Patient Overdue Identification Using Billing Data Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for identifying patients overdue for healthcare appointments are unreliable and often result in incomplete and inaccurate call lists, failing to account for resolved conditions and lacking the necessary precision for scheduling follow-ups effectively.
Innovation Solution
A system utilizing standard diagnosis and procedure codes from billing data to identify patients due for appointments, eliminating those with resolved conditions, and ensuring accurate scheduling by integrating with existing practice management systems without relying on electronic medical records or recall data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods of identifying overdue patients are used, then the process is simple, but the call list is incomplete and inaccurate
Solution Approach 1:
The system segments the patient identification process into distinct components: retrieving recall data from the practice management system, determining current status (appointment scheduled, condition resolved, or still overdue), and generating the final call list. This segmentation allows each component to be optimized independently while maintaining overall system accuracy.
Solution Approach 2:
The system introduces an intermediary processing layer between the practice management system and the call list generation. This intermediary layer retrieves recall data, applies status determination logic, and filters patients based on current condition, thereby improving accuracy without requiring direct modification of the existing practice management system.
2Reliability
If recall data from practice management systems is utilized, then existing infrastructure is leveraged, but the data may be outdated or incomplete
Solution Approach 1:
The system performs preliminary actions by retrieving recall data from the practice management system before final call list generation. This preliminary retrieval allows the system to identify potential overdue patients and then apply additional status determination logic to ensure the data is current and accurate before including them in the call list.
Solution Approach 2:
The system implements feedback mechanisms by continuously checking the current status of patients against their recall data. If a patient has scheduled an appointment or had their condition resolved, the system receives feedback and removes them from the overdue list, ensuring the call list reflects the most current patient status.
3Loss of information
If manual tracking of patient contacts is implemented, then contact history can be recorded, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system enables self-service by automatically tracking and recording contact history and appointment scheduling outcomes. The system maintains its own call list and updates patient status without requiring manual intervention, thereby preserving contact information while maintaining high processing efficiency.
Solution Approach 2:
The system replaces manual mechanical tracking processes with automated electronic data processing. Instead of staff manually recording contact history and updating patient status, the system automatically retrieves data, determines status changes, and maintains the call list, eliminating human error and increasing productivity.
4Productivity
If automated calling systems are used, then reminder messages can be sent efficiently, but patients who have scheduled appointments may be contacted unnecessarily
Solution Approach 1:
The system implements dynamic filtering by continuously evaluating patient status before adding them to the call list. The system checks whether patients have scheduled appointments or had conditions resolved, and dynamically adjusts the call list accordingly. This dynamic approach ensures efficient contact only with patients who actually need reminders, avoiding unnecessary calls to patients with scheduled appointments.
Data Source
AI summary
A method and apparatus for identifying overdue patients using standard billing or other office management data, so that patients can be contacted and invited to make an appointment. The invention begins by querying the diagnosis codes for each visit from the billing or other encounter tables, and matching these with a set of target medical conditions requiring regular care. Procedure codes and encounter dates for past visits are queried for these patients, to determine when each patient was last seen, and what was done. These procedure codes are matched against a set of exam codes to determine last medical examination dates, and against a set of procedures known to resolve each medical condition. Each condition requiring regular care is matched against any resolving procedures, leaving a set of untreated conditions requiring regular care. Based on the date of the last exam or treatment and accepted standards of care or office policies, a due date is calculated for each patient. The management system is queried for each overdue patient to determine whether they already have an appointment scheduled in the future, or a recall notice recently sent or yet to be sent. Additional filtering based on administrative settings may also be done. Overdue patients requiring contact are then placed on the contact list.