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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A telco typically has numerous enterprise clients with varying duration of contracts for different connectivity services. While part of these contracts data are entered in enterprise systems like SAP, most contracts are stored as MS Word documents which are signed as agreements. Typically, dozens of such agreements are up for renewal every month and updating the new terms at multiple places is a tedious task. Fields like newly agreed rates, duration, discounts, service levels, payment terms, etc. have to be changed every time, which takes up large amount of human resource time. You can use intelligent automation which can peruse through emails, PDFs, MS Word and MS Excel documents to identify and pick new data fields (e.g. rates, SLAs) which have to be inserted in the new contract. Such an intelligent automation system would include RPA for operating ERP and other systems while OCR for reading unstructured data like PDF. Once the new clause related data are picked up and organized, RPA can draft new versions of agreements and make data entries into ERP systems which could be approved by the Commercial and Sales teams.
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.