Systems and methods for data cleansing such as for optimizing clinical scheduling
First Claim
1. A scheduling system configured for data cleansing to optimize clinical scheduling, the system comprising:
- one or more hardware processors of a clinical scheduling system configured by machine-readable instructions to;
receive clinical record data, in an agnostic manner, from a system including a source scheduling database containing the clinical record data, wherein;
received clinical record data is received in one of a plurality of different formats the clinical scheduling system is configured to operatively accept for purposes of optimizing scheduling templates,received clinical record data is received from at least two tables in the source scheduling database,received clinical record data includes a plurality of appointment records corresponding to historical clinical appointments,at least some of the appointment records include data from each of the at least two tables in the source scheduling database, andat least some of the appointment records including a plurality of appointment-record fields, the appointment-record fields for each of the at least some appointment records comprising a respective patient identifier, a respective provider identifier, a respective scheduled appointment start time, a respective actual appointment start time, a respective scheduled appointment end time, and a respective actual appointment end time;
map the clinical record data to a desired format, the desired format including a plurality of fields of standardized scheduling elements of the clinical scheduling system, wherein mapping comprises mapping respective appointment-record fields to corresponding fields of the standardized scheduling elements;
based on the mapping, conform the clinical record data to standardized scheduling elements of the scheduling system by parsing the clinical record data and reformatting the clinical record data by assigning portions of the data to appropriate fields to form the standardized scheduling elements from the appointment records, wherein a given standardized scheduling element has fields stored in a single table of the clinical scheduling system from each of at least two tables in the source scheduling database;
cleanse, in a manner configurable by a user, the clinical record data to filter out portions of the clinical record data, wherein cleansing comprises;
determining whether to exclude data of at least some appointment records based on whether the respective appointment records omit a given field;
determining whether to exclude data of at least some appointment records based on whether the respective appointment records include a given provider identifier; and
determining whether to exclude data of at least some appointment records based on whether the respective appointment records correspond to one or more durations of time;
provide the standardized scheduling elements to an optimization engine for optimization of provider and facility scheduling templates based on the clinical record data;
optimize, with the optimization engine, the provider and facility scheduling templates by applying configurable logic to the standardized scheduling elements in order to provide one or more at least partially newly defined optimized scheduling templates that configure both of providers and rooms for improved usage of time relative to un-optimized scheduling templates, wherein optimizing comprises;
matching provider availability with customized variables, the customized variables based on visit complexity, visit length, number of exam rooms, provider preference, and non-physician resources;
optimizing at least some of the scheduling templates for providers matched with the customized variables based on user-defined rules to optimize schedules; and
detecting and resolving a conflict in the user-defined rules to optimize schedules; and
generate one or more communications configured to upload one or more at least partially newly defined optimized scheduling templates via an outbound connection back to the scheduling system, wherein;
the scheduling system includes subject and provider dimensional tables with details that include one or both of subject demographics or provider specialty information;
the one or more hardware processors are further configured by machine-readable instructions to extract data from the source scheduling database or other source scheduling databases via an OLEDB connection, an ODBC connection, and another application program interface (API); and
the one or more hardware processors are further configured by machine-readable instructions to cleanse data errors including rows of data missing information, wherein;
the one or more hardware processors are further configured by machine-readable instructions to populate a primary fact table of data of the clinical scheduling system surrounded by dimensional tables of the clinical scheduling system, the primary fact table of data including appointment information, subject and provider keys, appointment scheduling start times, and appointment scheduling end times, the dimensional tables including subject dimensional tables and provider dimensional tables, andthe dimensional tables include standardized dimensional tables that comprise detail information that includes appointment outcome information having appointment statuses, actual appointment start times, and actual appointment end times, and wherein subject and provider dimensional tables include detail information that includes both of subject demographics and provider specialty information.
1 Assignment
0 Petitions
Accused Products
Abstract
A scheduling system and method for data cleansing may be used to optimize clinical scheduling. The present disclosure describes receiving clinical record data, in an agnostic manner, from a system including a source scheduling database containing the clinical record data; mapping the clinical record data to a desired format; conforming the clinical record data to standardized scheduling elements of the scheduling system; cleansing, in a manner configurable by a user, the clinical record data to purge portions of the clinical record data; providing the clinical record data to an optimization engine for optimization of the clinical record data; optimizing the clinical record data by applying configurable logic to the clinical record data; and uploading one or more newly defined optimized scheduling templates via an outbound connection back to the scheduling system.
