Systems and methods for healthcare intervention

Abstract

A computer-implemented method for providing healthcare intervention is presented. The method includes obtaining an input to schedule a requested appointment from a user; obtaining a location for the appointment and details about a reason for the requested appointment; obtaining input relating to a selection of a healthcare provider; receiving a confirmation of the appointment from the user; determining a match between the user and a healthcare provider; transmitting a request to the healthcare provider; obtaining a confirmation from the healthcare provider; obtaining location information about the healthcare provider; and authenticating the healthcare provider and the user based on confirming their identities.

Description

SYSTEMS AND METHODS FOR HEALTHCARE INTERVENTIONCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims the benefit of and priority to U.S. Provisional Patent Application Serial No. 63 / 538,150 filed September 13, 2023, the entire contents of which is incorporated by reference herein.TECHNICAL FIELD

[0002] The present disclosure relates to healthcare intervention systems and, in particular, to determining and authenticating healthcare providers.BACKGROUND

[0003] The health system today faces different threats which affect the quality of care given to the patients. These problems include long waits in emergency departments of hospitals, easy access to care centers, physician burnout, and overcrowding in care centers. Some health complaints do not warrant a visit to health centers or emergency rooms. However, because such issues are still presented to the ER, they take away time from those cases that need immediate attention in the ER. Physicians and other health personnel also become exhausted attending to such unwarranted cases while they can save their energy for cases that need attention in the ER. The COVID-19 pandemic also contributes to the need to prevent overcrowding when necessary. Moreover, during overcrowding, physicians may be unable to provide specialized care, lacking the time and / or personnel to quickly gather the required information for a complete diagnosis.

[0004] Accordingly, there is a need for efficient, remote, in-home healthcare intervention system with ease of access.SUMMARY

[0005] In accordance with aspects of the disclosure, a system for providing healthcare intervention is presented. The system includes a processor and a memory. The memory stores instructions which, when executed by the processor cause the system to receive a first input from a graphical user interface on a user device the first input including an appointment request by a user; receive a confirmation of the requested appointment from the user; determine a match between the user and a provider based on the first input and second input; transmit an authenticated request to the provider, based on the first input and the match; receive a confirmation from the provider relating to the authenticated request; and output an alert on the user device indicating the confirmation, the alert including data relating to the requested appointment.

[0006] In an aspect of the present disclosure, the instructions, when executed by the processor, may further cause the system to display a first prompt on the user device relating to the requested appointment, and receive, by the user, at least one of a location, a date, or a time for the requested appointment.

[0007] In another aspect of the present disclosure, the location may include an address. The address may be provided by at least one of a Global Positioning System (GPS), the user device, or manually entered by the user.

[0008] In yet another aspect of the present disclosure, the instructions, when executed by the processor, may further cause the system to display a second prompt on the user device relating to the requested appointment, and receive, by the user, a reason for the requested appointment.

[0009] In a further another aspect of the present disclosure, the instructions, when executed by the processor, may further cause the system to determine that emergency services are required based on the reason for the requested appointment, and automatically transmit user details to the emergency services based on the determination that emergency services are required.

[0010] In another aspect of the present disclosure, the second input may include a provider selection, where the provider selection may be determined based on at least one of the provider preference, a provider proximity, a provider specialty, a provider skill, or a randomly selected provider.

[0011] In another aspect of the present disclosure, the instructions, when executed by the processor, may further cause the system to obtain a third input including at least one of an acceptance, a rejection, or a request from the provider, and transmit a confirmation to the user device based on the third input.

[0012] In yet another aspect of the present disclosure, outputting the alert may include receiving a provider location from a provider device and displaying the provider location on the user device.

[0013] In a further aspect of the present disclosure, the instructions when executed by the process, may further cause the system to display a direct messaging system on the user device. The direct messaging system may be configured to communicate with the provider by receiving a touch input on the user device from the user.

[0014] In another aspect of the present disclosure, determining the match may further include providing a confidence level of the match between the user and a provider using machine learning, the confidence level based on at least two of a user profile, providerqualifications, a user health history, a provider availability, and insurance coverage; and determining the match based on the confidence level being over a predetermined threshold.

