FIELD OF THE INVENTION

[001] The present disclosure is directed, in general, to data processing systems and methods and, more particularly, to methods and systems for determining a clinical health risk score and for forecasting the potential risk of diagnoses specific treatment pathways, or the site of service for surgical procedure.

BACKGROUND TO THE INVENTION

[002] In the last several decades, g l o ba l healthcare spending increased dramatically. Consequently, restraining the growth of healthcare spending is seen as an increased priority. Various plans have been put forward to slow the growth of healthcarespending.

[003] Some plans support greater emphasis on prevention, wellness, and public health activities to reduce the overall healthcare cost. Other plans include proper risk assessment before admission to attempt to reduce the overall risk and reduce potentialsecondary problems and procedures.

SUMMARY OF THE INVENTION

[004] Various disclosed embodiments include methods and systems for determining a plurality of pacients' c li n ica l health risk score and for forecasting risk prior and during procedure or treatment.

[005] The method includes receiving a plurality of patients' clinical data from encounters over a predetermined time period and mapping personalized patient risk scoring with each individual's clinical profile parameters.

[006] The method includes determining, for each patient, the personalized health risk scores for each respective procedure or treatment by utilize configurable key risk parameters as inputand linking the key risk parameters to weighted scoring for a specific risk score instrument.

[007] Various parameters can feed various risk score instruments in a configurableway, with different weightings per instrument.

[008] Each healthcare facility can develop their own integrated risk score instrument based on that healthcare facility's individualized patient population and health risk profiles.

[009] The method includes determining, for at least one patient, weighted health risk scores which is continuously validated against the outcomes with a continuous feedback loop that enables continuous improvement and refinement.

[010] The method includes the steps of allowing a patient to complete an online questionnaire, processing the information received by means of clinical algorithms provided on a processor and mapping a risk score based on weighted average.

[011] The method includes comparing the outcomes of each procedure or treatment or treatment to the health risk score prior to the procedure or treatment by means of an intelligent evidence-based scoring algorithm, configuring the results to ensure continuous improvement.

[012] The method yet further includes a risk assessment by a physician during face to face interaction, the physician amending the patient clinical parameters, allowing the system to re-calculate clinical algorithm outcome in real-time to allow interactive informed decision making.

[013] After the re-evaluation, the system, by means of the clinical algorithm calculates the patient individual clinical risk score and the most appropriate clinical treatment.

[014] The method includes multiple levels of completions before any risk score canbe configured.

[015] The weighted health risk score is determined from the average health risk score of the healthcare practitioner selected clinical scoring instrument, which will vary based on each healthcare facility's treatment options and clinical priorities. The method includes storing the health risk scores, the weighted health risk scores and other calculated parameters in a memory for future access.

[016] According to disclosed embodiments, a data processing system for determining a plurality of patients' health risk score and forecasting procedure or treatment risk includes at least one processor and a memory connected to the processor. The data processing system isconfigured to receive a plurality of patients' clinical data from encounters over a predetermined time period. The data processing system is configured to map the clinicaldata of the plurality of patients to respective procedural risks.

[017] The data processing system is configured to determine, for the plurality of patients, the health risk scores for the respective procedure oorr treatment by applying i n te l l i g e n t evi d e n c e- ba sed scoring algorithms to the clinical data. The data processing system is configured to determine, for the plurality of patients, average health risk scores for the respective procedure or treatment.

[018] The data processing system is configured to determine, for the plurality of patients, weighted health risk scores, wherein the weighted risk score is determined from the average health risk score of healthcare practitioner selected clinical scoring instrument, which will vary based on each healthcare facility's treatment options and clinical priorities

[019] According ttoo disclosed embodiments, , a non-transitory computer-readable medium is encoded with computer- executable instructions for determining a plurality of patients' health risk scores and for forecasting procedure or treatment risk.

