Google Uses Big Data to Provide Critical Information for Prompt Disease Control
Back in 2009, a new flu virus - H1N1 was discovered, and it spread quickly. In the United States, the Centers for Disease Control and Prevention (CDCP) requested doctors inform CDCP of new flu cases so that CDCP can take action to contain its spread.
Big Data at United Healthcare
United Healthcare, like many large organizations pursuing big data, has been focused on structured data analysis for many years, and even advertises its analytical capabilities to consumers (“Health in Numbers”). Now, however, it is focusing its analytical attention on unstructured data - in particular, the data on customer attitudes that is sitting in recorded voice files from customer calls to call centers.
Advanced data analytics key to increasing pharmaceutical sales
For nearly 50 years, CCM Pharmaceuticals or CCM has had a remarkable corporate presence in Malaysia to provide sustainable solutions based on innovative sciences to the healthcare, agricultural and manufacturing sectors. To sustain its growth in the next 50 years, this company has turned to Big Data Analytics (BDA) to enhance its sales performance in order to boost market penetration within Malaysia, regionally and beyond.
Healthcare Service Provider Uses Big Data To Predict Malfunctions or Performance Issues
The leading blood glucose monitoring systems provider continuously monitors glucose levels in people with Type 1 diabetes via devices implanted directly in patients’ abdomen. The company uses Striim to monitor the health of these implanted devices in real time and to predict any malfunctions or performance issues.
Striim collects device data in real time and performs multi-source correlation on data-in-motion for early prediction of device errors. With Striim, the company can offer high-quality devices to diabetes patients and complies with FDA’s strict Class 3 regulations.
Reduced time-to-issue-detection from 1 week to seconds using real-time analytics.
Significantly improved patient safety and ensures compliance with FDA regulations.
Gained the ability to improve service quality with real-time feedback from implanted devices.
Healthcare Provider Improves Patient By Reducing Wait Time
For this emergency room application. Striim analyzes patient sensor data by enriching it with their exact location within the hospital, and tracks how much time they spend in each service area of the emergency room. When wait times exceed thresholds, alerts are immediately sent, allowing more resources to be allocated and wait times reduced.
Striim helps improve patient care by reducing wait time and ensure timely attention to the most critical patients. It also enables better use of existing resources by allowing the staff to work in different areas when they are not busy, ultimately reducing operational costs.
Provides better care to ER patients by monitoring wait times and allocating more staff to crowded departments.
Improved patient experience by reducing wait times significantly and streamlining end-to-end service delivery in the ER.
Manages the ER staff based on real-time patient needs and increases overall staff productivity.
Not really a case study, but it is surely a case for study