Dental Appointment Optimization System for Billing Efficiency
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Solution Overview
Problem
Dental offices face inefficiencies in scheduling appointments due to uncertainties in time requirements, leading to either insufficient or excessive time for procedures, which can result in disrupted schedules, incomplete treatments, and reduced productivity.
Innovation Solution
A computer-implemented method that optimizes dental procedures by accessing data on procedures, billing rates, and minimum times to generate a list of procedures for a scheduled appointment, ranking additional procedures based on monetary value, frequency, and time-allocation requirements, and automatically adjusting the appointment set to optimize billing value and ensure minimum time allocation for each procedure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the scheduled timeslot for an appointment is extended to ensure complete patient treatment, then patient care quality is improved, but practitioner productivity and schedule efficiency deteriorate
Solution Approach 1:
The system performs preliminary analysis of patient data, procedure requirements, and scheduling constraints before the appointment occurs. It pre-calculates the optimal set of procedures that can be completed within the scheduled time slot, ensuring that the treatment plan is both comprehensive and time-feasible, thereby maintaining patient care quality without extending appointment duration.
Solution Approach 2:
The system dynamically adjusts the procedure selection based on individual patient needs, historical data, and real-time scheduling constraints. It optimizes the procedure set for each patient-practitioner pairing, adapting to varying treatment requirements while maintaining overall schedule efficiency and practitioner productivity.
2Productivity
If the scheduled timeslot for an appointment is shortened to increase practitioner productivity, then schedule efficiency is improved, but patient care completeness deteriorates
Solution Approach 1:
The system pre-analyzes patient information and procedure requirements before scheduling to determine the maximum feasible treatment scope within the allocated time slot. This preliminary planning ensures that the selected procedures can be completed within the shortened timeframe while still providing comprehensive care.
Solution Approach 2:
The system changes the parameters of procedure selection based on available time, patient priority, and treatment urgency. It dynamically adjusts which procedures are included in the appointment set, prioritizing high-value and time-sensitive procedures to maintain care completeness within condensed time slots.
3Reliability
If additional mandatory tasks (PPE, COVID screening, rinse) are added to the appointment requirements, then patient safety is improved, but available treatment time is reduced
Solution Approach 1:
The system incorporates mandatory safety tasks (PPE donning, COVID-19 screening, pre-rinse) into the preliminary planning phase. It calculates the time required for these tasks and adjusts the procedure selection accordingly, ensuring that safety protocols are completed without encroaching on the time allocated for actual treatment procedures.
Solution Approach 2:
The system dynamically adjusts the treatment procedure selection based on the time consumed by mandatory safety tasks. It adapts the procedure set to fit within the remaining available time, prioritizing procedures that provide the highest patient value within the constrained timeframe.
4Productivity
If setup and cleanup time is reduced to maximize patient appointment capacity, then schedule density is improved, but practitioner workload intensity increases
Solution Approach 1:
The system performs preliminary organization of the procedure set to minimize setup requirements. It selects procedures that can be performed with minimal equipment changes and preparation, reducing the time and effort required for setup between appointments while maintaining high schedule density.
Data Source
AI summary
A computer implemented optimization method automatically provides a set of dental procedures to be performed during a scheduled appointment. A processor determines, from the first plurality of dental procedures, a first list of dental procedures that are to be performed for a first patient during the scheduled appointment. The processor also generates a second list of additional dental procedures that are available to be optionally performed for the same first patient during the same scheduled appointment, and ranks the additional dental procedures based on at least one criterion. The processor automatically generates from the first list and from the second list an appointment set of procedures to optimize the billing value of the scheduled first appointment.