[020] The computer-executable instructions when executed cause at least one data processing system to: receive a plurality of patients' clinical data from encounters over a predetermined time period; mapping the clinical data of the plurality of patients by intelligent evidence-based scoring algorithm; determine, for at least one patient, the health risk score for the respective procedure or treatment to follow by an average weighted health risk scoresof the respective procedure or treatment and in real-time comparing the outcomes of each procedure or treatment to the health risk score prior to the procedure or treatments by means of an intelligent evidence-based scoring algorithm, configuring the results to ensure continues improvement

[021] The weighted health risk score is determined from the average risk score of the healthcare practitioner selected clinical scoring instrument, which will vary based on each healthcare facility's treatment options and clinical priorities

[022] The foregoing has outlined rather broadly the features and technical advantagesof the present disclosure so that those skilled in the art may better understand the detailed description that follows.

[023] Additional features and advantages of the disclosure will be described hereinafter that form the subject of the claims. Those skilled in the art will appreciate that they may readily use the conception and the specific embodiment disclosed as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. Those skilled in the art will also realize that such equivalent constructions do not depart from the spirit and scope of the disclosure in its broadestform.

[024] Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words or phrases used throughout this patent document: the terms "include" and "comprise," as well as derivatives thereof, mean inclusion without limitation; the term “or" is inclusive, meaning and/or; the phrases "associated with" and "associated therewith," as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, orthe like; and the term “controller" means any device, system or part thereof that controls at least one operation, whether such a device is implemented in hardware, firmware, software or some combination of at least two of the same.

[025] It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. Definitions for certain words and phrases are provided throughout this patent document, and those of ordinary skill in the art will understand that such definitions apply in many, if not most, instancesto prior as well as future uses of such defined words and phrases. While some terms may include a wide variety of embodiments, the appended claims may expressly limit these terms to specific embodiments.

BRIEF DESCRIPTION

[026] The invention is now further described by way of example.

Figure 1 is a flow diagram of the real time processing and continuous cycleaccording to the invention;

Figure 2 is a step diagram of the various steps involved according to theinvention; and

Figure 3 a clinical dashboard display according to the invention, DETAILED DESCRIPTION

[027] Figures 1 to 3 discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Those skilled in the art will recognize that the principles of the present disclosure may be implemented in any suitably arranged device or a system. The numerous innovative teachings of the present disclosure will be described with reference to exemplary non- limiting embodiments.

[028] Various disclosed embodiments provide methods and systems for determininga population's health risk score and for forecasting risk associated with a particular procedure or treatment or treatment. These generally include questionnaires. Problems generally associated with questionnaires, are that they are either completed incorrectly, or alternatively are completed with limited information. This makes a proper analysis of therisk associated with a particular patient very difficult.

[029] The current invention allows for anytime anywhere mobile technology which utilizes a real time intelligent algorithm and application (as clinical parameters are selected /changed for an individual patient the clinical risk profile scoring and recommendations change in real time during interactive patient /doctor discussions). This enables real time interactive informed decision making at the time ofpatient consultation [030] The invention relates to personalized patient clinical risk scoring based on individual clinical profile parameters that are used as input and making use of clinical risk score algorithms to determine Personalized patient treatment pathway recommendations.

[031] One embodiment of the invention allows for graphic dashboard views (Figure3) designed to provide answers visually at a glance / intuitive / pre-empting any possible questions that can be asked and not requiring any interpretation or further analysis (actionable insight).

[032] The technology application is configurable by users in real time, allowing for continuous learning and refinement. Another benefit is that the application is roles and permission based allowing each healthcare facility to individualize the system for use.

[033] The clinical risk score capability utilizes key risk parameters as input (directlyfrom patient as on-line questionnaires and/or through real time feeds from various data sources for example Electronic Health Record systems (EHR's) or Electronic Medical Records (EMR's)). These key risk parameters are configurable, can add, change as required and are linked to weighted scoring for a specific risk score instrument (weighted risk scoring can be changed as required per parameter).

[034] Various parameters feed various risk score instruments in a configurable way, with different weightings per instrument allowing a personalized risk score determination for each healthcare facility which can develop their own integrated risk scoreinstrument based on that healthcare facility's individualized patient population risk profile. [035] The invention allows for multiple risk scoring instruments which may be selected to have various risk scoring instruments that focuses on various dimensions with an integrated risk score that can combine various individual risk score ratings (individualized in terms of what is included and weightings).

[036] Each risk score is validated continuously against the outcomes with a continuous feedback loop that enables continuous improvement and refinement.

