Patent Publication Number: US-11398313-B2

Title: Intelligent touch care corresponding to a patient reporting a change in condition

Description:
CROSS-REFERENCE 
     This application claims priority to U.S. Provisional Patent Application No. 62/742,754, filed on Oct. 8, 2018, which is hereby incorporated by reference in its entirety. 
     BACKGROUND 
     Early warning systems are often used in the clinical setting (e.g., acute care) to detect patient deterioration and drive clinical decision-making. For example, the early warning system may detect that a particular condition a patient has been diagnosed with or a particular medication the patient is being treated with makes the patient a higher risk for a particular negative outcome. Unfortunately, these systems are limited to the clinical setting and do not account for, for example, a patient in a community care setting (e.g., in person visit in the community, in person visit at a clinic, clinical video visit, telephonic assessment or follow-up, electronic assessment via a patient portal or a voice system, upstream transition to a higher level of care setting, or a referral for an outside service such as transportation, meal service, or behavioral health evaluation). Moreover, these systems fail to consider additional patient information that is particularly relevant outside of a clinical facility (e.g., social determinant of health risk factors such as transportation limitations or food insecurity). This results in overlooked risk factors for the patient that increases the risk of deterioration or an acute event, resulting in an overall increase in health care costs. 
     Various touch points may be needed based on the needs of a particular patient in a community care setting. For example, based on demographics corresponding to the patient, a particular condition the patient has been diagnosed with or the particular medication the patient is being treated with, or other factors, the patient may need follow-ups at particular time intervals. However, in the community care setting, in-person follow-ups are not always needed and are over-utilized which results in inefficient workforce management and fewer patient touch points. This results in unnecessary or missed touch points, unnecessary in-person appointments, and an overall increase in health care costs. 
     BRIEF SUMMARY 
     This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. 
     Embodiments of the present disclosure relate to systems, methods, and user interfaces for providing intelligent touch care. More particularly, embodiments of the present disclosure utilizes contributing data elements in a community early warning score (CEWS) to predict touchpoint discipline and to recommend frequency, modality, and upstream transitions of care and outside service referrals for a patient in a community care setting. In response to a touch point (e.g., a change in condition or medication, a scheduled or unscheduled appointment, or a patient question), the CEWS can be utilized along with data in an EHR of a patient, data from a patient device, or data from a patient portal to initiate a follow-up (e.g., personal health question or encounter). 
     Notification tools and scheduling functionality are provided via a user interface of the patient device to improve clinical workforce capacity, increase the number of patient touches, and encourage heightened patient engagement. Moreover, the ability to capture dynamic rising risk provides clinical insight into changing risk outside of the controlled environment of a clinical facility. Overall, outcomes for the patient can be improved, touch points can be increased, and unnecessary in-person appointments and overall health care costs can be reduced. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       The patent or application file contains at least one drawing executed in color. The present invention is described in detail below with reference to the attached drawing figures, wherein: 
         FIG. 1  is a block diagram of an exemplary operating environment suitable to implement embodiments of the present invention; 
         FIG. 2  depicts an exemplary framework of a community early warning score system suitable to implement embodiments of the present invention; 
         FIG. 3  depicts an exemplary framework of an intelligent touch care system suitable to implement embodiments of the present invention; 
         FIG. 4  depicts an illustrative screen display of a community early warning score interface, in accordance with an embodiment of the present invention; 
         FIGS. 5-6  depict illustrative screen displays of an intelligent touch care interface, in accordance with an embodiment of the present invention; 
         FIG. 7  depicts a flow diagram of a method illustrating a touch point corresponding to a change in a condition or an order that initiates a workflow, in accordance with an embodiment of the present invention; 
         FIG. 8  depicts a flow diagram of a method illustrating a touch point corresponding to an unscheduled appointment with a clinician that initiates a workflow, in accordance with an embodiment of the present invention; 
         FIG. 9  depicts a flow diagram of a method illustrating a touch point corresponding to a scheduled appointment with a clinician that initiates a workflow, in accordance with an embodiment of the present invention; 
         FIG. 10  depicts a flow diagram of a method illustrating a touch point corresponding to change in condition for an active community care patient that initiates a workflow, in accordance with an embodiment of the present invention; 
         FIG. 11  is a flow diagram of a method illustrating a touch point corresponding to a patient message of an active community care patient that initiates a workflow, in accordance with embodiments of the invention; and 
         FIG. 12  is a flow diagram of a method illustrating dynamically updating a CEWS, in accordance with embodiments of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     The subject matter of the present invention is described with specificity herein to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the terms “step” and/or “block” might be used herein to connote different elements of methods employed, the terms should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly stated. 
     As noted in the background, early warning systems are often used in the clinical setting (e.g., acute care) to detect patient deterioration and drive clinical decision-making. For example, the early warning system may detect that a particular condition a patient has been diagnosed with or a particular medication the patient is being treated with makes the patient a higher risk for a particular negative outcome. Unfortunately, these systems are limited to the clinical setting and do not account for, for example, a patient in a community care setting. Moreover, these systems fail to consider additional patient information that is particularly relevant to a patient in a community care setting. This results in overlooked risk factors for the patient that increases the risk of deterioration or an acute event, resulting in an overall increase in health care costs. 
     Various touch points may be needed based on the needs of a particular patient in a community care setting. For example, based on demographics corresponding to the patient, a particular condition the patient has been diagnosed with or the particular medication the patient is being treated with, or other factors, the patient may need follow-ups at particular time intervals. However, in the community care setting, in-person follow-ups are not always needed and are over-utilized which results in inefficient workforce management and fewer patient touch points. This results in unnecessary or missed touch points, unnecessary in-person appointments, and an overall increase in health care costs. 
     Embodiments of the present disclosure relate to systems, methods, and user interfaces for providing intelligent touch care. More particularly, embodiments of the present disclosure utilizes contributing data elements in a community early warning score (CEWS) to predict touchpoint discipline and to recommend frequency, modality, and upstream transitions of care and outside service referrals for a patient in a community care setting. In response to a touch point (e.g., a change in condition or medication, a scheduled or unscheduled appointment, or a patient question), the CEWS can be utilized along with data in an EHR of a patient, data from a patient device, or data from a patient portal to initiate a follow-up (e.g., personal health question or encounter). 
