Physician Scheduling System Prioritizing Notifications
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Solution Overview
Problem
Current scheduling systems for notifying physicians of potential patient appointments face challenges in efficiently managing network connections and bandwidth, leading to increased costs and potential delays in response times due to the large number of notifications required.
Innovation Solution
A system that narrows the number of notifications sent by prioritizing physicians based on their experience and performance scores, availability, and response rates, using a real-time bidding-like mechanism to ensure timely and efficient appointment scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a scheduling system notifies all physicians of potential patient appointments, then patients can be matched with suitable physicians, but network bandwidth and connection costs increase significantly
Solution Approach 1:
The system segments the physician population into different groups based on their characteristics (specialty, availability, performance metrics) and only notifies relevant segments for each patient match, rather than notifying all physicians universally
Solution Approach 2:
The scheduling system acts as an intermediary that pre-processes match requests using performance data and availability information, filtering and prioritizing notifications before they reach physicians, thus reducing unnecessary network traffic
2Reliability
If notifications are sent to all physicians, then comprehensive matching is achieved, but response time increases due to notification volume
Solution Approach 1:
The system performs preliminary actions by pre-calculating physician performance scores, availability status, and match compatibility before generating notifications, so that only pre-filtered, high-probability matches are notified, reducing notification volume and response time
Solution Approach 2:
The notification system dynamically adjusts which physicians receive notifications based on real-time performance data and availability, prioritizing notifications to physicians with higher likelihood of positive response, thereby reducing overall notification processing time
3Productivity
If performance-based prioritization is implemented, then notification efficiency improves, but system complexity increases
Solution Approach 1:
The system changes parameters by incorporating performance metrics (response rate, acceptance rate, patient satisfaction) into the notification prioritization algorithm, allowing efficient filtering without requiring complex structural changes to the core scheduling functionality
Data Source
AI summary
In one embodiment, a matching-engine system may receive a set of physician-selection parameters from an administrator. The physician-selection parameters may comprise a range of acceptable performance-scores and experience-scores for physicians. The matching-engine system may receive, from a user, a search query comprising a geographic location of the user, a preferred date and time for an appointment, and a user-specified symptom or a user-specified treatment. A first set of physicians may be determined based on a geographic location of each physician, a performance-score associated with the physician with respect to a base-concept associated with the search query, and an experience-score associated with the physician with respect to the base-concept. A second set of physicians is identified from the first set based on one or more physician preferences, the preferred date and time, and an indication of whether the physician is available at the preferred date and time.