Why Pharma and Healthcare Data Analytics ?
There is huge amount of data that is being generated in the life sciences industry and often the challenge lies in managing and processing them to gain the right insights. For eg: In a hospital system, from billing, treatment and discharge there are multiple departments that generate different information for one patient. These information has to be pictured holistically by the hospitals to serve that patient better and these multiple different information for multiple different patients will help hospitals to gain many important clinical and business insights. There are EHR systems available to centralize a patient’s information at one place but they are not available on Cloud. On the other hand, major pharma players often want to leverage real world evidence data (RWE) that come from multiple sources to streamline, analyse effectiveness and compare the cost & benefits of its drug against competing products.
With Cloud’s innovative data analytics solutions data from disparate sources could be unified, without having to worry about the security issues or adhering to compliance standards.
8K Miles being a pioneer in serving pharma and healthcare industries for over a decade, we excel in addressing the security and GxP or HIPAA compliance needs while providing cutting edge Cloud analytics services. Our analytics are based on numerous reliable algorithms and methods to obtain latest applicable insights that aid in making effective business decisions.
Some scenarios where Pharma and Healthcare Data analytics
play a role in Life sciences industry
- Prevention of lifestyle diseases based by tracking one’s wearables and sensors
- Prediction of Lab equipment maintenance to avoid down time
- Accurate diagnostic and in turn apt treatment for patients
- Realtime healthcare and Clinical analytics for better treatment and care for patients
- Patient readmission
- Calculating length of stay based on the patient’s disease for effective usage of hospital’s resources
- Aids insurance players to predict fraudulent claims and take preventive measures
- Efficient management and analysis of Clinical trials and Real World Evidence data
- Evaluation of public health in near future for government to take necessary steps
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