     Notification tools and scheduling functionality are provided via a user interface of the patient device to improve clinical workforce capacity, increase the number of patient touches, and encourage heightened patient engagement. Moreover, the ability to capture dynamic rising risk provides clinical insight into changing risk outside of the controlled environment of a clinical facility. Overall, outcomes for the patient can be improved, touch points can be increased, and unnecessary in-person appointments and overall health care costs can be reduced. 
     Accordingly, one embodiment of the present disclosure is directed to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computer, causes the computer to perform operations. The operations comprise receiving a touch point for a patient in a community care setting. The touch point corresponds to a change in a condition or order. The operations also comprise, in response to the touch point, crawling data in an electronic health record (EHR) for the patient. The operations further comprise, based on the touch point and the data in the EHR, triggering a follow-up for the patient. The operations also comprise, in response to the follow-up, notifying the patient. 
     In another embodiment, the present disclosure directed to a computerized method. The method comprises receiving a touch point for a patient in a community care setting. The touch point corresponds to a change in a condition or order. The method also comprises, in response to the touch point, crawling data in an electronic health record (EHR) for the patient. The data includes a community early warning score (CEWS). The method further comprises, based on the touch point and the data in the EHR, triggering a follow-up for the patient. The method also comprises, in response to the follow-up, notifying the patient with a notification provided via a consumer device or personal assistant voice service, the notification indicating that a personal health question is available for the patient. 
     In yet another embodiment, the present disclosure is directed to a system. The system comprises a processor; and a computer storage medium storing computer-usable instructions that, when used by the processor, cause the processor to: receive a touch point for a patient in a community care setting, the touch point corresponding to a change in a condition or order; in response to the touch point, crawl data in an electronic health record (EHR) for the patient, the data including a community early warning score (CEWS); based on the touch point and the data in the EHR, trigger a follow-up for the patient; and in response to the follow-up, notify the patient with a notification provided via a consumer device or personal assistant voice service, the notification indicating that a personal health question is available for the patient. 
     Another of the present disclosure is directed to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computer, causes the computer to perform operations. The operations comprise receiving a touch point for a patient in a community care setting, the touch point corresponding to a new order provided during an unscheduled appointment. The operations also comprise, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The operations further comprise, crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The operations also comprise, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient. The operations further comprise, in response to the follow-up, scheduling an encounter or generating a new touch point. 
     In another embodiment, the present disclosure directed to a computerized method. The method comprises receiving a touch point for a patient in a community care setting. The touch point corresponds to a new order provided during an unscheduled appointment. The method also comprises, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The method further comprises crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The method also comprises, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient. The notification is provided via a consumer device or via a personal assistant voice service and indicates that a personal health question is available for the patient. The method further comprises, in response to the follow-up, scheduling an encounter or generating a new touch point. 
     In yet another embodiment, the present disclosure is directed to a system. The system comprises a processor; and a computer storage medium storing computer-usable instructions that, when used by the processor, cause the processor to: receive a touch point for a patient in a community care setting, the touch point corresponding to a new order provided during an unscheduled appointment; in response to the touch point, communicate data corresponding to the touch point to an electronic health record (EHR) for the patient; crawl data in the EHR for the patient. The data includes a community early warning score (CEWS); based on the touch point and the data in the EHR, trigger a follow-up for the patient; and in response to the follow-up, schedule an encounter or generate a new touch point. 
     Another embodiment of the present disclosure is directed to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computer, causes the computer to perform operations. The operations comprise receiving a touch point for a patient in a community care setting. The touch point corresponds to a new order provided during a scheduled appointment. The operations also comprise, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The operations further comprise, crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The operations also comprise, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient. The operations further comprise, in response to an indication the patient has questions or concerns, initiating a telephone clinical assessment. 
     In another embodiment, the present disclosure directed to a computerized method. The method comprises receiving a touch point for a patient in a community care setting. The touch point corresponds to a new order provided during a scheduled appointment. The method also comprises, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The method further comprises crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The method also comprises, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient. The method further comprises, in response to an indication the patient has questions or concerns, initiating a telephone clinical assessment. 
     In yet another embodiment, the present disclosure is directed to a system. The system comprises a processor; and a computer storage medium storing computer-usable instructions that, when used by the processor, cause the processor to: receive a touch point for a patient in a community care setting, the touch point corresponding to a new order provided during a scheduled appointment; in response to the touch point, communicate data corresponding to the touch point to an electronic health record (EHR) for the patient; crawl data in the EHR for the patient, the data including a community early warning score (CEWS); based on the touch point and the data in the EHR, trigger a follow-up comprising a notification for the patient, the notification is provided to the patient via a consumer device or via a personal assistant voice service and indicating that a personal health question is available for the patient; based on a response to the personal health question, receive an indication the patient has questions or concerns; in response to the indication, initiate a telephone clinical assessment; and provide a recommendation to a clinician performing the telephone clinical assessment to address the questions or concerns. 
     Another embodiment of the present disclosure is directed to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computer, causes the computer to perform operations. The operations comprise receiving a touch point for a patient in a community care setting. The touch point indicates the patient has a question for a clinician. The operations also comprise, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The operations further comprise crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The operations also comprise, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient or initiating a telephone clinical assessment. 
     In another embodiment, the present disclosure directed to a computerized method. The method comprises receiving a touch point for a patient in a community care setting. The touch point indicates the patient has a question for a clinician. The method also comprises, in response to the touch point, communicating data corresponding to the touch point to an electronic health record (EHR) for the patient. The method further comprises crawling data in the EHR for the patient. The data includes a community early warning score (CEWS). The method also comprises, based on the touch point and the data in the EHR, triggering a follow-up comprising a notification for the patient or initiating a telephone clinical assessment. 
     In yet another embodiment, the present disclosure is directed to a system. The system comprises a processor; and a computer storage medium storing computer-usable instructions that, when used by the processor, cause the processor to: receive a touch point for a patient in a community care setting, the touch point indicating the patient has a question for a clinician; in response to the touch point, communicate data corresponding to the touch point to an electronic health record (EHR) for the patient; crawl data in the EHR for the patient, the data including a community early warning score (CEWS); and based on the touch point and the data in the EHR, trigger a follow-up comprising a notification for the patient or initiating a telephone clinical assessment. 