35 Citations
12 Claims
-
1. A scheduling system configured for data cleansing to optimize clinical scheduling, the system comprising:
-
one or more hardware processors of a clinical scheduling system configured by machine-readable instructions to; receive clinical record data, in an agnostic manner, from a system including a source scheduling database containing the clinical record data, wherein; received clinical record data is received in one of a plurality of different formats the clinical scheduling system is configured to operatively accept for purposes of optimizing scheduling templates, received clinical record data is received from at least two tables in the source scheduling database, received clinical record data includes a plurality of appointment records corresponding to historical clinical appointments, at least some of the appointment records include data from each of the at least two tables in the source scheduling database, and at least some of the appointment records including a plurality of appointment-record fields, the appointment-record fields for each of the at least some appointment records comprising a respective patient identifier, a respective provider identifier, a respective scheduled appointment start time, a respective actual appointment start time, a respective scheduled appointment end time, and a respective actual appointment end time; map the clinical record data to a desired format, the desired format including a plurality of fields of standardized scheduling elements of the clinical scheduling system, wherein mapping comprises mapping respective appointment-record fields to corresponding fields of the standardized scheduling elements; based on the mapping, conform the clinical record data to standardized scheduling elements of the scheduling system by parsing the clinical record data and reformatting the clinical record data by assigning portions of the data to appropriate fields to form the standardized scheduling elements from the appointment records, wherein a given standardized scheduling element has fields stored in a single table of the clinical scheduling system from each of at least two tables in the source scheduling database; cleanse, in a manner configurable by a user, the clinical record data to filter out portions of the clinical record data, wherein cleansing comprises; determining whether to exclude data of at least some appointment records based on whether the respective appointment records omit a given field; determining whether to exclude data of at least some appointment records based on whether the respective appointment records include a given provider identifier; and determining whether to exclude data of at least some appointment records based on whether the respective appointment records correspond to one or more durations of time; provide the standardized scheduling elements to an optimization engine for optimization of provider and facility scheduling templates based on the clinical record data; optimize, with the optimization engine, the provider and facility scheduling templates by applying configurable logic to the standardized scheduling elements in order to provide one or more at least partially newly defined optimized scheduling templates that configure both of providers and rooms for improved usage of time relative to un-optimized scheduling templates, wherein optimizing comprises; matching provider availability with customized variables, the customized variables based on visit complexity, visit length, number of exam rooms, provider preference, and non-physician resources; optimizing at least some of the scheduling templates for providers matched with the customized variables based on user-defined rules to optimize schedules; and detecting and resolving a conflict in the user-defined rules to optimize schedules; and generate one or more communications configured to upload one or more at least partially newly defined optimized scheduling templates via an outbound connection back to the scheduling system, wherein; the scheduling system includes subject and provider dimensional tables with details that include one or both of subject demographics or provider specialty information; the one or more hardware processors are further configured by machine-readable instructions to extract data from the source scheduling database or other source scheduling databases via an OLEDB connection, an ODBC connection, and another application program interface (API); and the one or more hardware processors are further configured by machine-readable instructions to cleanse data errors including rows of data missing information, wherein; the one or more hardware processors are further configured by machine-readable instructions to populate a primary fact table of data of the clinical scheduling system surrounded by dimensional tables of the clinical scheduling system, the primary fact table of data including appointment information, subject and provider keys, appointment scheduling start times, and appointment scheduling end times, the dimensional tables including subject dimensional tables and provider dimensional tables, and the dimensional tables include standardized dimensional tables that comprise detail information that includes appointment outcome information having appointment statuses, actual appointment start times, and actual appointment end times, and wherein subject and provider dimensional tables include detail information that includes both of subject demographics and provider specialty information. - View Dependent Claims (2, 3, 4, 5)
-
-
6. A scheduling method configured for data cleansing to optimize clinical scheduling, the method being performed by one or more hardware processors configured by machine-readable instructions, the method comprising:
-
receiving clinical record data, with one or more processors of a clinical scheduling system, in an agnostic manner, from a system including a source scheduling database containing the clinical record data, wherein; received clinical record data is received in one of a plurality of different formats the clinical scheduling system is configured to operatively accept for purposes of optimizing scheduling templates, received clinical record data is received from at least two tables in the source scheduling database, received clinical record data includes a plurality of appointment records corresponding to historical clinical appointments, at least some of the appointment records include data from each of the at least two tables in the source scheduling database, and at least some of the appointment records including a plurality of appointment-record fields, the appointment-record fields for each of the at least some appointment records comprising a respective patient identifier, a respective provider identifier, a respective scheduled appointment start time, a respective actual appointment start time, a respective scheduled appointment end time, and a respective actual appointment end time; mapping, with one or more processors of the clinical scheduling system, the clinical record data to a desired format, the desired format including a plurality of fields of standardized scheduling elements of the clinical scheduling system, wherein mapping comprises mapping respective appointment-record fields to corresponding fields of the standardized scheduling elements; based on the mapping, conforming, with one or more processors of the clinical scheduling system, the clinical record data to standardized scheduling elements of the scheduling system by parsing the clinical record data and reformatting the clinical record data by assigning portions of the data to appropriate fields to form the standardized scheduling elements from the appointment records, wherein a given standardized scheduling element has fields stored in a single table of the clinical scheduling system from each of at least two tables in the source scheduling database; cleansing, with one or more processors of the clinical scheduling system, in a manner configurable by a user, the clinical record data to filter out portions of the clinical record data, wherein cleansing comprises; determining whether to exclude data of at least some appointment records based on whether the respective appointment records omit a given field; determining