Patient Data Triggered Pooling -System For Risk Sharing of Cronic Critical
Illness Risks Of Cohorts of Elderly Persons And Corresponding Method
Thereof
Field of the Invention
The present invention relates to critical illness insurance systems for providing
risk sharing of critical illness risks associated with elderly persons by providing a dynamic
self-sufficient risk protection for the risk exposure components by means of resource
pooling system. In particular, the invention relates to automated event-driven systems
triggering on the patient dataflow pathway.
Background of the Invention
These days, there is significant risk exposure related to many aspects in life
and non-life sectors. Risk exposed units a s any kinds of objects, individuals, corporate
bodies and/or legal entities, necessarily are confronted with many forms of active and
passive risk management to hedge and protect against the risk of certain losses and
events. In the prior art, one way to address such risk of loss is based on transferring and
pooling the risk of loss from a plurality of risk exposed entities to a dedicated pooling
entity. In essence, this can be executed by effectively allocating the risk of loss to this
pooling unit or entity by pooling resources of associated units, which are exposed to a
certain risk. In case, that one of the units is hit by a n event occurring related to a
transferred risk, the pooling entity directly intercepts the loss or damage caused by the
event by transferring resources from the pooled resources to the affected unit. Pooling
of resources can be achieved by exchanging predefined amounts of resources with
the resource-pooling system; e.g. payments or premiums to be paid, for the transfer of
the risk. This means that predefined amounts of resources are exchanged for the other
unit assuming the risk of loss.
For living individuals, a special kind of risk is based on the risk of loss of life
and related possible losses; i.e., losses that occur a s a consequence of the death of
that individual. Such risks are traditionally handled by so-called life insurance systems. To
administer a loss for benefits provided by a life insurance policy, a substantial amount of
information must be collected and managed by the pooling entity in order to allow risktransfer.
Appropriate documentation must be identified, captured and analyzed, such
a s death certificates or medical provider verification of condition or service in the cases
of health/supplementary health. One important problem arises by the fact that life
insurance methods are triggered by the death of the unit, which risk is transferred.
However, often problems arise for a n individual before then, in that financial resources
were threatened by losses occurring prior to death a s a consequence of the events
leading to death. This is mostly the case when the individual suffers from potentially
terminal disease, like malignant cancer, which will inevitably lead to the death of the
individual. Typically, the patient is confronted with increasing costs for medical
treatment or other related costs a s travel expenses or additional heating costs, but also
by the decreasing ability to earn the money needed to fulfill their monthly financial
needs. This may lead to the necessity of having to make many sacrifices; e.g. not be
able to provide sufficient financial support for care, selling their house and filling for
bankruptcy. All these financial concerns contrariwise impacted on their health.
Recovery is delayed, stress additionally aggravates poor health, and even sometimes
ends in suicide.
As a solution, resource-pooling systems were developed that cover such "critical
illnesses", where the resource-pooling unit operated by the insurer provides a lump sum
cash payment if the risk-exposed unit, which is, seen from the perspective of the insurer
the policyholder, is diagnosed with one of the critical illnesses listed in a defined table of
transferred risk. The operation of the resource-pooling system may also be structured to
pay out regular income, and the payouts may also benefit the policyholder undergoing
a surgical procedure, for example, having a heart bypass operation. Typically, such
systems require the risk-exposed unit to survive a minimum number of days (the socalled
survival period) from when the illness was first diagnosed. The survival period can
vary; however, 1 days is the most commonly used survival period used. In the
Australian market, survival periods are set between 8 - 14 days. However, systems a s
e.g. indemnity based o n accelerated payment and stand-alone products, are also
known. The terms, a s defined for the risk transfer, typically contain specific predefined
triggers or rules to be applied that provide the basis for the determination of when a
diagnosis of a critical illness is considered valid. Terms for survival periods may also
define parameters providing that the diagnosis need be made by a physician who
specializes in the treatment of that illness or condition or name specific tests, e.g. ECG
changes in case of a myocardial infarctions, that confirm the diagnosis. In many
markets, the trigger parameters for many of the diseases and conditions have become
standardized; thus typically resource-pooling systems would use the same definition (cf.