     Another embodiment of the present disclosure is directed to one or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computer, causes the computer to perform operations. The operations comprise receiving, at a community early warning score (CEWS) engine comprising a plurality of data crawlers, a request to dynamically update a CEWS for a patient. The operations also comprise initiating a first set of the plurality of data crawlers to collect data in an electronic health record (EHR) of the patient. Each of the first set of the plurality of data crawlers is responsible for collecting a distinct type of data within the EHR. The operations further comprise initiating a second set of the plurality of data crawlers to collect data originating from a patient device corresponding to the patient. The operations also comprise utilizing the data collected by the plurality of data crawlers, dynamically updating the CEWS at the CEWS engine. The operations further comprise, based on the updated CEWS, initiating a workflow for the patient at the patient device or a clinician device. 
     In another embodiment, the present disclosure directed to a computerized method. The method comprises receiving, at a community early warning score (CEWS) engine comprising a plurality of data crawlers, a request to dynamically update a CEWS for a patient. The method also comprises initiating a first set of the plurality of data crawlers to collect data in an electronic health record (EHR) of the patient. Each of the first set of the plurality of data crawlers is responsible for collecting a distinct type of data within the EHR. The method further comprises utilizing the data collected by the plurality of data crawlers, dynamically updating the CEWS at the CEWS engine. The method also comprises, based on the updated CEWS, initiating a workflow for the patient at the patient device or a clinician device. 
     In yet another embodiment, the present disclosure is directed to a system. The system comprises a processor; and a computer storage medium storing computer-usable instructions that, when used by the processor, cause the processor to: receive, at a community early warning score (CEWS) engine comprising a plurality of data crawlers, a request to dynamically update a CEWS for a patient; initiate a first set of the plurality of data crawlers to collect data in an electronic health record (EHR) of the patient, each of the first set of the plurality of data crawlers responsible for collecting a distinct type of data within the EHR; initiate a second set of the plurality of data crawlers to collect data originating from a patient device corresponding to the patient; utilizing the data collected by the plurality of data crawlers, dynamically update the CEWS at the CEWS engine; and based on the updated CEWS, initiate a workflow for the patient at the patient device or a clinician device. 
     Having briefly described embodiments of the present invention, an exemplary operating environment suitable for use in implementing embodiments of the present invention is described below.  FIG. 1  provides an aspect of an example operating environment with which embodiments of the present invention may be implemented. The aspect of an operating environment is illustrated and designated generally as reference numeral  100 . 
     Example operating environment  100  comprises a general purpose computing device in the form of a control server  102 . Exemplary components of the control server  102  comprise a processing unit, internal system memory, and a suitable system bus for coupling various system components, including database cluster  104 , with the control server  102 . The system bus might be any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, and a local bus, using any of a variety of bus architectures. Exemplary architectures comprise Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronic Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus, also known as Mezzanine bus. 
     Control server  102  typically includes therein, or has access to, a variety of computer-readable media, for instance, database cluster  104 . Computer-readable media can be any available media that might be accessed by control server  102 , and includes volatile and nonvolatile media, as well as, removable and nonremovable media. Computer-readable media might include computer storage media. Computer storage media includes volatile and nonvolatile media, as well as removable and nonremovable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules, or other data. In this regard, computer storage media might comprise RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVDs) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage, or other magnetic storage device, or any other medium which can be used to store the desired information and which may be accessed by the control server  102 . Computer storage media does not comprise signals per se. Combinations of any of the above also may be included within the scope of computer-readable media. 
     The computer storage media discussed above and illustrated in  FIG. 1 , including database cluster  104 , provide storage of computer-readable instructions, data structures, program modules, and other data for the control server  102 . In some embodiments, data cluster  104  takes the form of a cloud-based data store, and in some embodiments is accessible by a cloud-based computing platform. 
     The control server  102  might operate in a computer network  106  using logical connections to one or more remote computers  108 . Remote computers  108  might be located at a variety of locations in a medical or research environment, including clinical laboratories (e.g., molecular diagnostic laboratories), hospitals and other inpatient settings, veterinary environments, ambulatory settings, medical billing and financial offices, hospital administration settings, home health care environments, and providers&#39; offices. Providers may comprise a treating physician or physicians; specialists such as surgeons, radiologists, cardiologists, and oncologists; emergency medical technicians; physicians&#39; assistants; nurse practitioners; nurses; nurses&#39; aides; pharmacists; dieticians; microbiologists; laboratory experts; laboratory technologists; genetic counselors; researchers; veterinarians; students; and the like. 
     The remote computers  108  might also be physically located in nontraditional medical care environments so that the entire health care community might be capable of integration on the network. The remote computers  108  might be personal computers, servers, routers, network PCs, peer devices, other common network nodes, or the like and might comprise some or all of the elements described above in relation to the control server  102 . The devices can be personal digital assistants or other like devices. 
     Exemplary computer networks  106  comprise local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. When utilized in a WAN networking environment, the control server  102  might comprise a modem or other means for establishing communications over the WAN, such as the Internet. In a networked environment, program modules or portions thereof might be stored in association with the control server  102 , the database cluster  104 , or any of the remote computers  108 . For example, various application programs may reside on the memory associated with any one or more of the remote computers  108 . It will be appreciated by those of ordinary skill in the art that the network connections shown are exemplary and other means of establishing a communications link between the computers (e.g., control server  102  and remote computers  108 ) might be utilized. 
     In operation, an organization might enter commands and information into the control server  102  or convey the commands and information to the control server  102  via one or more of the remote computers  108  through input devices, such as a keyboard, a pointing device (commonly referred to as a mouse), a trackball, or a touch pad. Other input devices comprise microphones, satellite dishes, scanners, or the like. Commands and information might also be sent directly from a remote health care device to the control server  102 . In addition to a monitor, the control server  102  and/or remote computers  108  might comprise other peripheral output devices, such as speakers and a printer. 
     In some embodiments, control server  102  is a computing system or platform made up of one or more computing devices. Embodiments of control server  102  may be a distributed computing system, a centralized computing system, a single computer such as a desktop or laptop computer or a networked computing system. Thus, in some embodiments, control server  102  comprises a multi-agent computer system with software agents. 