[037] In healthcare facility, a patient will book an appointment. The booking of the appointment is done telephonically, or alternatively through an online booking application using a computer or handheld device such as a telephone, or in person by walk-in at the healthcare facility. Each patient is sent a questionnaire (push notification) link to be completed. A patient is thus promoted to complete the online questionnaire. In the event that the patient does not have access to any electronic communication, the patient will be allowed to complete the questionnaire at the clinic, hospital or rooms of the doctor. This will typically be achieved through any electronic device such as an iPad or a computer.

[038] The information provided by each patient can be verified by the staff. Thesefirst steps complete the collection of patient data (10).

[039] In the following step a real time assessment by evidence- based clinical algorithms (14) areachieved. The output of the clinical algorithm allows for an informed decision.

[040] A continuous improvement cycle (16) is embedded in the real time processing by comparing i n t e l l i g e n t e v i d e n c e - b a s e d scoring algorithm results to outcomes. Continuous improvement is achieved by intelligent learning (18). Continuous learning is achieved by comparing data such as scores, decisions, surgeons' input and capabilities, procedure oorr treatments and patient outcomes and demographic details.

[041] The information learned combined with the questionnaires and weightings allows the results to be configured to achieve real time and configurability.

[042] According to disclosed embodiments, the personal risk score indicates the riskof a specific procedure or treatment taking into consideration for example, medical history, lifestyle risks and chronic disease such as, for example, diabetes, coronary heart disease, asthma, CORD, osteoporosis, etc.

[043] The personal risk score is used to determine the health risk based on information from a patient's health record such as, for example, clinical data. The clinical data may be gathered during a patient's visit to aa healthcare provider, alternatively through a questionnaire prior to procedure or treatment and admission. The clinical data may also beobtainedwhile the patient is hospitalized, and such information may be obtained from, for example, an Electronic Medical Record (EMR) system.

[044] According to disclosed embodiments, the personal health risk analyzer enables superior preventive care, reduce acute care admissions and reduces Per-Member Per- Month (PMPM) cost. According to disclosed embodiments, the method identifies patient risk using EMR and/or EHR data and performs risk stratification of patients by lifestyle risks, and medical history like chronic conditions ssuucchh aass,, for example, diabetes, coronary heart disease, asthma, andosteoporosis. In one aspect, the method predicts risk of procedure or treatment as well as hospitalization and also measures quality of primary care provided to acute or chronic care of patients.

[045] According to some disclosed embodiments, the method includes a visual dash board to visualize color codes based on severity of risk.

[046] The mmeetthhoodd iiss aa provider-centric, clinical-driven care management tool. It promotes superior care management through best healthcare facilities and comparative effectiveness for risk associated with various conditions such as chronic conditions.

[047] Health care providers use health risk scores to identify high risk patients by, for example, chronic conditions based on clinical data. Healthcare providers may classify patients into risk pools and may develop optimal procedure or treatments and care- management programs.

[048] The current iinnvveennttiioonn allows for the improvement and management of risk byvarious roll players. The health risk score method provides self-funded employers and healthcare insurers increased visibility to the performance of the providers and managed care programs. Also, self-funded employers, and healthcare insurers may measure the effectiveness and return of investment (ROI) of the procedure or treatment and wellness, disease management or benefits programs.

[049] Similarly care coordinators may utilize the method and the health risk score to identify successful and appropriate care management and well-being programs and the return on investment (ROI). It may yet further be utilised to identify providers that aresuccessful in providing Quality-of-Care associated with a particular procedure or treatment.

[050] Figure. 1 depicts a flow diagram of data processing system (10) in which an embodiment can be implemented, for example as a system particularly configured by software or otherwise to perform the processes as described herein, and in particular aseach one of a plurality of interconnected and communicating systems as described herein.

[051] The data processing system typically includes a processor which is in communication with a local system bus. The local system bus may be, for example, a peripheral component interconnect (PCI) architecture bus. Also connected to local system are main memory and a graphics adapter. The graphics adapter is connected to display, capable to display a dashboard according to Figure 3.