stand alone products and accelerated critical illness systems). The standardization of
the critical illness definitions serves many purposes, including better clarity of coverage
for the risk-exposed units and greater comparability of terms and conditions for risk
transfers among different resource-pooling systems. Such terms and conditions are
often defined in the policy covering the risk transfer. For example, in the UK the
Association of British Insurers (ABI) has issued a Statement of Best Practice, which
includes a number of standard definitions for common critical illnesses. The prior art also
provides for alternative methods of critical illness risk transfer, other than the lump sum
cash payment method. These critical illness insurance systems can directly pay health
providers (as e.g. "tiers payant" systems) for the treatment costs involving critical and
life-threatening illnesses that are covered by the policyholder's insurance policy,
including fees for specialists and procedures at a select group of high-ranking hospitals
up to a certain amount per course of treatment a s set out in the policy, but also transfer
the payment to the customer.
In the prior art, critical illnesses are typically covered by critical illness risk transfer; these
are heart attack, cancer, stroke and coronary artery by-pass surgery. Examples of other
conditions that might be covered include: Alzheimer's disease, blindness, deafness,
kidney failure, major organ transplant, multiple sclerosis, HIV/AIDS contracted by blood
transfusion or during a n operation, Parkinson's disease, paralysis of limb, terminal illness.
One of the problems of the risk transfer system a s provided by the prior art lies in the
fact that the incidence of a condition may vary (i.e. in- or decrease) over time, and
that diagnosis and treatment may improve over time, that the financial need to cover
some illnesses deemed critical a decade ago is no longer considered necessary today.
Likewise, some of the conditions covered today may no longer need to be covered a
decade or so from now. It is very difficult to adapt the prior art systems to such
changing conditions. What is clear is the fact that the financial hardship at the time of
diagnosis and afterwards increases during the course of treatment, which seldom can
be meet by the present systems. Furthermore, operating the systems of the prior art
requires a high level of human resources, because these systems cannot be
adequately automated. Therefore, a large quantity of the pooled resources are used
by the resource-pooling system itself to administer the risk transfer, which makes the risk
transfer expensive for the risk-exposed unit. Finally, another problem comes from the
fact that, due to the medical progress, many patients no longer die but can survive for
many years after undergoing treatment for a heart attack, stroke and cancer. Due to
the long survival period, such individuals, who were struck already once by a critical
illness, continue to be exposed to the risk of a second or consequential occurrence of a
critical illness. In fact, the risk typically does not decrease, since the health of these
patients is already weakened by the first incidence of a critical illness. Since critical
illnesses are traditionally meant to lead to death, the risk involving such individuals, who
may be affected by a second or even more critical illnesses is no longer covered by
the resource-pooling system. Therefore, although the patient survived his first bout with
a critical illness, he may, a t least financially, not survive the second time.
Another limiting feature of traditional critical illness insurance systems is related to
mandatory boundary conditions for these systems given by age restrictions for critical
illness risk transfer. Traditional systems normally provide a child procedure associated to
risk transfer of individuals for example in the age of 30 days to 17 years, and for example
a adult procedure associated to risk transfer of individuals between 18 years to 50
years. Above the upper limit (here 50 years), the system does not allow a new individual
to pool resources in exchange for risk transfer of critical illness. In some systems, the
actual risk cover is longer, e.g. up to the age of 65 year. However, the individual also in
those cases must have applied to the system before the first upper limit (here 50 years).
For example for UK, individuals can usually apply for cover up to the age of 65 with
cover expiring a t 75. Therefore, the know system for critical illness risk transfer necessarily
are restricted to age conditions a s boundary requirements. Older individuals cannot
anymore be captured by these systems. Another disadvantage of the state of the art
systems, which is especially relevant for risk transfer of critical illness risk for individuals in
older age, is already mentioned above. Advances in health care, especially in the
intensive care unit (ICU) health care, have enabled more patients to survive acute
critical illness, but created a new population who are chronically critically ill. Patients
with chronic critical illness have persistent respiratory failure, dysfunction of other
organs, and complications including neuropathy/myopathy, anemia, pressure ulcers,
and recurrent infections. For example, it could be imaginable that one class of chronic
critical illness can be identified by the placement of tracheotomy for prolonged
mechanical ventilation. It is a severe condition, imposing heavy burdens on patients,
families, professional caregivers, and the health care system. Distressing symptoms are
common, resource utilization and costs are enormous, return to the community is rare,
and 6-mon†h mortality rates exceed those for most malignancies. An other class of
problematic chronic critical illness is related to dementia.
