PATIENT DATA TRIGGERED SYSTEM FOR RISK TRANSFER LINKED TO PROLONGING INDEPENDENT LIVING BY ELDERLY ILLNESS OCCURRENCE AND CORRESPONDING METHOD THEREOF

Abstract

A resource pooling system and method for multi-pillar triggered risk transfer associated with prolonged independent living under elderly illness occurrence by providing dynamic self-sufficient risk protection for a variable number of risk exposure components by the resource pooling system. The risk exposure components are connected to the resource pooling system by a plurality of payment receiving devices configured to receive and store payments from the risk exposure components for the pooling of their risks and resources. The resource pooling system includes a filter device configured to capture age-related parameters of risk exposure components and filter risk exposure components associated with an age-related parameter greater than a predefined age-threshold value by the predefined age-threshold value.

Claims

1. A resource pooling system for multi-pillar triggered risk transfer associated with prolonged independent living under elderly illness occurrence by providing dynamic self-sufficient risk protection for a variable number of risk exposure components by the resource pooling system, wherein the risk exposure components are connected to the resource pooling system by a plurality of payment receiving devices configured to receive and store payments from the risk exposure components for the pooling of their risks and resources, wherein the resource pooling system comprises a filter device configured to capture age-related parameters of risk exposure components and filter risk exposure components associated with an age-related parameter greater than a predefined age-threshold value by the predefined age-threshold value, and wherein the resource pooling system provides automated risk protection for each of the connected risk exposure components based on received and stored payments and the age-related parameters of the risk exposure components triggering the predefined age-threshold value, the resource pooling system comprising: processing circuitry configured to generate a multi-dimensional trigger-table comprising a multi-layered data structure with predefined searchable acute and/or chronic elderly illness parameters for triggering by elderly illness triggers in a patient dataflow pathway, the predefined parameters of a first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses, the predefined parameters of a second-layer data structure providing measuring parameters for the occurrence of an acute broken bone trauma, the predefined parameters of a third-layer data structure providing measuring parameters for long-term care indications, the predefined parameters of a fourth-layer data structure providing measuring parameters for assisted living indications, and the predefined parameters of a fifth-layer data structure providing measuring parameters for extended assistance indications, the resource pooling system comprising elderly illness triggers triggering measuring values in patient dataflow pathways of the connected risk exposure components, and when an occurrence of an acute or chronic elderly illness on the patient dataflow pathway of a risk exposure component is triggered by exceeding one of the predefined searchable acute and/or chronic elderly illnesses parameters, set a corresponding trigger-flag and assign a parametric transfer of payments to the corresponding trigger-flag, wherein a loss associated with the acute or chronic elderly illness is distinctly covered by the resource pooling system based on the respective trigger-flag and based on the received and stored payment parameters from risk exposure components by at least one parametric payment transfer from the resource pooling system to the risk exposure component.

2. The resource pooling system according to claim 1, wherein the predefined parameters of the first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses comprise at least parameters indicating the occurrence of dementia, heart attack, cancer, stroke, coronary artery by-pass surgery, Alzheimer's disease, blindness, deafness, kidney failure., major organ transplant, multiple sclerosis, HIV/AIDS contracted by blood transfusion or during an operation, Parkinson's disease, paralysis of limb or terminal illness in the patient dataflow pathway.

3. The resource pooling system according to claim 1, wherein the predefined parameters of the first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses comprise at least elderly illness trigger parameters for triggering the occurrence of measuring parameters indicating dementia based on measuring parameters associated with the permanent clinical loss of the ability to remember and/or reason and/or perceive, understand, express and give effect to ideas in the patient dataflow pathway.

4. The resource pooling system according to claim 3, wherein the triggered measuring parameters indicating dementia comprise physical parameters and/or psychological parameters and/or biochemical parameters and/or cognitive factors based on adrenal exhaustion factors and/or food and chemical reaction factors and/or nutritional deficiency factors and/or stress factors and/or depression factors, and/or denial factors, indicating confirmed impairment of cognitive functions.

5. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to process risk-related component data and to provide a likelihood of the risk exposure for one or a plurality of the pooled risk exposure components based on the risk-related component data, wherein receiving and preconditioned storage of payments from risk exposure components for the pooling of their risks is dynamically determinable based on a total risk and/or the likelihood of the risk exposure of the pooled risk exposure components.

6. The resource pooling system according to claim 5, wherein the total risk of the pooled risk exposure components comprises elderly illness risk contributions of each pooled risk exposure component associated with risk exposure in relation to a possibility of triggering at least one acute or chronic elderly illnesses, wherein elderly illness losses occur as a consequence of the triggered diagnosis of risk exposure components with one of the searchable elderly illnesses based upon the predefined trigger measuring values.

7. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to dynamically adapt the elderly illness triggers based on time-correlated incidence data for an elderly illness condition and/or diagnosis or treatment conditions indicating improvements in diagnosis or treatment.

8. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to dynamically adapt the number of pooled risk exposure components to a range where non-covariant occurring risks covered by the resource pooling system affect only a relatively small proportion of the total pooled risk exposure components at a given time.

9. The resource pooling system according to claim 1, wherein the elderly illness triggers trigger elderly illness parameters indicating psychiatric or old-age in--patient care associated with the risk exposure component comprising acute in-patient admission parameters as a result of deterioration in dementia status requiring urgent treatment.

10. The resource pooling system according to claim 1, wherein the elderly illness triggers triggering an ongoing care or management phase of the chronic elderly illness comprise ongoing care or management phase parameters indicating permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or ongoing care or management phase parameters indicating permanent cognitive and/or motor impairment requiring constant supervision by another person.

11. The resource pooling system according to claim 1, wherein the elderly illness triggers comprise on elderly illness trigger for triggering the occurrence of measuring parameters indicating stroke based on measuring parameters associated with possibly permanent cognitive or motor impairment and; or indicating the time of an acute stroke episode in the patient dataflow pathway.

12. The resource pooling system according to claim 1, wherein the elderly illness triggers triggering treatment phase of the chronic elderly illness comprise treatment phase parameters indicating a measured time interval of the risk exposure component spent in the hospital due to the triggered stroke.

