SISTEMA E MÉTODO DE GERENCIAMENTO DE ATENDIMENTO MÉDICO HÍBRIDO SOB DEMANDA

Description

SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE [oooi] This invention patent refers to a system and method for managing multimodal healthcare, operating in a hybrid manner for in-person home visits and remote care (telemedicine). The invention features an integrated ecosystem of technological modules, allowing the intermediation between doctor and patient to be carried out continuously and automatically, optimizing the work schedule of professionals and eliminating waiting lists in physical units. The system is additionally configured to reduce the response time for low- and medium-complexity home visits through a dynamic geospatial selection algorithm of the active professional with the shortest estimated time of arrival (ETA), decentralizing the fixed hospital model and converting virtual demand into logistically optimized in-person medical care.

[0002] In the current scenario of Brazilian public and private healthcare, the increasing saturation of emergency care units and hospital centers is noticeable, resulting in extensive waiting lines and exposing patients to high-risk biological environments. In addition, a significant portion of the population with reduced mobility, such as the elderly, people with disabilities, and post-operative patients, faces severe logistical barriers to accessing basic healthcare. Simultaneously, the job market for medical professionals presents a surplus of labor that cannot find efficient allocation in hospital physical infrastructures, often limited by rigid schedules and geographically distant working conditions. Petition 870260020061, dated 04 / 03 / 2026, page 17 / 40 2 / 13

[0003] In the state of the art, we find some systems that aim to perform consultations, such as, for example, document BR 10 2015 019130 - 8 filed on 08 / 10 / 2015 and named “MEDICAL ARTIFICIAL INTELLIGENCE CONTROL CENTER WITH REMOTE SYSTEM FOR DIAGNOSIS DEVELOPMENT, MEDICATION PRESCRIPTION AND ONLINE MEDICAL TREATMENT DELIVERY VIA TELEMEDICINE”. This system, through a control center via medical intelligence, allows medical professionals, using the World Wide Web (internet), to attend to and conduct consultations with patients without quantity limits, on a global scale, regardless of location, language, or distance, through telemedicine. The work is done without barriers regarding the specialty of the treatment, in different languages ​​between doctors and patients, and with an unlimited number of consultations and resulting treatments.While the proposed model represents an evolution in the architecture of healthcare service delivery by introducing the concept of hybrid care logistics, the previous patent focuses on thinking (AI diagnosis) and speaking (telemedicine / translation), while Dr. Noble's focuses on doing and going. The innovation here lies not only in remote consultation, but in the dynamic management of a network of professionals for on-demand in-home care, using real-time geolocation algorithms (geofencing) and an emergency triage system (SOS) that connects the patient to the physically nearest doctor.

[0004] Another document that can be cited is BR 10 2013 030998 - 2 deposited on 02 / 12 / 2013 and named “SYSTEM OF "ONLINE VIDEO CONSULTATIONS VIA INTERNET" with the purpose of providing a website for online consultations via video conferencing, where the user has the possibility to find Petition 870260020061, dated 04 / 03 / 2026, p. 18 / 40 3 / 13 of these professionals share their resumes and reviews from other users who have already used their services, making it very easy for users to find a professional they like. After finding a professional, the user can choose to speak with them if they are online or schedule a video conference appointment. In this aspect, the user gains speed of choice, saves time, has a wider variety of options for the right professional, and can also choose based on the price each professional charges for their time. The technical focus of this advancement lies in the selection interface (resume, reviews, and price) and in enabling remote communication to reduce fixed office costs. It is a communication convenience solution, where the system functions as an intermediary for scheduling and video calls. The proposed model, however, presents a substantially different and more complex architecture.While previous models were limited to the virtual environment (working from home), the hybrid healthcare management system and method introduces the Georeferenced Field Operation module. The innovation doesn't stop at choosing the professional; it extends to the logistics of traceable physical travel and is not just an advertising website. It's a crisis management and home care platform that uses proximity algorithms (geofencing) to convert a virtual need into immediate in-person medical care.

[0005] The on-demand hybrid medical care management system and method consists of a disruptive healthcare technology ecosystem, configured as a multimodal platform that synergistically integrates telemedicine care and the provision of in-person medical services under Petition 870260020061, dated 04 / 03 / 2026, page 19 / 40 4 / 13 demand. Through a centralized processing core, the system manages the care flow from biometric screening and digital anamnesis to the dynamic allocation of healthcare professionals via real-time georeferencing. The solution aims to decentralize hospital care, offering a complete logistical infrastructure that guarantees clinical safety, route traceability, and financial efficiency for both patients with reduced mobility and physicians seeking professional autonomy outside conventional physical structures.