Dementia is defined a s a serious loss of global cognitive ability in a previously
unimpaired person, beyond what might be expected from normal aging. It may be
static, the result of a unique global brain injury, or progressive, resulting in long-term
decline due to damage or disease in the body. Although dementia is far more
common in the geriatric population (about 5% of those over 65 are said to be
involved), it can occur before the age of 65, in which case it is called "early onset
dementia". Dementia is not a classical disease, but is indicated typically by set of nonspecific
symptoms. Affected cognitive areas can be memory, attention, language, and
problem solving. Normally, symptoms must be present for at least six months to support
a diagnosis. Cognitive dysfunction of shorter duration is called delirium. In advanced
stages of dementia, subjects can be disoriented in time (not knowing the day, week, or
even year), in place (not knowing where they are), and in person (not knowing who
they and/or others around them are). Dementia is classified a s either reversible or
irreversible, depending upon the etiology of the disease. It is important to note that
dementia is not reversible in the sense that the system (human) undergoing the process
can be returned to its original state, i.e. can be cured to a state without dementia. In
the present state of neurological research, dementia is not curable a s such. However,
there can be specific conditions where the clinical symptoms mimic or closely mimic
those suffered by those with dementia. Reversible used in connection with dementia
means that these conditions are reversible. However, a s mentioned, it is not the case
with dementia itself, and the condition/symptoms most probably will deteriorate over
time. Nevertheless that there is no known cure, some treatments can potentially also
slow down the process. Concerning reversibility, fewer than 10% of cases of dementia
are due to causes that may be reversed with treatment. Some of the most common
forms of dementia are: Alzheimer's disease, vascular dementia, frontotemporal
dementia, semantic dementia and dementia with Lewy bodies. A patient can exhibit
two or more dementing processes at the same time, a s none of the known types of
dementia protects against the others. About 10% of people with dementia have what is
known a s mixed dementia, which may be a combination of Alzheimer's disease and
multi-infarct dementia. As for other critical illnesses, like malignant cancer, also in the
case of dementia, especially in advanced stages of dementia, the patient is exposed
to the same problems a s above mentioned for critical illnesses. The patient will be
ό
confronted with increasing costs for medical treatment or other related costs, and
further by the decreasing ability to earn the money needed to fulfill their financial
needs. Cost estimations of treating the chronically critically ill in the United States
already exceed $20 billion and are increasing. Therefore, it is a need, especially for
older people, to provide the possibility for risk transfer related to chronic critical illnesses
without a n age restriction, excluding the age group, which need risk transfer most for
chronic critical illnesses.
There is a further problem, why traditional risk transfer systems related to critical illnesses
fail to provide appropriate mechanism in relation to dementia a s critical illness, i.e.
resource-pooling systems for risk transfer associated with elderly. As mentioned, the
traditional critical illness systems are triggered by the occurrence of a critical illness.
After the pay out of a n associated lump sum, the insured is not any more covered by
the risk-transfer system. However, risk factors for dementia increase after critical illness
diagnosis in elderly patient. Unfortunately, hospitalization increases the risk of a
subsequent diagnosis of dementia. Studies show that illness requiring hospitalization and
treatment in the intensive care unit (ICU) due to infection or severe sepsis, neurological
dysfunction, such a s delirium, or acute dialysis are all independently associated with a n
increased risk of a subsequent diagnosis of dementia (cf. C. Guerra et al., Risk factors
for dementia after critical illness in elderly medicare beneficiaries, Critical Care 201 2,
16:R233).DThe studies show that over the three years of follow-up of the occurrence of
a critical illness, dementia was newly diagnosed in almost 18% of the patients who
received intensive care and survived to hospital discharge. The results of the studies are
significant, since even patients with previous indications of cognitive impairment for
whom dementia could have been a n escalation of a pre-existing condition were
excluded from the studies (cf . fig. 8, C. Guerra et al., Critical Care 201 2 16:R233,
doi:10.1 186/ccl 1901 ) . The studies clearly indicate that statistically increasing age is very
strongly associated with diagnosis of dementia following ICU. The risk a t 75 was more
than double that of the 66 to 69 year olds. And this rose to more than five times the risk
for those age 85 and older. Women had a marginally higher risk than men and, a s other
studies have shown, race was also important to risk. Length of stay in ICU was not a
factor nor was the need for mechanical ve ntilatio n (cf. fig. 5/6, C. Guerra et al., Critical
Care 201 2 16:R233) Three factors could be identified related to the critical illness a s
being independently associated with a n increased risk of a diagnosis of dementia (cf.