13. The resource pooling system according to claim 1, wherein the elderly illness triggers triggering an ongoing care or management phase of the chronic elderly illness comprise ongoing care or management phase parameters indicating permanent impairments of cognitive functions and/or permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or permanent cognitive and/or motor impairment requiring constant supervision by another person.

14. The resource pooling system according to claim 1, wherein the elderly illness triggers further comprise an elderly illness trigger for triggering measuring parameters indicating alcohol and/or drug abuse in the patient dataflow pathway, wherein upon triggering measuring parameters indicating alcohol and/or drug abuse, the processing circuitry rejects the related risk exposure component from pooling of the risk and resources.

15. The resource pooling system according to claim 1, wherein acute treatment phase parameters are triggerable by the elderly illness triggers of acute elderly illness, indicating surgery and/or chemotherapy and/or radiotherapy and/or reconstructive surgery in the patient dataflow pathway,

16. The resource pooling system according to claim 1, wherein a plurality of transferred payment portions are generatable to add up to the allocated total parametric payment and to be transferred with a time shift.

17. The resource pooling system according to claim 16, wherein the allocated total parametric payment is determinable at least based on the risk-related component data and/or on a likelihood of the risk exposure for one or a plurality of the pooled risk exposure components based on the risk--related component data, and wherein a first portion is transferred up to predefined percentage of the total payment sum and the following portions are transferred up to the residual part given by the total payment sum.

18. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to request a periodic payment transfer from the risk exposure components to the resource pooling system by the plurality of payment receiving devices, and interrupt the risk protection for the risk exposure components when the periodic transfer is no longer detectable.

19. The resource pooling system according to claim 18, wherein the processing circuitry interrupts or waives the request for periodic payment transfer when occurrence of indicators for elderly illness is triggered in the patient dataflow pathway of the risk exposure component.

20. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to trigger an independent verification elderly illness trigger, which is activated in the event of triggering of the occurrence of indicators for elderly illness in the patient dataflow pathway of a risk exposure component by the elderly illness triggers, and which additionally is a trigger for the occurrence of indicators for elderly illness in an alternative patient dataflow pathway with independent measuring parameters from the primary patient dataflow pathway to verify the occurrence of the elderly illness at the risk exposure component.

21. The resource pooling system according to claim 20, wherein the parametric transfer of payments is only assigned to the corresponding trigger-flag when the occurrence of the elderly illness at the risk exposure component is verified by the independent verification elderly illness trigger.

22. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to monitor the patient dataflow pathway by capturing a patient measuring parameter of the patient dataflow pathway at least periodically and/or within predefined time frames.

23. The resource pooling system according to claim 1, wherein the processing circuitry is further configured to dynamically monitor the patient dataflow pathway by triggering of patient measuring parameters of the patient dataflow pathway transmitted from associated measuring systems.

24. A method for a patient data-driven system for multi-pillar triggered risk transfer associated with prolonged independent living under elderly illness occurrence by providing dynamic self-sufficient risk protection for a variable number of risk exposure components via resource pooling system, wherein the risk exposure components ore connected to the resource pooling system by a plurality of payment receiving devices configured to receive and store payments from the risk exposure components for the pooling of their risks and resources, wherein the resource pooling system comprises a filter device configured to capture age-related parameters of risk exposure components and filter risk exposure components associated with an age-related parameter greater than a predefined age threshold value via the predefined age-threshold value, and wherein the resource pooling system provides automated risk protection for each of the connected risk exposure components based on received and stored payments and the age-related parameters of the risk exposure components triggering the predefined age-threshold value, the method comprising: generating, by processing circuitry of the resource pooling system, a multi-dimensional trigger-table comprising a multi-layered data structure with predefined searchable acute and/or chronic elderly illnesses parameters for triggering, by elderly illness triggers in a patient dataflow pathway, the predefined parameters of a first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses, the predefined parameters of a second-layer data structure providing measuring parameters for the occurrence of an acute broken bone trauma, the predefined parameters of a third-layer data structure providing measuring parameters for long-term care indications, the predefined parameters of a fourth-layer data structure providing measuring parameters for assisted living indications, and the predefined parameters of a fifth-layer data structure providing measuring parameters for extended assistance indications, the resource pooling system comprising elderly illness triggers triggering measuring values in patient dataflow pathways of the connected risk exposure components; and when an acute or chronic elderly illness occurs on the patient dataflow pathway of a risk exposure component or is triggered by exceeding one of the predefined searchable acute and/or chronic elderly illness parameters, setting a corresponding trigger--flag via the resource pooling system, and assigning a parametric transfer of payments to the corresponding trigger-flag, wherein a loss associated with the acute or chronic elderly illness is covered separately by the resource pooling system based on the respective trigger-flag and based on the received and stored payment parameters from risk exposure components by at least one parametric payment transfer from the resource pooling system to the risk exposure component.

25. The method according to claim 24, wherein the predefined parameters of the first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses comprise at least parameters indicating the occurrence of dementia, heart attack, cancer, stroke, coronary artery by-pass surgery, Alzheimer's disease, blindness, deafness, kidney failure., major organ transplant, multiple sclerosis, HIV/AIDS contracted by blood transfusion or during an operation, Parkinson's disease. paralysis of limb or terminal illness in the patient dataflow pathway.

26. The method according to claim 24, wherein the predefined parameters of the first-layer data structure providing measuring parameters for the occurrence of serious elderly illnesses comprise at least elderly illness trigger parameters for triggering the occurrence of measuring parameters indicating dementia based on measuring parameters associated with the permanent clinical loss of the ability to remember and/or reason and/or perceive, understand, express and give effect to ideas in the patient dataflow pathway.

27. The method according to claim 26, wherein the measuring parameters indicating dementia comprise physical parameters and/or psychological parameters and/or biochemical parameters and/or cognitive factors based on adrenal exhaustion factors and/or food and chemical reaction factors and/or nutritional deficiency factors and/or stress factors and/or depression factors, or denial factors, indicating confirmed impairment of cognitive functions.

28. The method according to claim 24, further comprising: processing, by the processing circuitry of the resource pooling system, risk-related component data and providing a likelihood of the risk exposure for one or a plurality of the pooled risk exposure components based on the risk-related component data, wherein receiving and preconditioned storage of payments from risk exposure components for the pooling of their risks is dynamically determinable based on a total risk and/or the likelihood of the risk exposure of the pooled risk exposure components.

