USER INTERFACE AND INCENTIVES

CROSS REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Patent Application Serial No. 62/093,207, filed on December 17, 2014, entitled Clinical Population Analytics, and U.S. Patent Application Serial No. 14/180,694, filed on February 14, 2014, entitled System, Method and Computer Program Product for Providing a Healthcare User Interface and Incentives, the contents of which are incorporated herein by reference in their entirety. FIELD OF TECHNOLOGY

The present disclosure is in the field of information technology and more particularly in the field of healthcare data analytics.

BACKGROUND

Healthcare providers, healthcare payers and other healthcare industry stakeholders have access to an increasing amount of information about individual healthcare consumers and various populations and demographic groups. Electronic medical records are commonly used by healthcare providers to store patient health information. Various other forms of patient health information may be stored in various databases and formats by healthcare payers and healthcare providers. Electronic health records and electronic health information exchange are commonly used to securely share electronically stored patient health information among healthcare providers and healthcare payers and consumers. Secure, timely sharing of patient information through electronic health information exchanges can better inform decision making at the points of care and allows providers to improve diagnosis and to avoid readmissions, medication errors and duplicate testing, for example. Different healthcare industry stakeholders may operate and maintain their own secure health information storage systems and machines or may communicate with other healthcare industry stakeholders via health information exchanges to access patient health information and population health information. A network of two or more health industry stakeholders, such as healthcare providers, healthcare payers and other health data sources in secure communication with each other via a health information exchange is referred to herein as a health information exchange network.

Various standards, policies and technologies for implementing health information exchange are currently available or under development to enable the secure exchange of health information over the Internet. Data that has been standardized for electronic health information exchange may be seamlessly integrated into a recipient's electronic medical records, for example. Even though a vast amount of health information is stored electronically, analyzing the information to improve health care delivery generally involves extensive efforts to identify appropriate data sources and to secure access to the data sources.

Additionally, rising healthcare costs lead to a desire by payers that their members (such as employees and their families) become more engaged and participate more actively in managing their health. For example, if a pool of members includes a substantial fraction who are obese, there would be substantial costs associated with heart problems that could likely result. If these members, or even some of them, could be convinced to make healthy lifestyle changes, such as losing weight and increasing exercise, they would become healthier. This would have the effect that members develop fewer and less severe heart problems. Providers would be happier with a healthier member population. Payers would benefit with consequential reduction in cost.

A first known solution is for health insurers to educate members, encourage them to adopt healthy lifestyles, and remind them about activities that would assist in member healthcare. These can include a plethora of possibilities, such as posters, mailings, nurse response lines, reminder calls about appointments, and otherwise. While these activities can promote the general goal of raising member awareness of healthcare needs, they can be subject to some drawbacks. Members receiving the information may find it too complex, overly-diverse, contradictory or redundant. It sometimes occurs that members remain unaware of important healthcare issues or unresponsive due to members ignoring excessive efforts at member outreach by payers or due to the outreach being delivered through channels of which the member is unaware. It sometimes occurs that these techniques are not personalized to the member's particular healthcare needs. These techniques might also tend to frustrate members, have high costs, and produce relatively minimal outcomes.

A second known solution is for members to seek out healthcare information, such as by using the Internet or one (or more) of the many healthcare applications (sometimes called "apps") available for smartphones, tablets, or other computing devices. Members can sometimes obtain a relatively large amount of information from search engines, health and wellness portals, health and wellness applications, and from email and other communication with payers. While these activities also can also promote the general goal of raising member awareness of healthcare needs, they are also subject to some drawbacks. Similar to the first known solution, it sometimes occurs that members receive information that is too complex, overly-diverse, contradictory or redundant, and it sometimes occurs that members remain unaware of or unresponsive to important healthcare issues. Moreover, these techniques sometimes lead to members obtaining or believing healthcare information that is erroneous, not up to date, or misleading.

A third known solution is for members to obtain healthcare information directly from providers during visits. For example, a member might get advice from their doctor about keeping their cholesterol level down, while at a regular checkup. While this can also promote the general goal of raising member awareness of healthcare solutions, it is also subject to some drawbacks. It sometimes occurs that the doctor has many other patients scheduled for that day, and so cannot take the time for a proper review. The doctor may he focused on the specific issues the member arrived for, and so cannot take the time to review the member's longitudinal history. In some cases the member's questions would be better addressed by a different medical professional, such as a nutritionist. In this latter case, the member is burdened with having to schedule yet another appointment, at a different time and possibly a different facility, with the effect of frustrating the member and reducing the likelihood of the member becoming engaged in their own healthcare.

Each of the examples described above, as well as other possible considerations, can cause difficulty in healthcare aspects including costs, quality, outcomes, and engaging members in actively managing their own healthcare.

Data in Electronic Medical Record (EMR) systems is generally centered around patient records and generally does not include information based on overall measurement of a patient population. Due to the diverse nature and format of the data in most EMR systems, healthcare providers and payers must often spend excessive time exploring records in various locations and formats within an EMR system in order to gain an understanding a patient's history, conditions, medications, and overall health healthcare. Thus, clinicians, health insurance providers and other healthcare stake holders who access EMR systems generally do not have access to sufficient analytics and reporting of clinical data to efficiently identify opportunities for quality, cost and outcome improvement for particular patient populations.

Previous health data reporting techniques include systems and methods for presenting various specific health data from data sources such as healthcare insurance claims. Some previous techniques generate data presentations based on measure categories such as risk measures, quality measures, cost measures, utilization measures, and meaningful use measures, for example. These previous healthcare data reporting techniques generally do not incorporate measures and dimensions from diverse categories into a single solution and are not configured to automatically interpret patient health information and population health information of various types and in a variety of formats. The previous reporting systems and methods also lack dynamic, interactive longitudinal view of the patient to more intuitively visualize the health of the patient. Thus, in order to gain a holistic view of individual patients across the various measure categories, healthcare stakeholders such as healthcare payers healthcare providers must often access multiple systems and methods. The lack of efficient access to appropriate clinical population information by healthcare stakeholders often results in inefficient use of healthcare resources and less effective patient health outcomes.

SUMMARY

The present application provides, systems, methods, and devices configured to generate and display a dashboard (for example, in the form of a user interface) that incorporates multiple categories (such as measures). The dashboard incorporates dynamic drill-down visualization using various dimensions according to the selected category and/or parameter of the category. The dashboard is further configured to allow for contextual drill-down to summary patient reports or summary provider reports using dynamic formatting and content based on the selected category and/or parameter of the category. The dashboard may also use attribution analytics to associate conditions to encounters, patients to facilities, and current medications to patients.

Clinical data, prescription medication records, claims data, socio-demographic data and care management data may be integrated into, processed, and used by the dashboard to provide both retrospective and prospective views of healthcare consumers and healthcare consumer populations. This enables healthcare providers to identify at-risk patients earlier, preserve patient health, reduce costs and prevent complications, for example.

This application also provides apparatuses and techniques that can enable members to actively engage in managing their own healthcare, and to, by the member's behavior, improve their health and reduce healthcare costs to the payer and the member. This application also provides apparatuses and techniques that can enable the member to receive a simplified and unified interface to their healthcare system, which can be personalized to the history and status of the member, and that can provide a variety of possible action alerts and related rewards to the member, to encourage member behavior that is effective in reducing healthcare costs.

In one embodiment, the apparatuses and techniques can provide guidance and describe progress to the member with an application (or "app") with a convenient user interface (UI) in the form of a pathway, in which the member can be able to set intermediate goals, actions and alerts can be presented to the member, and when those actions by the member are verified, can provide the member with a selection of rewards. These intermediate goals, actions and alerts can provide the member with a unified interface, collecting for the member personalized, timely information with respect to what to do, and when to do it, to maintain their best health and quality of life.

In one embodiment, the apparatuses and techniques can be responsive to information about the member, can apply a set of rules to that information, and can generate alerts in response to application of those rules. The information about the member can be collected from disparate sources, including reports of insurance and flexible spending account (FSA) claims, reports from medical personnel (such as with respect to visits and procedures, chart notes, observations and diagnoses, and otherwise), reports from laboratory technicians (such as with respect to laboratory visits and procedures, chart notes, laboratory observations and diagnoses, and otherwise), reports from physical therapists and other professionals (such as with respect to visits and procedures, and measurements), reports from pharmacists (such as with respect to filled prescriptions), reports from biometric devices (such as measurements of blood pressure, cholesterol, glucose level, weight, and otherwise), self -reports from members (such as with respect to diet and exercise), and reports derived from the user interface (such as which intermediate goals are set by the user). The rules applied to that information can include medical rules (such as derived from evidence-based medicine), business rules (such as programs or promotions offered by payers to encourage selected behaviors), and otherwise. The alerts generated in response to those rules can include messages displayed by the UI (such as when the member logs in to the application).

In one embodiment, the apparatuses and techniques can provide one or more alerts that prompt healthy actions by the member, which upon verification, mean the apparatuses and techniques can make available one or more rewards to the member. Rewards can include positive recognition of the member, "points" that can be exchanged by the member for other items of value, money, rebates of co-pays or other fees, lowered insurance rates, free or discounted consumer goods, and other things of value.

After reading this application, those skilled in the art would recognize that techniques shown in this application are applicable to more than just the specific embodiments shown herein. For a first example, the concept of healthcare activities is intended to be broad, and can include medical and dental activity, nutrition and exercise, mental health, physical therapy and other therapies, and promoting checkups (such as prenatal and well baby care). For a second example, healthcare activities could be replaced or augmented with any other activity the payer desires to encourage or discourage, including workplace activities such as accident/safety awareness, short and long-term disability prevention and management, or otherwise.

While multiple embodiments are disclosed, including variations thereof, still other embodiments of the present application will become apparent to those skilled in the art from the following detailed description, which shows and describes illustrative embodiments of the application. The application is capable of modifications in various aspects, all without departing from its scope or spirit. The drawings and detailed description are illustrative in nature and not restrictive.

BRIEF DESCRIPTION OF THE FIGURES

Embodiments of devices, systems, and methods are illustrated in the figures of the accompanying drawings which are meant to be exemplary and not limiting, in which like references are intended to refer to like or corresponding parts, and in which:

FIG. 1 illustrates a system overview according to embodiments of the present disclosure.

FIG. 2 illustrates an overview of a health information processing system according to embodiments of the present disclosure.

FIG. 3 illustrates an example information flow according to embodiments of the present disclosure.

FIG. 4 illustrates an example of a prior art information flow.

FIG. 5 illustrates an exemplary visualization of integration of data according to embodiments of the present disclosure.

FIG. 6 illustrates a functional block diagram of an overview of a data model according to embodiments of the present disclosure.

FIG. 7 illustrates a method of processing and integrating data according to embodiments of the present disclosure.

FIG. 8 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 9 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 10 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 1 1 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 12 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 13 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 14 illustrates an exemplary user interface according to embodiments of the present disclosure.

FIG. 15 illustrates a system overview for administering an incentive program according to embodiments of the present disclosure.

FIG. 16A illustrates a flow diagram of a method of member engagement with the system of FIG. 15 according to embodiments of the present disclosure.

FIG. 16B illustrates a flow diagram of a method for granting incentives under a rewards program according to embodiments of the present disclosure.

FIGS. 17A and 17B illustrate a user interface for use by a member according to embodiments of the present disclosure.

FIGS. 18A-18B illustrate a user interface for use by a member according to embodiments of the present disclosure.

FIGS. 19A-19B illustrate a user interface for use by a member according to embodiments of the present disclosure. DETAILED DESCRIPTION

The following definitions are intended to be exemplary and illustrative, not necessarily limiting:

The terms "member", "consumer", "employee", "insured", "patient", and variants thereof, generally refer to any person or family unit with respect to whom receives healthcare services from providers. The term member can include any person in the covered family unit or other group.