fig. 7, C. Guerra et al., Critical Care 201 2 16:R233): a critical illness with the presence of
a n infection which increased to a higher risk with more severe infection such a s severe
sepsis, having acute neurologic dysfunction during critical illness, including anoxic brain
damage, encephalopathy, and transient mental disorders, and finally acute renal
failure requiring dialysis. This last risk was time-dependent and only increased the risk 6
months after the patient had been discharged from hospital.
Therefore, with good reasons, older people often worry about dementia. While some
risks are well known, for example alcoholism or stroke, also the effects of illness are
significant. So, it is a great need in the state of the art, to provide automated resource
pooling systems, especially for elderly, also covering risks for chronic critical illnesses. The
system should be designable to be based on a single occurrence scheme following the
diagnosis of specific condition having multiple triggers following each diagnosis. As a n
option, the system should also be able to capture for multiple occurrence of critical
illness, including dementia followed by the occurrence of a critical illness. Traditional
critical illness risk transfer systems are not able to capture this group of persons affected
by critical chronic illnesses and provide a n efficient method for risk transfer, thereby
providing mechanism to unburden public social wellness services and duties and to
alleviate social hardship.
It has to be mentioned that the above-mentioned correlation is exemplary for the risk
group of elderly. Other correlated critical illnesses for elderly are well known. Compare
for example the correlation of the risk for a stroke after coronary artery bypass (cf. S.
Stamou et al., Stroke After Coronary Artery Bypass, American Heart Association,
January 18, 2001 ).
Summary of the Invention
It is a n object of the invention to provide a system and method for risk
sharing of acute and/or chronic critical illness risks associated with elderly persons by
providing a dynamic self-sufficient risk protection for the risk exposure components by
means of the critical illness insurance system. The critical illness insurance system,
realized a s a automated resource-pooling system shall be completely automated and
self-adaptable/self-maintaining by its technical means and shall provide the technical
risk transfer basis, which can be used by service providers in the risk transfer or insurance
technology for risk transfer related to critical illness risks (CI). A further object of the
invention provides for a way to technically capture, handle and automate complex
related operations of the insurance industry related to critical illness risk transfer. Another
object is to synchronize and adjust such operations based o n technical means. In
contrast to the standard approach, the resource-pooling system shall create a
reproducible operation with the desired, technically based, repetitious accuracy based
on technical means, process flow and process control/operation. It is also a n object of
the invention to provide a risk and resource-pooling system able to cope with difficult
chronic progress of critical illnesses and further with complex related multiple risk events,
especially associated with a cohort of elderly persons.
According to the present invention, these objects are achieved particularly
through the features of the independent claims. In addition, further advantageous
embodiments follow from the dependent claims and the related description.