29. The method according to claim 28, wherein the total risk of the pooled risk exposure components comprises elderly illness risk contributions of each pooled risk exposure components associated with risk exposure in relation to a possibility of triggering of at least one acute or chronic elderly illnesses, wherein elderly illness losses occur as a consequence of the triggered diagnosis of risk exposure components with one of the searchable elderly illnesses based upon the predefined trigger measuring values.

30. The method according to claim 24, further comprising: dynamically adapting the elderly illness triggers based on time-correlated incidence data for an elderly illness condition and/or diagnosis or treatment conditions indicating improvements in diagnosis or treatment.

31. The method according to claim 24, further comprising: dynamically adapting the number of pooled risk exposure components to a range where non-covariant occurring risks covered by the resource pooling system affect only a relatively small proportion of the total pooled risk exposure components at a given time,

32. The method according to claim 24, wherein the elderly illness triggers trigger elderly illness parameters indicating psychiatric or old-age in-patient care associated with the risk exposure component comprising acute in-patient admission parameters as a result of deterioration in dementia status requiring urgent treatment.

33. The method according to claim 24, wherein the elderly illness triggers trigger an ongoing care or management phase of the chronic elderly illness comprise ongoing care or management phase parameters indicating permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or ongoing care or management phase parameters indicating permanent cognitive and/or motor impairment requiring constant supervision by another person.

34. The method according to claim 24, wherein an elderly illness trigger of the elderly illness triggers triggers the occurrence of measuring parameters indicating a stroke based on measuring parameters associated with the possibly permanent cognitive or motor impairment and/or indicating the time of an acute stroke episode in the patient dataflow pathway.

35. The method according to claim 34, wherein the elderly illness triggers triggering a treatment phase of the chronic elderly illness comprise treatment phase parameters indicating a measured time interval of the risk exposure component spent in a hospital due to the triggered stroke.

36. The method according to claim 24, wherein the elderly illness triggers triggering an ongoing care or management phase of the chronic elderly illness comprise ongoing care or management phase parameters indicating permanent impairments of cognitive functions and/or permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or permanent cognitive and/or motor impairment requiring constant supervision by another person. 15

37. The method according to claim 24, wherein an elderly illness trigger of the elderly illness triggers further triggers measuring parameters indicating alcohol and/or drug abuse in the patient dataflow pathway, the method further comprising: upon triggering measuring parameters indicating alcohol and/or drug abuse, rejecting the related risk exposure component from pooling of the risk and resources.

38. The method according to claim 24, wherein the elderly illness triggers of acute elderly illness trigger acute treatment phase parameters indicating surgery and/or chemotherapy and/or radiotherapy and/or reconstructive surgery in the patient dataflow pathway.

39. The method according to claim 24, further comprising: generating a plurality of transferred payment portions to odd up to the allocated total parametric payment and to be transferred with a time shift.

40. The method according to claim 39, further comprising: determining the allocated total parametric payment at least based on the risk-related component data and/or a likelihood of the risk exposure one or a plurality of the pooled risk exposure components based on the risk-related component data, and wherein a first portion is transferred up to predefined percentage of the total payment sum and the following portions are transferred up to the residual t given by the total payment sum.

41. The method according to claim 24, further comprising: requesting a periodic payment transfer from the risk exposure components to the resource pooling system by the plurality of payment receiving devices: and interrupting the risk protection for the risk exposure components when the periodic transfer is no longer detectable.

42. The method according to claim 41, further comprising: interrupting or waiving the request for periodic payment transfer when the occurrence of indicators for elderly illness is triggered in a patient dataflow pathway of a risk exposure component.

43. The method according to claim 24, further comprising: activating on independent verification elderly illness trigger of the resource pooling system in the event of triggering of the occurrence of indicators for elderly illness in the patient dataflow pathway of a risk exposure component by the elderly illness triggers, and which is additionally a triggering for the occurrence of indicators for elderly illness in an alternative patient dataflow pathway with independent measuring parameters from the primary patient dataflow pathway to verify the occurrence of the elderly illness at the risk exposure component.

44. The method according to claim 43, wherein the parametric: transfer of payments is only assigned to the corresponding trigger-flag when the occurrence of the elderly illness at the risk exposure component is verified by the independent verification elderly illness trigger.

45. The method according to claim 24, further comprising: monitoring the patient dataflow pathway by capturing patient measuring parameters of the patient dataflow pathway at least periodically and/or within predefined time frames.

46. The method according to claim 24, further comprising: dynamically monitoring the patient dataflow pathway by triggering of patient measuring parameters of the patient dataflow pathway transmitted from associated measuring systems.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be explained in more detail, by way of example, with reference to the drawings, in which:

[0028] FIG. 1 shows a block diagram schematically illustrating an exemplar/parametric, event-driven elderly illness insurance system based on a resource pooling system 1 according to the invention for risk sharing of elderly illness risks associated with elderly persons by providing dynamic self-sufficient risk protection for a variable number of risk exposure components 21, 22, 23, said elderly persons. The resource pooling system 1 comprises an assembly module 5 to process risk-related component data 211, 221, 231 and to provide the likelihood 212, 222, 232 of said risk exposure for one or a plurality of the pooled risk exposure components 21, 22, 23, wherein the risk exposure components 21, 22, 23 are connected to the resource pooling system 1 by means of a plurality of payment receiving modules 4 that are configured to receive and store 6 payments 214, 224, 234 from the risk exposure components 21, 22, 23 for the pooling of their risks, and wherein the resource pooling system 1 comprises an event-driven core engine 3 that comprises elderly illness triggers 31, . . . , 35, which trigger a patient dataflow pathway 213, 223, 233 to provide risk protection for a specific risk exposure component 21, 22, 23. The patient dataflow pathway 213, 223, 233 is monitored by the resource pooling system 1 in that patient measuring parameters of the patient dataflow pathway 213, 223, 233 are captured, wherein the patient dataflow pathway 213, 223, 233 is dynamically monitored and triggered for patient measuring parameters of the patient dataflow pathway 213, 223, 233, which is transmitted from associated measuring systems.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0029] FIG. 1 schematically illustrates an architecture for a possible implementation of an embodiment of the parametric, event-driven resource pooling system 1 for risk sharing of elderly illness risks associated with elderly persons. In FIG. 1, reference numeral 1 refers to the resource pooling system for risk sharing of the risk exposure components 21, 22, 23, etc. The resource pooling system 1 provides a dynamic self-sufficient risk protection and corresponding risk protection structure for a variable number of risk exposure components 21, 22, 23, i.e., elderly persons or individuals, by its means. The system 1 includes at least one processor and associated memory modules. The system 1 can also include one or more display units and operating elements, such as a keyboard, and/or graphical pointing devices, such as a computer mouse. The resource pooling system 1 is a technical device comprising electronic means that can be used by service providers in the field of risk transfer or insurance technology for risk transfer related to elderly illness risks and related to prolonging the chance for independent living through assisted living or the like. The invention seeks to technically capture, handle and automate complex related operations of the insurance industry. Another aspect is to synchronize and adjust such operations based on technical means. In contrast to the standard approach, the resource pooling system also achieves a reproducible operation with the desired technical, repetitious accuracy because it is completely based on technical means, process flow and process control operation.