whether to exclude data of at least some appointment records based on whether the respective appointment records include a given provider identifier; and determining whether to exclude data of at least some appointment records based on whether the respective appointment records correspond to one or more durations of time; providing, with one or more processors of the clinical scheduling system, the standardized scheduling elements to an optimization engine for optimization of provider and facility scheduling templates based on the clinical record data; optimizing, with one or more processors of the clinical scheduling system, the provider and facility scheduling templates by applying configurable logic to the standardized scheduling elements in order to provide one or more at least partially newly defined optimized scheduling templates that configure one or both of providers and rooms for improved usage of time relative to un-optimized scheduling templates, wherein optimizing comprises; matching provider availability with customized variables, the customized variables based on visit complexity, visit length, number of exam rooms, provider preference, and non-physician resources; optimizing at least some of the scheduling templates for providers matched with the customized variables based on user-defined rules to optimize schedules; and detecting and resolving a conflict in the user-defined rules to optimize schedules; and generating, with one or more processors of the clinical scheduling system, one or more communications configured to upload one or more newly defined optimized scheduling templates via an outbound connection back to the scheduling system, wherein; the scheduling system includes subject and provider dimensional tables with details that include one or both of subject demographics or provider specialty information; the one or more hardware processors are further configured by machine-readable instructions to extract data from the source scheduling database or other source scheduling databases via an OLEDB connection, an ODBC connection, and another application program interface (API); and the one or more hardware processors are further configured by machine-readable instructions to cleanse data errors including rows of data missing information, wherein; the one or more hardware processors are further configured by machine-readable instructions to populate a primary fact table of data of the clinical scheduling system surrounded by dimensional tables of the clinical scheduling system, the primary fact table of data including appointment information, subject and provider keys, appointment scheduling start times, and appointment scheduling end times, the dimensional tables including subject dimensional tables and provider dimensional tables, and the dimensional tables include standardized dimensional tables that comprise detail information that includes appointment outcome information having appointment statuses, actual appointment start times, and actual appointment end times, and wherein subject and provider dimensional tables include detail information that includes both of subject demographics and provider specialty information. - View Dependent Claims (7, 8, 9, 10)
-
-
11. A scheduling system configured for data cleansing to optimize clinical scheduling, the system comprising:
-
one or more hardware processors of a clinical scheduling system configured by machine-readable instructions to; receive clinical record data, in an agnostic manner, from a system including a source scheduling database containing the clinical record data, wherein; received clinical record data is received in one of a plurality of different formats the clinical scheduling system is configured to operatively accept for purposes of optimizing scheduling templates, received clinical record data is received from at least two tables in the source scheduling database, received clinical record data includes a plurality of appointment records corresponding to historical clinical appointments, at least some of the appointment records include data from each of the at least two tables in the source scheduling database, and at least some of the appointment records including a plurality of appointment-record fields, the appointment-record fields for each of the at least some appointment records comprising a respective patient identifier, a respective provider identifier, a respective scheduled appointment start time, a respective actual appointment start time, a respective scheduled appointment end time, and a respective actual appointment end time; map the clinical record data to a desired format, the desired format including a plurality of fields of standardized scheduling elements of the clinical scheduling system, wherein mapping comprises mapping respective appointment-record fields to corresponding fields of the standardized scheduling elements; based on the mapping, conform the clinical record data to standardized scheduling elements of the scheduling system by parsing the clinical record data and reformatting the clinical record data by assigning portions of the data to appropriate fields to form the standardized scheduling elements from the appointment records, wherein a given standardized scheduling element has fields stored in a single table of the clinical scheduling system from each of at least two tables in the source scheduling database; cleanse, in a manner configurable by a user, the clinical record data to filter out portions of the clinical record data, wherein cleansing comprises; determining whether to exclude data of at least some appointment records based on whether the respective appointment records omit a given field; determining whether to exclude data of at least some appointment records based on whether the respective appointment records include a given provider identifier; and determining whether to exclude data of at least some appointment records based on whether the respective appointment records correspond to one or more durations of time; provide the standardized scheduling elements to an optimization engine for optimization of provider and facility scheduling templates based on the clinical record data; optimize, with the optimization engine, the provider and facility scheduling templates by applying configurable logic to the standardized scheduling elements in order to provide one or more at least partially newly defined optimized scheduling templates that configure both of providers and rooms for improved usage of time relative to un-optimized scheduling templates, wherein optimizing comprises; matching provider availability with customized variables, the customized variables based on visit complexity, visit length, number of exam rooms, provider preference, and non-physician resources; optimizing at least some of the scheduling templates for providers matched with the customized variables based on user-defined rules to optimize schedules; and detecting and resolving a conflict in the user-defined rules to optimize schedules; and generate one or more communications configured to upload one or more at least partially newly defined optimized scheduling templates via an outbound connection back to the scheduling system, wherein; the scheduling system includes subject and provider dimensional tables with details that include one or both of subject demographics or provider specialty information; the one or more hardware processors are further configured by machine-readable instructions to extract data from the source scheduling database or other source scheduling databases via an OLEDB connection, an ODBC connection, and another application program interface (API); and the one or more hardware processors are further configured by machine-readable instructions to cleanse data errors including rows of data missing information, wherein; data that is excluded from the optimization engine is stored for analytics and reporting, and wherein the clinical scheduling system is configured to generate one or more reports on types and amounts of data that are being excluded from analysis, the types and amounts of data that are being excluded from analysis including one or more of data with missing information, data that is not relevant, data that is incomplete, or data that is erroneous.
