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US 11,887,723 B2Granted
Dental practice scheduling efficiencies and operational issue trainings
AssigneeSpear Education, LLC
InventorsMatthew M. Crego, Mitchell Ward Ellingson, Yonas Yohannes
Life of this patent
Estimating the term…
Abstract
System and methods for the integration of dental practice management systems are disclosed herein. The systems and methods may generate models (including schedule models and financial models) from the data provided by a plurality of dental practices. These models can be used to quantitatively evaluate the efficiency and other operating characteristics of a particular dental practice, and can identify operational issues within the practice. Further, the systems and methods can evaluate metrics of the dental practice against goal metrics and/or standard metrics, and recommend and implement solutions based on the comparison.
Claims20
A method comprising:
- comparing, by a processor, potential revenue from dental treatment plan data for a dental practice with at least one of total planned dental treatments, total accepted dental treatments, total scheduled dental treatments or total completed dental treatments, wherein the dental treatment plan data includes financial data, patient data, dental hygiene procedures, recommended dental treatments and dates for scheduling the recommended dental treatments;
- determining, by the processor, scheduling efficiency data based on the comparing;
- converting, by a processor, the dental treatment plan data in a first format to a second format that is a common format with a plurality of dental practices;
- creating, by the processor, a schedule model based on the dental treatment plan data of a plurality of dental practices sharing one or more characteristics with the dental practice;
- comparing, by the processor, the dental treatment plan data and the scheduling efficiency data with the schedule model;
- generating, by the processor, financial projections for the dental practice based on the financial data and the recommended dental treatments;
- generating, by the processor, a financial model from the financial projections based on the plurality of dental practices in a local geographic area to the dental practice;
- selecting, by the processor, and based on the schedule model and the financial model, an operational issue with a quantifiable metric being below a threshold value;
- obtaining, by the processor, an article of content related to the operational issue, wherein the article of content includes dental clinical content;
- identifying, by the processor, a solution to the operational issue;
- evaluating, by the processor using a machine learning module, an effectiveness of the solution by analyzing trend data for the quantifiable metric for a time period after the solution is implemented in the plurality of dental practices sharing one or more characteristics with the dental practice;
- and
- modifying, by the processor, the solution based on the trend data and from evaluating the effectiveness of the solution.
10 more elements
An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a processor, cause the processor to perform operations comprising:
- comparing, by the processor, potential revenue from dental treatment plan data for a dental practice with at least one of total planned dental treatments, total accepted dental treatments, total scheduled dental treatments or total completed dental treatments, wherein the dental treatment plan data includes financial data, patient data, dental hygiene procedures, recommended dental treatments and dates for scheduling the recommended dental treatments;
- determining, by the processor, scheduling efficiency data based on the comparing;
- converting, by a processor, the dental treatment plan data in a first format to a second format that is a common format with a plurality of dental practices;
- creating, by the processor, a schedule model based on the dental treatment plan data of a plurality of dental practices sharing one or more characteristics with the dental practice;
- comparing, by the processor, the dental treatment plan data and the scheduling efficiency data with the schedule model;
- generating, by the processor, financial projections for the dental practice based on the financial data and the recommended dental treatments;
- generating, by the processor, a financial model from the financial projections based on the plurality of dental practices in a local geographic area to the dental practice;
- selecting, by the processor, and based on the schedule model and the financial model, an operational issue with a quantifiable metric being below a threshold value;
- obtaining, by the processor, an article of content related to the operational issue, wherein the article of content includes dental clinical content;
- identifying, by the processor, a solution to the operational issue;
- evaluating, by the processor using a machine learning module, an effectiveness of the solution by analyzing trend data for the quantifiable metric for a time period after the solution is implemented in the plurality of dental practices sharing one or more characteristics with the dental practice;
- and
- modifying, by the processor, the solution based on the trend data and from evaluating the effectiveness of the solution.
10 more elements
A system comprising:
- a processor;
- and
- a tangible, non-transitory memory configured to communicate with the processor,
- the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising:
- comparing, by the processor, potential revenue from dental treatment plan data for a dental practice with at least one of total planned dental treatments, total accepted dental treatments, total scheduled dental treatments or total completed dental treatments, wherein the dental treatment plan data includes financial data, patient data, dental hygiene procedures, recommended dental treatments and dates for scheduling the recommended dental treatments;
- determining, by the processor, scheduling efficiency data based on the comparing;
- converting, by a processor, the dental treatment plan data in a first format to a second format that is a common format with a plurality of dental practices;
- creating, by the processor, a schedule model based on the dental treatment plan data of a plurality of dental practices sharing one or more characteristics with the dental practice;
- comparing, by the processor, the dental treatment plan data and the scheduling efficiency data with the schedule model;
- generating, by the processor, financial projections for the dental practice based on the financial data and the recommended dental treatments;
- generating, by the processor, a financial model from the financial projections based on the plurality of dental practices in a local geographic area to the dental practice;
- selecting, by the processor, and based on the schedule model and the financial model, an operational issue with a quantifiable metric being below a threshold value;
- obtaining, by the processor, an article of content related to the operational issue, wherein the article of content includes dental clinical content;
- identifying, by the processor, a solution to the operational issue;
- evaluating, by the processor using a machine learning module, an effectiveness of the solution by analyzing trend data for the quantifiable metric for a time period after the solution is implemented in the plurality of dental practices sharing one or more characteristics with the dental practice;
- and
- modifying, by the processor, the solution based on the trend data and from evaluating the effectiveness of the solution.
14 more elements
Dependencies are inferred from the claim text.