Patent Application Titled “Facilitating Integrated Behavioral Support Through Personalized Adaptive Data Collection” Published Online (USPTO 20220284489): Patent Application

2022 SEP 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Fodor, Eniko (Fremont, CA, US); Prakash, Adityo (Fremont, CA, US), filed on September 20, 2021, was made available online on September 8, 2022.

No assignee for this patent application has been made.

Reporters obtained the following quote from the background information supplied by the inventors: “

“Field of Art

“The present invention relates generally to interactive support and modification of user behavior patterns, and more particularly to interactive healthcare and a novel variation of a behavioral support agent that incentivizes individuals to interact with and actively participate in utilizing online resources to enhance their overall wellness, it adaptively modifies the type and frequency of data collection based upon users’ changing personal circumstances.

“Description of Related Art

“As the Internet evolves, access to information, including health-related information, continues to increase exponentially. Individuals currently have instant online access, from a wide variety of sources, to personal and aggregate information relating to patient histories, test results, physical and mental fitness, nutrition, health supplements, and a vast array of health research, as well as methods and devices for measuring, diagnosing and treating various conditions or simply enhancing overall wellness.

“Moreover, the advent of “smart” mobile devices and related technologies has provided individuals with access to such information on a continuous basis, as well as the ability to monitor health-related data (heart rate, blood pressure, etc.) and receive feedback covering virtually any period of time, including events such as a workout or a night’s sleep.

“However, this vast of array of information and device technology is far from integrated, and can be overwhelming to individuals. How does a layperson even identify relevant symptoms, much less sift through the vast array of available information “on demand” to obtain useful results? And how personalized are those results given the limited amount of data provided by a few search terms? Does a search engine know what medications patients are taking, or whether they recently stopped taking a particular medication, or took another substance or engaged in an activity that, in combination, might explain certain symptoms?

“There is clearly a need for a more holistic approach, particularly in light of the state of the technology currently available. In essence, there is a need for a “behavioral support agent” (BSA) that can facilitate the collection of relevant data on a continual basis, modify the type and frequency of such data collection based on changing circumstances, integrate such data with pertinent aggregate information, and guide individuals toward behaviors that will enhance their overall wellness.

“Various attempts to address one or more aspects of this problem have been implemented or proposed. For example, websites such as WebMD provide users with the ability to search an extensive database of health-related information. In addition to providing a searchable database, other features include a “symptom checker” (which provides potential diagnoses based upon users’ answers to questions relating to symptoms) and a “medication tracker” (which enables users to maintain lists of their current medications, and provides information relating to drug interactions, side effects, and FDA warnings). As noted above, however, such “on demand” systems provide limited personalization, as the information they provide is based on keyword searches rather than personal health-related data adaptively collected on a continual basis over time.

“Other websites and smartphone apps are targeted at specific aspects of healthcare, such as maintaining personal medical records or medication profiles (e.g., HealthVault or MphRx) or monitoring activity and fitness levels, often in connection with user monitoring devices (e.g., FitBit). While some of these approaches may be more engaging than searchable websites, they do not take a holistic approach. Beyond specific activities such as walking, running or taking a pill, they lack comprehensive day-to-day and historical monitoring of users’ symptoms, schedules and overall health conditions and the ability to adaptively collect, utilize and respond to such data to support users and enable them to improve their health outcomes.

“Other systems have adopted a more holistic approach to this problem. For example, U.S. Pat. No. 8,170,609 discloses a personal virtual assistant system that includes a remote station carried by users which has one or more physiological sensors, and a rules engine that provides advice to users based in part upon the sensor data. Other systems have attempted to reduce the need for human intervention in routine aspects of healthcare by programming virtual assistants to aid users in various tasks. For instance, the “Alme” virtual assistant platform from NextlT provides automated aid with navigation of choices for users. It has been recently deployed by Aetna to help members navigate their website better. Ann, Alme’s virtual assistant deployed by Aetna, is able to help the insured register on the website, get cost of service estimates, locate in-network providers and compare costs by facilities and physicians. Implementing Ann has enabled Aetna to cut costs by reducing the burden on their call center.