According to the present invention, the above-mentioned objects for risk
sharing of critical illness risks associated with elderly persons are achieved, particularly,
by providing a dynamic self-sufficient risk protection for a variable number risk exposure
components, i.e. a cohort of elderly persons, by means of the resource-pooling system,
wherein the risk exposure components are connected to the resource-pooling system
by means of a plurality of payment-receiving modules configured to receive and store
payments from the risk exposure components for the pooling of their risks and resources,
and wherein the resource-pooling system comprises a n event-driven core engine
comprising critical illness triggers triggering in a patient dataflow pathway to provide risk
protection for a specific risk exposure component based on received and stored
payments of the risk exposure components, in that the resource-pooling system
comprises a filter-module for capturing age-related parameters of risk exposure
components and for filtering risk exposure components associated with a n age-related
parameter greater than a predefined age-threshold value by means of the predefined
age-threshold value, in that the resource-pooling system comprises a predefined
searchable table of acute and/or chronic critical illnesses parameters indicating 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 a n operation and/or Parkinson's
disease and/or paralysis of limb and/or terminal illness in the patient dataflow pathway,
in that the total risk of the pooled risk exposure components comprises a critical illness
risk contribution of each pooled risk exposure components associated to risk exposure in
relation to a diagnosis of a n acute or chronic critical illness, wherein the acute or
chronic critical illness is comprised in a predefined searchable table of critical illnesses
and wherein critical illness losses occur a s a consequence to the first diagnosis of risk
exposure components with one of the searchable critical illnesses, in that in case of a
triggering of a n occurrence of a n acute or chronic critical illness in the patient data
flow pathway of a risk exposure component, a corresponding trigger-flag is set by
means of the resource-pooling system and a parametric transfer of payments is
assigned to this corresponding trigger-flag, wherein a loss associated with the acute or
chronic critical illness is distinctly covered by the resource pooling system based on the
respective trigger-flag and based o n the received and stored payment parameters
from risk exposure components by the parametric transfer from the resource-pooling
system to the risk exposure component, and in that a first parametric payment is
transferred by triggering the occurrence of the acute or chronic critical illness, a second
parametric payment is transferred, in case of a n acute critical illness, by a triggering of
a n acute treatment phase of the acute critical illness or, in case of a chronic critical
illness, by triggering of a first treatment phase of the chronic critical illness, and a third
parametric payment is transferred, in the case of a n acute critical illness, by a triggering
of a n aftercare phase linked to terminal prognosis data of the acute critical illness or, in
case of a chronic critical illness, by a triggering a n ongoing care or management
phase of the chronic critical illness. The critical illness triggers can for example comprise
a trigger for triggering the occurrence of measuring parameters indicating dementia
based o n 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. The critical illness triggers further can
e.g. comprise a 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 related risk exposure component
is rejected from pooling of the risk and resources by means of the resource-pooling
system. As a n embodiment variant, it can be provided that the first parametric
payment, for example can technically be implemented in that it only is transferred by
the triggering of the occurrence of measuring parameters indicating the critical illness
of malignant cancer and/or a smaller incidence for ductal carcinoma in situ (DCIS)
and/or early prostate carcinoma. Further, acute treatment phase parameters
indicating surgery and/or chemotherapy and/or radiotherapy and/or reconstructive
surgery can be triggered o n the patient data flow pathway by means of a critical illness
trigger by the core engine. As a n embodiment variant, it is provided that the total risk of
the pooled risk exposure components comprises a first risk contribution of each pooled
risk exposure components associated to risk exposure in relation to a first diagnosis of a
critical illness, wherein the critical illness is comprised in a predefined searchable table
of critical illnesses and wherein critical illness losses occur a s a consequence to the first
diagnosis of risk exposure components with one of the searchable critical illnesses, and
that the total risk of the pooled risk exposure components comprises at least a second
and/or successional risk contributions associated to risk exposure in relation to a second
and/or successional critical illnesses, wherein the critical illnesses are comprised in the
predefined searchable table of critical illness parameters, and wherein a critical illness
loss losses occurs a s a consequence to the second and/or successional diagnosis of risk
exposure components with one of the searchable critical illnesses, and that in case of a
triggering of a n occurrence of a first or second or successional critical illness in the
patient data flow pathway of a risk exposure component, a corresponding trigger-flag
is set by means of the resource-pooling system and a parametric draw-down transfer of
payments is assigned to this corresponding trigger-flag, wherein a loss associated with
the first or second or successional critical illness (es) 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 the parametric d raw
down transfer from the resource-pooling system to the risk exposure component, and
that a first parametric payment is transferred by triggering the occurrence of the acute
or chronic critical illness, a second parametric payment is transferred, in case of a n
acute critical illness, by a triggering of a n acute treatment phase of the acute critical
illness or, in case of a chronic critical illness, by triggering of a first treatment phase of
the chronic critical illness, and a third parametric payment is transferred, in the case of
a n acute critical illness, by a triggering of a n aftercare phase linked to terminal
prognosis data of the acute critical illness or, in case of a chronic critical illness, by a
triggering a n ongoing care or management phase of the chronic critical illness. As a n
embodiment variant, it is provided that the critical illness triggers comprise a trigger for
triggering the occurrence of measuring parameters indicating dementia based o n
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. The triggering measuring parameters indicating
dementia can e.g. 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 reactions factors and/or nutritional deficiencies
factors and/or stress factors and/or depression factors, or denial factors, indicating
confirmed impairment of cognitive functions. Further the critical illness triggers triggering
the first treatment phase of the chronic critical illness can e.g. comprise first treatment
phase parameter indicating psychiatric or old-age in-patient care associated with the
risk exposure component comprising acute in-patient admission parameters a s a result
of deterioration in dementia status requiring for urgent treatment. Finally, the critical
illness triggers triggering a n ongoing care or management phase of the chronic critical
illness can e.g. comprise ongoing care or management phase parameters indicating
permanent cognitive and/or motor impairment requiring continuous supervision of
another person and/or ongoing care or management phase parameters indicating
permanent cognitive and/or motor impairment requiring constant supervision of
another person. As a n further embodiment variant, the critical illness triggers can e.g.