[0030] The resource pooling system 1 comprises an assembly module 5 to process risk-related component data 211, 221, 231 and to provide the likelihood 212, 222, 232 of said risk exposure for one or a plurality of the pooled risk exposure components 21, 22, 23, etc. based on the risk-related component data 211, 221, 231. The resource pooling system 1 can be implemented as a technical platform, which is developed and implemented to provide elderly illness risk transfer through a plurality of (but at least one) payment receiving module 4. The risk exposure components 21, 22, 23, etc. are connected to the resource pooling system 1 by means of the plurality of payment receiving modules 4 configured to receive and store payments 214, 224, 234 from the risk exposure components 21, 22, 23, etc. to pool their risks in a payment data store 6. As a variant, the transferred and pooled payments can be grouped to provide risk-transfer for a defined group of risk exposure components 21, 22, 23. The plurality of risk exposure components 21, 22, 23 from a cohort of selected elderly persons, where during capturing the risk exposure components 21, 22, 23 to be pooled by the system 1, age-related parameters of risk exposure components are captured. Based on the captured age-related parameters, the risk exposure components are filtered using a filter module, wherein by means of the filter module, only risk exposure components 21, 22, 23 associated with an age-related parameter greater than a predefined age-threshold value are allowed to be pooled by the system 1. The predefined age-threshold value can for example be set to 50 years or another appropriate age allowing the selection of a specific cohort of elderly persons. As an alternative embodiment, the selection criterion can comprise further parameters such as gender, origin, habits, urban or rural conglomeration, etc.

[0031] The storage of the payments can be implemented by transferring and storing component-specific payment parameters. The payment amount can be dynamically determined by means of the resource pooling system I based on total risk of the overall pooled risk exposure components 21, 22, 23. For the pooling of the resources, the resource pooling system 1 can comprise a monitoring module 8 requesting a periodic payment transfer from the risk exposure components 21, 22, 23, etc. to the resource pooling system 1 by means of the plurality of payment receiving modules 2, wherein the risk protection for the risk exposure components 21, 22, 23, etc. is interrupted by the monitoring module 8, when the periodic transfer is no longer detectable by means of the monitoring module 8. In one alternative embodiment, the request for periodic payment transfers is automatically interrupted or waived by means of the monitoring module 8, if the occurrence 1001 of indicators for one of the predefined elderly illnesses 71, . . . , 75 of the multi-dimensional trigger-table 7 is triggered in the patient dataflow pathway of a risk exposure component 21, 22, 23, etc. The resource pooling system 1 further comprises said predefined multi-dimensional table 7 comprising a multi-layered data structure with predefined searchable acute and/or chronic elderly illness 71, . . . , 75 parameters for triggering by means of elderly illness triggers 31, . . . , 35 in the patient dataflow pathway 213, 223, 233. It is to be noted that at least one of the elderly illness triggers 31, . . . , 35 is based upon the classification of a risk exposure components 21, 22, 23, i.e. an elderly person, as being within a particular “state”, i.e. parameter state, having lost the ability to do certain physical activities due to the effect of ageing. Thus, measuring parameters indicating one of said acute and/or chronic elderly illnesses 71, . . . , 75, do not need to indicate a medical illness” at the same time, but can be simply a consequence of the ageing of a risk exposure component 21, 22, 23. The predefined parameters of a first-layer data structure 71 of said predefined multi-dimensional table 7 provide measuring parameters for the occurrence of serious elderly illnesses. The predefined parameters of a second--layer data structure 72 of said predefined multi-dimensional table 7 provide measuring parameters for the occurrence of an acute broken bone trauma. The predefined parameters of a third-layer data structure 73 of said predefined multi-dimensional table 7 provide measuring parameters for long-term care indications. The predefined parameters of a fourth-layer data structure 74 of said predefined multi-dimensional table 7 provide measuring parameters for assisted living indications. The predefined parameters of a fifth-layer data structure 75 of said predefined multi-dimensional table 7 provide measuring parameters for extended assistance indications. The trigger parameters of acute and/or chronic elderly illnesses 71, . . . , 75 parameters can indicate the occurrence of dementia and/or heart attack and/or cancer and/or a stroke and/or coronary artery by-pass surgery, Alzheimer's disease and/or blindness and/or deafness and/or kidney failure and/or major organ transplant and/or multiple sclerosis and/or HIV/AIDS contracted by blood transfusion or during an operation and/or

[0032] Parkinson's disease and/or paralysis of limb and/or terminal illness and/or any other definable and measurable elderly illnesses in the elderly patient dataflow pathway 213, 223, 233. The latter can simply comprise the “need for care” as measured by the ability to perform basic activities of daily living (e.g. washing, dressing, eating), i.e. is not a classical illness, but a measurable defined risk-transfer event (insured event). The triggers 31, . . . , 35 are uni- or bidirectionally connected with the predefined multi-dimensional table 7 of elderly illnesses 71, . . . , 75, wherein the triggering 31, . . . , 35 is performed based on the elderly illness 71, . . . , 75 parameters stored in the predefined multi-dimensional table 7 by means of the multi-layered data structure. The elderly illness triggers 31, . . . , 35 can comprise a trigger for triggering the occurrence of measuring parameters indicating dementia based on measuring parameters associated with the permanent clinical loss of the ability to remember and/or reason and/or perceive, understand, express and give effect to ideas in the patient dataflow pathway 213, 223, 233. The elderly illness triggers 31, . . . , 33 can further comprise a trigger for triggering measuring parameters as exclusion parameters, indicating e.g. alcohol and/or drug abuse in the patient dataflow pathway 213. 223, 233, and/or triggering ABS (atomic, biological or chemical weapons) terrorism and/or active participation in war etc., wherein upon triggering measuring parameters indicating alcohol and/or drug abuse, the related risk exposure component (21, 22, 23, . . . ) is rejected from pooling of the risk and resources by means of the resource pooling system 1.