“While some of these proposed “solutions” take a more patient-centric and preventive approach to wellness, some key obstacles remain unaddressed, even by existing virtual assistant systems. For example, healthcare is an expensive proposition. Regardless of the quality of the information obtained online, individuals may still find it necessary or desirable from time to time to visit clinics, hospitals, doctors and other specialists, and purchase medications, supplements, health monitoring devices and other health-related goods and services. The cost of such health-related goods and services can be quite significant, despite preventive measures. Additional cost-reduction efforts are still needed to address this problem effectively.

“Moreover, as is the case with healthcare generally, the quality of information generated by any of these systems depends greatly upon the degree to which individuals participate in the process and interact with the system. For example, individuals will derive greater benefits if they provide timely and accurate information, follow system suggestions and provide frequent feedback regarding their activities, likes, dislikes and so forth. While users may initially provide profile information and frequently interact with a new system, human behavior is such that, in most cases, their level of interaction quickly tapers off.

“While a BSA system could prompt users for relevant information on a timely basis and provide entertaining content in an effort to keep users engaged, additional incentives are needed to maintain sufficient patient participation in the process. Though seemingly unrelated, these problems of high healthcare costs and inadequate patient participation provide an opportunity for a novel approach that “kills two birds with one stone.”

“A key deficiency of existing systems is their lack of connection to the “healthcare transaction flow” through which users purchase health-related goods and services. If a BSA system could insert itself into this transaction flow, and provide users with economic incentives (credit, discounts, etc.) based upon the nature and extent of their interaction with the system, such additional economic incentives would complete a feedback loop that reduces healthcare costs as a means of encouraging active user participation, which in turn enhances overall wellness.

“Not surprisingly, some financial services companies have delved into the healthcare sector. For example, Citigroup’s “Money² for Health” project, is a payment processing and reconciliation system (online automated “spreadsheet” with integrated payment transaction capability) that allows consumers to maintain payment history and make payments from one portal to all healthcare providers and insurance companies registered on the site. But, this project neither includes nor suggests any connection to a BSA system, much less any reliance on patients’ interaction with such a system as a factor in assessing benefits provided to patients, such as credit and discounts on the purchase of health-related goods and services.

“While financial services companies such as Klarna (a European mobile payment provider based in Sweden), have experimented with “micro credit” and various other credit-assessment techniques (see, e.g., published patent applications WO/2013131971 and US/2011030738), no such company has even suggested targeting credit-assessment techniques at purchases of health-related goods and services, much less basing credit assessments on users’ interaction with a BSA system.

“Moreover, none of these existing systems employs a personalized approach to data collection, e.g., by adaptively modifying the type and frequency of data collection based upon users’ changing personal circumstances.

“Thus, there remains a need for a BSA system that addresses the problems of high healthcare costs and inadequate patient participation by enabling users to purchase health-related goods and services via their user accounts, adaptively modifying the type and frequency of data collection in a personalized manner, and automatically and dynamically providing economic incentives to users based upon the nature and extent of their interaction with the system.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “To address the above-referenced problems, the present invention includes various embodiments of a BSA system that facilitates the collection of user related data, including their relevant activities, on a continual and adaptive basis, integrates such data with other pertinent personal and aggregate information, and guides users toward behaviors that help achieve system level and user specific goals such as enhancement of the user’s overall wellness. The BSA system applies to any sphere of user activity, such as entertainment, travel or overall lifestyle, commercial transactions etc., but is described herein with regard to its application in healthcare and wellness support. The BSA system enables users to purchase health-related goods and services (directly using the system, as well as indirectly via their user accounts), while providing credit, discounts and other economic benefits in connection with such purchases that are determined dynamically based upon the nature and extent of users’ interaction with the system.

