PRIOR ART:
Insurance, is a form of risk management which primarily used to protect person against the risk of a contingent loss. Insurance is defined as the equitable transfer of the risk of a potential loss, from one entity to another, in exchange for a premium. Insurance Company, in economics, is the company that sells the insurance. Insurance rate is a factor used to determine the amount, called the premium, to be charged for a certain amount of insurance coverage.
Insurance premium is generally based on the type and amount of insurance value one buys and the chance of claim and probable amount of claim while the policy is in effect which is determined by policy holders' health and age and environment. So ideally the insurance company has to know the current health status of the consumer who intends to become a policy holder and the consumer ought to have a choice of schemes dependent on services demand from which choice may be made for desired services at desired premium.
We shall restrict our description to medical insurance for the purpose of this application. Generally medical Insurance Premium insurance schemes is subdivided into categories like individual coverages, for group coverage and credit coverages depending on the risk related to volatility of claims. The factors affecting the premium payable originate from the set of parameters that determines the minimum amount of surplus needed to protect the insurance company to run the Company profitably and also against a worst case scenario of extraordinary claims. Either a uniform percentage or a multi -tier formula based on various parameters may be applied to

calculate the premium. Depending on the situation a number of different sets of pricing assumptions may be used. Assumption sets may vary by mortality class, type of distribution used, or by other characteristics commonly used to distinguish between classes of insured members in that territory by the insurance industry. For example, health assumptions applicable are different for males versus females, a sick person versus a healthy, rich versus poor or to non-smokers versus smokers. Those skilled in the art are well aware of the fact that many other distinctions exist or are possible, atleast including but not limited to severity, co-morbidity, recurrence, age, sex, etc.
Many of these factors are not included by insurance companies and even if included it is not used in the right spirit. However it is to be appreciated that the premium payable assumptions used in pricing are important because they provide an adjustment for the timing differences between when payment goes into and out of the insurance company and the policy holder. Wrong assumptions affect pricing calculations by creating a wrong expectation.
For any successful insurance scheme, an accurate evaluation of the applicant's health characteristics and claim expectancy is necessary. Many often evaluation is based on expertise derived from prior experience, instead of using statistical values.
While policy holders have always paid premium, these premium have been a "fixed" policy premium calculated based on the underlying pricing factors used by

the insurance company, which were known only to insurance company actuaries, and were hidden from view of the policy holders.
Present methods of medical insurance schemes are not easily ascertainable as the projected policy pricing is generally based on many unknown variables that are subject to actual changes, which are not actual statistical derivatives but values obtained from the experience of expertise in fields of insurance companies, and as such, often result in hypothetical policy values instead of real values . The premium values are generally higher to protect the insurance company. These frequently lead to the selection of a less suitable policy than that which may otherwise be available by unwary consumers. Many policies of different types are generally dependent ofn factors like age, income, health profile, lifestyle etc but all factors generally are made applicable to all types of policies. The factors may be similarly weighted for the purpose of premium calculation of all types of policies. However, because some of these factors may be variables that are unique to a particular type of policy, ie a specific type of policy is never taken into consideration. Determining suitability of available offers from Insurance Companies is often a hard problem.. In addition to policy pricing variable factors that may be unique to a given policy, different policies shall also employ different methods of computing policy expenses and benefits. While individual pricing components may even be sometimes disclosed, the computational methods are not at all disclosed, again leading to the potential for evaluating different policies on a basis which may be incorrect but may never be disclosed to the policy holder. Due to the complex nature of insurance policies, the policy holders are frequently ill-equipped to identify differences in the multifarious

computations underlying the hypothetical policy values, again leading to the possibility that this method of policy comparison can lead to an incorrect conclusion. As such the prior art suffers from the usage of wrong parameters and wrong method of Computation.
Today policies are generally purchased by the policy holders based on a projected premium calculated with hypothetical policy values rather than selecting a policy based on, different appropriate variables, which may or may not be disclosed. There is no way to empirically measure the variables on an objective basis in any of the known prior art.
Policies are purchased on the basis a single policy pricing component. Due to standard policy costs, varying in amount which is dependent on the schemes proposed by company, the policy holders may unwittingly purchase a less suitable policy at a higher cost as the low end premium products may actually present an inferior value to the services expected by the policy holder. The most unfortunate are the healthy members amongst the policy holders who are penalized heavily.
Currently, the policy holders have no independent, objective, information-based resource made available and thereby have to depend on marketing relationship generated by the insurance company to buy a policy. The type and number of policies sold today is solely vitally dependent on the marketing skills of the insurance company.