[0015] In accordance with aspects of the present disclosure, a computer-implemented method for providing healthcare intervention is presented. The method includes receiving a first input from a graphical user interface (GUI) on a user device, the first input including an appointment request by a user; receiving a second input from the user device by the user; receiving a confirmation of the requested appointment from the user; determining a match between the user and a provider based on the first input and the second input; transmitting an authenticated request to the provider, based on the first input and the match; receiving a confirmation from the provider relating to the authenticated request; and outputting an alert on the user device indicating the confirmation, the alert including data relating to the requested appointment.

[0016] In an aspect of the present disclosure, the computer-implemented method may further include displaying a first prompt on the user device relating to the requested appointment, and receiving, by the user, at least one of a location, a date, or a time for the requested appointment.

[0017] In another aspect of the present disclosure, the location may include an address. The address may be provided by at least one of a Global Positioning System (GPS), the user device, or manually entered by the user.

[0018] In yet another aspect of the present disclosure, the computer-implemented method may further include displaying a second prompt on the user device relating to the requested appointment and receiving, by the user, a reason for the requested appointment.

[0019] In a further aspect of the present disclosure, the computer-implemented method may further include determining that emergency services may be required on the reason for the requested appointment, and automatically transmit user details to the emergency services based on the determination that emergency services are required.

[0020] In an aspect of the present disclosure, the second input may include a provider selection. The provider selection may be determined based on at least one of a provider preference, a provider proximity, a provider specialty, a provider skill, or a randomly selected provider.

[0021] In another aspect of the present disclosure, the computer-implemented method may further include obtaining a third input including at least one of an acceptance, a rejection, or a request from the provider and transmitting a confirmation to the user device based on the third input.

[0022] In yet another aspect of the present disclosure, outputting the alert may further include receiving a provider location from a provider device and displaying the provider location on the user device.

[0023] In another aspect of the present disclosure, the computer-implemented method may further include displaying a direct messaging system. The direct messaging system may be configured to communicate with the provider by receiving a touch input on the user device from the user.

[0024] In a further aspect of the present disclosure, the match may further include, providing a confidence level of the match between the user and a provider using machine learning, the confidence level based on at least two of a user profile, provider qualifications,a user health history, a provider availability, and insurance coverage; and determining the match based on the confidence level being over a predetermined threshold.

[0025] Further details and aspects of exemplary embodiments of the present disclosure are described in more detail below with reference to the appended figures.BRIEF DESCRIPTION OF THE DRAWINGS

[0026] A better understanding of the features and advantages of the disclosed technology will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the technology are utilized, and the accompanying drawings of which:

[0027] FIG. 1 is a network diagram illustration showing an exemplary system for a computer-implemented method for healthcare intervention in accordance with aspects of the present disclosure;

[0028] FIG. 2 is a block diagram of a controller for the system of FIG. 1 in accordance with aspects of the present disclosure;

[0029] FIG. 3 is an example home screen of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0030] FIGS. 4-6 are example edit profile screens of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0031] FIG. 7 is an example change password screen of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0032] FIGS. 8 and 9 are an example booking screen with an address selection feature of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0033] FTG. 10 is an example booking screen with a date selection feature of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0034] FIG. 11 is an example booking screen with a time selection feature of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0035] FIG. 12 is an example pending booking screen of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0036] FIG. 13 is an example home screen where a requested booking may be accepted, rejected, or forwarded, of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0037] FIG. 14 is an example booking screen with completed requests for the system of FIG. 1 in accordance with aspects of the present disclosure;

[0038] FIG. 15 is an example earning screen of the system of FIG. 1 in accordance with aspects of the present disclosure;

[0039] FIGS. 16 and 17 are example medical history screens of the system of FIG. 1 in accordance with aspects of the present disclosure; and

[0040] FIG. 18 is a computer-implemented method for healthcare intervention, in accordance with aspects of the present disclosure.DETAILED DESCRIPTION

[0041] The present application relates to systems and methods for healthcare intervention.