The terms "payer", "employer", "insurer", and variants thereof, generally refer to any entity, such as an employer of the member, or an insurance or reinsurance company, or government entity responsible for paying a substantial fraction of healthcare costs (excluding "co-pay" amounts generally assessed against the member), or otherwise subject to economic harm from member health problems (such as an organization that would suffer from the member's absence).

The terms "insurance", "insurance benefits", "health insurance", and variants thereof, generally refer to any benefit, such as payment for provider services (excluding "co-pay" amounts generally assessed against the member), including without limitation a negotiated lower rate for provider services, payment for most of the cost of provider services, provider services offered at no cost to the member to encourage healthy behavior, and otherwise.

The terms "provider", "medical personnel", "doctor", "hospital", "laboratory technician", "nurse", "physical therapist", "facility", and variants thereof, generally refer to any provider of one or more healthcare services.

The terms "healthcare", "healthcare services", "medical procedure", "office visit", "therapy", and variants thereof, generally refer to provision of healthcare services. The concept and scope of healthcare activities is intended to be broad, and can include medical and dental activity, nutrition advice and exercise coaching, mental health services and counseling, physical therapy, chiropractic, acupuncture, aromatherapy, other non-Western therapies, and other therapies, and includes promoting periodic and aperiodic checkups (such as prenatal and well baby care), healthy diet, regular exercise, and age-appropriate and gender-appropriate testing.

The terms "points", "miles", "credits", and variants thereof, generally refer to any credit to, or debit from, a member, that can be converted into any thing of value. For example, points that can be exchanged, once a designated amount of them are reached, for rewards of any kind (as described herein), would be included.

The terms "incentive", "reward", "award", "rebate", and variants thereof; generally refer to any thing of value, including money, securities, rebates or refunds of funds already paid in (such as regular health insurance payments), reduced costs for any thing of value (such as reduced health insurance rates for the future), consumer goods, consumer supplies, airline or other travel tickets, sports or other events tickets, coupons for discounted goods or services, things of value conditioned substantially on chance (such as lottery tickets or a chance to win a new car), "perks" (such as a good parking spot), recognition (such as an award or announcement of achievement), or anything else a member might think has value.

The terms "incentive program", "reward program", "reward campaign", "campaign", and variants thereof, generally refer to any plan, designed or adopted by the payer, for providing rewards to members, when those members follow the actions indicated by the healthcare incentives and earn "points" and "miles" that they can exchange for things of value. In some cases the reward program might be limited by relevant law or regulation, such as the CMS reward guidelines promulgated at 42 CFR 422.2268 and 42 CFR 423.2268, and summarized in CMS Medicare Guidelines on Rewards, § 70.2.

Before the widespread use of computer technology to store and communicate patient health information, patient records were difficult to access in a timely manner. A dynamic or holistic view of patient information from a variety of sources was unavailable. Some healthcare measures could be researched, tabulated and graphed based on paper medical records, for example. However, the time and cost involved prohibited generating and presenting patient health information from a variety of sources in a variety of useful forms.

Since the adoption of computer technology for storing electronic medical records, multiple separate data analysis and visualization tools have been used to generate useful data presentations based on health claims data, for example. The data presentations have presented specific point presentations based on categories (including various measures, such as risk measures, quality measures, utilization measures and meaningful use measures, for example). Previously available data analysis and visualization tools have not been dynamic enough to compute and present various individual healthcare categories and health data dimensions in a single reporting / presentation system. The diverse nature and format of electronic health data has heretofore prohibited efficiently generating a dynamic interactive holistic presentation of health data for visualizing patient histories, patient health and population healthcare measures. This problem did not arise before the adoption of computer technology for storing electronic medical records, because the various data formats of medical information could be manually interpreted by humans.

A large amount of consumer healthcare information is routinely collected by healthcare providers, insurance providers, government agencies, researchers and other institutions. According to aspects of the present disclosure, useful compilations of healthcare data are created and stored in one or more integrated healthcare data warehouses. The healthcare data warehouse may compile healthcare data from various sources, process the compiled data, and store the processed data in a useful, secure and appropriately accessible form.

According to aspects of the present disclosure, the processed health information may include clinical data for a large number of patients, decades of longitudinal healthcare claim data for a large number of healthcare consumers, and various socio-demographic and care management data, for example.

Clinical data, prescription medication records, claims data, socio-demographic data and care management data may be integrated into the processed health information to provide both retrospective and prospective views of healthcare consumers and healthcare consumer populations. This enables healthcare providers to identify at-risk patients earlier, preserve patient health, reduce costs and prevent complications, for example.

Members may also input health information and actively engage in managing their own healthcare. This allows members, by the member's behavior, to improve their health and reduce healthcare costs to the payer and the member. Members may also be provided with a simplified and unified interface to their healthcare system, which can be personalized to the history and status of the member, and that can provide a variety of possible action alerts and related incentives and rewards to the member, to encourage member behavior that is effective in reducing healthcare costs. FIG. 1 illustrates an exemplary functional block diagram of a system 100 for analyzing and navigating health information according to the present disclosure. As illustrated, the system 100 includes a user preferences portion 102, a clinical analysis portion 104, a health navigator portion 106, an actions portion 108 and a predictive processing portion 110. The system 100 may include a login portion 1 12 that allows users, such as payers, providers, members, etc. to securely log into the system 100, for example, using a username and password, and access the various components and functions of the system 100.

The user preferences portion 102 may include preferences 1 14 that may include demographic information 1 16, reminders and alerts 118, active medications 120, and provider & clinic information 122. The demographic information 1 16 may be information that a member user enters into the system 100. The reminders and alerts 1 18 may include settings that may be selected or otherwise set by a member user based on the member user's preference for how, when, and the type of reminders and alerts the member user may desire to receive. The active medications 120 and provider & clinic information 122 may also be information that a member user enters into the system 100 relating to the medications and provider of the member user.

The clinical analyzer portion 104 is described in further detail below, and generally includes one or more dashboards 124 that incorporate multiple measure categories and dynamic drill-down visualization using various dimensions according to the selected measure. The dashboard may implement, be connected to or coupled to a time machine type analyzer 126 and a summary analyzer 128. These also provide categories (such as measures) and dynamic drill- down visualization using various dimensions.

The health navigator portion 106 is described in further detail below, and may also include the summary analyzer 128, as well as biometrics 130 (such as data corresponding to measurements of blood pressure, cholesterol, glucose level, weight, and otherwise from biometric devices), health and wellness 132 (such as reports from members with respect to diet and exercise), rewards or incentives 134, alerts 136, advice 138, and programs 140. These portions of the health navigator portion 106 of the system 100 allow member users to input health information and actively engage in managing their own healthcare. Member users may also be provided with a simplified and unified interface, which can be personalized using the preferences described above, and that can provide a variety of possible alerts and related incentives and rewards to the member user, to encourage member behavior that is effective in reducing healthcare costs.

The actions portion 108 may include actions 142 that may be used as alerts 136. These actions may include contact provider 144 (such as informing the member user to contact his/her provider), prescription usage and refill 146 (such as or the member user reporting having taken a dose of prescribed medication, informing the member user and/or requesting that the member user refill a prescription), exercise 148 (such as a member user reporting having exercised or reminding the member user to exercise in accordance with a selected program), diet 150 (such as 5 a member user reporting having followed a diet plan or reminding the member user to diet in accordance with a selected program), and schedule appointment 152 (such as informing the member user to schedule an appointment with his/her provider and/or the member user reporting that he/she scheduled an appointment with his/her provider).

The predictive processing portion 110 may include models 154 such as lifetime cost

10 models 156 (for example calculated from actuarial tables or lifetime cost curves based on current values of the member user's information) and trending models 158 (for example, providing a decrease (or increase) in estimated lifetime healthcare cost as the member user takes action to alter his/her biometric measures).

It should be appreciated that any of the various portions and blocks illustrated in FIG. 1

15 may be linked to any other and receive, transmit, and share data and other information to provide the aspects described herein. The data may be processed data, as described herein, which is secure and stored in an appropriately accessible form.

The system 100 may also include or be in bi-directional communication with a health information processing system for use in implementing the clinical analyzer 104 (described

20 above) according to an aspect of the present disclosure. Referring to FIG. 2, the health information processing system 200 may include a secure health information data storage machine 202 coupled to or in communication with one or more a health information data sources 204. The health information data sources may include one or more clinical data sources 206 such as healthcare providers, a health information exchange network, claims data sources 208

25 such as healthcare payers, socio-demographic data sources 210 and case management data sources 212, for example. The secure health information data storage machine 202 processes and stores the processed health information and health claims information received from the health information data sources 204. The health information may be received from electronic medical records of a numerous healthcare consumers via the health information data sources

30 204, for example.

The health information processing system 202 also includes a healthcare analytics processor 214 coupled to the secure health data storage machine 202. According to aspects of the disclosure, the healthcare analytics processor 214 is configured to generate and display a dashboard (such as the dashboards 124) that incorporates multiple categories (such as measures) and incorporates dynamic drill-down visualization using various dimensions according to the selected category and/or parameter of the category. In another example, the healthcare analytics processor 214 is further configured to perform contextual drill-downs to summary patient reports or summary provider reports using dynamic formatting and content based on the selected category and/or parameter of the category. In another example, the healthcare analytics processor 214 is further configured to use attribution analytics to associate conditions to encounters, patients to facilities, and current medications to patients, for example.

According to another aspect of the present disclosure, the healthcare analytics processor 214 is further configured to perform contextual drill-downs to patient history and to display the patient history as a longitudinal, interactive, dynamic visualization (such as the time machine 126) which can zoom in/out to shorter/longer time periods respectively, pan through various time periods, etc.

According to aspects of the present disclosure, the healthcare analytics processor 214 may be further configured to filter and display only one or more various categories and/or parameters of the categories, such as medical event types in the timeline such as inpatient, medications, emergency room visits. In another example, the healthcare analytics processor 214 is further configured to generate detailed tabular information on events based on visible events in the timeline. In another example, the healthcare analytics processor 214 is further configured to allow the user to select events in the timeline and display the corresponding event's detailed information below such as medication details, lab results and histories, encounter diagnoses/procedures/providers/insurance, or provider text reports.

The presently disclosed systems and methods are dynamic enough to compute and present various individual healthcare measures and health data dimensions into a single reporting/presentation system because they include the collection and pre-processing of a vast compilation of clinical data and claims data from numerous sources of electronic medical records and other health information. The processed data includes data formatted in a manner that can be quickly and securely accessed and interpreted by the healthcare analytics processor 214 to efficiently generate a dynamic interactive holistic presentation of health data for visualizing patient histories, patient health and population healthcare measures.

According to an aspect of the present disclosure, the processed data includes claims data integrated with encounter data to show corresponding cost information. According to another aspect of the present disclosure, the processed data includes integrated consumer data to inform patient outreach activities. According to an aspect of the present disclosure, the healthcare analytics processor 214 is further configured to utilize Extract/Transform/Load (ETL) technologies to parse, normalize, and integrate clinical/HL7 data (for example, including ADT's (Admission, Discharge, Transfer), Labs, Prescription/Pharmaceutical (Rx), and Text Reports) into a relational database. According to an aspect of the present disclosure, the healthcare analytics processor 214 is further configured to generate and/or utilize a proprietary, integrated clinical, claims, and consumer data model.

The secure health information storage machine 202 may include one or more data storage computers which may be located in a secure location or may be distributed over a number of secure locations. The secure health information storage machine may also include means for protecting data privacy and security such as means for encryption and secure communication, for example.

The health information processing system 200 enable various payers and providers to quickly and easily upload, download, and access data. Referring to FIG. 3, an example information flow 300 is illustrated. As illustrated in FIG. 3, various payers 302 and providers 304 may upload, download, and access data using the health information processing system 200 via single payer data feeds and single provider data feeds. This allows the payers 302 and providers 304 to exchange information using a common infrastructure. Referring to the information flow 400 of FIG. 4, previously, the payers 302 and providers 304 communicated with one another directly. This caused the payers 302 to have multiple data feeds per provider 304, and the providers 304 to have multiple data feeds per payers 302 resulting in inefficient duplication of infrastructure across payers 302 and providers 304. For example, multiple payers 302 were requesting clinical data from providers 304 in custom formats. The solution of FIG. 3 solves this problem by providing a common infrastructure through which the payers 302 and providers 304 may upload, download, and access data.