[0033] As also schematically illustrated in FIG. 1, the resource pooling system 1 includes a data storing module for capturing the risk-related component data and multiple functional modules; e.g., the payment receiving modules 4, the core engine 3 with the triggers 31, . . . , 33, the assembly module 5 or the operating module 30. The functional modules can be implemented at least partly as programmed software modules stored on a computer-readable medium, connected as fixed or removable means to the processor(s) of system 1 or to associated automated systems. One skilled in the art understands, however, that the functional modules can also be fully implemented by means of hardware components, units and/or appropriately implemented modules. As illustrated in FIG. 1, the system 1 can be connected via a network, such as a telecommunications network, to the payment-receiving module 4. The network can include a wired or wireless network; e.g., the Internet, a GSM network (Global System for Mobile Communication), a UMTS network (Universal Mobile Telecommunications System) and/or a WLAN (Wireless Local Region Network), and/or dedicated point-to-point communication lines. In any case, the technical electronic money schemes for the present system comprise adequate technical, organizational and procedural safeguard means in order to prevent. contain and detect threats to the security of the scheme, particularly the threat of counterfeits. The resource pooling system 1 further comprises all necessary technical means for electronic money transfer and association, for example initiated by one or more associated payment-receiving modules 4 over an electronic network. The monetary parameters can be based on all possible electronic and transferable means such as e-currency, e-money, electronic cash, electronic currency, digital money, digital cash, digital currency, or cyber currency, etc., which can only be exchanged electronically. The payment data store 6 provides the means for associating and storing monetary parameters associated with a single one of the pooled risk exposure components 21, 22, 23. The present invention can involve the use of the aforementioned networks, such as computer networks or telecommunications networks, and/or the internet and digital stored value systems. Electronic funds transfer (EFT), direct deposit, digital gold currency and virtual currency are further examples of electronic money. Also, the transfer can involve technologies, such as financial cryptography and technologies enabling the same. For the transaction of the monetary parameters, it is preferable for hard electronic currency to be used without the technical possibilities for disputing or reversing any charges. The resource pooling system 1 for example supports non-reversible transactions, The advantage of this arrangement is that the operating costs of the electronic currency system are greatly reduced by not having to resolve payment disputes. However, this way, it is also possible for electronic currency transactions to clear instantly, making the funds available to the system 1 immediately. This means that using hard electronic currency is more akin to a cash transaction, However,. the use of soft electronic currency is also conceivable, such as currency that allows for the reversal of payments, for example having a “clearing time” of 72 hours, or the like. The electronic monetary parameter exchange method applies to all connected systems and modules related to the resource pooling system 1 of the present invention, such as the payment receiving module 4. The monetary parameter transfer to the resource pooling system 1 can be initiated by a payment-receiving module 4 or on request by the resource pooling system 1.

[0034] The resource pooling system 1 comprises an event-driven core engine 3 comprising elderly illness triggers 31, . . . , 35 for triggering component-specific measuring parameters in the patient dataflow pathway 213, 223, 233 of the assigned risk exposure components 21, 22, 23, etc., i.e., the insured elderly person, where insured means a person transferring risk to a unit in exchange for resources, The patient dataflow pathway 213, 223, 233 can for example be monitored by the resource pooling system 1, capturing patient-related measuring parameters of the patient dataflow pathway 213, 223, 233 at least periodically and/or within predefined time periods. The patient dataflow pathway 213, 223, 233 can for example also be dynamically monitored by the resource pooling system 1, by triggering patient-measuring parameters of the patient dataflow pathway 213, 223, 233 transmitted from associated measuring systems. By triggering the patient dataflow pathway 213, 223, 233, which comprises dynamically recorded measuring parameters of the concerned risk exposure components 21, 22, 23, etc., the system 1 is able to detect the occurrence of an elderly illness and dynamically monitor the different stages during the progress of the elderly illness in order to provide appropriately adapted and gradated risk protection for a specific risk exposure component 21, 22, 23, etc. Such a risk protection structure is based on received and stored payments 214, 224, 234 from the related risk exposure component 21, 22, 23, etc. and/or related to the total risk of the resource pooling system, 1 based on the overall transferred elderly illness risks of all pooled risk exposure components 21, 22, 23, etc.

[0035] In FIG. 1, the block diagram shows the possible trigger stages, wherein the elderly illness triggers 31, . . . , 35 can for example comprise a trigger for triggering the occurrence of the measuring parameters, indicating a heart attack and/or cancer and/or a stroke and/or coronary artery by-pass surgery in the patient dataflow pathway 213, 223, 233. Further, the elderly illness triggers 31, . . . , 35 can comprise a trigger for triggering the occurrence of measuring parameters indicating Alzheimer's disease, dementia, blindness, deafness, kidney failure, major organ transplant, multiple sclerosis, HIV/AIDS contracted by blood transfusion or during an operation, Parkinson's disease, paralysis of limb, terminal illness in the patient dataflow pathway 213, 223, 233. A significant portion of cases of occurrences of elderly illness can be related to heart attack, stroke and cancer, and dementia, The average age of individuals 21, 22, 23 at which an elderly illness can be detected in the patient dataflow pathway 213, 223, 233 is for instance over 50 years, depending on the system's definition of the pooled elderly persons; however, this depends on the development of diagnostic and other medical means. Normally, the statistics obey the same factors for all countries where statistics are maintained. However, it is of great concern to observe the increasing number of elderly illness occurrences—particularly regarding prolonging independent living cases.