     Turning now to  FIG. 2 , an exemplary framework of a community early warning score (CEWS) system  200  is shown, in accordance with an aspect of the present invention. It should be understood that this and other arrangements described herein are set forth only as examples. Other arrangements and elements (e.g., machines, interfaces, functions, orders, and groupings of functions, etc.) can be used in addition to or instead of those shown, and some elements may be omitted altogether. Further, many of the elements described herein are functional entities that may be implemented as discrete or distributed components or in conjunction with other components, and in any suitable combination and location. Various functions described herein as being performed by one or more entities may be carried out by hardware, firmware, and/or software. For instance, various functions may be carried out by a processor executing instructions stored in memory. The CEWS system  200  may be implemented via any type of computing device, such as computing device  100  described above with reference to  FIG. 1 , for example. 
     The CEWS system  200  generally operates to determine a CEWS for a patient. More particularly, the CEWS system  200  dynamically updates the CEWS for the patient which may be utilized by an intelligent touch care system to provide a workflow to a patient device  240  and/or a clinician device (e.g., clinician device  316  of  FIG. 3 ). To do so, the CEWS system utilizes the data in an EHR to periodically dynamically update the CEWS of the patient which can be utilized by an intelligent touch care engine (such as the intelligent touch care engine  306  of  FIG. 3 ), as described herein, to improve outcomes for the patient, increase overall touch points, reduce unnecessary in-person appointments, and reduce overall health care costs. In some embodiments, an update to the CEWS may trigger a workflow provided by the intelligent touch care engine. 
     As shown in  FIG. 2 , the CEWS system  200  includes, among other components not shown, EHR  204 , CEWS engine  218 , and patient device  240 . It should be understood that the CEWS system  200  shown in  FIG. 2  is an example of one suitable computing system architecture. Each of the components shown in  FIG. 2  may be implemented via any type of computing device, such as computing device  100  described with reference to  FIG. 1 , for example. 
     The components may communicate with each other via a network  202 , which may include, without limitation, one or more local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. It should be understood that any number of EHRs and CEWS engines may be employed within the CEWS system  200  within the scope of the present disclosure. Each may comprise a single device or multiple devices cooperating in a distributed environment. For instance, the CEWS engine  218  (or any of its components: initial index component  220 , clinical risk factors component  222 , social determinants of health (SDOH) risk profile component  224 , clinical risk profile score component  226 , biometrics component  228 , symptomatology component  230 , and clinical assist component  232 ) and/or the EHR  204  may be provided via multiple devices arranged in a distributed environment that collectively provide the functionality described herein. In other embodiments, a single device may provide the functionality of multiple components of the CEWS system  200 . For example, a single device may provide the EHR  204  and the CEWS engine  218 . In some embodiments, some or all functionality provided by the CEWS engine  218  (or any of its components) may be provided by a patient device or a clinician device (such as patient device  240  or clinician device  316  of  FIG. 3 ). Additionally, other components not shown may also be included within the network environment. 
     EHR  204  includes an electronic version of patient records including information for the patient, such as surveys, trauma documentation, including images, clinical notes, orders, summaries, reports, analyses, information received from medical devices, or other types of electronic medical documentation relevant to a particular patient&#39;s condition and/or treatment. Electronic clinical documents contain various types of information relevant to the condition and/or treatment of a particular patient and can include information relating to, for example, patient identification information, images, alert history, culture results, physical examinations, vital signs, past medical histories, surgical histories, family histories, histories of present illnesses, current and past medications, allergies, symptoms, past orders, completed orders, pending orders, tasks, lab results, other test results, patient encounters and/or visits, immunizations, physician comments, nurse comments, other caretaker comments, clinician assignments, and a host of other relevant clinical information. The content and volume of such information in the EHR is not intended to limit the scope of embodiments of the present invention in any way. 
     As shown, EHR  204  includes medical history  206 , facility biometric data  208 , assessment data  210 , medication profile  212 , active diagnoses  214 , and risk assessments  216 . The data that comprises each of these components of EHR  204  can be utilized by various components of the CEWS engine  218  at various time intervals to dynamically update a CEWS. The CEWS combines the National Early Warning Score 2, a comprehensive risk profile, clinical assessment data and biometric data to predict rising risk of: 1) a condition or chronic disease exacerbation; 2) a clinical system decline; or 3) an acute event or change (e.g., urinary tract infection or pneumonia). Although the CEWS is described herein with reference to a community care setting, it is contemplated that the CEWS is venue agnostic and can be utilized across any post-acute or acute venues. 
     Generally, and as mentioned, the CEWS engine  218  crawls data in the EHR to dynamically update the CEWS. As shown, the CEWS engine  218  comprises an initial index component  220 , a clinical risk factors component  222 , a social determinants of health (SDOH) risk profile component  224 , a clinical risk profile score component  226 , a biometrics component  228 , symptomatology component  230 , and a clinical assist component  232 . Each of the components of CEWS engine  218  are responsible for crawling a distinct type of data within the EHR  204 . 
     For example, initial index component  220  crawls facility biometric data  208  and assessment data  210  of EHR  204  to calculate the National Early Warning Score 2 for a patient. The assessment data includes respiratory rate, an estimate of arterial oxygen saturation, hypercapnia, supplemental Oxygen, systolic blood pressure, heart rate, level of consciousness (or new onset confusion), temperature, and the like. 
     Clinical risk factors component  222  crawls medical history  206  and medication profile  212  of EHR  204  to determine the clinical risk factors of the patient. The clinical risk factors may include if the patient is an opioid risk, an amputee, body mass index, utilizes a medicinal sleep aid, is paraplegic or quadriplegic, has a recent acute admission, is polychronic or polypharmacy, and the like. 
     Social determinants of health (SDOH) risk profile component  224  crawls assessment data  210  and risk assessments  216  of EHR  204  to determine a SDOH risk profile of the patient. The SDOH risk profile may include various factors corresponding to the patient such as the current housing situation of the patient, transportation available to the patient, utilities available to the patient, a financial situation of the patient, a health literacy of the patient, modes of communication available to the patient, social engagement of the patient, stress of the patient, food insecurity of the patient, and the like. 
     Clinical risk profile score component  226  crawls risk assessments  216  of EHR  204  to determine a clinical risk profile score. The clinical risk profile score may be comprised of risks corresponding to pain, fall, depression, anxiety, dyspnea, Activities of Daily Living/Instrumental Activities of Daily Living, frail or elderly, medication adherence, engagement, confusion, suicide risk, post-traumatic stress disorder, and the like. 