The health information processing system 200 also allows members / consumers / patients to access, upload, and download data. This allows the health information processing system 200 to integrate data from payers, providers, and patients to provide quick and easy access to the data and more accurate analysis of the data. An exemplary visualization 500 of the integration of data is illustrated in FIG. 5. As illustrated, payers 302, providers 304, and patients 502 may all access, upload, and download data, such as claims data 504, clinical data 506, and consumer data 508. This data may then be integrated with one another and analyzed using analytics 510 to provide meaningful dynamic results (as described in further detail below).

For example, the health information processing system 200 may provide automated transactional risk/quality services from clinical data, including supplemental data extracts / $X/chart automated, quality/risk enhancement data that doesn't come through to claims $X/trx, additional PAF channels for current portal/paper/CDROM offerings $X/trx, and additional risk adjustment $PMPM (per member per month) based on clinical data. The health information processing system 200 may provide quality and risk improvements 2-3 months' earlier than claims data based on improved reporting timeliness/accuracy, and suppression of unneeded member and provider outreach activities. The health information processing system 200 may also provide improved member/provider relations through optimized member/provider outreach and reduced conflict between payer/provider reporting.

FIG. 6 illustrates an exemplary overview of a data model 600 of the system according to the present application. As illustrated, the system acquires or receives data from various healthcare data sources 602, such as Health Information Exchanges 604, hospitals and clinics 606, clinical data aggregators 608, health insurance plans, etc. Each data provider may send input data 610 from multiple internal source systems, such as HL7 ADT (Admit Discharge Transfer) feeds 612, HL7 Lab feeds 614, HL7 Medication Order feeds 616, HL7 Text report feeds 618, and custom formats 620 (for example, health insurance enrollment, healthcare claims, geography data, etc.). The data is received from the various sources at frequencies that can vary by source system. For example, some data sources may transmit data to the system on a weekly basis, others on a daily basis, yet others may transmit data several times a day. The data is either pushed to the system by the data provider or an extract/data transfer process is run by the system on the data provider's system to transfer data to the system on a regular basis. The data is transferred via a secure encrypted data transfer protocol (SFTP).

The data may be archived and stored in a landing location until data intake and integration processes are run. Data intake 622 and integration 624 processes may run on schedules that are independent of the data acquisition processes. For example, while some data sources may transmit data several times a day, data may be integrated once or twice a week. In order to maximize performance and throughput, data may be processed in batches. For example, 100,000 HL7 messages may be processed all at one time as opposed to processing each message one by one. During the data intake process 622, the data is parsed 626, normalized 628, standardized 630, and source rules 632 are applied. For example, the data is cleaned (i.e., control characters are removed, strings are upper-cased, trimmed, etc.). The source rules 632 are applied to normalize 628 the data. The data is parsed 626 and transformed from the source formats to a common format that is used as an input for the data integration 624. The parsing 626 may be performed according to a mapping to create a level of granularity in the common format. For example, one HL7 message may create one patient record, one encounter record, multiple diagnosis records, etc. To maximize performance, several processes may be run in parallel.

The input to the data integration 624 is the common format created by the data intake processes 622. The data integration 624 integrates data from the various healthcare sources 602 into a common set of concepts stored in a relational database, via concept integration 634. 5 Concepts include Patient, ER Visit, Medication Order, Lab Result, etc. Multiple transactions are applied in the appropriate order to create a view of each concept from multiple (potentially duplicated source records), via transaction integration 636. A Master Person Index is applied to tie records for the same patient from different sources together. This enables the view of a patient across all of the hospitals/facilities/data source systems. Business rules 638 may also be 10 applied.

The data (represented as processed data 676) may be integrated and stored according to one or more subject areas, for example including: patient 640, outpatient visit 642, inpatient stay 644, ER visit 646, medication (Rx) order 648, lab results 650, population programs 652, discharge summaries 654, radiology reports 656, cardiology reports 658, microbiology reports

15 660, pathology reports 662, health insurance enrollment eligibility 664, and healthcare claims, including medical claims 666, pharmacy (Rx) claims 668, dental claims 670, vision claims 672, and behavioral claims 674. The source data may be stored at the source level (i.e., as it was received) to enable longitudinal view of patients as well as historical population analysis. The system also provides the ability to report on the source values as well as standard values. For 0 example, if source A represents gender as 'M' or 'F' and source B represents gender as '0' or ' 1 ', the standard reporting values for these may be 'MALE' and 'FEMALE'.

The processed data 676 may be analyze using analytics 678. The analytics 678 may include measures 680 and groupers 682. The measures 680 (for example, in the form of numerator/denominator) are calculated and stored for application consumption. For example, an 5 inpatient 30 day re-admit measure calculates patients who have been discharged (denominator) and out of those patients, who was re-admitted to the hospital within 30 days of discharge (numerator). The groupers 682 are software packages that group various healthcare records into episodes of care for the purpose of determining cost, risk, and quality. For example, during a course of a pregnancy, there may be various seemingly unrelated records for office visits, lab

30 tests, ultra sound tests, etc. generated. The groupers 682 tie these records together to represent one episode of care - pregnancy. This allows healthcare providers to measure how well the providers follow protocols for caring for patients during pregnancy, with diabetes, etc.

The processed data 676 and analytics 678 may be accessed by users 684, including providers 304, payers 302, patients 502, and government agencies 686. The processed data 676, analytics 678, and other analyses corresponding to the processed data 676 may be presented to the users 684 via various presentation means 688, including dashboards 124, reports 690, portals 692, on a mobile device 694, on a tablet 696, or via other electronic computing type devices.

FIG. 7 illustrates a method 700 of processing and integrating the data from various 5 providers, payers, and patients / consumers. As illustrated, the system receives health information and health claims information from one or more healthcare data source, illustrated as 702. As described herein, the healthcare data source may be one or more of a health information exchange, a hospital, a clinic, a clinical data aggregator, and a health insurance plane provider, etc. The health information and health claims information may also be received or acquired in a

10 plurality of source data formats, including one or more of a HL7 Admit Discharge Transfer message, a HL7 Lab message, a HL7 Medication Order message, and a HL7 Text report message. The health information and health claims information is parsed and transformed into a common format, illustrated as 704. The transformed health information and the health claims information is processed and integrated into concepts to form processed health data, illustrated as

15 706. The concepts may include one or more of a patient, an outpatient visit, an inpatient stay, an emergency room visit, a medication (Rx) order, a lab result, a population program, a discharge summary, a radiology report, a cardiology report, a microbiology report, a pathology report, a health insurance enrollment eligibility, a medical claim, a pharmacy (Rx) claim, a dental claim, a vision claim, and a behavioral claim.

0 A master person index may also be applied to the processed health data to tie healthcare records for a same patient from different healthcare data sources together, illustrated as 708. The processed health data is stored in at least one database (which may be a relation database), illustrated as 710. The processed health data may be analyzed according to one or more measures / categories, illustrated as 712. The one or more categories may include a percentage 5 of patient re-admittance to an emergency room, a percentage of patients with greater than three visits to the emergency room, and a percentage of patients with undiagnosed diabetes, etc. The information may be further analyzed and healthcare records of the processed health data may be grouped into episodes of care corresponding to a patient.

An interactive user interface for presenting at least a portion of the processed health data

30 using one or more of the categories / measures is generated, illustrated as 714. Upon a user selecting a category / measure, the system may dynamically filter and correlate the processed health data and present the processed health data using the interactive user interface, illustrated as 716. The interactive user interface may present a bubble chart corresponding to medical conditions associated with the selected category, a list of providers associated with the selected category, etc. (as described in further detail below). Upon further selection of a parameter of the selected category / measure, the system may dynamically filter and correlate the processed health data further and present the processed health data using the interactive user interface, illustrated as 718. The interactive user interface may present a list of providers associated with the selected category and the selected parameter, etc. (as described in further detail below). This enables the user to dynamically drill-down into the data to view different views and more targeted sections of the data.

Using the data structure and methods described herein, the clinical analyzer portion 104 of the system 100 may provide one or more dashboards 124 that incorporate multiple categories and dynamic drill-down visualization using various dimensions and/or parameters according to the selected category or measure. For example, the secure health information data storage machine may be configured to receive health information and health claims information from a plurality of healthcare consumers via the health information exchange network, parse and normalize the health information and the health claims information to form processed health data, and store the processed health data. The healthcare analytics processor may generate an interactive user interface for presenting at least a portion of the processed health data using one or more categories, dynamically filter and correlate the processed health data based on selection of a category, and dynamically filter and correlate the processed health data based on selection of a parameter of the category by a user. The interactive user interface may be dynamically generated in response to the selection of the parameter.

An exemplary user interface 800 implementing a dashboard is illustrated in FIG. 8. As illustrated, the user interface 800 includes a select a measure region 802, a select a condition region 804, and a select a facility region 806. The select a measure region 802 includes various categories or measures, such as Emergency Room (ER) Re-admittance percentage (i.e., the percentage of discharged patients that were re-admitted to the emergency room in the last 30 days), ER high usage (i.e., the percentage of patients with greater than three visits to the ER), undiagnosed diabetes (i.e., the percentage of patients with high hemoglobin Ale (HbAlc) and not diagnosed with diabetes), HIV viral load, etc. The number any type of measures presented in the user interface 800 may change, and any type of measure can be implemented in the user interface 800.

Each of the measures may display a percentage (for example, ER Re-admittance percentage is 10.2%), an arrow pointing up or down to indicate the trend of the percentage as increasing or decreasing, and a trend-line for the last 8 periods (such as 30 day periods). The arrows and other portions of each measure may be color-coded according to whether the percentage is good (i.e., green), bad (i.e., red), or in between good and bad (i.e., yellow). As illustrated, the ER Re-admittance percentage is 10.2%, increasing (as shown by the arrow pointing up), and a trend-line that shows the percentage is increasing. The ER high usage percentage is 2.3%, decreasing (as shown by the arrow pointing down), and a trend-line that shows the percentage is decreasing. The undiagnosed diabetes percentage is 5.9%, increasing (as shown by the arrow pointing up), and a trend-line that shows the percentage is increasing. The HIV viral load percentage is 85.6%, increasing (as shown by the arrow pointing up), and a trend-line that shows the percentage is increasing.

The select a condition region 804 includes a bubble type chart corresponding to various conditions (such as diabetes, joint issues, HIV infection, asthma, chronic obstructive pulmonary disease (COPD), unclassified, unknown, allergy, congestive heart failure (CHF), leukemia, urinary tract infection (UTI), kidney issue, etc.). The size of the bubble indicates the size of the patient population of that condition associated with a selected measure. The bubbles may also be color-coded to indicate performance (such as good (i.e., green), bad (i.e., red), or in between good and bad (i.e., yellow)). As illustrated, the measure ER Re-admittance percentage is selected, and condition X is selected. Based on the selected category (i.e., the ER Re-admittance percentage measure) and a selected parameter of the category (i.e., the condition X), a chart relating to the percentage of patients that have been re-admitted to the ER having condition X is displayed (i.e., next to the bubble chart type). This chart indicates 12.5% of patients were re- admitted to the ER corresponding to condition X.

The select a facility region 806 includes a list of providers and the statistics for each provider relating to the selected category and/or parameter. As illustrated, the selected category is ER Re-admittance percentage and the selected parameter of the category is condition X. Based on the selected category and parameter, the user interface 800 displays that Provider 1 has an ER re-admittance percentage of 18.1% corresponding to condition X, Provider 2 has an ER re-admittance percentage of 17.2% corresponding to condition X, Provider 3 has an ER re- admittance percentage of 12.8% corresponding to condition X, and Provider 4 has an ER re- admittance percentage of 1 1.8% corresponding to condition X.