[0042] For purposes of promoting an understanding of the principles of the present disclosure, reference will now be made to exemplary embodiments illustrated in the drawings, and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the present disclosure is thereby intended.Various alterations, rearrangements, substitutions, and modifications of the inventive features illustrated herein, and any additional applications of the principles of the present disclosure as illustrated herein, which would occur to one skilled in the relevant art and having possession of this disclosure, are to be considered within the scope of the present disclosure.

[0043] Referring to FIG. 1, an exemplary system 100 for providing healthcare intervention includes a controller 200. The disclosed system 100 provides a technical solution to the problem of ER overcrowding and related stresses on the healthcare system. The system 100 provides the benefit of expeditious and / or automated assistance to users from the comfort of their own homes, thereby reducing the strain on health centers and emergency rooms and avoiding the spread of disease.

[0044] It is contemplated that the controller 200 may run programs locally on the controller 200, remotely via a network 130, over the cloud, and / or on a remote server 120. The controller 200 may include, but is not limited to, a mobile phone, a personal computer, a tablet, and / or other handheld devices. The disclosed system is configured to reduce the burden on emergency rooms and to provide access to healthcare by providing healthcare interventions. Such healthcare interventions enable a user to access healthcare providers (e.g., a medical professional such as a doctor or other licensed practitioner).

[0045] The network 130 may be wired or wireless and can utilize technologies such as Wi-Fi®, Ethernet, Internet Protocol, 3G, 4G, 5G, TDMA, CDMA, or other communication technologies. The network 130 may include, for example, but is not limited to, a cellular network, residential broadband, satellite communications, private network, the Internet,local area network, wide area network, storage area network, campus area network, personal area network, or metropolitan area network.

[0046] The term “application” may include a computer program and / or machine- readable instructions designed to perform particular functions, tasks, or activities for the benefit of a user. Application may refer to, for example, software running locally or remotely, as a standalone program or in a web browser, or other software that would be understood by one skilled in the art to be an application. The configuration of FIG. 1 is exemplary, and variations are contemplated to be within the scope of the present disclosure.

[0047] Referring now to FIG. 2, exemplary components in the controller 200 in accordance with aspects of the present disclosure include, for example, a database 210, one or more processors 220, at least one memory 230, and a network interface 240. In aspects, the controller 200 may include a graphical processing unit (GPU) 250, which may be used for processing machine learning models.

[0048] The database 210 can be located in storage. The term “storage” may refer to any device or material from which information may be capable of being accessed, reproduced, and / or held in an electromagnetic or optical form for access by a computer processor. Storage may be, for example, volatile memory such as RAM, non-volatile memory, which permanently holds digital data until purposely erased, such as flash memory, magnetic devices such as hard disk drives, and optical media such as a CD, DVD, Blu-ray disc, or the like. In various embodiments, data may be stored on the controller 200, including, for example, user preferences, historical data, and / or other data. The data can be stored in the database 210 and sent via the system bus to the processor 220.

[0049] As will be described in more detail later herein, the processor 220 executes various processes based on instructions that can be stored in the server memory 230 and utilizing the data from the database 210. With reference also to FIG. 1, a request from a user device 140, such as a mobile device or a client computer, can be communicated to the server through the server’s network interface 240. The illustration of FIG. 2 is exemplary, and it will be understood by persons skilled in the art that other components may exist in a controller 200. Such other components are not illustrated in FIG. 2 for clarity of illustration. System 100 may include an account creation (“create account”) screen (not shown). Initially, a user accesses the create account screen and fdls in the requested information. For example, the user may be prompted to input their first and last name, phone number, and / or preferred language. In aspects, the user may also need to enter their email address, create a password, and / or agree to terms and conditions. The system 100 may transmit a message to the user (e.g., an SMS message) to verify that the phone number works. The text message may include a verification code that a user is subsequently prompted to enter in the application.