Public will have conflicting views on different schemes proviBed by different companies causing confusion, higher costs, less than optimal knowledge and may select a less than suitable policy.
Still another major drawback of the current art in the insurance is that detailed policy information is guarded as proprietary to the insurance companies. Accordingly without some means or method to aggregate competitive product information with the detail necessary for true comparisons, consumers are left to blindly make purchasing decisions that in no way correlate to the best product for their needs. The consumers simply compare the premium of different companies without understanding how it is calculated and the actual scope of coverage.
In the interest of the insurance company and policy holders, as described it is to be noted that underwriting has an essential role in the premium calculation. Medical underwriting for a medical health insurance policy means each potential policy user is considered individually, so that the overall health of everyone in a particular group determines the final premium. An element of social equity may be used in calculating premiums, so the risk is shared between the healthy and the sick. For very small groups, premiums can go up if there is one person with a history of chronic illness (such as diabetes) or with a catastrophic illness.
The insurance company may also apply different rates of premium to individuals in the same group based on their health status. Further, they may charge different rates based purely on age or gender. Some Insurance Companies increase premiums

above the average, for groups or geographical territories with poor medical histories or with poor environments.
In other known methods, The insurance company is also known to apply a community rating. This is a standard for setting health insurance premiums which eliminates health status from the list of factors that insurance companies consider when they set insurance premiums. Pure community rating means that everybody in a particular geographic area or in a group pays the same premium for the health insurance. This is rarely appreciated for the pricing is not fair to many.
The credit score based premium calculation has also been attempted, which has not been successful commercially. In this method, there is no assumption or weightage given to sick dependent members. In such a case, a "good" credit score gets associated with a policy having high incurred losses.
Keeping in line with existing prior art, some of known criteria needed for deciding whether to insure events or not are many.
Firstly, there shall be a larger number of similar objects so the financial outcome of insuring the group of members may become predictable. In this circumstance the Insurance Company can calculate a "fair" premium. Here the large member is used to spread the cost and losses. The rate and distribution of losses must be precisely predictable in order for Insurance Companies to set premiums accurately. This is done using the law of large numbers, which states that the larger the number of homogeneous factors considered, the more closely the losses reported will equal the

underlying probability of loss. If the coverage is unique, the insured will pay a correspondingly higher premium.
Secondly, the losses shall only be accidental and unintentional. The insurance Company needs to check the claimed amount during a claim. So the insurance company has to realise the list of loss appreciable for the coverage. The basic principle is that insurable risks should cover only accidental losses, and they should offer economically feasible premiums, meaning that chance of loss must not be too high.
Thirdly, the Insurance Company also provides an incentive for insureds with benefits to protect operations and minimize the probability that losses will occur. The Insurance Companies encourage thereby the healthy policyholders to continue the policy year after year, inspite of not having made any claim in the previous year or years.
Insurance Company's business model is typically in the formula given below.
Profit = Income premium + investment income - incurred loss - underwriting expenses.
When insured parties experience a loss for a specified peril or ailment in a medical insurance within the period coverage, the coverage entitles the policyholder to make a 'claim1 against the Insurance Company for the covered amount of loss as specified by the policy. It is generally the reinbursement of medical expenses and also allied compensation benefits due to non-earning disability during the term of the suffering.

Insurance Companies make profit first through underwriting, the process by which Insurance Companies select the risks to insure and decide how much in premiums to charge for accepting those risks and second by investing the premiums they collect from Insurance Companies. The above model is applicable to all types of insurance including medical insurance. More than the investment, the most difficult aspect of the insurance business is the underwriting of policies. Using a wide range of parameters, insurance companies attempt to predict the likelihood that a claim will be made against their policies and price the policy accordingly. Insurance companies use actuarial science to quantify the risks they are willing to assume and the premium they will charge to assume them. Data are analyzed to project the rate of future claims based on a given risk. Actuarial science uses statistics and probability to analyze the risks associated with the range of perils covered, and these scientific principles are used to determine an Insurance Company's overall exposure. Upon termination of a given policy, the amount of premium collected and the investment gains thereon minus the amount paid out in claims is the Insurance Company's underwriting profit on that policy. Of course, from the Insurance Company's perspective, some policies are good when the Insurance Company pays out less in claims and expenses than it receives in premiums and investment income and some are bad when the Insurance Company pays out more in claims and expenses than it receives in premiums and investment income.
In certain types of insurance, such as fire insurance, policyholders are often required to conduct risk mitigation practices, such as installing sprinklers and using fireproof building materials to reduce the odds of loss to fire. In addition, after a proven loss, Insurance Companies specialize in providina rehabilitation to minimi7f> thp total IOQQ