“In one embodiment, the BSA system continually monitors and analyzes users’ behavioral interactions with the system. This health-related behavior includes various factors relating to the nature and frequency of information the user provides to and receives from the system (e.g., queries and responses, symptoms and other shared health status information, content browsed, games played, interactions with other users on social networks, health-related purchases, and shared third-party lab results, fitness data and other external information, among other factors).

“In another embodiment, the type and frequency of data collection is adaptively modified based upon users’ changing personal circumstances. For example, based upon symptoms or other diagnostic data collected over time, the system may not only detect a problem requiring certain follow-up actions (e.g., recommending and scheduling a visit to a doctor or specialist), but may also increase the frequency of the data being collected (e.g., hourly instead of daily monitoring of blood pressure) as well as the type of data collected (e.g., adding a new heart-rate test perhaps via the same wearable device that tests blood pressure). As a result, the doctor or specialist may have more relevant data to analyze or may cancel the visit should the symptoms subside based upon the additional data collected.

“Triggers for modifying the type and frequency of data collection include (among others) indicators of a new significant or potentially significant medical condition (e.g., a persistent cough), detected changes to a user’s “normal” status over time, and even a current outbreak in a user’s local geographic area (which might trigger actions to identify other users who are similarly affected, or potentially at risk). By increasing the frequency and adjusting the type of data collection when warranted by various triggers, this technique can be analogized to a form of “signal compression” that only increases sampling frequency when it detects movement or changes.

“This adaptive approach to data collection can also be analogized to a “universal doctor” who knows all patients intimately and provides personalized services to patients who benefit from the aggregate knowledge accumulated from other patients. By continuously collecting data from users and refining the type and frequency of data collection in a personalized manner, the present invention enables results beyond those achievable by any individual doctor or other health professional. It should be noted that adaptive data collection methodologies may also include follow-up questions or other data collection techniques, as well as manual and automated data sensors and monitors that target not only individual users but also dynamically identified groups of users. Various other personalized adaptive data collection scenarios will be discussed in greater detail below.

“In yet another embodiment, users accumulate and lose points, based upon the nature and frequency of virtually all of these direct and indirect interactions with the system. Various algorithms are employed to convert this raw data into particular attributes of credit levels, discounts for specific health-related products and services, and other benefits.

“A Benefits Engine assesses the appropriate amount of credit (as well as discounts and other promotions) to offer users based upon this multi-dimensional data. Over time, the Benefits Engine may raise or lower a user’s credit level (credit limit, interest rate, appropriateness of particular purchases, etc.) and reward the user with particular discounts, based upon dynamic changes in the user’s behavior, as well as standard financial profile and transactional behavior data (including timeliness of payments to the BSA system provider).

“The BSA system facilitates this dynamic feedback process by continually monitoring user interaction and medical and financial behavior, which results in dynamic adjustments to their credit levels and offers of discounts and other promotions, which in turn incentivizes users to continue participating in the process (thereby modifying their system interactions and behavior, and thus perpetuating this feedback loop). As a result, users are incentivized to actively participate in the process and thereby enhance their wellness while reducing healthcare costs.

“For example, if a user frequently browses or searches for information relating to a particular nutritional supplement, and provides periodic information relating to their usage of that supplement over time, this behavior suggests that the user places a relatively high value on that supplement, perhaps justifying a discount on that supplement (or on related products and services). Moreover, the user may in fact value that supplement over other non-healthcare-related items (e.g., a cable bill), perhaps justifying a higher credit limit and/or lower interest rate in connection with purchases of health-related goods and services via their user account.

“The credit assessment process of the present invention involves consideration not only of standard financial profile and transactional behavior data, but also of specific health-related behavioral data, which is particularly relevant given that user credit is targeted at financing purchases of health-related goods and services. In one embodiment, aggregate behavior of others (including other BSA system users, or a correlated subset of such users) is also considered in the credit-assessment process, as well as in the determination of which discounts, or other benefits (including targeted advertisements and product promotions) are offered to particular users.