The user interface 800 also allows the user to hover over or click on /select any of the areas, for example, the bubbles in the bubble chart to view more details and drill-down further into the data that makes up the category and/or parameter. In this respect, the user interface 800 may change and be dynamically generated in response to the selection of the category and/or parameter. The user interface 800 also allows the user to drill-down into a particular provider to view how that particular provider is performing based on one or more selected measures. Additionally, the information and way information is displayed may change based on the selected category and/or parameter. For example, when the category of undiagnosed diabetes is selected, the bubble type chart may be replaced with a chart or other data relating to lab value stratifications (such as FIbAlc values of X to Y and Y to Z), patient age ranges, etc.

Thus, each category or measure can be looked at from a number of different parameters

(including, condition, patient age, facility / provider, etc.). As the user drills down into a particular category and/or parameter, the information and way information is displayed may change to become more targeted at what the user is drilling down into.

Additionally, each facility / provider can be analyzed. For example, a user may select a measure and a facility or provider. The user may then view the whole population corresponding to the measure and facility, select a condition (such as abdominal pain) and view the population of patients associated with the measure, facility, and condition. The user may then drill down further, for example, to individual patient names and identifications. The report for the individual patients may include demographics about the patient as well as information about the initial hospital stay (such as for admitted patients), the condition the patient had, why the patient was discharged, the readmit information about the patient, etc.

The user interface 800 is dynamic and changes as the user clicks on and drills down into the relevant data. The areas and information presented in the user interface is also clickable, sortable (i.e., high to low, low to high) the order of columns, etc. The user interface 800 may also accommodate new measures, with new parameters, headings, etc.

Another view of the user interface is illustrated in FIG. 9. As illustrated the user interface 900 includes the select a measure region 802, the select a facility region 806, and a select a condition region 902. The select a condition region 902 presents a number of different conditions that may be selected, such as diabetes, joint issues, HIV infection, asthma, chronic obstructive pulmonary disease (COPD), unclassified, unknown, allergy, congestive heart failure (CHF), leukemia, urinary tract infection (UTI), kidney issue, etc. As described above with respect to FIG. 8, the user interface 900 may be dynamic similar to the user interface 800.

Another view of the user interface is illustrated in FIG. 10. As illustrated the user interface 1000 includes the select a condition region 902 and a select a measure region 1002 based on the selected condition(s). For example, the user may select a facility / provider and one or more conditions (such as asthma and diabetes). The select a measure region 1002 may then present various measures based on the selected conditions, along with a trend-line, and one or more clickable icons that allow the user to select and drill down into the data further. As described above with respect to FIG. 8, the user interface 1000 may be dynamic similar to the user interface 800.

Another view of the user interface is illustrated in FIG. 1 1. As illustrated the user interface 1100 includes a select a measure region 1102, a select a condition region 1 104, and a select a facility region 1 106. In this example, the select a measure region 1102 includes an inpatient re-admittance percentage (i.e., the number of patients re-admitted within the past 30 days). As illustrated, the select a measure region 1 102 is showing a timeline of the past 1 week for the measure. Each of the measure displays a percentage (for example, 10.2%), an arrow pointing up or down to indicate the trend of the percentage as increasing or decreasing, and a trend-line.

Like the select a condition region 804 described above with respect to FIG. 8, the select a condition region 1 104 includes a bubble type chart corresponding to various conditions As illustrated, the measure inpatient 30 day re-admittance percentage is selected, and condition X is selected. Based on the selected category (i.e., the inpatient 30 day re-admittance percentage measure) and a selected parameter of the category (i.e., the condition X), a chart relating to the percentage of patients that have been re-admitted in the past 30 days having condition X is displayed (i.e., next to the bubble chart type). This chart indicates 10.2% of patients were readmitted within 30 days corresponding to condition X.

Like the select a facility region 806 described above with respect to FIG. 8, the select a facility region 1106 includes a list of providers and the statistics for each provider relating to the selected category and/or parameter. As described above with respect to FIG. 8, the user interface 1100 may be dynamic similar to the user interface 800.

Another view of the user interface is illustrated in FIG. 12. As illustrated the user interface 1200 includes a select a measure region 1202, a select a disposition region 1204, and a select a facility region 1206. In this example, the select a measure region 1102 includes an inpatient re-admittance percentage (i.e., the number of patients re-admitted within the past 30 days), an activity ratio (corresponding to a ration between potential activities that could be taken by the provider and the number of opportunities for taking such activity), a reached percentage (corresponding to a percentage of activities relating to contacting a patient), and an engaged percentage (corresponding to a percentage of contacted patients that were engaged), etc. As described above, each of the measure displays a ratio or percentage, an arrow pointing up or down to indicate the trend of the percentage/ratio as increasing or decreasing, and a trend-line.

The select a disposition region 1204 includes a graph relating to the disposition corresponding to the inpatient re-admittance percentage with respect to the activity ratio, reached percentage, and engaged percentage. Like the select a facility region 806 described above with respect to FIG. 8, the select a facility region 1206 includes a list of providers and the statistics for each provider relating to the selected category and/or parameter. As described above with respect to FIG. 8, the user interface 1200 may be dynamic similar to the user interface 800.

As mentioned above, the dynamic drill down aspect may allow a user to drill down to a single patient's record or search for a patient. An exemplary patient record user interface 1300 is illustrated in FIG. 13. As illustrated, the user interface 1300 includes demographic information, medical history (which may be from numerous hospitals), etc. The user interface may also present a longitudinal history of the patient using a time line (for example, the time machine type analyzer 126 described above with respect to FIG. 1). The user may zoom in and out of along the time line to view the history of the patient. The history may be represented as selectable icons along the time line 1302. For example, the icons may include an encounter icon (which looks like a plus sign), a lab result (which looks like a flask), a medication icond (which looks like a pill, a test report icon (which looks like a document), etc.

One or more of respective icons are placed along the time line 1302 corresponding to the date and time when they were performed, prescribed, etc. The user zoom in and out of the time line and selects one or more of the icons. Upon selecting an icon, a more detailed description of the information corresponding to the icon may be displayed in the user interface 1300, for example, including the provider, diagnoses, procedures, doctors, insurance information, etc. The user may also filter the patient's history for certain events, such as inpatient stays, outpatient stays, medications, and other patient events. The user interface 1300 may also indicate which measures the patient is eligible for, either in the numerator or denominator, illustrated as measure section 1304. As described above with respect to FIG. 8, the user interface 1300 may be dynamic similar to the user interface 800.

Another view of the user interface is illustrated in FIG. 14. As illustrated the user interface 1400 includes a geographic analysis region 1402 and a patient summary region 1404. In this example, a user may drill down into a geographic analysis of a measure, condition, or other category and/or parameter based on locations of patients and distance the patients are located away from a particular location (such as the location of the provider). As described above with respect to FIG. 8, the user interface 1400 may be dynamic similar to the user interface 800.

In other aspects, claims data may also be integrated into the user interface(s) and dashboard(s) described herein. This information may then be used in combination with the clinical and other data (including member / patient / or consumer data) to provide analysis of cost, gap and care closures from the providers, and manage the quality and risk for the payers. The disclosed systems and methods enable various payers and providers to quickly and easily navigate large patient populations down to individual patient opportunities and find actionable intelligence to inform patient outreach more efficiently and effectively to drive better outcomes for the healthcare ecosystem. It also allows them to avoid the time and cost of system or manual integration between various reporting systems to manage performance across risk, quality, cost, utilization, meaningful use, etc.

In yet another aspect, member / patient / consumer information may also be integrated with the clinical and claims data. The consumer information may include self-reported information, such as progression through diet and/or exercise regimes, taking of medications, etc. This may be used to influence behavior using incentives, for example.

FIG. 15 is a diagram of a system 1500 for administering a incentive / rewards based program according to exemplary embodiments of the present disclosure. The system may be used to implement the health navigator portion 106 of the system 100 described above with reference to FIG. 1.

As illustrated, the system 1500 includes at least a member workstation 1510 disposed to be used by a member 1501, a payer workstation 1520 disposed to be used by a payer 1502, a provider workstation 1530 disposed to be used by a provider 1503, and a database/analytics system 1540 disposed to be used by an operator 1504. The system 1500 can also include one or more communication links configured to carry messages between and among the member workstation 1510, the payer workstation 1520, the provider workstation 1530, and any other devices coupled to the system 1500. For example, the communication links can include Internet connections, and the member workstation 1510, the payer workstation 1520, the provider workstation 1530, and any other devices coupled to the system 1500, can communicate using the Internet, such as using the HTTP or HTTPS protocols, or variants thereof, themselves using the TCP/IP protocols, or variants thereof, themselves using (at least in the case of the member workstation 1510) the IEEE 802.11 family, or variants thereof.

The elements of the system 1500 can include any devices appropriate to the functions described herein, disposed (such as by programming) to perform those functions. For a first example, the member workstation 1510 can include a "smartphone", such as a cellular telephone or tablet (such as an iPhone™, iPad™, or a device using an Android OS) capable of sending and receiving voice and data, and including a screen 151 1 capable of presenting a user interface 1512, and optionally including touch-sensitive buttons 1513 (as the user interface 1512 is further described herein). For a second example, the payer workstation 1520 and the database/analytics system 1540 can each include a server, such as a web server coupled to the Internet and disposed to interact with (at least) the user workstation 1510 and (optionally) the provider workstation 1530 and each other. The payer workstation 1520, the provider workstation 1530, and the database/analytics system 1540 can communicate using the Internet at web communication ports or other communication ports, or may alternatively eschew the Internet and use other communication techniques.

As further described herein, data flow within the system 1500 includes communication between and among all four of the member workstation 1510, the payer workstation 1520, the provider workstation 1530, and the database/analytics system 1540.

The member 1501, using the member workstation 1510, engages with the system 1500 with respect to health-related actions, such as by receiving advice (such as advice 138) and alerts (such as alerts 136) from the payer workstation 1520 or the provider workstation 1530, electing particular health programs (such as programs 142 and/or health and wellness 132), electing and conducting some of the actions (such as actions 142) recommended by those programs (e.g., via electronic links, contact information, a scheduling feature or live chat) such as scheduling a biometrics screening test (such as biometrics 130 and/or schedule appointment 152), and reports on other actions recommended by those programs (such as reporting having exercised (such as exercise 148), or reporting having taken a dose of prescribed medication (such as Rx usage and refill 146)). In some cases, the member 1501 can engage with the system 1500 by coupling a biometric device (not shown in this figure) to the member workstation 1510, and allowing the device to generate clinical data and report biometric measurements to the system 1500 (such as biometrics 130). The member 1501 may also earn "points" or "miles", as further described herein, by participating in surveys suggested by the payer 1502 or the provider 1503. The member 1501, having earned and accumulated "points" or "miles", may elect one or more rewards by virtue of having earned those "points" or "miles" (such as rewards 134).

Medical data from the member 1501 can be sent to the provider workstation 1530, which can aid the provider 1503 in making sound medical decisions and in advising the member 1501 (such as advice 138). For example, the provider 1503 might observe from the member's medical data that the member 1501 should have a dosage change for a particular medication; the provider 1503 can send an alert informing the member 1501 and requesting that the member 1501 refill the prescription, and can also send an alert to the member's pharmacy (a different provider 1503) informing them of the prescription change. In some embodiments, medical data may also be sent to the payer workstation 1520, which aids the payer 1502 in making sound financial decisions in setting insurance rates for the member 1501. For example, successful completion of a smoking- cessation program, or a weight-loss program, might allow the payer 1502 to determine that the member 1501 represents a lesser risk of medical costs, and can lower rates for the member 1501. Alternatively, successful program completion might allow the member 1501 to select lower co- pays as the member's reward. In some embodiments, the database/analytics system 1540 might also receive medical data from the member 1501, for the purpose of aggregating that 5 information, and possibly determining which rewards are most effective at reducing healthcare cost, after adjusting for other statistical factors.