[0050] FIG. 3 shows an exemplary home screen. From the home screen, the user may select “schedule visit” and / or “prompt visit.” The home screen may include various tabs, which a user can toggle between to obtain healthcare data, e.g., appointment information. For example, a requests tab may include booking details such as a user ID (e.g., AKAND83359), a health complaint (e.g., “cold”), and / or a booking start time (e.g., 9:53AM EST) may be shown. In aspects, a user may forward the booking details to a third party, such as a healthcare provider and / or administrative user. In another example, an upcoming appointments tab may include booking details related to authorized appointments, whichmay be similar to the request details and / or with additional provider data. Tn aspects, system 100 may include a sidebar screen (not shown). The sidebar screen enables access to various functions, such as the home screen and / or a user’s profile.

[0051] FIGS. 4-6 are exemplary edit profile screens. In the edit profile screens, a provider and / or user may enter and / or amend a variety of personal information. For example, as shown in FIGS. 4 and 5, a provider may edit their full name, email address, phone number, qualifications, specializations, location, bio, and skills. In aspects, a profile may be tagged in system 100 with their selected skills (e.g., similar to searchable “hashtags”) in order to provide personalized searches to users. As seen in FIG. 6, a user may edit their name, phone number, email address, and insurance details (e.g., file upload for documentation). In aspects, a user may personalize their profile by adding a profile picture, editing the color scheme on their application (i.e., “skin” including various background, text, and / or text colors), and / or adding a pseudo name. The edit profile screen may include a prompt to enable the uploading of insurance information. The insurance information may be uploaded in a non-searchable format, and the system 100 may recognize the characters using, for example, OCR or natural language processing to determine insurance information.

[0052] FIG. 7 is an example of a change-password screen. If a provider and / or user desires to change their password, the system may prompt the provider and / or user to enter the old password, in addition to the new password, for authentication. The password(s) entered may be hidden from view and / or encrypted for security purposes. In aspects, the provider and / or user may save their password and / or utilize alternative login procedures for ease and security. For example, the system 100 may support multi-factor authentication, facial identification, etc.

[0053] Referring to FIGS. 8-14, example booking screens are shown. For example, the system 100 may display a booking screen that displays a “visit location.” The System 100 may provide a series of prompts to explain the reason for the visit request. The user may select between a preferred provider, a random provider, and / or the closest provider. The user may access a screen that enables them to select a preferred payment method. In aspects, the user may select an address (FIG. 9), a date (FIG. 10), and / or a time for the visit (FIG. 11). For example, as shown in FIG. 9, a user may select an address interactively from a map or directly by entering an address. In aspects, a user may enter additional information such as the required specialty of the provider and a description of their symptoms. As shown in FIG. 8, a dropdown with pre-fdled specialties may be provided to assist the user with such information.

[0054] With further reference to FIGS. 12-14, system 100 may provide a screen to indicate that the booking is pending (FIG. 12). While pending, a requested booking may be accepted, rejected, or forwarded by a healthcare provider or administrative user (FIG. 13). FIG. 14 is an example booking screen with completed requests indicating their status (i.e., rejected or completed).

[0055] FIG. 15 shows an example earning screen of the system 100. The system 100 may display the healthcare provider’s earnings, start time, and end time for a particular visit and / or for prior visits. For example, the screen may display calculations such as total earnings and balances in addition to individual earnings data. In aspects, such data may be exported into a separate document (e.g., .xlsx or .csv file) for review by a healthcare provider or administrator for billing purposes. In aspects, a user may be able to connect their bank account to the system 100 in order to transfer funds earned. In aspects, the system 100may use machine learning to determine the efficiency of the healthcare provider based on data such as the total time per visit, procedure / test(s) performed, and / or type of patient.

[0056] FIGS. 16 and 17 show example medical history screens of system 100. The system 100 may provide a screen where a user may indicate medical history. In the medical history screens, a user may enter and / or amend a variety of personal medical history information. For example, as shown in FIGS. 16 and 17, a user may provide past medical and / or surgical history, current medication, family history, allergies, and / or social history. The system 100 may use the information provided on the medical history screen to aid in matching a provider and provide the provider with the necessary information in order to adequately care for the user. For example, the user’s medical history may be used as an input when determining the healthcare provider match (e.g., as an input to the machine learning network).