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 a n acute stroke episode in
the patient dataflow pathway. The critical illness triggers triggering the first treatment
phase of the chronic critical illness can e.g. further comprise first treatment phase
parameter indicating a measured time interval of the risk exposure component spend
in hospital due to the triggered stroke. Further, the critical illness triggers triggering a n
ongoing care or management phase of the chronic critical illness 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 of another person and/or permanent cognitive and/or motor
impairment requiring constant supervision of another person. As a n other embodiment
variant, it is provided that a second parametric payment is transferred due to the
triggering of acute treatment phase parameters indicating surgery and/or
chemotherapy and/or radiotherapy and/or reconstructive surgery. Additionally,
recovery phase parameters associated with terminal prognosis data can e.g. be
triggered in a patient data flow pathway by means of a critical illness trigger of the
core engine. As a further embodiment variant, a third parametric payment is
transferred by the triggering of the recovery phase parameters and/or terminal
prognosis parameters. As a further variant, the critical illness data of the patient
dataflow pathway of the risk exposure component can e.g. additionally be transferred
to a n automated employee assistance system (EAP: Employee Assistance Program)
providing automated support to the risk exposure component. Alternatively or in
addition, the critical illness data of the patient dataflow pathway of the risk exposure
component can e.g. be transferred to a n alert system of a n Citizens Advice Bureau
(CAB) to activate automated or at least semi-automated, CAB actions. It can also be
advantageously that the patient dataflow pathway is e.g. monitored by the resourcepooling
system by capturing patient-measuring parameters of the patient data flow
pathway a t least periodically and/or within predefined time frames or periods. Finally,
the patient data flow pathway can e.g. be dynamically monitored by the resourcepooling
system in that it triggers patient-measuring parameters of the patient dataflow
pathway transmitted from associated measuring systems. The invention has, inter alia,
the advantage that the system provides the technical means to meet customer needs
related to the financial hardships a t the time of the diagnosis of a n chronic or acute
critical illness, which will become more acute a s the treatment progresses. Therefore,
cancer fears and the related consequences that are suffered by many people can be
met with the automated resource-pooling system according to the invention. The
system has, furthermore, the advantage that smaller payments than in traditional
critical illness systems are sufficient to allow for a safe operation of the system. The
operational aspects of the system are transparent for operators a s well a s covered risk
units, since payment is transferred in response to certain triggers on the cancer patient's
information pathways. The system is able to provide a n adaptable survival period e.g.
14, 2 1 or 28 days, to be confirmed or defined by the risk transfer. The system is further
able to provide the technical implementation of a n automated system that is based on
a drawdown payment operation or a predefined payment operation. The system also
provides the technical means, which can support different underwriting options, such
a s (i) underwritten with a set of questions, (ii) in/out underwriting, (iii) inclusion or
exclusion of Pre-Existing Condition Exclusion (PECE) and/or a Related Conditions
Exclusion with the associated problems of risk transfer. PECE-problems are based on the
fact that resource-pooling systems are often required by a n employer to create safety
provisions, if there is a diagnosis of a critical illness in a n employee, in order to provide a
lump sum benefit for a n employee (or the employee's spouse or children, if comprised
in the risk transfer), who is diagnosed with one of the defined medical conditions or
undergoes one of the listed surgical procedures. However, many systems fail to take
over risk transfers if the individual suffered from the insured condition, before the risk
transfer was activated (this is known a s the Pre-Existing Condition Exclusion), or because
the individual suffered from a condition that led to a claim under the insured illness - for
example, it was known that a n individual suffered from high blood pressure before the
risk transfer being activated, and suffered a stroke after the risk transfer had been
activated. Another advantage of the system is based on the fact that payments are
directly transferred to the risk transfer unit or the consumer/client. Therefore, the system
is able to enhance critical illness insurance offerings by independent financial advisers
(IFA). IFAs are persons who give impartial advice to clients on financial matters and who
are not employed by any financial institution, although commissions for the sale of
products may be received. Especially the IFA service is made completely costtransparent
to the consumer.