Alternatively, medical data or self-reported data from the member 1501 can be withheld from the payer 1502, and only reported to the payer 1502 in a statistically aggregate, or otherwise anonymous way (such as by the provider 1503 or by the database/analytics system

10 1540), so that the payer 1502 can make sound financial decisions, but cannot obtain information on the medical condition of any particular member 1501.

The payer 1502, using the payer workstation 1520, engages with the system 1500 with respect to financial actions, such as by receiving aggregated medical data, as described above, and such as by responding to individual claims, and by generating and publicizing new rewards

15 or new campaigns for health improvement. For example, if the payer 1502 identifies back injuries as a particular safety hazard at the workplace, with the statistical effect that reduction in back injuries would reduce healthcare cost, the payer 1502 can create a new program for proper lifting techniques, or alternatively, for team lifting or forklift use, and can publicize this new program to members 1501 using alerts. Similarly, if the payer 1502 identifies a particular

20 disease as being reported with unexpectedly high frequency, the payer 1502 can send information to providers 1503 to look out for early signs of that disease, and can publicize that information to providers 1503 using alerts. The payer 1502 might even reward providers 1503 who are able to make early identifications and head off the more expensive stages of the disease, by rewarding providers 1503 with a providers' reward program, similar to rewarding members

25 1501 with the members' reward programs primarily described herein. The payer 1502 also engages with the system 1500 whenever a member 1501 is able to claim a reward (or when a provider 1503 is able to claim a provider's reward), such as by issuing payment for that reward, or in those cases of payers 1502 who are employers and rewards that are employer "perks", directly providing the reward.

30 In some cases the reward program or campaign might be limited by relevant law or regulation, such as the CMS reward guidelines promulgated at 42 CFR 422.2268 and 42 CFR 423.2268, and summarized in CMS Medicare Guidelines on Rewards, § 70.2. In some cases the reward program or campaign might be designed to be similar to health insurance and insurance benefits coverage available to the member, so as to reduce claims against those insurance benefits. In some cases the reward program or campaign might be encouraged by the employer's insurance company, as a condition of allowing the employer price breaks or rebates on insurance paid by the employer. Aspects of an exemplary reporting portal are described in a co-pending application having at least one common inventor having the Serial Number 13/875,516, entitled "CMS Stars Rating Data Management," and filed on May 2, 2013, the content of which is incorporated by reference in its entirety for any useful purpose.

The provider 1503, using the provider workstation 1530, engages with the system 1500 with respect to medical actions, such as by receiving medical data for individual members 1501, as described above, as well as aggregated medical data for member populations and sub- populations, as described above. Both the payer 1502 and the provider 1503 can generate surveys and publicize them to members 1501 using alerts, and can collect the data either directly from members 1501, or indirectly from the database/analytics system 1540. The provider 1503 can also provide encouragement as a quasi-reward to members 1501, such as by noticing whenever a particular member 1501 hits the next goal in their elected long-term program, and congratulating those members 1501 with personalized messages.

In these interactions in which the member 1501, the payer 1502, or the provider 1503 engage with the system 1500, the system 1500 is, providing information that is personalized to the particular member 1501 as a patient, and also accounts for longitudinal effects of the member's behavior as a future patient. This has the effect that the system 1500 provides a member-centric set of information, and in particular, a member-centric user interface 1512 at the place of engagement between the member 1501 and the system 1500. This also has the effect that the system 1500 provides a longitudinal set of information (and in particular, a detailed medical and behavioral history) with respect to the member's behavior and the medical condition thereof. This also has the effect that the system 1500 encourages members' behavior, both individually and in the aggregate, that tends to improve members' health, and that tends to reduce healthcare costs to the payer 1502, and in particular, that the payer 1502 regards as cost-effective in reducing healthcare costs. For example, by encouraging healthy behavior by members, it might be possible for the payer to expand the benefits available according to the member's healthcare insurance, such as by one or more of reducing co-pay amounts, covering additional medical providers, covering additional procedures by medical providers, covering additional medications or reducing co-pay amounts for those medications. In addition, by reducing healthcare costs to the payer through member engagement in their health, the rating and quality of a healthcare plan may be improved.

The database/analytics system 1540 may be operated by an operator 1504 of the system. In some cases the operator 1504 may be a provider party, a payer party or a third party, and the database/analytics system 1540 may be updated and maintained by any of these parties. The database/analytics system 1540 may receive member information

FIG. 16A illustrates a flowchart of a method 1600 of providing healthcare incentives according to the present disclosure.

The method 1600 can be performed by the system 1500 and its elements, such as one or more members 1501 at member workstations 1510, one or more payers 1502 at payer workstations 1520, one or more providers 1503 at provider workstations 1530, and the database/analytics system 1540, or combinations thereof. Where described herein that a step is performed by the method 1600, it should be understood from context (or from the figure) which element of the system 1500, takes the specific actions described for that step.

Although the steps are shown in a particular order, in the context of the invention, there is no reason for any such limitation. The steps may be performed in a different order, or may be performed in a parallel or pipelined manner, or otherwise.

A flow point 1600A indicates a beginning of the method 1600.

At a step 161 1, the member 1501 launches the user interface app at their member workstation 1510, and logs in to their individual account at the database/analytics system 1540, with a username, and a password. In alternative embodiments, other forms of security may be used to protect the member's medical information from improper exposure, such as facial recognition (using an attached camera at the member workstation 1510), fingerprint detection, retinal identification, typing speed detection, or some other security system. Two-factor authentication may optionally be required.

Since this step 1611 involves using a particular app at the member workstation 1510, the app will have been loaded onto the member workstation 1510 at some earlier time. For example, the member 1501 might have downloaded and installed the app on the member workstation 1510, or the member workstation 1510 might have been purchased with the app pre-installed. In alternative embodiments, there might be no such requirement for an app, and the database/analytics system 1540 (or the payer workstation 1520, or the provider workstation 1530) might perform as a web server and emulate the user interface 1512 described herein. In the context of the invention, there is no particular requirement for using an app, or a smartphone, or even the user interface 1512 described herein. For example, the member 1501 might optionally re-skin the app, with the effect of providing a completely different look and feel.

At a step 1612, the user interface 1512 presents the member 1501 with an overview, as further described with respect to FIGS. 17A and 17B. The overview can include a summary of the member's biometrics information, a summary of the member's health and wellness information, a summary of the member's rewards points, a summary of the member's alerts/advice awaiting receipt by the member 1501, and a summary of the member's engagement with long-term programs, all as further described with respect to FIGS. 17A and 17B.

At a flow point 1620, the member 1501 is ready to interact with the system 1500, using the user interface 1512, with the effect of engaging with the system 1500. The member 1501 can conduct a substantial number of individual interactions with the system 1500, with the effect that the member 1501 exchanges information with the system 1500. From the overview, the system 1500 is ready to present other parts of the user interface 1512, as further described herein.

At a step 1631, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to biometrics, as further described with respect to FIG. 17B, FIG. 18A, and FIG. 18B.

After performing this step, the method 1600 continues with the flow point 1620.

At a step 1632, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to health and wellness.

After performing this step, the method 1600 continues with the flow point 1620.

At a step 1633, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to rewards.

As described herein, the member 1501 can earn rewards "points" for actions that are clearly verifiable, and the member 1501 can earn rewards "miles" for actions that are not clearly verifiable. Rewards "points" are generally more valuable than rewards "miles", and are exchangeable for things with more tangible value. For example, when rewards include money (cash payments, rebates of co-pays, reduced insurance rates, reduced co-pay requirements, or otherwise), they generally require rewards "points". When rewards "miles" are exchanged for rewards, they generally are exchangeable only for less-valuable rewards, such as coupons for discounted goods or services, "buy one get one free" deals, lottery tickets, a chance to win a new car, "perks" (such as a good parking spot), or recognition (such as an award or an announcement of the member's achievement). Methods for identifying actions for completion that may be eligible for rewards and granting such rewards are described further with respect to FIG. 16B.

As described herein, rewards can also include consumer goods (such as a free iPad™, a free cell phone, free airline tickets, free sport event tickets), consumer supplies (such as a "year's supply of some product), or any other thing of value.

After performing this step, the method 1600 continues with the flow point 1620.

At a step 1634, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to alerts.

Alerts are described in further detail with respect to FIG. 17 A.

After performing this step, the method 1600 continues with the flow point 1620.

At a step 1635, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to advice.

Advice messages are described in further detail with respect to FIG. 17 A.

After performing this step, the method 1600 continues with the flow point 1620.

At a step 1636, the member 1501 can select, and the system 1500 can present, that part of the user interface 1512 with respect to long-term programs, as further described with respect to FIGS. 19A and B.

After performing this step, the method 1600 continues with the flow point 1620.

A flow point 1600B indicates an end of the method 1600. The method 1600 repeats when the member 1501 re-triggers it. Alternatively, the method 1600 may repeat until some selected condition occurs.

In one embodiment, the system 1500 includes a relatively large set of rules, such as at the database/analysis system 1540, that convert information about the member 1501 into possible requests for action by the member 1501, the payer 1502, or one or more providers 1503. These requests for action can take the form of alerts/advice, or can take the form of chart notes with respect to the member 1501, or otherwise. Thus, the overview and member interaction with the system in steps 1612 and 1620 may involve the system 1500 executing various functions to provide the member with meaningful information to improve the health of the member.

In one embodiment, the system's rules are responsive to information the system 1500 can collect about the member 1501, possibly from disparate sources. The system 1500 can collect information from reports of insurance and flexible spending account (FSA) claims, as these can indicate medical conditions or mental health conditions that might apply to the member 1501. The system 1500 can collect information from reports, as these can also indicate medical conditions or mental health conditions that might apply to the member 1501. Reports can include those from medical personnel, laboratory technicians, physical therapists, mental health professionals, and other therapists.

In one embodiment, the system 1500 can also collect health-related member information such as medical, provider, pharmaceutical, and eligibility information with respect to a member of a health plan. The information may include pre-adjudicated medical claims, pharmacy claims, clinical data such as electronic medical records ("EMRs") and HL7 messages, and/or member eligibility information such as demographics information including age, gender, health status. The information may be obtained from providers, pharmacists, biometric devices, self-reports by members and health insurance companies. Providers such as doctors and hospitals may supply a member's medical information to the system 1500. For example, information with respect to visits and procedures, chart notes, observations and diagnoses, and otherwise may be supplied. Laboratory technicians can supply information with respect to laboratory visits and procedures, chart notes, laboratory observations and diagnoses, and otherwise. Physical therapists and other professionals can supply information with respect to visits and procedures, and measurements. Providers may also supply information about the provider itself such as provider ratings, costs and scheduling. Pharmacists can supply information with respect to filled prescriptions (but cannot assure that the filled prescription doses were actually taken). Similarly, biometric devices can supply relatively reliable information about the member 1501, but only when they are used, and used correctly. They can measure blood pressure, cholesterol, glucose level, weight, and other facts. Health insurance companies may provide information related to a member's health plan, eligibility, annual deductibles, annual out-of-pocket amounts, accrued deductibles and out- of-pocket amounts and so on. Similarly, actions by members 1501 generate information, at least in the sense that when members 1501 express preferences, they provide information about their values and measures of importance. When members 1501 self-report about their activities, the frequency and reliability of their reports provides information about their degree of interest. For example, when members set goals (e.g., intermediate goals, long-term goals), they express preferences (as to what to do, and how hard to work on it), and they provide information about their degree of interest.

The rules the system 1500 applies can include medical rules; for example, rules derived from evidence-based medicine can help providers 1503 maintain best practices. The rules the system 1500 applies can also include business rules; for example, the payer might wish to encourage specific positive behaviors. And the rules the system 1500 applies can also include rules of inference derived from statistical implications or from domain knowledge.