However currently no such data of consumer health status is used to conduct risk mitigation practices in medical insurance policies.. So there is no motivation for healthy persons to continue payng the premium year after year inspite of no fear of suffering major illness and further the sick policy holders continue to pay the premium term after term, adding loss to the insurance company. Insurance Company prefers to deny coverage to high risk persons.
Redlining is the practice of denying insurance coverage under specific conditions, purportedly because of a high likelihood of loss. However the insurance company is never transparent to inform consumer why the policy was refused. Some reasons being that government may ban such refusal and secondly the company may not have goodwill with the public for such attitude. Inreality and mathematically the chances of success improves with large number of policy holders. So there is a general practice not to discriminate against low-income and/or minority applicants, and ethnicity. The database used in such insurance company in certain centres will not generally contain information on named insured income, ethnicity, or physical address. This is not the situation in India.
References
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3. Ash, A,Ellis, RP and lezzoni, L- Clinical refinements to the Diagnostic Cost Group Model'- Final report, June 1990
4. Bhat , R , Sumesh, K,B,'Health Insurance and Third Party Administrators: :lssues & Challenges', IIM Ahmedabad, 2003
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8. Kronick R, Gilmer T.P, Dreyfuss T, et al,- 'CDPS-Medicare: the Chronic Illness & Disability Payment System modified to predict expenditures for Medicare beneficiaries', 2002
9. Mavlankar, D and Bhat, R, 'Health Insurance in India: Opportunities, Challenges and Concerns', In: D.C. Srivastava and Shashank (eds): Indian Insurance Industry-Transition & Prospects, 2001
10. Mills, A-'Health Insurance for the demand and supply of health services, Conference at IIM Ahmedhabad, 2000.
11. Pope, G, Ellis R.P and Liu,C et al.-'Revised Cost Group (DCG)/HCC Models for Medicare Risk Adjustment'- Final Report, 1998
12. Pope, G, Liu C.F, Ellis, R.P Ash, A, et al,- 'Principal Inpatient Diagnostic Cost Group Models for Medicare Risk Adjustment', Final report-1998.

13.Newhouse JP, Buntin MB, Chapman JD- 'Risk adjustment and Medicare:
taking a closer look', Health affairs, September/October 1997, Volume 16, No
5 14.Sinha, Tapen, 'An Analysis of the Evolution of Insurance in India', CRIS
Discussion Paper Series- 2005 III 15.Zhao Y, Ash A, Haughton J, McMillan B-'Identifying future high cost cases
through predictive modeling'-Disease Management and Health Outcomes,
2003, 11(6). 16.Zhao Y, Ash A, Ellis R.P., et al- 'Disease burden profiles: an emerging tool for
managing managed care'-Health Care Management Science. 2002,5(3)
OBJECTS OF INVENTION:
Accordingly, what is needed in the art is method for accurately comparing the value and performance of a medical insurance policy.
The present invention is directed towards effectively resolving the aforementioned problems and shortcomings of the prior art.
The present invention also provides automated systems and methods for assisting insurance companies and policy users in the management of financial risk inherent in the insurance industry, and the public, such method being equally fair to insurance company and the policy holder.

Another object of the present invention is to provide automated systems and methods which allow an equitable relationship between policy users and insurance companies, to more efficiently and effectively buy and deliver medical insurance policies and services under varying reimbursement arrangements.
In prior art many parameters are not based on any standard statistical technique but rather intuitive choices, whereas the object of this invention is to make use of dynamic statistical measurements of the parameters affecting the premium payable. The present system suggests nevertheless a better system of calculating the premium by the insurance companies, based on two conditions, ie first condition being using the plurality of parameters affecting the premium and second condition being using the dynamic values of parameters for the purpose of calculating the invention.
However, in view of the prior art in at the time the present invention was made, it was not obvious to those of ordinary skill in the pertinent art how the identified needs could be fulfilled.
Another object is to suggest a method in which the premium is a fair price, and shall depend and includes the dynamic health status of the consumers and policy holders. In all prior art, the premium is independent of the volatile situation of environmental hazards and policy holders on health.