     Biometrics component  228  crawls facility biometric data  208  and assessment data  210  of EHR  204  to determine biometrics for the patient. Biometrics may include temperature, heart rate, systolic blood pressure, diastolic blood pressure, mean arterial blood pressure, weight, glucose, supplemental Oxygen, an estimate of arterial oxygen saturation, respiratory rate, activity, sleep, and the like. 
     Symptomatology component  230  crawls assessments  216  of EHR  204  to determine symptomology for the patient. Symptomatology may include any assessed symptoms. 
     Clinical assist component  232  crawls facility biometric data  208  of EHR  204  to determine clinical assist mechanisms associated with the patient. For example, clinical assist mechanisms may include whether the patient is on oxygen, infusion, a particular nutrition plan, dialysis, chemotherapy, radiation, assistive devices, and the like. 
     Additional information from patient device  240  may be crawled by clinical risk factors component  222 , social determinants of health (SDOH) risk profile component  224 , clinical risk profile score component  226 , biometrics component  228 , symptomatology component  230 , and clinical assist component  232 . Additionally or alternatively, the information from patient device  240  may be initially communicated from patient device  240  to EHR  204  where it is stored and later crawled by one of clinical risk factors component  222 , social determinants of health (SDOH) risk profile component  224 , clinical risk profile score component  226 , biometrics component  228 , symptomatology component  230 , and clinical assist component  232 . 
     The additional information may be derived from a symptom diary of the patient, biometric data from a device owned or utilized by the patient, biometric data from a prescribed kit, caregiver risk assessments (i.e., community home health caregiver), patient schedule, personal data of the patient, and the like. 
     CEWS engine  218  utilizes the data crawled by each of the components of CEWS engine  218  to periodically dynamically update the CEWS of the patient which can be utilized by an intelligent touch care engine (such as the intelligent touch care engine  306  of  FIG. 3 ), as described herein, to improve outcomes for the patient, increase overall touch points, reduce unnecessary in-person appointments, and reduce overall health care costs. In some embodiments, an update of the CEWS communicated by the CEWS engine  218  to the intelligent touch care engine may trigger a workflow provided by the intelligent touch care engine. 
     Referring now to  FIG. 3 , an exemplary framework of an intelligent touch care system  300  is shown, in accordance with an aspect of the present invention. It should be understood that this and other arrangements described herein are set forth only as examples. Other arrangements and elements (e.g., machines, interfaces, functions, orders, and groupings of functions, etc.) can be used in addition to or instead of those shown, and some elements may be omitted altogether. Further, many of the elements described herein are functional entities that may be implemented as discrete or distributed components or in conjunction with other components, and in any suitable combination and location. Various functions described herein as being performed by one or more entities may be carried out by hardware, firmware, and/or software. For instance, various functions may be carried out by a processor executing instructions stored in memory. The intelligent touch care system  300  may be implemented via any type of computing device, such as computing device  100  described above with reference to  FIG. 1 , for example. 
     The intelligent touch care system  300  generally operates to provide intelligent touch care for a patient. More particularly, the intelligent touch care system  300  utilizes contributing data elements in the CEWS to predict touchpoint discipline and to recommend frequency, modality, and upstream transitions of care and outside service referrals. As described above, the CEWS is a dynamic risk score used for risk stratification for a patient in a community care setting. In response to a touch point (e.g., a change in condition or medication, a scheduled or unscheduled appointment, or a patient question), the CEWS can be utilized along with data in an EHR of a patient, data from a patient device, or data from a patient portal to initiate a follow-up (e.g., personal health question or encounter). 
     As shown in  FIG. 3 , the intelligent touch care system  300  includes, among other components not shown, community early warning score (CEWS) engine  304 , intelligent touch care engine  306 , patient device  314 , and clinician device  316 . It should be understood that the intelligent touch care system  300  shown in  FIG. 3  is an example of one suitable computing system architecture. Each of the components shown in  FIG. 3  may be implemented via any type of computing device, such as computing device  100  described with reference to  FIG. 1 , for example. 
     The components may communicate with each other via a network  302 , which may include, without limitation, one or more local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet. It should be understood that any number of hinting engines and vocabulary databases may be employed within the intelligent touch care system  300  within the scope of the present disclosure. Each may comprise a single device or multiple devices cooperating in a distributed environment. For instance, the intelligent touch care engine  306  (or any of its components: patient workflow component  308 , clinician workflow component, and communication component  312 ) and/or the CEWS engine  304  may be provided via multiple devices arranged in a distributed environment that collectively provide the functionality described herein. In other embodiments, a single device may provide the functionality of multiple components of the intelligent touch care engine  306 . For example, a single device may provide the intelligent touch care engine  306  and/or the CEWS engine  304 . In some embodiments, some or all functionality provided by the intelligent touch care engine  306  (or any of its components) and/or the CEWS engine  304  may be provided by a patient device  314  or a clinician device  316 . Additionally, other components not shown may also be included within the network environment. 
     Generally, the intelligent touch care engine  306  provides intelligent touch care for a patient. The intelligent touch care engine  306  provides notification tools and scheduling functionality via a user interface of the patient device  314  to improve clinical workforce capacity, increase the number of patient touches, and encourage heightened patient engagement. Moreover, the ability to capture dynamic rising risk provides clinical insight into changing risk outside of the controlled environment of a clinical facility. Overall, outcomes for the patient can be improved, touch points can be increased, and unnecessary in-person appointments and overall health care costs can be reduced. 
     As described above, the intelligent touch care engine  306  includes several components including a patient workflow component  308 , a clinician workflow component  310 , and a communication component  312 . The patient workflow component  306  generally provides the notification tools and scheduling functionality described herein for the patient via a user interface of the patient device  314 . The patient workflow component  306  enables the patient to interact with a clinician, such as via telephone clinical assessments or video visits, or to enable the patient to ask questions of or express concerns to the clinician. In embodiments, the patient device  314  may include a personal assistant voice service (e.g., ALEXA). Additionally, the patient workflow component  306  may guide the patient through a series of tasks or self-assessments that may be part of the overall workflow initiated by a touch point and/or utilized by CEWS engine  304  to dynamically update the CEWS of the patient. 
     The clinician workflow component  310  generally provides notification tools and scheduling functionality for a clinician via a user interface of the clinician device  316 . The clinician workflow component  310  enables the clinician to interact with the patient, such as via telephone clinical assessments or video visits, or to enable the clinician to receive and/or answer concerns expressed by or questions asked by the patient. Additionally, the clinician workflow component  310  may guide the clinician through a series of tasks, assessments, and/or clinical decision support that may be part of the overall workflow initiated by a touch point. 