[0006] Furthermore, when compared to platforms for professional directories and generic video conferencing, the system demonstrates technical superiority by integrating life safety layers that are absent in common marketplaces. The system has an emergency module (SOS Button) with a priority trigger that bypasses elective steps for critical cases, connecting the nearest medical resource in seconds. Unlike online consultation websites and apps that are limited to scheduling appointments, the present invention manages the chain of custody of in-person care, including monitoring the professional's travel, validating arrival via GPS proximity, and financial protection of the transfer through dynamic cancellation fees and pre-authorization of credit.

[0007] The system's operating mode is simple and cyclical and can be easily understood through the following sequence of steps:

[0008] The multimodal healthcare management system that is the subject of this invention operates through a distributed microservices architecture, preferably hosted on cloud infrastructure, which coordinates the interaction between three interfaces. Petition 870260020061, dated 04 / 03 / 2026, page 20 / 40 5 / 13 main features: Patient App, Doctor App, and intelligent dispatch backend. The logical operation follows a real-time event processing flow, detailed in the following steps:

[0009] The process begins with the data entry module, where the patient, after secure multi-factor authentication, submits a service request. This request is processed by an intelligent triage module based on risk classification algorithms. The system uses fuzzy logic to analyze the responses to a dynamic clinical form completed by the user.

[0010] If the algorithm identifies patterns of high criticality (such as chest pain, mental confusion, or loss of consciousness), the system automatically raises the call status to emergency, triggering a maximum priority event. If the system detects that there are no doctors available in the region for that level of severity, it instantly presents a direct dialing command to public emergency services (SAMU), ensuring the user's safety.

[0011] Once the urgency level of the service has been classified, the dispatch backend consults a geospatial database and a high-speed cache to identify active doctors within a virtual perimeter (geofencing). The selection of the professional is carried out by a cost function that considers three main variables:

[0012] Logistics: Estimated time of arrival (ETA) calculated via map APIs;

[0013] Qualification: The medical specialty compatible with the patient's age and symptoms (e.g., pediatrics for children under 13 years old); Petition 870260020061, dated 04 / 03 / 2026, page 21 / 40 6 / 13

[0014] Operational performance: A reliability index based on the physician's punctuality history and evaluations of previous appointments.

[0015] The system sends a real-time notification to the selected doctor. If there is no acceptance within a short period of time, the algorithm automatically reprocesses the queue, searching for the next available professional based on demand heatmaps.

[0016] Upon acceptance, the system establishes an encrypted communication channel between the parties. The patient's application displays the doctor's location on the map in real time, updating GPS coordinates at short intervals. Simultaneously, the patient's health profile and their attached exam history (stored in the cloud with end-to-end encryption) are released for viewing on the doctor's device, allowing the professional to study the case during the journey.

[0017] An internal chat is activated for preliminary instructions. The system uses location sensors to automatically detect when the doctor arrives at the patient's residence, recording the exact start time for monitoring service quality. If the patient is absent from the location after confirmed arrival, the system allows the doctor to end the call and charge the full amount.

[0018] The system supports the transition to telemedicine via low-latency video protocol if in-person care is not the chosen method. During in-person or remote care, the doctor can generate prescriptions and exam requests through integration with digital prescription platforms, sending the access link directly to the patient's chat. Petition 870260020061, dated 04 / 03 / 2026, page 22 / 40 7 / 13

[0019] Upon completion of the procedure, the doctor signals completion in the application, which triggers automatic billing to the previously registered credit card. The processed amount takes into account whether there was physical travel (transportation fee) or if the service was strictly virtual. If payment fails, the system blocks new appointments for that profile until the payment is settled. The cycle ends with the sending of a mandatory satisfaction survey, whose data feeds back into the operational intelligence algorithm for optimization of future medical dispatches.

[0020] The innovation lies in the orchestration of states: the software maintains a state machine for each call, ensuring that the transition between the triage, dispatch, routing, and service phases occurs seamlessly, even in situations of connection failure. The system is designed to be offline-first on mobile, synchronizing data as soon as the network is restored, which is critical for home visits in areas with poor signal.

[0021] The following description and associated figures will make clear the subject matter of this invention patent.

[0022] Figure 01 represents a detailed flowchart of the system's operation and the hybrid on-demand service management method.

[0023] Figure 02 represents a flowchart of the application's operation from registration to the completion of the service.

[0024] Figure 01 presents a flowchart of the system's operation. The upper layer, called Mobile, houses the applications dedicated to the patient and the doctor, which act as the system's interaction terminals. Communication between these devices and the Back-end is mediated by an API Gateway, using REST protocols for data requests and WebSockets for the Petition 870260020061, dated 04 / 03 / 2026, page 23 / 40 8 / 13 real-time information exchange, ensuring the low latency required for geographic monitoring.

[0025] Once the request passes through the Gateway, it is directed to specialized modules that make up the system's intelligence:

[0026] - The AI ​​triage service receives clinical data to perform risk classification and prioritize care.