DESCRIPTION OF DRAWINGS:
Flowchart illustrates the method of computing as illustrated in Fig. 1. An enrollee is considered healthy and risk free if no Pre-existing disease is reported at the time of taking a policy. An enrollee becomes a claimant and a health score is computed once a claim is made to the insurance company. The individual's health score (IHS) is updated only when a claim for another different ailment is made. The claimant is not repeatedly scored for the same ailment suffered to avoid distortion of the score. For example ailments like Cancer and Renal Failure are of recurrent nature and need to be constantly treated medically; but updating the health score every time will distort the score. The severity of the ailment is however; take into consideration when computing the IHS score the first time. So the number of ailments and severity are the major considerations for evaluating the premium payable.
DESCRIPTION OF INVENTION : SUMMARY:
Medical insurance, which is coverage for individuals to protect them against medical costs, is a highly charged issue in the countries which does not have socialized health coverage.
As of date, as described in the prior art the formula to calculate the policy premium is a function of merely claimed amount previously, by the policy holder. This is insufficient and incorrect in many situations.

This invention relates to a method for evaluating relevant data and information, and more specifically to evaluating policies for cost and performance criteria of health insurance policies.
These methods involve collecting data applicable to the current health of an policy holder including but not limited to the most recent medical reports available on the health status of the policy holder in order to determine a current Health Score rating to be applied to a standard Health Score table.
It is important to carefully consider which factors influence a rate are being included and which factors are being left out. The different schemes may have different factors with different weighting values.
In determining premiums and premium rate structures, Insurance Companies may consider quantifiable factors, including location, credit scores, gender, occupation, marital status, and education level. However, the use of such factors is often considered to be unfair or unlawfully discriminatory in many cases, and the reaction against this practice has in some instances led to disputes about the ways in which Insurance Companies determine premiums and regulatory intervention to limit the factors used. To avoid such issues the insurance companies rarely disclose the method of computing the premium.
The present invention comprises a method of evaluating a insurance policy premium comprising the steps of establishing the health level of policy holders with reference to predetermined benchmark level.

A matrix of Health Scores may be established wherein the benchmark cost of insurance premium is adjusted in relation to the matrix. The matrix may include but is not limited to gender-based, agebased, obvious claim-bound, lifestyle and pricing method risk values. Gender-based risk values reflect the differing effects between men and women. Lifestyle-based risk values may include dangerous habits such as drinking, tobacco use, job occupation etc. Pricing method risk values are based on the statistical evidence that affluent individuals generally lead healthier lifestyles. In addition to comparing the illustrated cost of insurance value with the benchmark cost of insurance value, a number of other comparisons are preferable to gain a fair understanding of the performance and value of a life insurance policy. As more and more factors are considered, the calculated premiums will be fair and the loss of the insurance Company will become predictable. Fixed expenses may also be factored by establishing a benchmark fixed expense value. Policy earning values may also be featured by establishing a benchmark policy earning value.
The invention envisages a method of calculating insurance premium values such that in which the selection and ultimate purchase of the product is determined by both qualitative factors, which includes atleast the perceived level of associated service, perceived financial strength and claims paying ability of an insurance company, and quantitative factors which atleast includes the policy costs, the credibility of policy pricing patterns, and the reliability of those pricing assumptions as it relates to actual policy performance over a time.

V
The method comprising the steps of: establishing an objective and reliable means of identifying, calculating, benchmarking and comparing both the cost-effectiveness and the pricing adequacy of an insurance policy, establishing an objective and reliable means of identifying and quantifying the credibility of policy pricing factors, establishing an objective and reliable means of identifying and quantifying the reliability of illustrated policy pricing factors, establish a means of collecting policy pricing data on any/every product available, and atleast capturing the health status of the policy holders over the tenure of the policy.
With the premium dependent on the health of the consumer, the consumer appreciates and healthy buyers will be motivated by promise of premium savings associated with identifying most cost-effective policy in the circumstances relating to his own health and financial status. There will be peace of mind associated with identifying a reasonably-priced policy with credible and reliable pricing assumptions, which are not merely hypothetical but is dependent mainly on the health of the prospective buyer who becomes a policy holder.
In accordance with the present invention, a current Health Score for a user is calculated by a novel method. The current Health Score includes multiple measured physical parameters and multiple measured environmental parameters. Multiple options for selection by the Insurance Company and user is calculated by the system. The multiple options are prioritized according to the current Health Score of the user and designated Premium Payable By the user to the health Insurance Company, such that the health Scoring system aids the user and the insurance