     The communication component  312  generally communicates and/or receives data utilized by the intelligent touch care engine  306 . For example, the communication component  312  may receive updates to the CEWS from the CEWS engine  304 . Additionally, the communication component may provide data to the CEWS engine  304  received from other components of the intelligent touch care engine  306  to dynamically update the CEWS. The communication component  312  may also receive data from the patient device  314  and/or the clinician device  316  that may be utilized to provide features of other components of the intelligent touch care engine  306 . 
     With reference to  FIGS. 4-6 , illustrative screen displays  400 ,  500 ,  600  of embodiments of the present invention are shown. It is understood that each of the illustrative screen displays are connected logically, such that they comprise a user interface designed for an intelligent touch care system, in accordance with embodiments of the present invention. The screen displays may appear in any order and with any number of screen displays, without regard to whether the screen display is described or depicted herein. The screen displays provide tools that enable more frequent, more effective, and more efficient care in a community care setting, in accordance with embodiments of the present invention. 
     In  FIG. 4 , an illustrative screen display of a CEWS interface  400  is shown, in accordance with an embodiment of the present invention. As illustrated, the CEWS interface  400  enables a patient to complete the patient profile that includes clinical risks and determinants of health. The information provided by the patient to the CEWS interface  400  is a portion of the data utilized by a CEWS engine (such as CEWS engine  218 ,  304  of  FIGS. 2 and 3 ) to determine a dynamically updated CEWS for the patient. 
     Turning to  FIGS. 5-6 , illustrative screen displays of an intelligent touch care interface  500 ,  600  are shown, in accordance with an embodiment of the present invention. In  FIG. 5 , recent touchpoints and visit tasks are provide to the patient. Each of the recent touchpoints and visit tasks may include various documents, assessments, and/or other information that may require additional action by the patient. As a result of the additional action, the CEWS may be updated by a CEWS engine (such as CEWS engine  218 ,  304  of  FIGS. 2 and 3 ) which may update a workflow provided by an intelligent touch care engine (such as the intelligent touch care engine  306  of  FIG. 3 ). In  FIG. 6 , the visit tasks has been expanded to show an updated CEWS, key risk indicators, and plan suggestions (which may include an ability to schedule a follow-up with a clinician as part of the workflow). 
     In  FIG. 7 , a flow diagram of a method illustrating a touch point corresponding to a change in a condition or an order that initiates a workflow is depicted, in accordance with an embodiment of the present invention. Method  700  may be performed by any computing device (such as computing device described with respect to  FIG. 1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, as shown at step  702 , a touch point corresponding to a change in a condition or order is received for a patient in a community care setting. At step  704 , the EHR receives new data corresponding to the touch point. Data may also be provided by patient, at step  706 , and stored in EHR. In response to the touch point being received, data is crawled in the EHR for the patient, at step  708 , to determine the appropriate workflow for the patient. Additionally, data provided by the patient may also be crawled. 
     At step  710 , based on the touch point and the CEWS, a follow-up is triggered for the patient. In response to the follow-up, the patient is notified at step  716  and/or step  720 . For example, the notification may be provided via a consumer device, as shown at step  716 . The user may open the notification, at step  718 , via touch or password on the consumer device. Additionally, or alternatively, the notification may be provided via a personal assistant voice service, as shown at step  720 . The notification may indicate, at step  722 , that a personal health question is available for the patient. 
     At step  724 , it is determined if the personal health question has been delivered to the patient. If the personal health question has not been delivered to the patient, as shown at step  726 , the patient may be the patient is prompted, at step  728 , to provide a time the patient is available to answer the personal health question. In response to the patient providing a time the patient is available to answer the personal health question, at step  732 , the time is captured and an encounter is scheduled, at step  736 , for the patient. Alternatively, as shown at step  730 , in response to the patient not providing a time the patient is available to answer the personal health question, a second follow-up is triggered, as shown at step  710 , for the patient. 
     If an indication that the patient is available to answer the personal health question is received, as shown at step  740 , the intelligent touch care questions are delivered to the patient. If the patient provides a response to the intelligent touch care questions, as shown at step  742 , the intelligent touch care workflow is advanced. Consequently, a second touch point is generated or a telephone follow-up is initiated, at step  744 . 
     Referring  FIG. 8 , an exemplary flow diagram  800  illustrates a touch point corresponding to an unscheduled appointment with a clinician that initiates a workflow, in accordance with an embodiment of the present invention. Method  800  may be performed by any computing device (such as computing device described with respect to  FIG. 1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, as shown at step  802 , a touch point is received for a patient in a community care setting. The touch point corresponding to a new order provided during an unscheduled appointment. In response to the touch point, data corresponding to the touch point is communicated, at step  804 , to an EHR for the patient. Data is crawled, at step  806 , in the EHR for the patient. The data may include a CEWS that is determined, at least in part, by patient provided data, as shown at step  808 . The patient provided data be communicated to the EHR before the EHR is crawled, or may be crawled in addition to data being crawled in the EHR. 
     Based on the touch point and the data in the EHR (including the CEWS), a follow-up comprising a notification is triggered, at step  816 , for the patient. In response to the follow-up, an encounter is scheduled or a new touch point is generated, as shown at steps  838  or  856 . 
     In some embodiments, the notification is provided to the patient via a consumer device, as shown at step  822 . The notification may be opened via touch or password on the consumer device, as shown at step  824 . If the patient has connectivity with a personal assistant voice service, as shown at step  818 , the notification may instead be delivered via the personal assistant voice service indicating, at step  820 , that a personal health question is available for the patient. 
     At step  826 , it is determined whether the personal health question has been communicated to the patient. Upon determining, in one embodiment as shown at step  828 , the personal health question has not been communicated to the patient, the patient is prompted, at step  830 , with an option to receive the personal health question at another time. Upon receiving an indication the patient has not provided another time, at step  832 , a second follow-up is triggered for the patient, at step  816 . Upon receiving an indication, in one embodiment as shown at step  834 , the patient has provided another time, the time is captured, at step  836 , to schedule the encounter, at  838 . 
     Upon determining, in one embodiment as shown at step  826 , the personal health question has been communicated to the patient, the patient is prompted, at step  842 , to indicate whether the patient has complied with the new order (e.g., has the patient picked up a new medication). Upon determining, in one embodiment as shown at step  844 , the patient has not complied with the new order, a telephone follow-up is initiated, at step  846 , for the patient. 