[0027] - The intelligent dispatch module operates in dynamic allocation, interacting directly with the infrastructure layer to consume map services, which allows for route calculation and real-time tracking.

[0028] - Simultaneously, the system manages call management, user management, and the administrative portal for governance control.

[0029] - Operational performance is monitored by the SLA / Score management module, which audits the efficiency of service delivery.

[0030] The infrastructure layer provides essential support for the execution of business rules. In addition to map services, it integrates payment modules (for financial processing of queries) and notification modules (for push or SMS alerts). Information persistence is performed in a hybrid way: a relational database is used for structured data, such as registrations and financial transactions, while a NoSQL database processes dynamic and high-volume data, such as location records and event logs.

[0031] The integration between mobile applications and the system core occurs via API Gateway, which manages data traffic using REST protocols for asynchronous state requests and WebSockets for maintaining bidirectional communication tunnels. Petition 870260020061, dated 04 / 03 / 2026, page 24 / 40 9 / 13 in real time, essential for GPS telemetry and low-latency notifications.

[0032] The artificial intelligence integration flow begins with the receipt of structured clinical data packages, which are submitted to the AI ​​triage service. This module consumes fuzzy logic and language processing algorithms to convert symptoms into a risk and priority classification, returning a status token that dynamically alters the behavior of the Dispatch Backend. Technically, the integration with dispatch is done through synchronous queries to a high-performance database (NoSQL / Redis), which maintains the presence status and updated geographic coordinates of all active medical devices. The dispatch algorithm cross-references the triage data with the georeferenced location, using map service APIs to calculate the shortest time of arrival (ETA) and route feasibility, selecting the professional whose profile and geographic position optimize the care response.

[0033] The infrastructure layer ensures the persistence and security of this integration through a hybrid database model, where sensitive and financial data are allocated in relational systems supporting ACID transactions, while route logs and telemetry are processed in non-relational databases to support high volume. Financial integration is performed via webhooks with payment gateways, allowing the completion of the service in the Doctor's App to atomically trigger the capture of the value and the update of the clinical history in the Patient's App. Finally, technical traceability is ensured by an SLA and Score Management module, which audits each data packet transmitted between modules, allowing the administrative portal to have a comprehensive view. Petition 870260020061, dated 04 / 03 / 2026, page 25 / 40 10 / 13 real-time efficiency of the entire logistics and clinical network of the platform.

[0034] The System also comprises an assisted decision infrastructure that operates through a multi-layer adaptive anamnesis engine. This engine uses a weighted symptom graph and sequential Bayesian update logic to perform a mathematical reduction of diagnostic uncertainty in real time. Unlike static triage systems, the invention dynamically selects the next question based on information gain, generating a structured probabilistic diagnostic hypothesis that anticipates clinical reasoning for the attending physician.

[0035] Operational intelligence is governed by a multi-objective medical-geospatial orchestrator, which executes a weighted cost function for dispatching professionals. This algorithm minimizes estimated time of arrival (ETA), distance, and clinical risk variables, while maximizing performance score and specialty compatibility. The system operates under a dynamic composite risk classification model, which uses multimodal data fusion and sliding time windows to detect patterns of clinical deterioration, allowing for automatic resource escalation and prioritization of care based on a continuously recalculated risk index.

[0036] The care cycle is completed by a clinical learning and safety loop, which implements a continuous feedback system based on real outcomes. This module collects longitudinal post-consultation data for retraining AI models, recalibrating diagnostic probabilities and automatically adjusting clinical protocols. Additionally, an automated safety layer performs cross-checking. Petition 870260020061, dated 04 / 03 / 2026, page 26 / 40 11 / 13 medication and the detection of warning signs (red flags) in real time, generating an immutable clinical audit trail that ensures the integrity of the validated medical decision.

[0037] A continuous clinical reclassification module configured to monitor, during the care cycle, data entered by the professional and / or patient, being able to dynamically recalculate the care risk index and automatically change the priority of the call, including escalation to higher levels of criticality or redirection to public emergency services when necessary.

[0038] The internal collaborative consultation mechanism allows the attending physician to request, in real time, a second opinion from another qualified professional in the network, with encrypted sharing of clinical data and auditable recording of the technical intervention. A module for longitudinal evaluation of clinical outcomes is configured to correlate diagnostic hypotheses and adopted actions with subsequently reported or recorded results, generating a clinical assertiveness index that feeds back into the prioritization and professional qualification algorithm.

[0039] Anomalous behavior detection module based on statistical analysis of transactional, clinical and operational patterns, configured to assign an anti-fraud risk score and automatically block profiles with relevant indications of misuse.