company in selecting from among the multiple options in order to balance the comprehensive health of the user and the premium payable by the user.
The comprehensive health of an individual includes health history database . Health history database preferably includes both health and non-health related parameters received at computer system in association with a particular user. Health parameters may include physical and environmental parameters Physical parameters may include, but are not limited to including, bodily health measurements, and monitored medicinal measurements. Environmental parameters may include, but are not limited to including, atleast the diseases prevalent at the time during the term of policy or to that geographical location. As will be further described, health history database may be utilized for multiple types of analysis. Typically, a health history database may be analysed and calibrated by health data calibrator in order to determine factors that effect the health of a user over the term of policy and health and non-health characteristics for a user. Factors that effect the health of a user and non-health characteristics may be added to health Score for a user. In addition, health data calibrator may recommend to a user to adjust premium payable according to patterns and averages detected in analyzing health history database.
In addition, health history database may be transmitted with associated additional data to remote analysis systems for further analysis. As will be further described, remote analysis systems may include predetermined conditional analysis criteria for analyzing health history database in order to detect factors that effect the health of the user and non-health characteristics of the user. In addition, remote analysis

systems may make the contents of health history database accessible to others, such as a physician, consultants etc who may analyze health history database according to selected criteria. A group of remote analysis systems may incorporate both conditional analysis criteria and user selected analysis criteria for analysis of health history database. So the health of the policy holder is monitored and docketed continuously in this manner. The invention assists in the "Score Management" meaning a mechanism put into place to manage the consumption of health care to appropriate levels based on the use of clinically validated health care protocols, guidelines and/or standards. Score management functions include preliminary evaluation, concurrent review, so thus ensuring that each policy holder is covered under the correct policy and referral algorithms. It also includes mechanism for reducing the inappropriate use or misuse of health care services by those seeking health care, and also for increasing compliance with a medical regiment by patients with chronic diseases, or for increasing patient satisfaction while avoiding uncalled for and unnecessary claims. This is ensured by updation of Score to policy holder from time to time. So there is a tendency or inclination to remain generally healthy and to improve health for sick policy holders.
Although disease management and preventive services are very different elements of a health care system, they are equally important and essential and thereby are grouped together in the process of calculation of premium. In the invention, the first of the three sub-parts of an aggregation model is the function of severity, comorbidity and recurrence measure factors. The second sub part is age factor and

third sub part is the Length of Hospitalization (LOH) factor. The aggregation model ensures that the health score is calculated precisely.
An insurance underwriter's job is to evaluate a given risk as to the likelihood that a loss will occur. Any factor that causes a greater likelihood of loss should theoretically be charged a higher rate. This basic principle of insurance must be followed if insurance companies are to remain solvent. Thus, "discrimination" against or differential treatment of potential insureds in the risk evaluation and premium-setting process is a necessary by-product of the fundamentals of insurance underwriting. For instance, Insurance Companies charge sick and/or old people significantly higher premiums than they charge healthy and/or younger people. The rationale for the differential treatment is that the risk of loss is greater in former cases in any given period of time and therefore the risk premium must be higher to cover the greater risk. However, treating Insurance Companies differently when there is no actuarially sound reason for doing so is considered as unlawful discrimination. The invention attempts to give a method to ascertain the actual health status of the policy holder, thereby making the premium calculation a transparent affair.
The invention also includes a program for calculating health of a person residing on a computer usable medium having computer readable program code means, said program comprising: means for compiling a plurality of health Scores from a plurality of personal health measuring systems each respectively measuring a current health score including physical parameters and environmental parameters indicative of the current health of one of a plurality of users; means for comparing said physical

parameters and said environmental parameters of each of said plurality of health scores to determine health affecting factors for said plurality of users, such that health affecting factors of health are calculated; means for comparing said plurality of health scores with a model health score; means for determining a factor of adjustment of actual score and model score and means for corresponding adjustments of premium to users associated with said plurality of health scores.
The invention also includes an apparatus for providing healthcare information, said apparatus comprising a processor for processing at least one of physical information and environment information received from measuring systems corresponding to a user, in conjunction with at least one of healthcare information, healthcare theories, healthcare principles, and healthcare research, wherein said processor generates a health score, and further wherein said score contains information in two parts, the first part containing the value of health rating of the user and second part containing the numbers of diseases suffered by the user.
Now herein the description relates to the process of computing the overall health score of an individual as per invention: - generally referred to as IHS hereinafter.
IHS can be calculated from the following data: Claim History data of all claimants consisting of:
1. Age
2. Gender
3. Ailment Description, as specified in the International Disease Classification -Ver10(ICD-10)
4. Ailment for which a claim is made