     In some embodiments, a second question (e.g., is the patient taking the new medication as prescribed) may be communicated to the patient, as shown at step  848 . If a second question is communicated and the patient does not respond, a telephone follow-up is initiated, at step  846 , for the patient. Upon determining, the patient has answered all questions and/or complied with the new order, the patient is prompted, at step  852 , to indicate if the patient has questions or concerns. If the patient has questions or concerns, as shown at step  854 , a telephone follow-up is initiated, at step  846 , for the patient. If the patient does not have questions or concerns, as shown at step  854 , the second touch point is generated at step  856 . 
     Referring now to  FIG. 9 , an exemplary flow diagram  900  illustrates a touch point corresponding to a scheduled appointment with a clinician that initiates a workflow, in accordance with an embodiment of the present invention. Method  900  may be performed by any computing device (such as computing device described with respect to  FIG. 1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, as shown at step  902 , a touch point is received for a patient in a community care setting. The touch point corresponds to a new order provided, as shown at step  904 , during a scheduled appointment. In response to the touch point, data corresponding to the touch point is communicated, at step  906 , to an EHR for the patient. At step  910 , data is crawled in the EHR for the patient. The data may include a CEWS that is determined, at least in part, by patient provided data, as shown at step  908 . The patient provided data may be communicated to the EHR before the EHR is crawled, or may be crawled in addition to data being crawled in the EHR. 
     Based on the touch point and the data in the EHR, a follow-up is triggered, at step  916 . The follow-up may comprise a notification for the patient. The follow-up may be communicated, at step  920 , to the patient via a consumer device or via a personal assistant voice service. The notification indicates, at step  922 , that a personal health question is available for the patient. The personal health question may be a series of questions  924 ,  926 ,  928  (e.g., did you pick up your medication, are you taking it as prescribed, do you have any other questions or concerns, etc.). 
     In embodiments, as shown at step  930 , upon receiving an indication the patient has questions or concerns, a follow-up may be necessary. Accordingly, a telephonic clinical assessment may be initiated at step  932 . During the telephonic clinical assessment, the patient may report, at step  934 , the questions or concerns. Upon receiving the questions or concerns (i.e., entry by clinician or patient, or by voice recognition), the intelligent touch care system (such as the intelligent touch care system  200  of  FIG. 2 ), identifies the questions or concerns. As a result, the intelligent touch care system may provide, at step  938 , a recommendation to a clinician performing the telephone clinical assessment the patient to address the questions or concerns. A second touch point is generated, at step  940 . The second touch point triggers a second follow-up comprising a second notification for the patient that is provided to the patient via the consumer device or via the personal assistant voice service at a particular time and indicates that a second personal health question is available for the patient. For example, the second personal health question may confirm that any questions or concerns of the patient have been resolved, as shown at step  942 . 
     In  FIG. 10 , an exemplary flow diagram  1000  illustrates a touch point corresponding to change in condition for an active community care patient that initiates a workflow, in accordance with an embodiment of the present invention. Method  1000  may be performed by any computing device (such as computing device described with respect to  FIG. 1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, as shown at step  1002 , an active community care patient (i.e., a patient that interacts with an intelligent touch care system has change in a condition, as shown at step  10002 . A touch point for the patient in community care is received, at step  1004 . The touch point indicates the patient has a question for a clinician. In response to the touch point, data corresponding to the touch point is communicated, at step  1006 , to an EHR for the patient. Data is crawled, at step  1010 , in the EHR for the patient. The data may include a CEWS that is determined, at least in part, by patient provided data, as shown at step  1008 . The patient provided data may be communicated to the EHR before the EHR is crawled, or may be crawled in addition to data being crawled in the EHR. 
     Based on the touch point and the data in the EHR, a follow-up is triggered, at step  1014 . The follow-up may comprise a notification for the patient or initiating a telephone clinical assessment, as shown at step  1016 . In one example, a notification is provided, at step  1020 , to the patient via a personal assistant voice service. The notification may indicate, as shown at step  1022 , that a personal health question is available for the patient. In another example, a telephonic follow-up may be initiated, at step  1018 , to the patient via the consumer device. 
     At step  1024 , it is determined whether the issue corresponding to the question has been resolved. Upon determining, the issue corresponding to the question has been resolved, a second touch point is generated, at step  1026 , for the patient. The second touch point may indicate the issue corresponding to the question has been resolved and be communicated to the EHR. 
     Alternatively, upon determining the issue corresponding to the question has not been resolved, as shown at step  1030 , a second follow-up is recommended. The second follow-up may comprise a video visit, an in-person visit, or a clinician visit. A second touch point is generated, at step  1032 , for the patient. The second touch point may schedule the second follow-up for the patient and initiate any corresponding workflow. 
     Turning now to  FIG. 11 , an exemplary flow diagram illustrates a touch point corresponding to a patient message of an active community care patient that initiates a workflow, in accordance with embodiments of the invention. Method  1100  may be performed by any computing device (such as computing device described with respect to  FIG. 1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, at step  1102 , a touch point for a patient in a community care is received. The touch point may indicate, as shown at step  1104 , the patient has a change in a condition to report to a clinician. In response to the touch point, data corresponding to the touch point is communicated, at  1106 , to an EHR. At step  1110 , data is crawled in the EHR for the patient. The data may include a CEWS that is determined, at least in part, by patient provided data, as shown at step  1108 . The patient provided data may be communicated to the EHR before the EHR is crawled, or may be crawled in addition to data being crawled in the EHR. 
     Based on the touch point and the data in the EHR, a follow-up is initiated, at step  1114 , with the clinician. The follow-up may comprise initiating, as shown at step  1116 , a telephone clinical assessment. Upon completing the telephone clinical assessment, as shown at step  1118 , a second follow-up is determined to be needed. The second follow-up may comprise a video visit. At step  1120 , the video visit between the patient and the clinician is initiated. During the video visit, as shown at step  1122 , a recommendation may be provided by the intelligent touch care system to the clinician performing the video visit to address the change in the condition of the patient. A third follow-up may be scheduled, at step  1124 . The third follow-up may include a second video visit. 