FIG. 16B shows a flow diagram of a method 1650 of encouraging healthy behavior by providing healthcare incentives according to the present disclosure. Method 1650 may be performed by system 1500 according to exemplary embodiments of the present disclosure. In method 1650, the system 1500 receives health-related information for the member in operation 1655. As described herein, health-related information may include but is not limited to medical, provider, pharmaceutical, and eligibility information with respect to a member of a health plan. The information may be obtained from providers, pharmacists, biometric devices, self-reports by members and health insurance companies. The method proceeds to operation 1660 where evidence-based medicine rules are applied to the received member information to identify one or more actions to improve the member's health or health risk. The evidence-based medicine rules may be associated with identifying member gaps in care. For example, analysis against a set of predefined business rules may identify a group of healthcare services generally recommended for the member, e.g., a general set of gaps in care. The group of services recommended may be based on evaluating the member's healthcare plan eligibility, historic claims data, recently adjudicated medical claim data, recently adjudicated medication prescription claim data, and/or recent laboratory procedure data to identify services recommended for the member. Determining member healthcare plan eligibility may involve identifying the services for which the member qualifies under their healthcare plan. Historic claims data may be claims data from the past two to ten years. Member data that is recently adjudicated, such as recently adjudicated medical, prescription and laboratory procedure data, may be a set of data that is received from a data storage device on a periodic basis, such as weekly, bi-weekly or monthly. This information may be monthly aggregations of claims data extracted from a data warehouse. Identification of healthcare services recommended for the member, also referred to as gaps in member care, is discussed in a co-pending application having at least one common inventor having the Serial Number 14/086,714, entitled "System, Method and Computer Program Product for Administering Consumer Care Initiatives," and filed on November 21, 2013, the content of which is incorporated by reference in its entirety for any useful purpose. Currently, 17 HEDIS measures with over 580 rules may be used to analyze member claim data to identify gaps in care and determine whether the member is eligible to receive services for closing the gap in care. In this example, the rules may be run for each member, and the measures may be aggregated by health plan, which may enable the payer to identify members to target to incent activities to improve their health and health plan rating.

Method 1650 continues by comparing the received member information with the identified one or more actions to determine whether the one or more actions are completed or pending in operation 1665. The comparison identifies, for example, whether the member's previous actions result in completion of a recommended action and thus closed a gap in care that otherwise would be an open action (e.g., an open gap in care). For example, where the member is eligible for an annual physical identified in operation 1660, comparison of the received member information, such as member claims data, may indicate the member has not yet received their annual physical. In this case, the member may be presented with information about completion of their annual physical such as links to providers offering these services. For example, the member may be alerted about the one or more actions to as they engage with the user interface of system 1500. The actions may be classified as closures in gaps in care and may be considered HEDIS-based measures, accountable care organization ("ACO") measures, Medicaid guidelines, patient-centered medical home ("PCMH") measures, health plan-specific measures, employer-specific measures, Medicare risk-based measures or Medicare quality measures, which the member may engage in to improve their health or health risk. In addition, a payer, provider or third party may receive these completed or pending actions and may monitor the member's health or health risk. In some cases, the monitoring party may incent the member to engage in specific recommended action. In a particular example, the payer may incent the member to engage in an activity that will close a gap in the member's care, which may facilitate the payer in improving the quality rating of their health plan. In the aforementioned example, the action of receiving an annual physical may be a step in a rewards program described herein, the completion of which may result in the member being granted rewards.

In exemplary embodiments, the completed actions may be those that are verifiable, such as completion of a scheduled appointment with a provider, undergoing a lab procedure, refilling a prescription, and so on. In other exemplary embodiments, completed actions may be non- verifiable, such as self-reported actions. Such actions may be the member's reporting of self- weighing, exercise, and dieting. In yet other cases, completed actions may be temporarily non- verifiable but ultimately verifiable. These actions may include reported actions by the member or a provider where the action has not yet been verified by a secondary source of information. For example, where a provider or a member reports that the member has received a prescription for a medication, the system may associate a member-reported action of filling a prescription as temporarily non-verifiable until this action is verified using a pharmacy claim. The secondary source of information may be a party that regularly provides verifiable information and may include, but is not limited to: providers, laboratories, pharmacies and so on.

In operation 1670, rewards under a rewards program are granted for completed actions, such as completion of an annual physical by the member. As described in more detail in connection with FIGS. 17A, 17B, 18A, 18B and 19A and B, the rewards program generally includes a sequence of steps associated with actions that may be taken by the member to receive a reward under the program. The actions may include but are not limited to those actions that may help improve the health or health risk of the member. Each of the steps may be associated a reward, e.g., points, miles or other reward. The series of steps may be associated with both verifiable (e.g., medical claims data, pharmacy claims data, laboratory data) and non-verifiable actions (e.g., self-reported data) which may include both non- verifiable and temporarily non- verifiable actions. Because the comparison involves using verifiable and non-verifiable member data, the system 1500 may grant rewards differently based on whether the action is verifiable.

For verifiable actions, prior to granting rewards, completion of the action may be verified based on the system 1500 receiving information that confirms or denies completion of the action. For example, medical information for the member may be obtained from a medical provider that confirms or denies the completion of the action. In addition or alternatively, medical provider information may be obtained from a third party, such as a payer, that confirms or denies completion of the action. In addition or alternatively, biometric data may be obtained from authenticated devices that confirms or denies completion of the action by the member. For non- verifiable actions, self-reported member data may satisfy completion of the action as verification from a secondary source may be unavailable. Where the action is temporarily non-verifiable, actions associated with the self-reported member data are verified using a secondary source, for example, that regularly provides verifiable data. Rewards are granted in operation 1670 based on whether the completed action is verifiable or non- verifiable. For completed verifiable action, the level of reward granted may be a first level of reward, while completed non-verifiable actions may be granted a second level of reward having a lesser value relative to the first. In addition or alternatively, verifiable actions may be associated with points, while non-verifiable actions may be associated with miles, and points may have a higher relative value compared to miles. As provided herein, accumulation of rewards, points and/or miles may allow the member to surrender these in exchange for things of value. In some implementations, where the rewards program is administered by a payer, the rewards for completion of actions associated with gap closures that can help improve a health plan's star rating, quality rating and/or financial performance may have a higher relative value compared to other actions.

In operation 1675 a payer may be notified of the member's completion of the action and of the member's health plan. This notification enables a payer, such as a health insurance company, to be updated on the activities of the member and on the effectiveness of the rewards program in incenting their members to engage in activities that can improve member health as well as the health plan. Providers using the system may therefore track performance of quality measures under the health plan of the member.

FIGS. 17A and 17B illustrate a user interface that may be provided according to exemplary embodiments of the present disclosure.

FIG. 17A illustrates the user interface 1512, including an overview, as shown at the user workstation 1510 on its screen 151 1.

The overview includes a set of elements 1710, each element 1710 being presented on the screen 151 1. In one embodiment, each element 1710 can include a title 1701 and sub-title 1702, a summary presentation 1703, and a detail button 1704.

A first element 1710 includes a summary of the member's biometrics information. Its title 1701 can include the word "Biometrics". Its sub-title 1702 can include the phrase "In Goal Range". Its summary presentation 1703 can include an indicator of how many or which biometrics values for the member 1501 are within their goal range. In this particular case, the summary presentation 1703 includes the term " 17%", or approximately one value out of six; in alternative embodiments, the summary presentation 1703 for biometrics can indicate which ones of the biometrics values for the member 1501 are within their goal range. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 1511 to show the member's actual biometrics values.

A second element 1710 includes a summary of the member's health and wellness information. Its title 1701 can include the phrase "Health & Wellness". Its sub-title 1702 can be blank. Its summary presentation 1703 can include one indicator of how many calories worth of exercise the member 1501 has performed for the day, expressed as a bar graph labeled "Exercise", and one indicator of how many calories worth of food the member 1501 has consumed for the day, expressed as a bar graph labeled "Diet". In this particular case, the element 1710 does not include a summary presentation 1703 or a detail button 1704.

A third element 1710 includes a summary of the member's rewards points. Its title 1701 can include the word "Rewards". Its sub-title 1702 can be blank. Its summary presentation 1703 can include a numerical value of the number of rewards "points" and "miles" the member 1501 has earned, and a bar graph showing an approximate magnitude, optionally relative to a number of rewards points the member 1501 could have earned by this time. In this particular case, the member 1501 has earned several rewards points, and the bar graph shows that this is about 40% of the number of rewards points the member 1501 could have earned by this time. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 1511 to show the member's actual rewards points values (not shown).

As described herein, rewards "points" are earned by the member 1501 by conducting health-related activities that can be clearly confirmed, such as attending a meeting with a health coach, or having a weight measure confirmed at an office visit or physical therapy session. As described herein, the member 1501 earns rewards "miles" by conducting health-related activities that can only be confirmed with room for error, such as a self-report that the member 1501 ran for 30 minutes today, or filled a prescription for prescribed medication. In the latter case, filling the prescription and pickup from the pharmacy can be clearly confirmed, but whether the member 1501 actually took the medication cannot be clearly confirmed. Rewards "points" are more valuable than rewards "miles" when the member 1501 wishes to redeem them for actual rewards. In some implementations, points may be associated with both verifiable and non- verifiable actions. Verifiable actions may be associated with relatively more points compared to those that are non-verifiable.

A fourth element 1710 includes a summary of the member's pending alerts. Its title 1701 can include the word "Alerts". Its sub-title 1702 can include either the phrase "You have alerts" or the phrase "You do not have alerts", or some variant thereof. Its summary presentation 1703 can include a box with a number of alerts shown therein; in alternative embodiments, the summary presentation 1703 for alerts can be colored to show alerts more blatantly than just a number. For example, the summary presentation 1703 can be green for no alerts, yellow for one alert, and red for two or more alerts, or any alerts that are marked urgent In this particular case, the summary presentation 1703 for alerts includes the number "2", indicating two pending alerts. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 1511 to show the actual text of the member's alerts (not shown).

A fifth element 1710 includes a summary of the member's pending advice messages. Its title 1701 can include the word "Advice". Its sub-title 1702 can include either the phrase "You have advice" or the phrase "You do not have advice", or some variant thereof. Its summary presentation 1703 can include a box with a number of advice messages shown therein; in alternative embodiments, the summary presentation 1703 for advice can be colored to show advice more blatantly than just a number. For example, the summary presentation 1703 can be green for no advice messages, yellow for one advice message, and red for two or more advice messages, or any advice messages that are marked urgent. In this particular case, the summary presentation 1703 for advice includes the number " 1", indicating one pending advice message. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 1511 to show the actual text of the member's advice messages (not shown).

As described herein, in one embodiment, the member 1501 can receive advice/alerts from the payer workstation or the provider workstation 1530. For example, the member 1501 can receive advice/alerts by having them displayed at the user interface 1512, by forwarding them to the member's email address, by directing them (possibly wirelessly) to a nearby printer, by playing a synthesized voice reading of the advice/alerts, or otherwise. The system 1500 notes which advice/alerts the member 1501 receives, and by what media, with the effect that the system 1500 can later determine how effective any one advice/alert is in prompting action by the user, after accounting for frequency, importance, and urgency. In one embodiment, advice/alerts can be tailored to the particular member 1501 and the medical issues being engaged by the particular member 1501. For example, the system 1500 can determine, in response to the member's biometric information, as well as age and gender, office visits, prescriptions, and otherwise, whether the member 1501 is at risk for a heart problem.

Advice can include information of interest to the particular member 1501, not based on any particular event, but tailored to the particular member 1501, such as in response to which advice they have read in more detail than just the headline. For example, advice can include heart-healthy recipes, suggestions for exercise activities that might be of interest to the member, suggestions on how to spend less on medications, and otherwise. If the particular member 1501 does not read recipes, the system 1500 can send other types of advice instead, such as suggestions on how to eat healthy meals while traveling.

Alerts can include information that is time sensitive, such as a reminder to schedule a follow-up to the member's most recent office visit. In such cases, the alert can include a user interface element, such as a pop-up or a screen, aiding the member 1501 in scheduling the office visit from the user workstation 1510 in response to the alert. Depending on their importance, alerts can be tailored to demand the member's attention (without getting ignored for being obnoxious). For example, alerts can also include a reminder to attend a scheduled office visit, a reminder to fill a particular prescription, and a reminder to take that prescription when scheduled. Alerts can also indicate how many "points" or "miles" the member 1501 earns by taking each alerted action.

