We will be getting the data from various sources like emails, Patients records, devices, diagnostics etc and when it is combined together in streamlined manner, the providers of healthcare can easily recognize inefficiencies in the costs, risks involved. Here they use our solutions for quicker analysis, metrics to do different types actionable data insights on structured and unstructured data, probably real time.
With the services we are providing, patient records are analyzed and anomalies such as frauds in billing will be detected. While patient privacy is being guaranteed, healthcare providers gain a 360-degree view of the patient by storing, processing, and correlating.
As we see in the hospitals always, nurses do rounds and manually monitor patient vital signs. Though a patient is monitored based on time frame, the condition may decline between the times of scheduled visits as it can’t be predicted. So, a quick response during that time will save the lives.
Of course, the latest technologies have made huge difference in healthcare and hospitals have already adopted. With these advanced measurements, Patients are monitored in live and the data that is streamed will be captured into cluster so that whenever a patient gets any problem, hospital staff will be alerted automatically. Using this stream data, healthcare predictive analytics can be done apart and Machine learning algorithms will be written to predict the happening of any emergency even before it could be detected with a bedside visit.
It is not just stopped! The services we provide will be highly useful for the patients with heart disease As you know, the heart attack can be happened any time. When the patient is in hospital , he will be monitored regularly. But it may not be same when they are discharged as many ppl ignore the prescription of the doctor. This ignorance is the main cause for the High/ low BP, Weight gain or sometimes death also. So, to avoid this kind of severe problems, we at Bigdatamatica are providing a personalized solution for patients, where they can monitor themselves or by members of family by just sitting at home.
According to health statistics, Autism is one of major challenges to be faced by the world now-a-days. It affects 1 in 100 children at an annual cost estimated at more than $100 billion. Told by experts, it takes eighteen months to detect autism in a person, who has been affected. Sadly, more than 1 in 4 cases are still undiagnosed at 8 years of age. Many people don’t know that the most common diagnostic test typically takes 2 hours to administer and score.
Dr. Dennis Wall is Director of the Computational Biology Initiative at the Harvard Medical School. In this presentation, he describes a process his team developed for low-cost, mobile screening for autism. It takes less than five minutes and relies on the ability to store large volumes of semi-structured data from brief in-home tests administered and submitted by parents. Wall’s lab also used Facebook to capture user-reported information on autism.
Artificial intelligence running on those huge data sets helps maximize efficiency of diagnosis without loss of accuracy. This approach, in combination with data storage on a Hadoop cluster, can be used for other innovative machine learning diagnostic processes.
Our company uses analytics on speech-to-text records from calls to the call center to identify potential fraudsters.
Our platform will be able to identify providers who demonstrate aberrant billing trends and patterns in Hospitals. We mine data to reveal hidden patterns and relationships that lead to potential waste, overutilization of services and alert providers for investigation.
The doctor can match symptoms to a larger patient database in order to come to an accurate diagnosis faster and more efficiently.
Treating a patient personally is definitely a big thing to improve his health condition. Bigdatamatica’s services provide real-time patient data access so that the treatment decisions can be adjusted in a timely manner.
As mentioned above Healthcare facilities can provide proactive care by continuously monitoring patient vital signs from various smart, connected devices. We stream this data in real-time to detect changes and predict a patient’s need for effective interventions.