Geo-dialing Algorithm for Healthcare Provider Scheduling
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Solution Overview
Problem
Current health risk assessment systems face inefficiencies in scheduling health risk assessments, particularly in optimizing the geographic location and travel distance of healthcare providers, leading to suboptimal utilization of time slots and increased travel costs.
Innovation Solution
Implementing a geo-dialing algorithm that identifies candidates for health risk assessments based on geographic proximity and radial distance from the healthcare provider's location, prioritizing candidates within a specified radial distance and adjusting distances using offset values to optimize scheduling and reduce travel time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If candidates are selected without geographic optimization, then scheduling is simpler, but travel time and costs increase
Solution Approach 1:
The system pre-calculates geographic distances between healthcare providers and candidates, and pre-ranks candidates by proximity before scheduling calls are made. This preliminary geographic optimization ensures that when scheduling decisions are made, the closest candidates are already identified and prioritized, reducing travel time without complicating the scheduling process
Solution Approach 2:
The system introduces a radial distance parameter that defines the maximum travel distance a healthcare provider is willing to travel. By adjusting this parameter, the system can optimize between scheduling more candidates (larger radius) versus reducing travel time (smaller radius), dynamically changing the scheduling parameters based on provider preferences and operational needs
2Loss of energy
If geographic proximity is optimized by calculating distances to all candidates, then travel costs are reduced, but computational complexity increases
Solution Approach 1:
The system segments the candidate pool by geographic region and calculates distances only within relevant segments rather than computing all possible provider-candidate distances. This segmentation approach reduces computational complexity while still achieving optimal geographic matching by dividing the large search space into manageable regional subsets
Solution Approach 2:
The system calculates distances to a subset of candidates who are most likely to be scheduled (those within the radial distance and who have not already been scheduled), rather than calculating distances to all candidates in the database. This partial action approach reduces computational burden while maintaining scheduling optimization for the relevant candidate pool
3Productivity
If time slots are populated by calling candidates in random order, then the process is simpler, but time slot utilization decreases
Solution Approach 1:
The system changes the ordering parameter from random to geographic proximity-based ranking. By sorting candidates by their distance to the healthcare provider before making scheduling calls, the system ensures that time slots are populated with the closest available candidates, maximizing time slot utilization while reducing overall travel requirements
Solution Approach 2:
The system replaces manual or random scheduling methods with an automated geo-dialing algorithm that systematically processes candidates in geographic order. This substitution of mechanical/random processes with an automated geographic optimization system improves time slot utilization without requiring complex manual intervention
Data Source
AI summary
A computer-implemented method includes, in one aspect, identifying, in a data repository, (i) information indicative of a health care provider who is assigned to a pre-defined calling zone, and (ii) radius information; accessing scheduling information that comprises a plurality of time slots, wherein each time slot corresponds to a time for the health care provider to perform the health risk assessment; selecting, by one or more computer systems, a particular slot from the scheduling information; for the selected slot, applying a geo-dialing algorithm to candidate information that is indicative of one or more members of one or more health plans who are candidates for scheduling in the selected time slot; identifying, based on application of the geo-dialing algorithm, a candidate with a geographic location that is a decreased distance from a geographic location of the health care provider; and causing a call to be placed to the identified candidate.