5. Length of Hospitalization This data is used to create three sub-parts of the score, described below, which are then aggregated to yield the final IHS.
Consider the calculation for the jth individual claimant, who has previously made claims for (M-1) claims, and has just made a fresh claim for the Mth ailment. These calculations are performed separately for male and female claimants. A) Aggregation Model
The sub-parts in the aggregation are the following:
1. Severity-Co Morbidity-Recurrence Measure This sub-part is defined as

where f(sk ck, rk) denotes a function of the co-morbidity, recurrence propensity and severity measures for ailment k. The acute/chronic nature of the ailment is represented by tk. These measures are pre-configured non-standard, experience-derived numbers assigned to each ailment class in the ICD-10 classification, and wkd denotes a pre-configured weight factor for the co-morbidity recurrence propensity and severity assigned to the specific ailment k.
(2)

where f(Uk, D/c, ay J denotes a function of the mean and standard deviation of distribution of age of the all claimants in the claim history data, who have previously claimed for this specific ailment jth, and a; denotes the specific age of the/7 claimant under consideration here. wka denotes a pre-configured weight factor for age measure.

where f(Uk, □*, hj) denotes a function of the mean and standard deviation of distribution of lengths of hospitalization reported by the all claimants in the claim history data, who have previously claimed for this specific ailment /c, and hk denotes the specific length of hospitalization of the fh claimant under consideration here. wka denotes a pre-configured weight factor for LOH measure.
B) Weight Factor Configuration
The weight factors w/, wak, and Whk are set as follows:
Severity-Co-Morbidity- Recurrence Weight Factor, wdk
This measure captures the level of severity, co-morbidity and propensity for repeat occurrence of the ailment on the basis of previous ailment history. The weight factor is a normalized number, which is derived from expert medical opinion and insurance assessors using a scoring scale in a Delphi method.

Age Weight Factor, wak
This weight is itself derived as a function of the distributional properties of the age of claimants with respect to the specific ailments. The weights for Age are calculated by evaluating the mean □, and standard deviation □ of the fitted distributions of the variables representing age by ailment, using historical data
LOH Weight Factor, whk
The weight for LOH is itself derived as a function of the distributional properties of the hospital stay of claimants with respect to the specific ailments. The weights for LOH are calculated by evaluating the mean D, and standard deviation □ of the fitted distributions of the variables representing length of hospitalization by ailment, using historical data.
C) Function Calculation
The function for each sub-part is computed by multiplying the weights discussed above with the original Age and LOH information submitted by an individual at the time of making a claim.
D) Final Model
An Agglomerate /Aggregate model that takes the combined effect of the scores of all these variables is used to obtain the final Individual's Health Score (IHS). The model is applied to every new ailment for which claim has been made.

The total score, IHSjt for the /* claimant, is calculated as the aggregate function:
IHSj=f{S1{,SJ2,Sj3) (4)
E) Normalization
The IHS algorithm scores every unique ailment reported and claimed. The score is
normalized between 1-100. Scores for multiple ailments are added up. A single
ailment cannot exceed 100; the value can thereafter however, exceed 100 on
account of multiple ailments. Outliers can however, distort the score.
Similarly, the characters attached to the numeric value of the health score reveal the
number of unique ailments for which claims were made. For example, an IHS score
of 77-B for a claimant can be interpreted as:
an individual has claimed for two ailments and the numeric value (77) reflects his
health status.
F) Rule Engine
A rule engine is used to consider the various constraints and conditions under which the IHS algorithm can be used in a health insurance industry.
System for Calculation of IHS
The health score calculation method is designed to be retro-fitted into a computerized insurance processing system in which there exists historical claim data with the elements described above. The system comprises software modules to implement all the calculation steps described above, in such a manner that it is triggered into operation, every time a new claim enters the system. Once the trigger is received, the following steps are initiated:

1. Update statistical properties
Fitting distributions are updated for all ailments, age-classes, and LOH, using new claimant data;
2. Calculate sub-part measures
Sub-part measures are calculated for this claim; Rules are implemented to handle multiple claims by the same individual for the same ailment, in a manner that they are not scored again, except in exceptional cases.
3. Calculate IHS for this claimant
Total IHS is calculated for this claimant; the final scores are converted to an alphanumeric score for easy human interpretation. The numeric part denotes the health status, with higher values indicating more serious health conditions. The alphabet denotes the unique multiplicity of the ailments claimed for by the specific claimant. A indicates one ailment; B indicates two, and so on
Examples
See Table shown below for illustrative purposes: Refer to ICD-10 document for description of the ailments. See Appendix for the list of ailment descriptions given below in the table, (appendix ?)
A i InrtAnt A iliviAnt A ilmAnt A Mm Art 4 A 1I rv% *■*!"» +