[0057] In aspects, the system 100 may also include a medical examination notes screen, where the healthcare provider may input a Review of Systems (ROS), an inventory of the body systems obtained during and after examination is completed. For example, the healthcare provider may input a description and label as either normal or abnormal for ROS ears / nose / mouth / throat, cardiovascular, respiratory, and gastrointestinal. The healthcare provider may also input information, labeling it as either normal or abnormal, determined from a Physical Exam. For example, the healthcare provider may provide general notes, vitals, cardiovascular, and / or head, eyes, ears, nose, and throat (HEENT) descriptions. The system 100 allows the healthcare provider to input the recommended patient plan and / or any prescriptions necessary. The medical examination notes screen may include text boxes for entering a description and radio buttons for indicating normal or abnormal observations.Data from the medical examination notes screen may be used by the system 100 to generate a report for the healthcare provider and / or insurance. Data from the medical examination notes screen may also be used by the system 100 when the system determines a healthcare provider.

[0058] Referring to FIG. 18, a flow diagram for a method 1800 for healthcare intervention is shown. Although the blocks of FIG. 18 are shown in a particular order, the blocks need not all be performed in the illustrated order, and certain blocks can be performed in another order. For example, FIG. 1 will be described below, with a controller 200 of FIG. 2 performing the operations. In aspects, the operations of FIG. 18 may be performed all or in part by another device, for example, a server, a user device, and / or a computer system. These variations are contemplated to be within the scope of the present disclosure.

[0059] Initially, at block 1802, the controller 200 causes the system 100 to obtain input to schedule an appointment (i.e., a visit). The appointment may be for a later time and / or an immediate visit. In aspects, the appointment may be a virtual appointment. By permitting virtual appointments, the user may schedule a visit without leaving their home, therefore preventing others from contracting potential diseases and reducing strain on the emergency medical system.

[0060] At block 1804, the controller 200 causes the system 100 to obtain a location for the appointment, the user’s location, as well as details about the reason for the requested appointment. For example, the user may indicate that they have a high fever or other symptoms. Based on the details provided by the user, the system 100 will determine whether immediate emergency services (i.e., 911) should be called prior to scheduling an appointment. In aspects, the system 100 may automatically provide user details toemergency services. For example, the user profile may indicate permission to provide user details to medical professionals (e.g., signing a HIPAA release form) in the event of an emergency and / or when the user is unresponsive, such as a medical history, allergies to medications, prior surgeries, etc. In aspects, the system may automatically call emergency services based on a user’s vitals.

[0061] At block 1806, the controller 200 causes the system 100 to obtain input relating to a selection of a healthcare provider. The user may select their preferred healthcare provider, or the system 100 may match the user with a provider, such as the nearest available provider. Then, the user may choose their preferred payment method from the options provided and tap “Confirm.” In aspects, additional scheduling input may be obtained from a user profile for physician matching purposes. For example, the system 100 may obtain information such as preferred doctor credentials, skills, length of practice, rating, special expertise, etc.

[0062] In aspects, the system 100 provides job opportunities for medical graduates waiting to match to residency (i.e., an unlicensed provider). Medical graduates waiting to match to residency constitute the majority of the unlicensed providers. Where a licensed provider is unable to physically visit the user, the system 100 may transmit user requests to a medical graduate waiting to match residency (to be supervised by a licensed provider). The system 100 enables a licensed provider the ability to remotely supervise an unlicensed provider. This way, the unlicensed provider will physically see the user under the license of the licensed provider.

[0063] In aspects, the system 100 may provide a setting screen for the healthcare provider that enables the entry of a distance (i.e., radius) of how far they are willing to travel(e.g., a slider from 0 to about 500 miles), their availability for emergency calls, and an on / off toggle to activate appointments.

[0064] At block 1808, the controller 200 causes the system 100 to receive a confirmation of the appointment from the user. For example, the system 100 may cause a user device to display on a graphical user interface (GUI) a confirmation prompt or a text prompt. The system may then receive from the user device a confirmation of the appointment.

