
Most countries today face the challenge of offering good quality healthcare services at a reasonable cost. When the doctor to patient ratio is poor, especially in smaller towns, use of technology becomes critical in filling the gap. AI is playing much role in areas like diagnostics and biological health monitoring using devices like fit-bits. AI is being used to find vaccines and medicines for deceases.
Further, high cost of operations for providers mean there is a need for intelligent automation to improve processes. Hospitals are using RPA, OCR and ML for improving processes like managing patient appointments, invoice payment processing and health data management. Players are using Geographical Information System (GIS) for population health monitoring and planning location for healthcare facilities.
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Such an intelligent automation can save precious time of resources in doing mundane tasks and improve customer satisfaction for turning around the renewal agreements quickly.
Case Studies
A leading Health insurer
The insurer conducted customer satisfaction study for their insurance claim process. We helped the client use NLP based Machine learning to analyze the customer feedback calls to assess topics highlighted by the customers and their sentiment related to claims experience.
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