A sixth element 1710 includes a summary of the member's engagement with care programs such as long-term programs that the member engages in over time with the goal of improving health or health risk. Its title 1701 can include the word "Programs". Its sub-title 1702 can include the word "Engagement", or some variant thereof. Its summary presentation 1703 can include an indicator of how many or which care programs the member 1501 is actively engaged with. In this particular case, the indicator shows "0%", that 'is, that the member 1501 is not engaged with any care programs. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 1511 to show the actual programs a member may be engaged in (not shown).

As described herein, in one embodiment, the member 1501 can elect one or more care health programs offered by the system 1500 and in particular to the member 1501. There might be more than one such program available for the member 1501, and it is the member 1501 who decides which program (if any) they engage in. For example, if the system 1500 has concluded that the member 1501 is at risk both for a heart problem and for developing diabetes, in response to their BMI value, their blood sugar measurement, and their blood pressure measurement, the system 1500 can (in response to one or more medical rules) suggest that the member 1501 engage in care programs for diabetes and for hypertension. The member 1501 can choose to engage in one or more such programs, and the system 1500 can determine a measure of enthusiasm for each program that the member 1501 exhibits by their actions.

FIG. 17B illustrates the user interface 1512, including the member's biometrics information, as shown at the user workstation 1510 on its screen 151 1 illustrated in FIG. 17A.

Similar to the elements 1710 in FIG. 17A, each element 1720 in FIG. 17B includes a summary of one selected biometrics measure, and can include a similar title 1701, sub-title 1702, summary presentation 1703, and detail button 1704. In each such element 1720 in FIG. 17B, its title 1701 can include the name of the biometrics measure. In the first particular case, its title 1701 can include the name "BMI". Its sub-title 1702 can include the phrase "Above Goal Range". Its summary presentation 1703 can include an indicator of what value the member's BMI has. In this particular case, the summary presentation 1703 includes the value "29", or a BMI value that is somewhat overweight in alternative embodiments, the summary presentation 1703 for biometrics can include a slider or some other indicator regarding those biometrics values for the member 1501. Its detail button 1704 includes a rightward-pointing chevron, which when triggered changes the screen 151 1 to show further detail about the member's biometrics value, in this case, the member's BMI.

In this particular case, the selected biometrics measures for the member 1501 are "BMI", which is above goal range with a (dimensionless) value of 29, "Blood Sugar", which is above goal range with a value of 125 mg/dL, "HDL's" (a cholesterol measure), which is in goal range with a value of 30 mg/dL, "LDL's" (another cholesterol measure), which is in goal range with a value of 160 mg/dL, "Triglycerides", which is in goal range with a value of 150 mg/dL, and "Blood Pressure", which is above goal range with a (systolic) value of 210 mmHg.

Biometrics Cost Estimate. FIGS. 18A-18B illustrate user interfaces according to exemplary embodiments of the present disclosure.

A biometrics cost estimate model can include a first element 1801 of the user interface 1512 of the member workstation 1510, shown in the left-hand panel of FIG. 18A. In that first element, a first biometrics cost estimate 1810 is presented, along with a first set of biometrics elements 1820.

The first biometrics cost estimate 1810 can include a current estimate 181 1, a modeled estimate 1812, and a difference 1813 (the latter calculated as current estimate 181 1 minus modeled estimate 1812). The current estimate 1811 is calculated from actuarial tables or lifetime cost curves in response to the current values of the member's information, e.g., biometric measures , conditions, age gender and/or diseases, if available or present. The modeled estimate 1812 is also calculated from actuarial tables or curves, in response to a set of slider values of the member's biometric measures that may be selected by a user. This has the effect of showing the member 1501 how much healthcare cost saving can be achieved over the member's lifetime or another time period by taking action to alter the current values of the member's biometric measures to reach the slider values of the member's biometric measures.

In the left-hand panel of FIG. 18A, the first set of biometrics elements 1820 can include selected ones of the member's biometric measures. Each such element 1820 includes a title 1821, an actual value 1822, a slider bar 1823 showing a scaled relative value with a slider 1824 positioned thereon, and a first model value 1825A. When the first model value 1825 A equals the actual value 1822, the slider 1824 is circled to so indicate.

In this particular case, the member 1501 has a BMI of 29, a Blood Sugar measure of 125 mg/dL, an HDL's measure of 30 mg/dL, and an LDL's measure of 160 mg/dL. The current estimate 1811 is $1,300,000 in lifetime predicted healthcare costs for the member 1501, in response to these current values. The slider 1824 has the first slider value 1825A equal to the actual value 1822 in all cases, so the modeled estimate 1812 is the same as the current estimate 1811, that is, also $1,300,000 in lifetime predicted healthcare costs for the member 1501, in response to these modeled values. The calculated difference 1813 is zero.

The biometrics cost estimate model can also include a second element 1802 of the user interface 1512 of the member workstation 1510, shown in the right-hand panel of FIG. 18A. In that second element, a second biometrics cost estimate 1830 is presented, along with a second set of biometrics elements 1840.

The second biometrics cost estimate 1830 can include a current estimate 1831, a modeled estimate 1832, and a difference 1833 (the latter calculated as current estimate 1831 minus modeled estimate 1832). The current estimate 1831 is calculated from actuarial tables in response to the current values of the member's biometric measures, and so should be the same as the current estimate 1811 in the first biometrics cost estimate 1810. The modeled estimate 1832 is also calculated from actuarial tables, but in response to the goal values of the member's biometric measures. This has the effect of showing the member 1501 how much healthcare cost saving can be achieved by taking action to alter the current values of the member's biometric measures to reach the goal values of the member's biometric measures.

In the right-hand panel of FIG. 18A, the second set of biometrics elements 1840 can include selected ones of the member's biometric measures. Each such element 1840 includes a title 1841, an actual value 1842, a slider bar 1843 showing a scaled relative value with a slider 1844 positioned thereon, and a second model value 1845A.

In this particular case, the member 1501 has elected a goal BMI of 25, a goal Blood Sugar measure of 100 mg/dL, a goal HDL's measure of 40 mg/dL, and a goal LDL's measure of 5 150 mg/dL. The current estimate 181 1 is $1,300,000 in lifetime predicted healthcare costs for the member 1501, in response to the member's current values (as shown in the left-hand panel). The slider 1844 has the second model value 1845A equal to the goal value in all cases, so the modeled estimate 1812 is what would be estimated if the member 1501 reached those goal values. In this particular case, the modeled estimate is $300,000, which is $1,000,000 less than0 the current estimate 1811, in response to these model values. The calculated difference 1813 is therefore $ 1,000,000; the member 1501 can save $1,000,000 in healthcare cost by taking action to alter the current values of the member's biometric measures to reach the goal values of the member's biometric measures. The payer 1502 hopes this large dollar amount is sufficient to motivate the member 1501.

5 FIG. 18B (collectively including a left-hand panel and a right-hand panel) shows a user interface according to exemplary embodiments of the present disclosure.

Similar to FIG. 17B, FIG. 18B, left-hand panel, shows the current biometrics measures for the member 1501 with biometrics titles 1701 and summary presentations 1703, and additionally, the first biometrics cost estimate 1810.

0 FIG. 18B, left-hand panel, also shows a trend button 1850, which transfers the user interface 1512 to a state in which it shows trend estimates 1851 from each calculated past current estimate 181 1 from FIG. 18A, once per month. This has the effect that the member 1501 can see in graphical form the decrease (or increase) in estimated lifetime healthcare cost as the member 1501 takes action to alter their biometrics measures.

5 FIG. 18B, right-hand panel, shows the trend information in graphical form, as described above. The user interface 1512 can include a screen 1511, showing a separate current estimate 1811 from FIG. 18A, computed once per month, that is, the trend estimates 1851, presented in a bar graph 1852. Below the bar graph 1852, the user interface 1512 can include a beginning estimate 1853, that is, the earliest of the trend estimates 1851, shown numerically and derived0 from cost curves and based on the earliest member information available, and a current estimate 1811, that is, the most recent of the trend estimates 1851, also shown numerically, and their difference 1854. This has the effect that the member 1501 can see in graphical form the decrease (or increase) in estimated lifetime healthcare cost as the member 1501 takes action to alter their biometrics measures. In this particular case, the member's beginning estimate 1853 is $2,300,000, their current estimate 1811 is $1,900,000, and the difference 1854 is $400,000, which corresponds to the November trend estimate 1851 in the bar graph 1852. As shown in FIG. 18B, right-hand panel, the member's trend estimates may be compared to a peer cost average baseline 1855 and may enable the member to understand how their projected healthcare costs compare others similarly situated.

According to certain embodiments, the completion of actions in the member's rewards program may result in a change to a current estimate 1811. For example, the completion of such actions may or may not affect the member's current biometrics, but may correlate to a reduction in the member's current estimate 181 1. In a further example, the completion of such actions may positively affect the member's health-related information and may be indicative an improvement of the member's heath or health risk, which may be correlated to actuarial tables or curves.

Although the cost estimates and cost savings estimates provided herein are lifetime estimates, lifetime estimates are exemplary, and embodiments of the present disclosure may provide estimates for other timeframes such as multi-year, annual, bi-annual, monthly and weekly timeframes. Such estimates may be based on the member's information as described above and may be determined in relation to actuarial tables or curves.

Example Rewards Programs. FIGS. 19A and 19B (each collectively including a left-hand panel and a right-hand panel) show a user interface 1512 for displaying a member's alerts and tracking a member's rewards according to exemplary embodiments of the present disclosure. The alerts and corresponding rewards may be displayed for open alerts. The user interface 1512 may be displayed when a user logs in to their account and the user has an active or open alert for a measure to be completed under their rewards program. Where the user does not have active or open alerts, the user may be directed to the user interface of FIG. 17A instead.

FIG. 19A, left-hand panel, shows a user interface 1512 scenario for alerts and rewards for a diabetic member. Where the member's information indicates the member is experiencing diabetes and hypertension, for example, the alerts and rewards programs for addressing each of diabetes and hypertension may be provided on a common interface. Further, where the member's information indicates the member is interested in engaging in a health and wellness program, e.g., such as jogging, and is experiencing one or more health conditions, the alerts and rewards diagnosis-related programs as well as a health and wellness program may be presented on a common interface. The alerts and rewards can include a pathway 1901, on which there can be a sequence of actions 1902 to be performed by the member 1501. A "points" value or "miles" value can be associated with each action 1902. This has the effect that the member 1501 can see the planned sequence of actions, their order, an approximate timing (perceived distance on the path can act as a proxy for time delay), and a reward value for each action. For example, in the panel, the member 1501 can see that entering a diabetes program, as a verifiable step, has a reward value of 1,000 points, going on a medium jog, as a non-verifiable step, has a reward value of 75 miles, and taking a glucose test, as either a verifiable or a non-verifiable step depending on whether the biometrics device is authenticated, has a reward value of 25 points when the test is verifiable and has a rewards value of miles when the test is not verifiable.

As described herein, "points" are earned for actions that the system 1500 can clearly verify (such as those conducted with an external party, such as a provider 1503), while "miles" are earned for actions that the system 1500 cannot clearly verify (such as those that are self- reported, or for which the external party can only partly verify the action). For example, joining a diabetes program has reward points instead of reward miles, because the action includes attending meetings of the program participants, and the provider 1503 can verify attendance. In contrast, a medium jog is self-reported by the member 1501; the system 1500 cannot ask any provider 1503 for verification, unless the member 1501 were to jog at the provider's location (such as if the provider 1503 were a physical therapist at a location with a jogging track).