     At step  1128 , the video visit is initiated. Upon the clinician performing the second video visit, it is determined, at step  1130 , whether the change in the condition of the patient has been resolved. Upon determining the change in the condition of the patient has been resolved, as shown at step  1132 , a second touch point is generated. The second touch point indicates the change in the condition of the patient has been resolved. 
     Upon determining the change in the condition of the patient has not been resolved, as shown at step  1138 , a fourth follow-up is triggered, at step  1138 . The fourth follow-up may comprise an in-person visit. The fourth follow-up is scheduled, at step  1142 . Upon completing the fourth follow-up or receiving an indication a new order has been provided for the patient, as shown at step  1144 , a fifth follow-up may be triggered, at step  1146 . The fifth follow-up may be an electronic assessment to be completed by the patient. After receiving an indication the electronic assessment has been completed, at step  1148 , it is determined whether an issue corresponding to the change in the condition of the patient has been resolved, at step  1150 . Upon determining the issue corresponding to the change in the condition of the patient has been resolved, at step  1152 , a second touch point indicating the conditions of the patient has been resolved is generated. Upon determining the issue corresponding to the change in the condition of the patient has not been resolved, at step  1154 , a fifth follow-up is scheduled. The fifth follow-up may comprise a video visit, an in-person visit, or a clinician visit. Accordingly, at step  1156 , a second touch point is generated for the patient that schedules the fifth follow-up and initiates any corresponding workflow. 
     In  FIG. 12 , a flow diagram of a method illustrating dynamically updating a CEWS is depicted, in accordance with embodiments of the present invention. Method  1200  may be performed by any computing device (such as computing device described with respect to FIG.  1 ) with access to a CEWS system and/or an intelligent touch care system (such as the systems described with respect to  FIGS. 2 and 3 ) or by one or more components of the CEWS system and/or intelligent touch care system. 
     Initially, as shown at step  1202 , a request to dynamically update a CEWS for a patient is received at a CEWS engine (e.g., CEWS engine of  FIG. 2 ) comprising a plurality of data crawlers (e.g., initial index component  220 , clinical risk factors component  222 , SDOH risk profile component  224 , clinical risk profile score component  226 , biometrics component  228 , symptomatology component  230 , or clinical assist component  232  of  FIG. 2 .). The request may be made periodically, based on a touchpoint, based on an update provided by or a request made by a patient device (e.g., patient device  240  of  FIG. 2 or 314  of  FIG. 3 ), clinician device (e.g.,  316  of  FIG. 3 ), ITC engine  306  (e.g., ITC engine  306  of  FIG. 3 ), or another clinical system. 
     At step  1204 , a first set of the plurality of data crawlers is initiated by CEWS engine to collect data in an EHR of the patient. Each of the first set of the plurality of data crawlers is responsible for collecting a distinct type of data within the EHR. A second set of the plurality of data crawlers is initiated, at step  1206 , by CEWS engine to collect data originating from a patient device corresponding to the patient. In embodiments, the plurality of data crawlers may comprise an initial index component, a clinical risk factors component, a social determinants of health (SDOH) risk profile component, a clinical risk profile score component, a biometrics component, symptomatology component, and a clinical assist component. The initial index component may collect facility biometric data and assessment data from the EHR or the patient device to calculate the National Early Warning Score 2 for the patient, the assessment data including respiratory rate, an estimate of arterial oxygen saturation, hypercapnia, supplemental oxygen, systolic blood pressure, heart rate, level of consciousness, or temperature. The clinical risk factors component may collect medical history and medication profile from the EHR or the patient device to determine clinical risk factors of the patient, the clinical risk factors including a body mass index of the patient and an indication if the patient is: an opioid risk, an amputee, utilizes a medicinal sleep aid, paraplegic or quadriplegic, has a recent acute admission, or polychronic or polypharmacy. The SDOH risk profile component may collect assessment data and risk assessments from the EHR or the patient device to determine a SDOH risk profile of the patient, the SDOH risk profile comprising various factors corresponding to the patient including current housing situation of the patient, transportation available to the patient, utilities available to the patient, a financial situation of the patient, a health literacy of the patient, modes of communication available to the patient, social engagement of the patient, stress of the patient, or food insecurity of the patient. The clinical risk profile score component may collect risk assessments from the EHR or the patient device to determine a clinical risk profile score, the clinical risk profile score comprising risks corresponding to pain, fall, depression, anxiety, dyspnea, Activities of Daily Living/Instrumental Activities of Daily Living, frail or elderly, medication adherence, engagement, confusion, suicide risk, or post-traumatic stress disorder. The biometrics component may collect facility biometric data and assessment data from the EHR or the patient device to determine biometrics for the patient, the biometrics comprising temperature, heart rate, systolic blood pressure, diastolic blood pressure, mean arterial blood pressure, weight, glucose data, supplemental oxygen, an estimate of arterial oxygen saturation, respiratory rate, activity data, or sleep data. The symptomatology component may collect assessments from the EHR or the patient device to determine symptomology for the patient, the symptomatology comprising assessed symptoms. The clinical assist component may collect facility biometric data from the EHR or the patient device to determine clinical assist mechanisms associated with the patient. The clinical assist mechanisms comprise an indication the patient is on: oxygen, infusion, a particular nutrition plan, dialysis, chemotherapy, radiation, or assistive devices. Additionally or alternatively, the plurality of crawlers may collect data derived from a symptom diary of the patient, biometric data from a device owned or utilized by the patient, biometric data from a prescribed kit, caregiver risk assessments, a patient schedule, or personal data of the patient 
     At step  1208 , utilizing the data collected by the plurality of data crawlers, the CEWS is dynamically updated at the CEWS engine. Based on the updated CEWS, a workflow for the patient may be initiated, at step  1210 , at the patient device or a clinician device (e.g., such as any of the workflows described herein with respect to the ITC engine). 
     Many different arrangements of the various components depicted, as well as components not shown, are possible without departing from the spirit and scope of the present invention. Embodiments of the present invention have been described with the intent to be illustrative rather than restrictive. Alternative embodiments will become apparent to those skilled in the art that do not depart from its scope. A skilled artisan may develop alternative means of implementing the aforementioned improvements without departing from the scope of the present invention. 
     It will be understood that certain features and subcombinations are of utility and may be employed without reference to other features and subcombinations and are contemplated within the scope of the claims. Not all steps listed in the various figures need be carried out in the specific order described. Accordingly, the scope of the invention is intended to be limited only by the following claims.