In a n embodiment variant, the above-mentioned objects for risk sharing of
critical illness risks of a variable number of risk exposure components are achieved,
particularly, by providing a dynamic self-sufficient risk protection for the risk exposure
components by means of the critical illness insurance system based o n a resourcepooling
system, in that risk-related component data are processed by a n assembly
module of the resource-pooling system and the likelihood of said risk exposure is
provided by means of the assembly module for one or a plurality of the pooled risk
exposure components based on the risk-related component data, wherein the risk
exposure components are connected to the resource-pooling system by means of a
plurality of payment receiving modules, and payment data are received and stored by
means of a payment data store from the risk exposure components for the pooling of
their risks, and wherein the resource-pooling system triggers a patient dataflow pathway
by means of critical illness triggers of a n event-driven core engine in order to provide risk
protection for a specific risk exposure component based on received and stored
payments from the risk exposure components, in that a first risk contribution of each
pooled risk exposure components related to a first diagnosis of a critical illness is
associated with risk exposure of each pooled risk exposure component, and the total
risk of the pooled risk exposure components is determined by means of the resourcepooling
system, wherein the critical illness is comprised in a predefined searchable table
of critical illnesses, and wherein critical illness losses occur a s a consequence of the first
diagnosis of risk exposure components due to any one of the searchable critical
illnesses, in that a first risk contribution of each of the pooled risk exposure components
related to a second and/or successional risk contribution diagnosis of a critical illness is
associated with risk exposure of each pooled risk exposure component, and the total
risk of the pooled risk exposure components is determined by means of the resourcepooling
system, wherein the critical illness is comprised in the predefined searchable
table of critical illnesses, and wherein critical illness losses occur a s a consequence of
the second and/or successional diagnosis of risk exposure components due to any one
of the searchable critical illnesses, in that, in case a n occurrence of a first or second or
successional critical illness o n the patient data flow pathway of a risk exposure
component is triggered, a corresponding trigger-flag is set by means of the resourcepooling
system and a parametric draw-down transfer of payments is assigned to this
corresponding trigger-flag, wherein a loss associated with the first or second or
successional critical illness is distinctly covered by the resource-pooling system based o n
the respective trigger-flag and based o n the received and stored payment parameters
from risk exposure components by the parametric draw-down transfer from the
resource-pooling system to the risk exposure component, and in that a first parametric
payment is transferred by the triggering of the occurrence of the critical illness, a
second parametric payment is transferred by the triggering of a n acute treatment
phase, and a third parametric payment is transferred by the triggering of a n recovery
phase associated with terminal prognosis data. This embodiment variant has the
advantage of further providing a parametric draw-down payment. It is clear to a man
skilled in the art, that the present system can easily be expanded to comprise more
than the herein described three trigger-levels.
In one embodiment variant, the receiving and preconditioned storage of
payments from risk exposure components for the pooling of their risks is dynamically
determined based o n total risk and/or the likelihood of the risk exposure of the pooled
risk exposure components. This embodiment variant has, inter alia, the advantage that
the operation of the resource-pooling system can be dynamically adapted to
changing conditions of the pooled risk, as, for example, changing demographic
conditions or changing age distributions or the like of the pooled risk components. A
further advantage is that the system needs no manual adaption, when it is operated in
different environments, places or countries, because the size of the payments of the risk
exposure components is directly related to the totally pooled risk.
In another embodiment variant, the number of pooled risk exposure
components is dynamically adapted, by means of the resource-pooling system, 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 a t
a given time. This variant has, inter alia, the advantage that the operational and
financial stability of the system can be improved.