[0065] At block 1810, the controller 200 causes the system 100 to match the user with a healthcare provider. For example, once the user confirms their request, the system 100 matches the user with the nearest available provider and / or notifies their preferred provider. In aspects, matching may be based on the particular healthcare provider(s) working during the timeframe scheduled or preferred, location and distance willing to travel, ability to take emergency calls, and / or other criteria such as level of experience and licensure. The match may be a simple match from a list and / or a random match. In aspects, the matching may be based on using machine learning to determine the best match based on the user profile, the profile of the healthcare provider, and / or other parameters. For example, a machine learning network may include a convolutional neural network or a large language model.

[0066] System 100 may match a user’s request by feeding input data into the machine learning network. This input data could include various factors such as one or more user profiles, the profile of the healthcare provider, the healthcare provider’s level of experience and licensure, the user’s medical history, and the user’s insurance coverage details. By processing this information, system 100 can make personalizedrecommendations, aiming to identify the most suitable healthcare provider for the user’s specific needs. In aspects, provider selection may be determined based on factors such as, for example, a provider preference, a provider proximity, a provider specialty, a provider skill, and / or a randomly selected provider.

[0067] The machine learning network may determine the best match by inferring patterns and correlations from the data. For example, it might weigh the healthcare provider’s expertise in treating particular conditions against the user’s health history. It could also consider the provider’s availability, geographic proximity, and compatibility with the user’s insurance plan. Based on these and other factors, the system can generate a recommendation that optimally aligns the healthcare provider’s qualifications and the user’s unique healthcare needs, improving the chances of a successful outcome.

[0068] This system offers a technical solution by utilizing machine learning algorithms to handle the complexity of matching users with healthcare providers based on multiple data inputs, such as medical history and insurance coverage. It addresses the technical problem of data overload and decision-making inefficiency by automating the analysis and recommendation process, which would otherwise be time-consuming and error-prone if done manually. By leveraging computational power and advanced models, it ensures more accurate, faster, and scalable matching solutions for healthcare needs.

[0069] This task requires processing large volumes of complex data, such as user profiles, healthcare provider qualifications, medical histories, and insurance details, which exceeds the cognitive capacity of the human mind. Additionally, humans cannot analyze these data points simultaneously to detect subtle patterns and correlations that a machine-learning network can infer. Finally, humans lack the ability to perform suchtasks with the speed, precision, and scalability that advanced algorithms provide, especially when handling multiple requests and diverse variables.

[0070] In another example, the match may be performed using natural language processing (NLP) on unstructured data. NLP may be used to process and analyze unstructured data from, for example, the patients’ medical history, electronic health records (EHRs), clinical notes, and / or patient reviews. It can extract relevant information about providers’ specialties, and / or patient satisfaction, that might be missed by a human.

[0071] At block 1812, the controller 200 causes the system 100 to transmit an authenticated request to the healthcare provider. For example, the provider receives from the system 100 a request, which they may approve, forward, or reject based on their availability, expertise, etc. For example, where additional licensing is required, a healthcare provider may perform the visit under the supervision of another provider, where permitted. Alternatively, the healthcare provider may forward the request to another known provider or to all providers in the region of the address selected by the user. At block 1812, the controller 200 causes the system 100 to transmit a confirmation that the healthcare provider has accepted, rejected, or forwarded the visit request. During this time, when the request is accepted, the user can monitor the healthcare provider’s progress and check the remaining wait time within the application. In aspects, the user can also contact the healthcare provider within the system 100 through a direct messaging system, or via text and / or call if they have any questions or special instructions, and the provider can reach out to the user if needed.

[0072] At block 1814, the controller 200 causes the system 100 to obtain a confirmation from the healthcare provider. For example, the healthcare provider mayreceive a notification on their device and confirm that they will handle the request. The confirmation may be transmitted by the healthcare provider’s device through the system 100 to the user’s device.

[0073] At block 1816, the controller 200 causes the system 100 to obtain location information about the healthcare provider. The system 100 may obtain GPS information from the provider’s mobile device and display the location information on a screen accessible by the user. In aspects, the location information may be used by the system 100 to determine an estimated time of arrival.