[0036] Earlier diagnosis due to better diagnostic equipment may be partially responsible for these figures. Therefore, to ensure proper operation of the resource pooling system 1, the definitions of the stored trigger parameters 71, . . . , 75 of elderly illness in the trigger table 7 can be dynamically adapted based on a monitoring of changing risks in the risk exposure components 21, 22, 23. In particular, the trigger parameters 71, . . . , 75 can be region-specific, country-specific and/or specific of the total pooled risk, adapted or changed. New elderly illnesses 71, . . . , 75 can be added, while others can be deleted from the triggerable list of elderly illnesses by the resource pooling system, owing to better treatments or other changed environmental conditions. In one alternative embodiment, the elderly illness triggers 31, . . . , 33 can be dynamically adapted by means of an operating module 30, based on time-correlated incidence dates of an elderly illness condition and/or diagnosis or treatment conditions indicating improvements in diagnosis or treatment.

[0037] In addition to the adaptation of the triggers 31, . . . , 35, the amount of the payments requested from the risk exposure components 21, 22, 23 can be adjusted accordingly by the resource pooling system 1. Therefore, the receiving and preconditioned storage 6 of payments 214, 224, 234 from risk exposure components 21, 22, 23, etc. for the pooling of their risks can be determined dynamically, based on total risk 50 and/or the likelihood of the risk exposure of the pooled risk exposure components 21, 22, 23, etc. To improve operational and functional security of the resource pooling system 1 even further, the number of pooled risk exposure components 21, 22, 23, etc. can be dynamically adapted by means of the resource pooling system 1 to a range where non-covariant, occurring risks covered by the resource pooling system 1 affect only a relatively small proportion of the total pooled risk exposure components 21, 22, 23, etc. at a given time.

[0038] The total risk 50 of the pooled risk exposure components 21, 22, 23, etc. can comprise several risk contributions, as it can comprise a first risk contribution 511 of each pooled risk exposure component 21, 22, 23, etc. that is associated with risk exposure in relation to the occurrence of serious elderly illnesses, a second contribution 521 of each pooled risk exposure component 21, 22, 23, etc. that is associated with the occurrence of an acute broken bone trauma, a third contribution 531 of each pooled risk exposure component 21, 22, 23, etc. that is associated with the need for long-term care, a fourth contribution 541 of each pooled risk exposure component 21, 22, 23, etc. that is associated with the need for assisted living support, and a fifth contribution 551 of each pooled risk exposure component 21, 22, 23, etc. that is associated with the need for extended assistance. The risk contributions 511, . . . , 551 are reflected by the multi-dimensional trigger-table 7 with the multi-layered data structure with predefined searchable acute and/or chronic elderly illnesses 71, . . . , 75 parameters. The triggering parameters 71, . . . , 73 of the covered elderly illnesses are comprised and stored in a predefined multi-dimensional table 7, such as an appropriately structured hash table of elderly illnesses 71, . . . , 75, respectively elderly illness parameters 71, . . . , 75. The elderly illness losses occur as a consequence of the triggering, respectively diagnosis of risk exposure components 21, 22, 23, etc. with regard to one of the searchable elderly illnesses; i.e., the possible need of a risk exposure component 21, 22, 23, etc. to be covered by the pooled resources of the resource pooling system 1 is linked to the risk of the occurrence of on elderly illness requiring complex medical treatment and handling, The total risk 50 of the pooled risk exposure components 21, 22, 23, etc. can also comprise further risk contribution not mentioned here; i.e., up to the i-th risk contribution, associated with risk exposure in relation to a second and/or subsequent elderly illness(es).

[0039] As mentioned, the resource pooling system 1 comprises an event-driven core engine 3 comprising elderly illness triggers 31, . . . , 35 triggering measuring values in patient dataflow pathways 213, 223, 233 of the connected risk exposure components 21, 22, 23, etc. If an occurrence of an acute or chronic elderly illness 71, . . . , 75 on the patient dataflow pathway 213, 223, 233 of a risk exposure component 21, 22, 23, . . . is triggered by exceeding one of the predefined searchable acute and/or chronic elderly illnesses 71, . . . , 75 parameters, a corresponding trigger-flag is set via the resource pooling system 1 and a parametric transfer of payments is assigned to that corresponding trigger-flag, wherein a loss associated with the acute or chronic elderly illness 71, . . . , 75 is covered separately by the resource pooling system 1 based on the respective trigger-flog and based on the received and stored payment parameters 214, 224, 234 from risk exposure components 21, 22, 23 by at least the one parametric payment transfer from the resource pooling system 1 to the risk exposure component 21, 22, 23, etc. The parametric payment transfer can comprise electronic and non-electronic cash transfer as well as non-cash payment transfers, as e.g. provisions of services or tangible goods. If multiple occurrences of a second or subsequent elderly illness 71, 72, 73 are triggered on the patient dataflow pathway 213, 223, 233 of a risk exposure component 21, 22, 23, i.e., if triggering of an occurrence of a first or second or subsequent elderly illness 71, . . . , 75 goes into effect in the patient dataflow pathway 213, 223, 233, thereby worsening the ability of the elderly person to live independently, respectively increasing his/her need for assisted living, adapted trigger-flags are set via the resource pooling system l and an adapted parametric draw-down or predefined transfer of payments is assigned to this corresponding trigger-flag. A loss associated with the first or second or subsequent elderly illness(es) 71, . . . , 73 is separately covered by the resource pooling system 1, based on the respective trigger-flag and the received and stored payment parameters 214, 224, 234 from risk exposure components 21, 22, 23 by the parametric draw-down or predefined transfer from the resource pooling system 1 to the risk exposure component 21, 22, 23, etc. The payment receiving module 4 can, as an input device, comprise one or more data processing units, displays and other operating elements, such as a keyboard and/or a computer mouse or another pointing device. As mentioned previously, the receiving operation of the payments with regard to the risk exposure components 21, 22, 23 is monitored based on the stored component-specific payment parameters in the payment data store 6. The different components of the resource pooling system 1, such as the payment receiving module 4 with the core engine 3 and the assembly module 5, can be connected via a network for signal transmission. The network can for example comprise a telecommunications network, such as a wired or wireless network, e.g., the Internet, a GSM network (Global System for Mobile Communications), a UMTS network (Universal Mobile Telecommunications System) and/or a WLAN (Wireless Local Area Network), a Public Switched Telephone Network (PSTN) and/or dedicated point-to-point communication lines. The payment receiving module 4 and/or core engine 3 and the assembly module 5 can also comprise a plurality of interfaces for connecting to the telecommunications network adhering to the transmission standard or protocol. As an alternative embodiment, the payment receiving module 4 can also be implemented as an external device relative to the resource pooling system 1, which provides the risk transfer service via the network for signal transmission, e.g., by a secured data transmission line.