4. Update IHS for all other claimants
IHS records for all other claimants are updated on the basis of changes, which may have occurred in the distributional properties due to the consideration of this specific claim.
The first novelty of the method is that the method combines knowledge of the nature of ailment morbidity and co-morbidity patterns from a prescriptive medical standpoint (how it should be), with a normative observable statistical measure of the distribution of current claim behavior of enrollees (how it is). The scores represent a weighted combination of these factors, making them more usable in the healthcare insurance sector, where claims need to be assessed not only from a diagnostic correctness point of view, but also from a prospective risk point of view.
The invention provides for calculating a unique score for each insured.
It is a single score which comprehensively captures the ailment and the demographic information to reflect the health status of a claimant
No other method uses this combined knowledge.
The method as per the invention is uniformly applicable to all enrollees; for non-claimants, if there are reported pre-existing ailments, they will be used to

calculate initial scores, if there are none, they will be considered risk-free since there is no ailment history. No other method known in prior can be applied to all enrollees, as envisaged in this invention.
The scores calculated as per the method of this invention captures the dynamic behavior of claim behavior patterns, through their distributional characteristics. If these characteristics shift over time, reflecting higher or lower propensities for claims for certain classes of ailments in certain age groups, these shift will automatically get reflected in the scores through the functional dependencies with the moments of the distributions. Hence they will continue to exhibit 'true' nature of claim behavior.
None of other method existing in prior art captures this dynamics.
Since the methodology automatically re-calibrates the scores for all claimants for every new claim, the scores auto-normalize themselves to stay in synchronization with emerging patterns of claim behavior at all times. None of other method existing in prior art updates and re-calibrates for every new claim event.
When viewed as a historical growth pattern over time, IHS lends itself well for use in detection of anomalies in claim behavior. The method also simultaneously offers a means to understand and catch anomalies. The method thereby is flexible for adaptations.
Growths in means for certain classes of ailments can be used to signal warning situations; e.g., thresholds could be set up on respiratory ailments which could be

indicative of endemic spreads of a specific class of diseases, which in turn would signal larger reserve requirements. None of other method existing in prior art offers means to create such alerts.
The scores for a Claimant over time constitute a moronically increasing positive sequence of numbers because the insurance database does not reflect or report recovery from that ailment. None of other method existing in prior art offers means to obtain the health status of a claimant during his relationship with the health insurance company.
An assessment of IHS as calculated in the method of invention can be used to analyze the possible risk posed by an enrollee in the future. The risk lifecycle of a claimant can be assessed by studying his health score over time. The method also simultaneously offers a means to assess risk.
The IHS score as calculated in the method of invention can be used by the health insurance companies for premium setting at the time of renewal of policies by both individuals and the Corporates. IHS method offers a means to set Premiums in the future.
The IHS score as calculated in the method of invention can be used in automated claim processing. All normal and routine claim requests can be handled by automatic claim processing, flagging out only abnormal and unclear requests for manual scrutiny.

WE CLAIM:
1. A method for calculating health score of every user seeking medical policy,
said method comprising the steps of:
a. compiling a plurality of health scores from a plurality of personal health
measuring systems each respectively measuring a current health score
including physical parameters and/or environmental parameters
indicative of the current health of one of a plurality of users; and
b. comparing said plurality of health scores with a model health score to
determine a premium payable by said plurality of users.
2. The method for calculating health score according to claim 1, said step of compiling a plurality of health scores from a plurality of personal health Measuring systems, further comprising the step of: receiving said plurality of information in electronic form from a plurality of personal health measuring systems.
3. The method for calculating health score according to claim 1, said step of compiling a plurality of health scores from a plurality of personal health measuring systems, further comprising the step of: updating a stored health score of a previously registered user with a current health score received from a personal health measuring system associated with said previously registered user.
4. The method for calculating health score according to claim 1, said step of compiling a plurality of health scores from a plurality of personal health measuring systems, further comprising the step of: compiling said plurality of health scores from

said plurality of personal health measuring systems associated with a plurality of users seeking health policies.
5. The method for calculating health score according to claim 1, said method further comprising the step of: performing statistical analysis on said plurality of health scores to determine plurality of health affecting factors.
6. The method for calculating health score according to claim 1, said method further comprising the step of: analyzing said plurality of health scores in view of selected health affecting factors to determine which users are affected or may be affected by any or some of the predetermined ailments.

7. The method for calculating health score according to claim 1, said method further comprising the step of updating a stored health score of a previously registered user with a current health score based on the information received from any of the personal health measuring systems associated with said previously registered user.
8. The method for calculating health score according to claim 1, further comprising the step of updating plurality of stored health score of plurality of previously registered users with a corresponding current health score received from a personal health Measuring System, associated with said plurality of registered users.