[0074] At block 1818, the controller 200 causes the system 100 to authenticate the healthcare provider. During the visit itself, depending on the user’s location, the user may need to inform a gatekeeper about the upcoming visit. After gaining access to the user’s location, both the user and the provider can confirm their identities within the application before proceeding. If the situation requires a clinic or hospital visit, the system 100 enables the provider the ability to initiate the necessary procedures. The authentication can be performed for security purposes.

[0075] A physician may conclude a visit by selecting a button (e.g., “end visit”) in the system 100, which the user may confirm. After the visit concludes, the system 100 will prompt the user to rate their experience. The user can provide a rating based on their satisfaction with the visit. Additionally, the user has the option to provide more detailed feedback. If the user rates the visit highly, the user can describe what the user liked about the visit. If the user rates the visit lower, the user can offer suggestions for improvement. The system 100 also provides the user the opportunity to provide a tip, although not mandatory, as a way to express appreciation for excellent service. The system 100displays predefined tip amounts and / or the user is provided the option to enter a custom tip amount.

[0076] In the event that the user needs to cancel a visit request, the system 100 is configured to understand that circumstances may arise. However, if the user cancels their request between about two to about five minutes after making the request, there may be a nominal cancellation fee to compensate providers for the provider’s time and effort. The system 100 may provide an indication of the fee to the user.

[0077] The embodiments disclosed herein are examples of the disclosure and may be embodied in various forms. For instance, although certain embodiments herein are described as separate embodiments, each of the embodiments herein may be combined with one or more of the other embodiments herein. Specific structural and functional details disclosed herein are not to be interpreted as limiting, but as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriately detailed structure. Like reference numerals may refer to similar or identical elements throughout the description of the figures.

[0078] The phrases “in an embodiment,” “in embodiments,” “in various embodiments,” “in some embodiments,” or “in other embodiments” may each refer to one or more of the same or different embodiments in accordance with the present disclosure. A phrase in the form “A or B” means “(A), (B), or (A and B) .” A phrase in the form “at least one of A, B, or C” means “(A); (B); (C); (A and B); (A and C); (B and C); or (A, B, and C).”

[0079] Any of the herein described methods, programs, algorithms, or codes may be converted to, or expressed in, a programming language or computer program. The terms “programming language” and “computer program,” as used herein, each include any languageused to specify instructions to a computer, and include (but is not limited to) the following languages and their derivatives: Assembler, Basic, Batch fdes, BCPL, C, C+, C++, Delphi, Fortran, Java, JavaScript, machine code, operating system command languages, Pascal, Perl, PL1, scripting languages, Visual Basic, metalanguages which themselves specify programs, and all first, second, third, fourth, fifth, or further generation computer languages. Also included are database and other data schemas, and any other meta-languages. No distinction is made between languages that are interpreted, compiled, or use both compiled and interpreted approaches. No distinction is made between compiled and source versions of a program. Thus, reference to a program, where the programming language could exist in more than one state (such as source, compiled, object, or linked) is a reference to any and all such states. Reference to a program may encompass the actual instructions and / or the intent of those instructions.

[0080] It should be understood the foregoing description is only illustrative of the present disclosure. Various alternatives and modifications can be devised by those skilled in the art without departing from the disclosure. Accordingly, the present disclosure is intended to embrace all such alternatives, modifications, and variances. The embodiments described with reference to the attached drawing figures are presented only to demonstrate certain examples of the disclosure. Other elements, steps, methods, and techniques that are insubstantially different from those described above are also intended to be within the scope of the disclosure.

Claims

CLAIMSWHAT IS CLAIMED IS:

1. A system for providing healthcare intervention, comprising: a processor; and a memory, including instructions stored thereon, which when executed by the processor cause the system to: receive a first input from a graphical user interface (GUI) on a user device, the first input including an appointment request by a user; receive a second input from the user device by the user; receive a confirmation of the requested appointment from the user; determine a match between the user and a provider based on the first input and the second input; transmit an authenticated request to the provider, based on the first input and the match; receive a confirmation from the provider relating to the authenticated request; and output an alert on the user device indicating the confirmation, the alert including data relating to the requested appointment.