-
-
12. A scheduling method configured for data cleansing to optimize clinical scheduling, the method being performed by one or more hardware processors configured by machine-readable instructions, the method comprising:
-
receiving clinical record data, with one or more processors of a clinical scheduling system, in an agnostic manner, from a system including a source scheduling database containing the clinical record data, wherein; received clinical record data is received in one of a plurality of different formats the clinical scheduling system is configured to operatively accept for purposes of optimizing scheduling templates, received clinical record data is received from at least two tables in the source scheduling database, received clinical record data includes a plurality of appointment records corresponding to historical clinical appointments, at least some of the appointment records include data from each of the at least two tables in the source scheduling database, and at least some of the appointment records including a plurality of appointment-record fields, the appointment-record fields for each of the at least some appointment records comprising a respective patient identifier, a respective provider identifier, a respective scheduled appointment start time, a respective actual appointment start time, a respective scheduled appointment end time, and a respective actual appointment end time; mapping, with one or more processors of the clinical scheduling system, the clinical record data to a desired format, the desired format including a plurality of fields of standardized scheduling elements of the clinical scheduling system, wherein mapping comprises mapping respective appointment-record fields to corresponding fields of the standardized scheduling elements; based on the mapping, conforming, with one or more processors of the clinical scheduling system, the clinical record data to standardized scheduling elements of the scheduling system by parsing the clinical record data and reformatting the clinical record data by assigning portions of the data to appropriate fields to form the standardized scheduling elements from the appointment records, wherein a given standardized scheduling element has fields stored in a single table of the clinical scheduling system from each of at least two tables in the source scheduling database; cleansing, with one or more processors of the clinical scheduling system, in a manner configurable by a user, the clinical record data to filter out portions of the clinical record data, wherein cleansing comprises; determining whether to exclude data of at least some appointment records based on whether the respective appointment records omit a given field; determining whether to exclude data of at least some appointment records based on whether the respective appointment records include a given provider identifier; and determining whether to exclude data of at least some appointment records based on whether the respective appointment records correspond to one or more durations of time; providing, with one or more processors of the clinical scheduling system, the standardized scheduling elements to an optimization engine for optimization of provider and facility scheduling templates based on the clinical record data; optimizing, with one or more processors of the clinical scheduling system, the provider and facility scheduling templates by applying configurable logic to the standardized scheduling elements in order to provide one or more at least partially newly defined optimized scheduling templates that configure one or both of providers and rooms for improved usage of time relative to un-optimized scheduling templates, wherein optimizing comprises; matching provider availability with customized variables, the customized variables based on visit complexity, visit length, number of exam rooms, provider preference, and non-physician resources; optimizing at least some of the scheduling templates for providers matched with the customized variables based on user-defined rules to optimize schedules; and detecting and resolving a conflict in the user-defined rules to optimize schedules; and generating, with one or more processors of the clinical scheduling system, one or more communications configured to upload one or more newly defined optimized scheduling templates via an outbound connection back to the scheduling system, wherein; the scheduling system includes subject and provider dimensional tables with details that include one or both of subject demographics or provider specialty information; the one or more hardware processors are further configured by machine-readable instructions to extract data from the source scheduling database or other source scheduling databases via an OLEDB connection, an ODBC connection, and another application program interface (API); and the one or more hardware processors are further configured by machine-readable instructions to cleanse data errors including rows of data missing information, wherein; data that is excluded from the optimization engine is stored for analytics and reporting, and wherein the clinical scheduling system is configured to generate one or more reports on types and amounts of data that are being excluded from analysis, the types and amounts of data that are being excluded from analysis including one or more of data with missing information, data that is not relevant, data that is incomplete, or data that is erroneous.
-
Specification