[0040] The system integrates an operational safety mechanism configured to monitor the movement of the professional in the field, including an emergency alert button, location sharing with the administrative center, and territorial risk classification. Petition 870260020061, dated 04 / 03 / 2026, page 27 / 40 12 / 13

[0041] Structured interoperability interface via standardized APIs for sending and receiving clinical data, enabling continuity of care with hospitals, clinics and public health services.

[0042] Adaptive pricing mechanism configured to automatically adjust service values ​​based on regional demand variables, estimated travel time, and operational availability.

[0043] The System integrates a digital clinical governance module configured for automated versioning of care protocols, adherence auditing, and traceable recording of regulatory updates.

[0044] Analytical module configured for anonymized aggregation of healthcare data with generation of regional epidemiological maps and automated identification of atypical incidence patterns.

[0045] The system comprises a parameterizable architecture configured for customization by third parties, including regulatory adaptation, visual identity and regional operational rules, without altering the core care logic.

[0046] The system also includes a multi-profile management module configured to allow the linking of multiple dependent users to a responsible holder, maintaining individualized segregation of clinical history, hierarchical access permissions, and centralized billing. This module enables granular authorization control for viewing and sharing health data, parameterization by age group or vulnerability condition, and auditable logging of actions performed by Petition 870260020061, dated 04 / 03 / 2026, page 28 / 40 13 / 13 legal representative, preserving the integrity and confidentiality of sensitive information.

[0047] The system may also integrate external biometric monitoring devices and / or wearable sensors configured for automatic collection of physiological data in real time, with structured transmission to the adaptive screening engine and the continuous reclassification mechanism.

Claims

1. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, which manages multimodal medical care, operating in a hybrid manner for in-person, home, and remote care, allowing the intermediation between doctor and patient to be carried out continuously and automatically, characterized by comprising: - an intelligent triage module configured to classify care risk through fuzzy logic and probabilistic processing; - an intelligent dispatch backend configured to identify active professionals within a georeferenced virtual perimeter (geofencing); - a multi-objective medical-geospatial orchestrator configured to execute a weighted cost function that includes at least the estimated time of arrival (ETA) as a logistical variable, and may also consider additional clinical and operational variables for optimizing care logistics;- A multi-layered adaptive anamnesis engine configured to dynamically select clinical questions based on information gain and sequential Bayesian updating; - A continuous clinical escalation mechanism configured to dynamically recalculate the care risk index during the care cycle; Petition 870260020061, dated 04 / 03 / 2026, page 30 / 40 2 / 5 - A care safety mechanism with an emergency trigger configured for automatic priority escalation and integration with public emergency services; - An automated safety layer configured for cross-checking of medications and detection of warning signs; - A clinical scoring module based on real outcomes; - A hybrid distributed computing architecture composed of a relational database for structured data and a NoSQL database for geographic telemetry; - A white-label configurable module configured for regulatory and operational adaptation;- A time-based healthcare optimization mechanism configured to minimize the estimated time of arrival (ETA) through dynamic georeferenced selection of the nearest active professional; 2. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by the fact that the anamnesis engine dynamically selects the next clinical question based on the information gained to generate a structured probabilistic diagnostic hypothesis.

3. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by performing automatic reprocessing of the care queue based on demand heat maps in case the call is not accepted within a predefined time interval.

4. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by a learning loop and clinical safety that performs longitudinal collection of post-consultation outcomes for automatic retraining of artificial intelligence models and protocol calibration.

5. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by the fact that the physician's application provides encrypted viewing of the patient's medical history and examinations during the traceable physical travel time.

6. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by comprising a hybrid data infrastructure layer, using a relational database for financial and registration transactions and a NoSQL database for GPS telemetry records and high-volume event logs.

7. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by a clinical escalation module, an internal clinical second opinion module, and an anti-fraud module with automated behavioral analysis.

8. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by an operational security mechanism configured to monitor the movement of the professional in the field. Petition 870260020061, dated 04 / 03 / 2026, page 32 / 40 4 / 5 9. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by a dynamic pricing module based on logistics and demand variables.

10. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by an epidemiological analysis module based on anonymized data aggregation.

11. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by a multi-profile family management module configured for hierarchical linking of dependents.

12. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by the medical-geospatial orchestrator executing an adaptive multi-variable cost function, with dynamic weighting recalculated in real time, combining logistical, clinical and operational variables, including estimated time of arrival (ETA), dynamic care risk index, medical specialty compatibility, historical professional performance score and regional demand density, being configured for simultaneous optimization of time, clinical safety and logistical efficiency.

13. SYSTEM AND METHOD FOR MANAGING HYBRID ON-DEMAND MEDICAL CARE, according to claim 1, characterized by an integration module with autonomous devices and / or external biometric sensors (Petition 870260020061, dated 04 / 03 / 2026, page 33 / 40 5 / 5) configured for automatic collection of clinical data in real time and feeding the adaptive triage engine and the continuous reclassification mechanism.

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