The Challenge
Healthcare service providers in USA raise large number of requests to update their demographic record which are executed by associates. Current system does this through manual process where managers identify the requests based on priorities and distributes to the associates based on their availability, experience and skillsets. However this causes significant delays on overall process cycle. As upon receiving the task from the managers, associates work on two systems simultaneously. Where one system captures the actual updates & the other tracks the progress of the request. The associates have to copy the data to be updated from one system to another manually, which leads to a huge risk of incorrect information updates in the system, costing significant resource time, as the associates fillout out the requests. Our task was to reduce the effort, cost and increase productivity.
Our Solution
Leverage Pega Case Management v7.2 to enable efficient push routing across various group of associates.
Leverage Pega Get Next functionality to enable seamless assignment of tasks.
Leverage Pega OOTB Urgency calculation conjunction with business rules to prioritize open tasks
Enhance user interface by using Pega OOTB features such as Action Menu, Pulse and 360-degree provider view
Leverage Pega Situational layer cake to address complex routing logic such as State and request type combinations which varies between associates within same group.
Leverage Pega OOTB Skill and load balancing mechanism to find out the right associate to route the task.
Leverage Pega’s delegation rule to enable Managers to manage associate’s entitlement matrix in a centralized space.
Output
The high degree of success of the project can be gauged by the following metrics:
We reduced the request processing cycle time from an average of 50 minutes to 10 minutes.
We reduced the Associate assignment of task from average 30-40 minutes to less than a minute.
We reduced the Provider’s Request handling time improved from 400-450/day to 2000/day.
We saved approximately $1.8M per month for our client.