9. A system for calculating health score of every user seeking medical policy,
said method of claim 1 comprising the steps of:
a. means for compiling a plurality of health scores from a plurality of personal
health measuring systems each respectively measuring a current health score
including physical parameters and/or environmental parameters indicative of the
current health of one of a plurality of users;
and
b. means for comparing said plurality of health scores with a model health score
to determine a premium payable by said plurality of users.
10. A method for calculating health score of every user seeking medical policy,
said method comprising the steps of>
a. Sensing plurality of physical and clinical measurements for identifying plurality
of ailments with plurality of sensing means;
b. Storing the assigned weighting factor to each of the physical and clinical
measurements for determining the ailment, said weighting factor having been
previously determined by independently measuring the contribution of each of
the measurements to the ailment in the memory means;
c. Summing the identified ailments, which is an accurate representation of the
number of ailments identified in and associated with the user in a processor
means coupled to the sensing means and the memory means; and configured
to identify a plurality of ailments to be associated with the user;
d. Storing the weighting factor to each of the physical and clinical measurements
for determining ailment characteristic to be measured, said weighting factor

having been previously determined by independently measuring the contribution of each of the measurements to values of said predetermined plurality of disease characteristics, which are already known in memory means;
e. Calculating a plurality of ailment weight scores for each of the plurality of
identified ailments;
f. Summing the said plurality of ailment weight scores;
g. Calculating the ailment weight scores over the number of identified ailments to
represent a health score by a processor coupled to the sensing means and the
memory means; and
h. Compensating the weight score based on representatives of other desired factor as compensation factor to calculate the health score, the health score comprises of scaled numeric, characters of alphanumeric value characters characterized in that;
11. A system for calculating health score of every user seeking medical policy, said method comprising the steps of:-
a. plurality of sensing means for sensing plurality of physical and clinical
measurements for identifying plurality of ailments;
b. memory means 1 for storing assigned weighting factor to each of the
physical and clinical measurements for determining the ailment, said weighting
factor having been previously determined by independently measuring the
contribution of each of the measurements to the ailment;

c. A processor means 1 for summing the identified ailments, which is an
accurate representation of the ailments identified in and associated with the
user by a processor coupled to the sensing means and the memory means;
and configured to identify a plurality of ailments to be associated with the user;
d. Memory means 2 for storing assigned weighting factor to each of the
physical and clinical assignments for determining ailment characteristic to be
measured, said weighting factor having been previously determined by
independently measuring the contribution of each of the measurements to
values of said predetermined plurality of disease characteristics, which are
already known in memory means;
e. Processor means 2 for calculating a plurality of ailment weight scores of
plurality of identified ailments;
f. Processor means 3 for summing the said plurality of ailment weight scores;
g. Processor means 4 for calculating the ailment weight scores over the
identified ailments to represent a health score by a processor coupled to the
sensing means and a memory means 2;
h. Processor means 5 for calculating a health score from the calculated health score based on representatives of other desired factor as compensation factor;
i. characterized in that health score comprises a scaled numeric, characters or alphanumeric value characters;
12. A method for compiling a composite health score value of every user seeking medical policy, said method comprising the steps of calculating the health score,

wherein the said health score has two components that is combinable to define the composite health report, the first component corresponding to the calculated score scaled in the range 0 to 100 over the plurality of ailments identified and second component corresponding to the actual number of ailments associated as suffered by the user; characterized in the 3 digit numeral in the first part and in the alphabet in the second part of the composite health score.
13. A method for calculating health score of every user seeking medical policy,
said method comprising the steps of
- sensing a plurality of clinical and environments parameters,
- producing electronic information corresponding thereto, and * recording the electronic information in a storage medium,
- characterized in an improvement wherein the recorded information is processed therein by which the number of ailments suffered and current health condition by the policy holder can be determined as a function of predetermined variable factors from a group comprising a first sub-part of severity, Co-morbidity-recurrence measuring factor, second sub-part of age factor and third sub-part of hospitalization factor.
14. A method for calculating health score of a user seeking medical policy, said
method comprising the steps of:-
- wherein the health score comprises of three sub-parts aggregated to form the health score, the first is a function of co-morbidity, recurrence propensity and severity measure of a specific ailment, the second is a function of the mean and

variance of distribution of age of all the claimants in the claim history database, previously claimed for a specific ailment and third is a function of mean and variance of distribution of lengths of hospitalization reported by all claimants in the claim history data previously claimed for specific ailment.
wherein the function of each sub-part is computed by multiplying the corresponding weight weighting factor with actual age and LOH information submitted by a claimant at the time of making a claim.