Your premier partner in Healthcare Data Analysis
Leverage our deep IoT and analytics experience to advance care quality, gain insights into patient satisfaction, data-driven approaches for chronic disease management, and more.
The ABCs of Data Analysis in Healthcare: data saved is data earned.
Data analysis in healthcare is like using a super-smart computer to look at a lot of health information from many people. This computer can spot patterns, like which treatments work best or how to prevent diseases. It’s like having a detective that helps doctors and hospitals make better choices for keeping everyone healthy.
Numbers speak louder than words:
The healthcare sector produces roughly 2,314 exabytes of data each year, growing at an average rate of 47% annually over the last seven years. Just imagine, one exabyte equals a billion gigabytes, and it’s estimated that the total of all human speech ever spoken amounts to just about five exabytes. *American Hospital Association
5 types of Healthcare Data Analytics that transform Big Data into insights.
Explained in simple words.
Type #1: Descriptive Analytics
This is like reading a diary entry about what’s happening in healthcare right now. It looks at current or past data to tell us what has happened. For example, it might show how many people visited a doctor for flu last month.
Type #2: Diagnostic Analytics
Think of this as being a detective. It tries to find out why something happened. So, if a hospital notices an increase in flu cases, diagnostic analytics helps figure out why – maybe there was a flu outbreak in the area.
Type #3: Predictive Analytics
This is like a fortune-teller for healthcare. It uses data to predict what might happen in the future. For instance, it could predict which patients are at risk of developing diabetes, so doctors can take early action.
Type #4: Prescriptive Analytics
Imagine this as a wise advisor. It goes a step further than predicting; it suggests what actions should be taken. If a predictive analysis shows a patient is at high risk of diabetes, prescriptive analytics might recommend a specific diet and exercise plan.
Type #5: Cognitive Analytics
This is like having a super-smart robot that learns and thinks. It uses artificial intelligence to understand, reason, and learn from healthcare data. For example, it can help doctors make better decisions by analyzing medical research, patient history, and current treatments all at once.
What are the origins of Healthcare Data?
8 medical Data Analytics development scenarios for integrating Big Data in healthcare.
Custom Solutions
Embedded BI (Business Intelligence)
Platform Customization
Real-time Data Analysis
Patient Data Mining
Predictive Risk Modeling
Telehealth Data Integration
Healthcare IoT Analytics
Top 10 Healthcare Data Analytics Use Cases unveiling the future of medical care.
Disease course prediction
Predicting how a disease will progress helps doctors plan the right treatments and give patients better care.
Treatment planning
It’s like creating a roadmap for each patient’s treatment, making sure they get the best care possible.
Chronic condition management
Managing long-term health issues, like diabetes or heart disease, to keep patients healthy and reduce hospital visits.
Self-harm prevention
Using data to identify individuals at risk of self-harm or suicide so that they can receive the help they need.
Resource allocation
Like distributing game pieces in a board game, this is about using data to allocate resources like hospital beds, doctors, and equipment efficiently.
Patient load management
Making sure hospitals have enough space and staff to handle all their patients without becoming overwhelmed.
Supply chain management
Ensuring that hospitals have the right medicines and equipment when they need them, just like making sure a store has enough products on its shelves.
Fraud prevention
Detecting and stopping any dishonest or fraudulent activities in healthcare billing or insurance claims.
Patient engagement
Engaging patients in their own healthcare by providing information and tools to help them make healthier choices.
Data security
Keeping patient data safe from hackers and ensuring that only authorized people can access it, like locking a diary with a secret code.
We at SumatoSoft develop custom Healthcare Data Analysis solutions for any challenges.
Get proof of our successfully completed projects in the profile.
Why companies choose SumatoSoft for their healthcare projects.
Healthcare Data Analytics services We offer
Custom Healthcare Data analytics solutions
Healthcare data visualization tools
Electronic Health Record (EHR) system integration
Healthcare predictive analytics models
Patient engagement analytics
Custom Healthcare Data analytics solutions
You will get tailored analytical services specifically designed to fit the unique needs and challenges of your healthcare organization. These solutions help in processing and interpreting complex medical data to provide actionable insights that improve patient care and operational efficiency.
Healthcare data visualization tools
You will get sophisticated tools that translate intricate healthcare data into easily interpretable visual formats. This service enhances the understanding of complex data sets and aids in the reporting process, making data-driven decision-making more accessible for healthcare professionals.
Electronic Health Record (EHR) system integration
You will get services that efficiently integrate your existing Electronic Health Records with advanced data analytics platforms. This integration allows for seamless data management and analysis, improving the accuracy and accessibility of patient information across different healthcare systems.
Healthcare predictive analytics models
You will get predictive models that utilize existing healthcare data to forecast future trends, patient outcomes, and resource needs. These models are instrumental in proactive healthcare planning and decision-making, helping to anticipate and address potential healthcare challenges.
Patient engagement analytics
You will get analytics focused on understanding and enhancing patient engagement and overall experience. This service provides insights into patient behaviors, preferences, and satisfaction, enabling healthcare providers to improve patient-centered care.
Success stories of our Clients
Real-time blood glucose monitoring app for a healthcare technology firm
Adaptive health monitoring mobile app for personalized wellness programs
Clinical trial matching platform for enhanced patient recruitment
Our Rewards & Recognitions
Technologies we work with
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Questions You may have
Can Healthcare Data Analysis be integrated with my existing systems?
Yes, our custom solutions ensure smooth integration with your current systems, ensuring a seamless transition and minimal operational disruption.
How do I start using Healthcare Data Analysis for my organization?
Contact us through our website, and our team will guide you from the initial consultation to full implementation and support.
What range of data can be analyzed with your services?
Our custom solutions are versatile, analyzing data from various sources, including medical equipment, patient records, and more, tailored to your specific needs.
How does SumatoSoft guarantee system reliability?
We use redundant systems and continuous monitoring to assure high availability, along with proactive maintenance for minimal downtime.
Are your Data Analysis services scalable?
Yes, our services are designed to grow with your business, from small-scale to extensive data analysis needs.