As described herein, reward points are "worth" more than reward miles, at least in the sense that reward points are generally associated with more clearly valuable, and more valuable, rewards, such as monetary rebates and free consumer goods. Reward miles are generally only associated with less clearly valuable, and less valuable, rewards, such as coupons for lower prices, and "perks" at work, such as a good parking spot. Of course, each member 1501 might value each reward differently. This has the effect that some rewards available in exchange for reward miles might be more motivating to one or more members 1501 than other rewards available in exchange for reward points. This does not pose a problem, as the system 1500 is intended to offer disparate rewards in the hope that one or more of them would be valuable enough to attract members 1501 to reduce their healthcare costs. Although the description addresses rewards in the context of points and miles, this context is exemplary and various types of rewards may be provided such as monetary accumulations (e.g., dollars), points accumulations and/or miles accumulations, where the different types of rewards have different relative values.

Taking a glucose test may, for example, only earn reward miles if the test were self- reported and not verifiable using an authenticated biometrics device. The figure shows, at the left-hand panel, that the user workstation 1510 can have a peripheral device 1514 coupled thereto. The peripheral device 1514 can be an authenticated device and may measure glucose level and report its measurement to the system 1500, with the effect that the peripheral device 1514 can verify that the member 1501 conducted a glucose test. Thus, in this figure, rewards are valued as points.

FIG. 19A, right-hand panel, shows a user interface 1512 for alerts and rewards for a member with a back injury. This second alerts and rewards scenario demonstrates use of a pathway 1901, on which there can be a sequence of actions 1902 to be performed by the member 1501, with a "points" value or "miles" value that can be associated with each action 1902. In the figure, the pathway 1901 is shown to be straight, as if a roadmap were laid out in front of the member 1501 and the pathway 1901 was the best path to a particular destination. In the context of the invention, there is no particular requirement for any such limitation. In alternative embodiments, the pathway 1901 may instead meander to and fro, optionally to present more actions on the pathway 1901, or might even form a closed loop, optionally to present some actions as being prescribed for endless repetition.

The actions associated with the back injury management program can differ from the actions associated with the diabetes management program. This has the effect that members 1501 with differing medical conditions can be alerted to take actions and offered rewards that can be matched to their particular medical conditions. This can be performed with the member's biometric measures, with the member's age and gender, with the member's history of reported ailments, and with the member's history of compliance with medical personnel's requests.

In one embodiment, the system receives self-reported member planned activities as input from the member to create at least one of the alerts and rewards instances. For example, the member may enter a health-related goal into the user interface of FIG. 18A. In this example, the member may set a goal for one or more of the member's biometrics such as BMI, blood sugar, HDLs, LDLs, triglycerides, blood pressure, resting heart rate and so on. In a further example, the member may set a goal for engaging in activities such as diet, exercise, taking and/or refilling prescriptions regularly. The member-entered goals may be used to generate alerts and rewards or any rewards or goal-oriented program of the present disclosure. The member may thus engage in the goal-oriented program having been customized according to the member's own goals.

In one embodiment, the system 1500 can assign a measure of engagement to the degree to which the member 1501 conducts the actions designated by the long-term rewards program. For example, a particular member 1501 that only rarely performs verifiable actions, and only infrequently self-reports individual un-verified actions, might be determined by the system 1500 to be relatively unmotivated to perform that particular long-term rewards program. This has the effect that the system 1500 determines that the member 1501 has a relatively low degree of engagement with that program. In response to a relatively low degree of engagement, the system 1500 might assign lesser rewards to less-engaged members 1501, effectively requiring fuller participation to earn greater rewards. In contrast, the system 1500 might assign greater rewards to less-engaged members 1501, on the grounds that greater rewards are required to coax those members 1501 into conducting the desired actions. Whether lesser rewards or greater rewards are superior is a question that can be left to the database/analysis system 1540, which can aggregate the many examples, correct for demographic and other unrelated factors that might affect the statistics, and pronounce upon which is more likely to yield results. Furthermore, in some implementations, the members engagement in the system bay be under the rewards program, cost savings program, or both.

In one embodiment, the system 1500 can display an amount of earned reward points assign a measure of engagement to the degree to which the member 1501 conducts the actions designated by the long-term rewards program. For example, a particular member 1501 that only rarely performs verifiable actions, and only infrequently self-reports individual un-verified actions, might be determined by the system 1500 to be relatively unmotivated to perform that particular long-term rewards program. This has the effect that the system 1500 determines that the member 1501 has a relatively low degree of engagement with that program.

FIG. 19B, left-hand panel, shows a user interface 1512 for tracking a member's alerts and rewards according to exemplary embodiments of the present disclosure. In this embodiment, the alerts and rewards may be associated with a member's selected goals and with alerting a member to actions that result in higher healthcare costs for the member. As with FIG. 19B, the rewards program can include a pathway 1901, on which there can be a sequence of actions 1902 to be performed by the member 1501. Although the rewards program may be associated with miles and points as described herein, the pathway 1901 may include alerts associated with high cost drivers. In this example, the pathway includes an alert for visiting an out-of-network doctor 1903 and an emergency room visit 1904 engaged in by the member. Each of these member activities, while potentially beneficial to the member to address the member's health and thus associated with miles and/or points, may be associated with higher costs including out-of-pocket and deductibles.

FIG. 19B, right-hand panel, shows a user interface 1512 for tracking a member's trending financial impact for electing high cost drivers compared to average peer costs of other members within the network that may elect alternatives to the high cost drivers. The member's past healthcare and lifestyle activities may be used to calculate the member's projected healthcare costs 1904. In FIG. 19B, the annual savings 1905 of $500 may be realized by the member by electing lower cost alternatives to out-of-network doctor visits and emergency room visits, such as scheduled doctor visits within the member's network or an urgent care visit as opposed to an emergency room visit. Based on the member's subsequent healthcare activities, the user interface may display lifetime savings 1906. In this example, the member's engagement in high cost 5 drivers results in a lifetime savings of $0.

According to certain implementations, the rewards program may utilize the member's estimated cost savings as a driver in determining rewards values. Where a member is presented with actions within the rewards program that, when completed, results in cost savings or projected cost savings, the value of the reward may be relatively higher compared to completion

10 of actions that are not associated with cost savings or are associated with a lesser cost savings.

For example, receipt of a back assessment may result in a higher projected cost savings compared to cost savings associated with receiving physical therapy alone, and thus completion of a back assessment may result in an award of a relatively higher points value, e.g., 750 points in FIG. 19A, right-hand panel, in relation to a points value for completing physical therapy, e.g.,

15 100 points in FIG. 19 A, right-hand panel. In some cases, a rewards value may be determined based on how cost-effectively the member completed an action within the rewards program. For a member completing an annual checkup, the rewards value may differ based on whether the member completed a checkup from an in-network or an out-of-network provider. An annual checkup from an out-of-network provider may have a rewards value that is relatively less, e.g.,

20 100 miles in FIG. 19B, left-hand panel, than a rewards value for completing the same service from an in-network provider, which may have a points value that generally is of more worth compared to miles, or may have a relatively higher miles value. Thus, the implementations may encourage the member to engage in both healthy and cost-effective actions in the rewards program.

25 According to further implementations, the rewards program may utilize a member's cost savings as the primary driver in encouraging the member to engage in healthy and cost-effective actions, and a rewards system with points and/or miles may not be included. In one exemplary embodiment, the user interface 1512 may display a rewards program pathway with actions for the member to view, but points/miles values may not be displayed. In a further exemplary

30 embodiment, the member's cost savings associated with a pending or completed action may be displayed. In yet a further exemplary embodiment, the member may be presented with information showing the trending financial impact as illustrated in FIGS. 18B and 19B as an alternative to an accumulation of points and/or miles. In still a further exemplary embodiment, accumulated cost savings for completing actions in the member's rewards program may result in awarding the member with a thing of value.

Access to the systems and methods disclosed herein may be sold and/or provided as a product to healthcare Health Information Exchanges (HIE's), Regional Health Information Organizations (RHIO's), Accountable Care Organizations (ACO's), providers, payers, employers, states, and other healthcare organizations, for example.

The disclosed systems, methods, processes and machines have a particular concrete or tangible form. For example, the aspect of a health information processing system has a concrete or tangible form including a secure health information storage machine and a healthcare analytics processor in communication with a plurality of health data sources. The disclosed health information storage machines and healthcare analytics processors are significant concrete and tangible elements. The aspect of a health information analytics process is implemented on and thus tied to the healthcare analytics processor coupled to a secure health data storage machine, which are significant concrete and tangible elements.

Aspects of the present disclosure contain elements and/or combination of elements that automatically transform health information from a variety of sources and in a variety of different formats into processed health data in one or more data storage systems. The processed data is configured for accessibility by one or more computer processors to dynamically and substantially instantaneously display selected healthcare measures based on the data. The dynamic display includes a dashboard that allows various healthcare measures to be selected for display. In response to the selection, the measures may be displayed in one of a number of particular formats that provide a preferred visualization of the selected measure.

Aspects of the present disclosure improve the particular technical environment of health information technology by allowing real-time visualization of health information from a variety of sources in which disparate formatting among the sources are accommodated in a pre- processed compilation of stored health data. The pre-processing renders the data accessible in real time for display of selected measures on a dashboard. A data model is configured to efficiently display useful combinations of health measures for individual patients and/or populations of patients. Aspects of the present disclosure improve the operation of certain health information dashboards, machines, networks and/or systems by generating a processed form of health information including real-time representations of patient measures and longitudinal visualizations of patient histories, thereby improving the quality of available health information, improving patient care, and reducing healthcare costs. Certain aspects of the present disclosure are confined to the field of health information technology, in which they provide substantial improvement and technological innovation. In various embodiments, software may be stored in a computer program product and loaded into a special purpose computer system using removable storage drive, hard disk drive or communications interface. Aspects of the disclosed process may be implemented in control logic or computer program instructions, which when executed causes the special purpose computer system to perform the functions of various embodiments as described herein. Implementation of system including special purpose machines to perform the functions described herein will be apparent to persons skilled in the relevant art(s).

The systems, machines and processes described herein may be used in association with web services, utility computing, pervasive and individualized computing, security and identity systems and methods, autonomic computing, cloud computing, commodity computing, mobility and wireless systems and methods, open source, biometrics, grid computing and/or mesh computing.

Databases discussed herein are generally implemented on special purpose machines, systems and/or networks to ensure privacy of confidential health information and data security is preserved in accordance with industry standards and government regulations. The databases may include relational, hierarchical, graphical, or object-oriented structure and/or other database configurations. Moreover, the databases may be organized in various manners, for example, as data tables or lookup tables. In addition to the inventive techniques for combining health information with social media information disclosed herein, association of certain data may be accomplished through various data association technique such as those known or practiced in the art. One skilled in the art will also appreciate that databases, systems, devices, servers or other components of the disclosed systems or machines may consist of any combination thereof at a single location or at multiple locations, wherein each database, system or machine may include of suitable security features, such as firewalls, access codes, encryption, decryption, compression, decompression, and/or the like. The special purpose systems, networks and/or computers discussed herein may provide a suitable website or other Internet-based graphical user interface which is accessible by users.

Functional blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and program instruction means for performing the specified functions. It should be understood that each functional block of the block diagrams and flowchart illustrations, and combinations of functional blocks in the block diagrams and flowchart illustrations, can be implemented by either special purpose hardware-based computer systems which perform the specified functions or steps, or suitable combinations of special purpose hardware and computer instructions. It should be further appreciated that the multiple steps as illustrated and described may be combined into single webpages and/or windows but have been expanded for the sake of simplicity. In other cases, steps illustrated and described as single process steps may be separated into multiple webpages and/or windows but have been combined for simplicity.

Although illustrative embodiments of the present disclosure have been described herein with reference to the accompanying drawings, it is to be understood that the present disclosure is not limited to those precise embodiments, and that various other changes and modifications may be made by one skilled in the art without departing from the scope or spirit of the disclosure.

Additional features and advantages of the present disclosure are described below. It should be appreciated by those skilled in the art that this disclosure may be readily utilized as a basis for modifying or designing other structures, systems and processes for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that such equivalent implementations do not depart from the teachings of the disclosure as set forth in the appended claims. The novel features, which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages, will be better understood from the present description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure.