care quality.
About the Author