[0040] A parametric payment is transferred by triggering the occurrence of the elderly illness 71, . . . , 75 by means of the elderly illness trigger of the core engine 3, thus triggering the measuring parameters of the specific risk exposure component 21, 22, 23 in the related patient dataflow pathway 213, 223, 233. The first, second and third parametric payments can be denoted in “units” operationally defined by means of the risk-transfer system 1. The amount of those units can be either set as fixed running parameters of the system 1 for the duration of the transferred risks or any other defined time frame, or dynamically adapted based upon possibly changing environmental boundary conditions, such as medical or therapeutic costs, or based upon the total pooled resources by means of the system 1. The changing of the environmental boundary conditions can be triggered dynamically or captured by the system 1. One “unit” can be assigned to correspond to an equivalent in a specific currency (e.g., Euros, dollars or Swiss francs). The core engine 3, analogously to the resource pooling system 1 and the other components of the system, is implemented based on underlying electronic components, steering codes and interacting interface devices, such as appropriate signal generation modules or other modules interacting electronically by means of appropriate signal generation between the different modules, devices, or the like. For example, a parametric payment of 10,000 can be transferred by triggering, by means of the first pillar elderly illness trigger 31, the occurrence of measuring parameters indicating the occurrence of a serious elderly illness, such as first heart attack, stroke, malignant cancer, smaller incidence of ductal carcinoma in situ (DCIS), early prostate carcinoma, dementia, etc. Another parametric payment can be transferred by triggering, by means of the second pillar elderly illness trigger 32, the occurrence of measuring parameters indicating the occurrence of an acute broken bone trauma, wherein the parametric payment comprises 1,000 per accident once per year, for hip or limb fracture with a maximum benefit of 5,000. A further parametric payment can be transferred by triggering, by means of the third pillar elderly illness trigger 33, the occurrence of measuring parameters indicating the need for initial long-term care, wherein the parametric payment for example comprises up to 2,500 per month to cover care costs when going into a care home for a maximum of six months. Another parametric payment can be transferred by triggering, by means of the fourth pillar elderly illness trigger 34, the occurrence of measuring parameters indicating the need for extended assistance services, concierge services to arrange independent care advice, etc. Finally, a further parametric payment can be transferred by triggering, via the fifth pillar elderly illness trigger 35, the occurrence of measuring parameters indicating the need for assisted living covers, wherein the parametric payment can comprise 18,000 for care at private home benefits and home adaption, with a maximum care at private home benefit payout of 1,000 per month up to a total assigned parametric amount and adaptions of up to 10,000. If a care at private home benefit is received, there may be a further maximum of 2,000 for respite care.

[0041] In the case of dementia, the elderly illness triggers 31, . . . , 35 can comprise a trigger for triggering the occurrence of measuring parameters indicating dementia based on measuring parameters associated with the permanent clinical loss of the ability to remember and/or reason and/or perceive, understand, express and give effect to ideas in the patient dataflow pathway 213, 223, 233. The triggering measuring parameters indicating dementia can also comprise physical parameters and/or psychological parameters and/or biochemical parameters and/or cognitive factors based on adrenal exhaustion factors and/or food and chemical reaction factors and/or nutritional deficiency factors and/or stress factors and/or depression factors, or denial factors, indicating confirmed impairment of cognitive functions. In the case of stroke, the elderly illness triggers 31, 32, 33 can comprise a trigger for triggering the occurrence of measuring parameters indicating stroke based on measuring parameters associated with the possibly permanent cognitive or motor impairment and/or indicating the time of an acute stroke episode in the patient dataflow pathway 213, 223, 233.

[0042] Another parametric payment can be transferred by triggering measuring parameters in the patient dataflow pathway 213, 223, 233 indicating the initiation of long-term care phase by means of the elderly illness trigger of the core engine 3. This is achieved by triggering 33, in the case of an acute elderly illness 71, . . . , 75, an acute treatment phase of the serious elderly illness 71, . . . , 73 or, in case of a chronic elderly illness 71, . . . , 73, by triggering 33 of a first treatment phase of the chronic elderly illness 71, . . . , 73. For example, acute or first treatment phase parameters indicating surgery and/or chemotherapy and/or radiotherapy and/or reconstructive surgery can be triggered in the patient dataflow pathway 213, 223, 233 via the elderly illness trigger 33 of the core engine 3, For example, the parametric payment can only be transferred by triggering 33 acute or first treatment phase parameters, indicating surgery and/or chemotherapy and/or radiotherapy and/or reconstructive surgery. In the example of dementia, the elderly illness triggers for triggering 33 the first long-term care treatment phase of the chronic elderly illness 71, . . . , 75 can comprise a first treatment phase parameter indicating psychiatric or old-age in--patient care associated with the risk exposure component 21, 22, 23, etc. comprising acute in-patient admission parameters as a result of deterioration in dementia status requiring urgent treatment. In the example of stroke, the elderly illness triggers for triggering 33 the first long-term care treatment phase of the chronic elderly illness 71, . . . , 75 can comprise a first long-term care treatment phase parameter indicating a measured time interval of the risk exposure component 21, 22, 23, etc. spent in the hospital due to the triggered stroke.

[0043] Finally, as an alternative, a parametric payment is transferred, in the case of an acute elderly illness 71, . . . , 75, only by triggering 33 recovery phase parameters and/or terminal prognosis parameters and/or an ongoing care or management phase. in case of dementia, the elderly illness triggers 31, . . . , 35 for triggering an ongoing care or management phase of the chronic elderly illness 71, . . . , 73 can comprise ongoing core or management phase parameters indicating permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or ongoing care or management phase parameters indicating permanent cognitive and/or motor impairment requiring constant supervision by another person. In case of stroke, the elderly illness triggers 31, . . . , 35 for triggering an ongoing care or management phase of the chronic elderly illness 71, . . . , 75 can comprise ongoing care or management phase parameters indicating permanent impairments of the cognitive functions and/or permanent cognitive and/or motor impairment requiring continuous supervision by another person and/or permanent cognitive and/or motor impairment requiring constant supervision by another person. For ongoing treatment, the allocated total parametric payment can be determined at least based on the risk-related component data 211, 221, 231 and/or on the likelihood of the risk exposure for one or a plurality of the pooled risk exposure components 21, 22, 23, etc. based on the risk-related component data 211, 221, 231 and wherein a first portion is transferred up to predefined percentage of said total payment sum and the following portions are transferred up to the residual part given by said total payment sum. Such an exemplary payment draw-down, as it can be provided by the resource pooling system 1 in the event of triggering of an elderly illness at a risk exposure component, is illustrated in the diagram of FIG. 1.