“Rather than address merely a single facet of a user’s health (fitness, prescription medications, test results, discrete illness or injury, etc.), the BSA system of the present invention provides a holistic approach that engages the user in interaction on a frequent basis over time. In one embodiment, the system provides a graphical, voice-enabled and touch and text-based user interface on mobile as well as desktop and other online platforms, aided by a natural language engine and back-end health expert system that guides users through a myriad of health concerns and queries. The system provides personalized suggestions relating to each user’s personal health condition and wellness goals, as well as reminders of medical appointments and medication schedules and real-time notifications of location-specific general health concerns (such as the spread of an infectious disease in a user’s geographic area).

“The system processes user voice and text input and queries and displays responses utilizing various media (voice, text, graphics, animation, video, etc.) that prompt users for additional information on an “as-needed” basis, rather than requiring users to fill out long forms and provide data that is not relevant at the time. Users provide proxies for external resources, such as pharmacies, labs, medical centers and retail providers of health-related goods and services. In one embodiment, the system notifies emergency contacts provided by users in the event of an emergency explicitly identified by a user or inferred from user interaction with the system (e.g., data from a wearable heart monitor).

“User profiles are maintained and updated dynamically, and are available to users on a secure basis at all times. A frequent “active check-in” process enables the system to monitor user health by listening to, recording and categorizing any health-related information users provide. Such information includes daily replies to check-in prompts (e.g., “How did you sleep last night?” or “How is the pain in your neck?”), volunteered symptoms (e.g., “My arm hurts.” with intelligent dialogue follow-up such as “What part of your arm?” to better identify the problematic location or “Are you experiencing numbness and/or tingling in your arm?” to identify nerve or vascular damage) and other health status factors relevant to their physical and mental state, as well as information obtained from wearable and other user monitors and other external sources (via user proxies where necessary-e.g., lab results following a blood test), including, for example, data mining of queries and other user inputs into Google, Facebook and various other websites or applications.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1. A method for performing adaptive data collection to enhance the quality of data and efficiency of collection and utilization of data related to one or more users with accounts on a behavioral support agent system, the method comprising the following steps: (a) collecting information from one or more users of the system on an ongoing basis during a first state, wherein the information includes a first type of data collected at a first frequency; (b) identifying a first set of triggers that warrant transitioning the system to a second state with respect to a subset of users, wherein the first set of triggers is discerned in whole or in part from the information collected from the users in step (a); © adjusting, during the second state, the type of information collected from the subset of users in step (b) by collecting a second type of data from the users, wherein the second type of data differs from the first type of data and is targeted at a potential condition relating to the first set of triggers; and (d) adjusting, during the second state, the frequency with which the second type of data is collected from the subset ofusers in step (b) to an adjusted frequency, wherein the adjusted frequency differs from the first frequency.

“2. The method of claim 1, wherein the first set of triggers includes symptoms evidencing a possible medical condition.

“3. The method of claim 1, wherein the information is obtained both from users of the system and from external data sources.

“4. The method of claim 1, wherein the first adjusted frequency with which information is collected from the first set of users is greater than the first baseline frequency, and is decreased in a third state to a second adjusted frequency below the first adjusted frequency but still above the first baseline frequency, and then returned to the first baseline frequency.

“5. The method of claim 1, wherein the first set of users includes a plurality of users from whom information is collected during the second state.”

For more information, see this patent application: Fodor, Eniko; Prakash, Adityo. Facilitating Integrated Behavioral Support Through Personalized Adaptive Data Collection. Filed September 20, 2021 and posted September 8, 2022. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220220284489%22.PGNR.&OS=DN/20220284489&RS=DN/20220284489

(Our reports deliver fact-based news of research and discoveries from around the world.)