2. The system of claim 1, wherein the instructions, when executed by the processor, further cause the system to: display a first prompt on the user device relating to the requested appointment; and receive, by the user, at least one of a location, a date, or a time for the requested appointment.

3. The system of claim 2, wherein the location includes an address, wherein the address is provided by at least one of a Global Positioning System (GPS), the user device, or manually entered by the user.

4. The system of claim 2, wherein the instructions, when executed by the processor, further cause the system to: display a second prompt on the user device relating to the requested appointment; and receive, by the user, a reason for the requested appointment.

5. The system of claim 4, wherein instructions, when executed by the processor, further cause the system to: determine that emergency services are required based on the reason for the requested appointment; and automatically transmit user details to the emergency services based on the determination that emergency services are required.

6. The system of claim 1, wherein the second input includes a provider selection, where the provider selection is determined based on at least one of a provider preference, a provider proximity, a provider specialty, a provider skill, or a randomly selected provider.

7. The system of claim 1, wherein instructions, when executed by the processor, further cause the system to:obtain a third input including at least one of an acceptance, a rejection, or a request from the provider; and transmit a confirmation to the user device based on the third input.

8. The system of claim 1, wherein outputting the alert further includes: receiving a provider location from a provider device; and displaying the provider location on the user device.

9. The system of claim 1, wherein instructions, when executed by the processor, further cause the system to: display a direct messaging system on the user device, wherein the direct messaging system is configured to communicate with the provider by receiving a touch input on the user device from the user.

10. The system of claim 1, wherein determining the match further includes: providing a confidence level of the match between the user and a provider using machine learning, the confidence level based on at least two of a user profile, provider qualifications, a user health history, a provider availability, and insurance coverage; and determining the match based on the confidence level being over a predetermined threshold.

11. A computer-implemented method for providing healthcare intervention, comprising: receiving a first input from a graphical user interface (GUI) on a user device, the first input including an appointment request by a user; receiving a second input from the user device by the user; receiving a confirmation of the requested appointment from the user; determining a match between the user and a provider based on the first input and the second input; transmitting an authenticated request to the provider, based on the first input and the match; receiving a confirmation from the provider relating to the authenticated request; and outputting an alert on the user device indicating the confirmation, the alert including data relating to the requested appointment.

12. The computer-implemented method of claim 11, further comprising: displaying a first prompt on the user device relating to the requested appointment; and receiving, by the user, at least one of a location, a date, or a time for the requested appointment.

13. The computer-implemented method of claim 12, wherein the location includes an address, wherein the address is provided by at least one of a Global Positioning System (GPS), the user device, or manually entered by the user.

14. The computer-implemented method of claim 12, further comprising: displaying a second prompt on the user device relating to the requested appointment; and receiving, by the user, a reason for the requested appointment.

15. The computer-implemented method of claim 14, further comprising: determining that emergency services are required based on the reason for the requested appointment; and automatically transmit user details to the emergency services based on the determination that emergency services are required.

16. The computer-implemented method of claim 11, wherein the second input includes a provider selection, where the provider selection is determined based on at least one of a provider preference, a provider proximity, a provider specialty, a provider skill, or a randomly selected provider.

17. The computer-implemented method of claim 11, further comprising: obtaining a third input including at least one of an acceptance, a rejection, or a request from the provider; and transmitting a confirmation to the user device based on the third input.

18. The computer-implemented method of claim 11, wherein outputting the alert further includes: receiving a provider location from a provider device; anddisplaying the provider location on the user device.

19. The computer-implemented method of claim 11, further comprising: displaying a direct messaging system on the user device, wherein the direct messaging system is configured to communicate with the provider by receiving a touch input on the user device from the user.

20. The computer-implemented method of claim 11, wherein determining the match further includes: providing a confidence level of the match between the user and a provider using machine learning, the confidence level based on at least two of a user profile, a provider qualification, a user health history, a provider availability, and insurance coverage; and determining the match based on the confidence level being over a predetermined threshold.

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