[052] Other peripherals, such as local area network (LAN)/Wide Area Network/Wireless (e.g. WiFi) adapter may also be connected to local system bus. Expansion bus interface connects local system bus to input/output (I/O) bus. I/O bus is connected to keyboard/mouse adapter, disk controller, and I/O adapter. Disk controller can be connected to storage, which can be any suitable machine usable ormachine readable storage medium, including but not limited to nonvolatile, hard-coded type mediums such as read only memories (ROMs) or erasable, electrically programmable read only memories (EEPROMs), magnetic tape storage, and user- recordable type mediums such as floppy disks. hard disk drives and compact disk readonly memories (CD-ROMs) ordigital versatile disks (DVDs), Solid state drives (SSD's) , cbud storage and other known optical, electrical, or magnetic storage devices.

[053] Also connected to I/O bus is an audio adapter, to which speakers (not shown) may be connected for playing sounds. Keyboard/mouse adapter provides a connection for a pointing device (not shown), such as a mouse, trackball, trackpointer, etc.

[054] Those of ordinary skill in the art will appreciate that the hardware described may vary for particular implementations. For example, other peripheral devices, such as an optical disk drive and the like, also may be used in addition or in place of the hardware depicted. The depicted example is provided for the purpose of explanation only and is not meant to imply architectural limitations with respect to the present disclosure.

[055] Data processing system in accordance with an embodiment of the presentdisclosure includes an operating system employing a graphical user interface. The operating system permits multiple display windows to be presented in the graphical user interface simultaneously, with each display window providing an interface to a different application or to a different instance of the same application. A cursor in the graphical user interface may be manipulated by a user through the pointing device. The position of the cursor may be changed and/or an event, such as clicking a mouse button, generated to actuate a desired response.

[056] One of various commercial operating systems, such as a version of Microsoft Windows™, a product of Microsoft Corporation located in Redmond, Wash, may be employed if suitably modified. The operating system is modified or created in accordance with the present disclosure as described.

[057] LAN/WAN/Wireless adapter can be connected to network (not a part of data processing system), which can be any public or private data processing system network or combination of networks, as known to those of skill in the art, including the Internet. Data processing system can communicate over network with server system, which is also not part of data processing system, but can be implemented, for example, as a separate data processing system. Data processing system may be configured as aworkstation, and a plurality of similar workstations may be linked via a communication network to form a distributed system in accordance with embodiments of the disclosure.

[058] According to disclosed embodiments, a population's clinical data is obtained. The population comprises a plurality of patients. The clinical data may be obtained from electronic health records or may otherwise be obtained manually or by means of questionnaires. It will be appreciated that the clinical data may be gathered from a plurality of encounters over a period of time. An encounter may be a patient visit to a healthcare provider or an encounter may be a hospitalization due to any condition or procedure or treatment.

[059] According to some disclosed embodiments, the following information may beobtained, which information is by no means limiting and includes Patient: date of birth and gender. Then for each encounter (visit) by the patient: Patient demographics (e.g., age, height, weight (BMI)) Vital signs (temperature, heart rate, blood pressure). Labs ordered Lab results (e.g.,blood sugar, HbAlc, LDL-C, HDL-C, triglycerides). Medications prescribed Diagnosis codes (e.g., ICD codes), Procedure or treatment codes (ICD, CRT codes) Hospital admission dates, charges, diagnosis codes and Pharmacy (medications ordered).

[060] According to some disclosed embodiments, the patient data is examined by the data system, which may be implemented as a risk score analyser, to identify one or more procedural risks associated with for example chronic diseases that the patient mayhave been diagnosed with.

[061] For example, diagnostic codes entered in an encounter may indicate chronic diseases. It will be appreciated that ICD (international classification of diseases) is a classification system for assigning specific diseases or conditions to a patient. For example, ICD 10=250.xx covers various types of diabetes. Thus, ICD 10=250.3 indicates that a patient has been diagnosed with a particular type of diabetes.

[062] According to some disclosed embodiments, predetermined disease specific evidence based risk indexes are applied to the clinical data related to calculate a health risk score.