[0044] As mentioned, the triggers 31, . . . , 35 are uni- or bidirectionally connected with the predefined searchable table 7 of acute or chronic elderly illnesses 71, . . . , 75, wherein the triggering 31, . . . , 35 is performed based on the acute or chronic elderly illness 71, . . . , 75 parameters stored in the predefined searchable table 7. The predefined searchable table 7 is multi-dimensionally structured, for instance as a multidimensional hash table, by means of the multi-layered data structure with predefined searchable acute and/or chronic elderly illness 71, . . . , 75 parameters for triggering by means of elderly illness triggers 31, . . . , 35 in the patient dataflow pathway 213, 223, 233. Each elderly illness 71, . . . , 75 selectable in the multidimensional table has assigned triggerable measuring parameters according to the trigger-step to be performed by means of the multi-pillar trigger 31, . . . , 35 or the resource pooling system 1, i.e., trigger 31 (serious elderly illness) and/or trigger 32 (acute broken bone trauma) and/or trigger 33 (initial long-term care (LTC)) and/or trigger 34 (assistance services) and/or trigger 35 (assisted living benefits). The stored trigger parameters of the multi--pillar trigger 31, . . . , 35 of the predefined searchable table 7 can for example comprise the mentioned trigger dependencies. Furthermore, as an alternative embodiment, the predefined searchable table 7 can also comprise a predefined amount for the various parametric payments assigned to the corresponding trigger 31, . . . , 35. The amount can be fixed for a time period contracted with the risk-exposed component. However, in a preferred alternative embodiment, the parametric payments transferable from the pooled resources via the resource pooling system 1 are dynamically adaptable by the system 1, for example based on the pooled resources or based upon dynamically-checked changing medical conditions or other boundary conditions to the system 1, respectively to the associated and transferred risks.

[0045] The predefined searchable acute and/or chronic elderly illness 71, . . . , 75 parameters for triggering by means of elderly illness triggers 31, . . . , 35 in the patient dataflow pathway 213, 223, 233 comprise said predefined values and trigger measuring parameter definition. For example, a heart attack of specified severity can be defined as death of heart muscle, due to inadequate blood supply, that has resulted in all of the following evidence of acute myocardial infarction: Typical clinical symptoms are for example characteristic chest pain, and/or new characteristic in electrocardiographic changes and/or the characteristic rise of cardiac enzymes or troponins recorded at the following levels or higher, wherein troponin T>200 ng/L (0.2 ng/ml or 0.2 ug/L) and troponin I>500 ng/L 10.5 ng/ml or 0.5 ug/L). The triggered evidence must show a definite acute myocardial infarction. As for the above definition, related elderly illnesses are sometimes not covered by the trigger, such as other acute coronary syndromes or angina without myocardial infarction. Such related elderly illnesses can be captured by other correspondingly adapted triggers. Another example is the trigger measuring parameters for stroke—resulting in permanent symptoms. The definition can be given as death of brain tissue due to inadequate blood supply or haemorrhage within the skull resulting in permanent neurological deficiency with persisting clinical symptoms. Again, there are related elderly illnesses which have to be measured and captured by separate triggers, since for the above definition, the following elderly illnesses are not covered: Transient ischaemic attack and/or traumatic injury to brain tissue or blood vessels, and/or death of tissue of the optic nerve or retina/eye stroke. A last example is acute broken bone trauma, In this example, the trigger measuring parameters may simply comprise a listing for measuring different bone fractures, such as closed fracture of the skull, open fracture of the skull, fracture of the vertebra, fracture of the shoulder blade, fracture of the jaw, fracture of the sternum, fracture of the pelvis, fracture of the wrist, fracture of the hand, fracture of the upper leg, fracture of the knee, fracture of the lower leg, fracture of the arm, fracture of the cheekbone, fracture of the foot, fracture of the ankle, fracture of the ribs, and fracture of the collar bone. The trigger parameters of the system 1 may be tuned, so that the system only triggers and transfers the fracture cover benefit to the risk exposed unit 21, 22, 23 for the following fractures as defined in official definition publications, such as ‘Black's Medical Dictionary’ (39th edition): comminuted, complicated, compound, depressed, greenstick, pathological and simple, and the risk-cover transfer will not be performed for any other type of fracture. If more than one of the above fractures occurs at any time, the system may only transfer one parametric fracture cover benefit for one of the fractures, or a plurality of parametric payments. Furthermore, time limits or thresholds can be set for the system 1, where the system 1 only will transfer parametric payments for one fracture suffered during any 12 month period, for instance. The first 12 month period can for example begin on the commencement date, and then each subsequent 12 month period will begin on each anniversary of the commencement date.

[0046] Finally, in a further specified alternative embodiment, an independent verification elderly illness trigger of the resource pooling system 1 can be activated in the event of triggering of the occurrence of indicators for elderly illness 71, . . . , 75 in the patient dataflow pathway 213, 223, 233 of a risk exposure component 21, 22, 23, etc. by means of the elderly illness trigger 31, and wherein the independent verification elderly illness trigger is additionally triggering with regard to the occurrence indicators for elderly illness 71, . . . , 75 in an alternative patient dataflow pathway with independent measuring parameters from the primary patient dataflow pathway 213, 223, 233 to verify the occurrence of the elderly illness 71, . . . , 73 at the risk exposure component 21, 22, 23, etc. As an alternative, the parametric draw-down or predefined transfer of payments is only assigned to the corresponding trigger-flag if the occurrence of the elderly illness 71, . . . , 73 at the risk exposure component 21, 22, 23, etc. is verified by the independent verification elderly illness trigger.