[063] The health risk score is calculated for example into consideration the chronic diseases for each patient. By way of example, an encounter may indicate that a particular patient has been diagnosed with diabetes and CHD. Accordingly, predetermined disease models for both diabetes and CHD are applied to the respective clinical data obtained during the encounter to calculate the health risk score for diabetes a nd CHD associated with a particular procedure or treatment. According to some disclosed embodiments, the health risk score may be represented by a number between 0 and 100 or may be represented by as a percentage (%). A high health risk score may indicate relatively poor health of a patient, and thus a relatively high risk of procedure or treatment and later hospitalization due to, for example, the chronic disease. A low health risk score may indicate relatively good health of a patient and thus a relatively low risk of the procedure or treatmentand hospitalization due to the chronic disease.

[064] According to disclosed embodiments, the diagnosis specific models are clinically validated models developed using multi- year trials on large patient populations. The diagnosis specific models utilize regression equations to determine the relationship between causal factors (independent variables) and outcomes. The regression equations predictthe probability of an outcome based on the clinical data. The regression equations are well known to those skilled in the art and thus will not be described herein.

[065] The health risk score is calculated for example for diabetes, asthma, CORD anddepression only if a patient is diagnosed with that particular chronic disease. For example, if a patient is diagnosed with diabetes, the health risk score is calculated according to the corresponding risk of procedure or treatment related to the specific condition, for diabetes. For patients that are not diagnosed with diabetes, a zero is assigned as the health risk score for diabetes. For all patients, the health risk score is calculated taking into consideration any diseases that could have an effect on the risk of the procedure or treatment.

[066] In the example hereinafter further described a patient with diabetes will be used as the base line.

[067] Clinical data, including for example diabetes, is applied to generate a health risk score associated with a particular procedure or treatment to follow, such as a knee replacement. As discussed before, diabetes risk may be used in weightings applied to the risk score, using regression equations. The resulting health risk score may be classified into one of three categories and may also be color coded. For example, a health risk score above 50 may be classified into a highrisk category and may be color coded red. A health risk score between 33 and 50 may be classified into a medium risk category and may be color coded yellow or orange. A health risk score below 35 may be classified into a low risk category and may be colorcoded green.

[068] The health risk score for a patient diagnosed with diabetes may be calculated using various guidelines. Initially, for both male and female patients with type 2 diabetes, a baseline number of 0.31 is assigned. If the patient is a white female, 0.038 is added to the score. If the female patient has a BMI of 35, 0.021 *5=0.105 is added tothe score. If the female patent is on insulin, 0.034 is added to the score. If the female patient has regular neuropathy, 0.065 is added to the score. If the female patient is diagnosed with congestive heart failure, 0.052 is added to the score. Finally, if the female patient is diagnosed with hypertension, 0.011 is added to the score. Based on the above, the health risk score for the female patient diagnosed with diabetes is 0.615or 61.5%.

[069] The health risk score for a patient diagnosed with, for example coronary heart disease (CHD) may be calculated using other guidelines and steps calculating the health risk score. Consider, for example, a 52 year old non-smoking male with the following conditions: LDL=192; HDL=46; systolic BP=130; and diastolic BP=90. Using various steps, the health risk score is calculated to be 9, which corresponds to 22% derived from a prepopulated table. [070] Similarly the health risk score for a patient diagnosed with asthma may becalculated using different parameters linked to points to be added to the score. For example, if total points for a patient equal 9, the health risk score is 50%.

[071] The calculated health risk scores are normalized using a scale between 1 and 100. Next, an average health risk score over a predetermined time period for each patient for each treatment is calculated to optimally manage a chronic condition and can be used to express either the average weighted risk score, or progression of disease. For example, the average health risk score of a patient during a 12 month period may be calculated. If the patient's last encounter (visit) was on Jul. 6, 2018, then encounters between Jul. 7, 2017 and Jul. 6, 2018 may be considered. Consider, for example, a patient had one encounter in each quarter during a 12 month time period and the health risk scores for diabetes were as follows:, Quarter4, 2011 : 50, Quarter 1 , 2012:

60, Quarter 2, 2012: 50, Quarter 3, 2012: 60. Based on the above, the average health risk score is 55.

[072] The average health risk scores are classified into one of a plurality of risk categories. For example, the average health risk scores may be classified into high risk, moderate risk and low risk categories.

[073] Sub-registries may be created based on additional parameters. For example, the high risk diabetic patients may be divided into the following sub-registries: (1) high risk diabetic patients with BMI>40; [2] high risk diabetic patients with HbAlC>9; and (3) high risk diabetic patients with BMI>40 and HbAlc>9 and Patient Age<40.

[074] Color codes may be assigned to patients and populations based on inclusion in sub-registries. By way of example, the patients may be color-coded as follows: (1) High risk diabetic patients with BMI>40: color code=RED; (2) High risk diabetic patients with HbAlC>9: Color code=RED; (3) High risk diabetic patients with BMI>35 and HbAlc between 8-9: color code=YELLOW or

ORANGE.

[075] The average health risk score in a registry may be calculated and may be referred to as the population health risk score for the registry.

[076] In healthcare facility the system receives a patient’s clinical data. As discussed before, theclinical data may be collected from a plurality of encounters over a predetermined time period. The system maps the procedure or treatment codes in the clinical data to respective chronic diseases or other associated risks. The system determines health risk scores for the respective patient and procedure or treatment taking into consideration for example chronic diseases. As discussed before, the health risk score is calculated by applying diagnoses specific models for the respective chronic diseases to the clinical information.

[077] The system determines average health risk scores of the respective procedure or treatmentfrom the plurality of encounters over the predetermined time period.

[078] According to some disclosed embodiments, a non-transitory computer-readablemedium encoded with computer-executable instructions determines a plurality ofpatients' health risk score and forecasts risk associated with a particular procedure or treatment. Thecomputer-executable instructions when executed cause at least one data processing system to: receive a plurality of patient's clinical data from encounters over a predetermined time period; map procedure or treatment codes in the clinical data of the plurality ofpatients to respective diseases; determine, for the plurality of patients, health risk scores for the respective procedure or treatment and associated chronic diseases by applying models for therespective procedure or treatments and diseases to the clinical information; determine, for the plurality of patients, average health risk scores of the respective procedure or treatment; and determine, for the plurality of patients, weighted health risk scores of the respective procedure or treatment associated with a disease, wherein the weighted health risk score is determined from the average health risk score of the disease, and the frequency of andrisk of hospitalization. It will be appreciated that reference to a disease includes by its definition any other medical condition.

[079] Those skilled in the art will recognize that, for simplicity and clarity, the full structure and operation of all systems suitable for use with the present disclosure is notbeing depicted or described herein. Instead, only so much of a system as is unique to the present disclosure or necessary for an understanding of the present disclosure is depicted and described. The remainder of the construction and operation of the disclosed systems may conform to any of the various current implementations and healthcare facilitys known in the art.

[080] Of course, those of skill in the art will recognize that, unless specifically indicated or required by the sequence of operations, certain steps in the processes described above may be omitted, performed concurrently or sequentially, or performed in a different order. Further, no component, element, or process should be considered essential to any specific claimed embodiment, and each of the components, elements, or processes can be combined in still other embodiments.

[081] It is important to note that while the disclosure includes a description in the context of a fully functional system, those skilled in the art will appreciate that at leastportions of the mechanism of the present disclosure are capable of being distributed inthe form of instructions contained within a machine-usable, computer- usable, or computer-readable medium in any of a variety of forms, and that the present disclosure applies equally regardless of the particular type of instruction or signal bearing medium or storage medium utilized to actually carry out the distribution. Examples of machine usable/readable or computer usable/readable mediums include: nonvolatile, hard-coded type mediums such as read only memories (ROMs) or erasable, electrically programmable read only memories (EEPROMs), and user-recordable type mediums such as floppy disks, hard disk drives and compact disk read only memories (CD-ROMs) or digital versatile disks (DVDs), Solid state disks (SSDs), or Cloud storage.

[082] Although an exemplary embodiment of the present disclosure has been described in detail, those skilled in the art will understand that various changes, substitutions, variations, and improvements disclosed herein may be made withoutdeparting from the spirit and scope of the disclosure in its broadest form.

[083] None of the description in the present application should be read as implying that any particular element, step, or function is an essential element which must be included in the claim scope: the scope of patented subject matter is defined only by theallowed claims.