In a further embodiment variant, the critical illness triggers are dynamically
adapted by means of a n operating module based o n time-correlated incidence data
for a critical illness condition and/or diagnosis or treatment conditions indicating
improvements in diagnosis or treatment. This variant has, inter alia, the advantage that
improvements in diagnosis or treatment can be dynamically captured by the system
and dynamically affect the overall operation of the system based o n the total risk of
the pooled risk exposure components.
In yet another embodiment variant, the first, second and third parametric
payment are leveled by a predefined total payment sum determined a t least based o n
the risk-related component data and/or o n the 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 the first parametric payment that is transferred is up to
30% of said total payment sum, and the second parametric payment that is transferred
is up to 50% of said total payment sum, and the third parametric payment that is
transferred is up to the left over part given by said total payment sum, minus the actual
first parametric payment and the second parametric payment. The predefined total
payments can e.g. be leveled to any appropriate lump sum, such as, for example,
$50,000 up to $500,000, or any other sum related to the total transferred risk and the
amount of the periodic payments of the risk exposure component. As embodiment
variant of the realization of the system, the critical illness trigger e.g. can comprise multi
dimensional trigger channels, wherein each of said trigger-flags is assigned to a first
dimension trigger channel, comprising a first trigger-level triggering occurrence
parameters of the critical illness, a second trigger-level triggering acute treatment
phase parameters, and a third trigger-level triggering recovery phase parameters
associated with terminal prognosis data, and each of said trigger-flags is assigned to a t
least a second or higher dimension trigger channel, and comprises additional triggerstages
based on the first, second and/or third trigger-level of the first dimension trigger
channel. As a further variant, the critical illness trigger can also comprise multi
dimensional trigger channels, wherein each of said trigger-flags is assigned to a first
dimension of a trigger channels comprising a first trigger-level relative to triggering
occurrence parameters of the critical illness, a second trigger-level relative to triggering
acute treatment phase parameters, and a third trigger-level relative to triggering
recovery phase parameters associated with terminal prognosis data, and each of said
trigger-flags is assigned to a second dimension of trigger channels comprising a first
trigger-level triggering on a first stage of progression-measuring parameters of the
occurred critical illness, and one or more higher trigger-levels triggering on higher
stages of progression-measuring parameters of the occurred critical illness. This variant,
inter alia, has the advantage that the draw-down payments or the payments of
predefined amounts, which depend on the first, second or third trigger level, i.e. the
different stages of triggers, allow for a n adapted payment of the total sum that is
dependent on the stage of the critical illness, a s triggered by the system.
In one embodiment variant, a periodic payment transfer from the risk
exposure components to the resource pooling system via a plurality of payment
receiving modules is requested by means of a monitoring module of the resourcepooling
system, wherein the risk transfer or protection for the risk exposure components
is interrupted by the monitoring module when the periodic transfer is no longer
detectable by means of the monitoring module. As a variant, the request for periodic
payment transfer can be interrupted automatically or waived by means of the
monitoring module, when the occurrence of indicators for critical illness is triggered in
the patient data flow pathway of a risk exposure component. These embodiment
variants have, inter alia, the advantage that the system allows for a further automation
of the monitoring operation, especially of its operation with regard to the pooled
resources.
In a further embodiment variant, a n independent verification critical illness
trigger of the resource pooling system is activated in cases of a triggering of the
occurrence of indicators for critical illness in the patient data flow pathway of a risk
exposure component by means of the critical illness trigger and wherein the
independent verification critical illness trigger additionally is triggering for the
occurrence of indicators regarding critical illness in a n alternative patient data flow
pathway with independent measuring parameters from the primary patient data flow
pathway in order to verify the occurrence of the critical illness a t the risk exposure
component. As a variant, the parametric draw-down transfer of payments is only
assigned to the corresponding trigger-flag, if the occurrence of the critical illness a t the
risk exposure component is verified by the independent verification critical illness
trigger. These embodiment variants have, inter alia, the advantage that the
operational and financial stability of the system can thus be improved. In addition, the
system is rendered less vulnerably relative to fraud and counterfeit.
In addition to the system, a s described above, and the corresponding
method, the present invention also relates to a computer program product that
includes computer program code means for controlling one or more processors of the
control system in such a manner that the control system performs the proposed
method; and it relates, in particular, to a computer program product that includes a
computer-readable medium containing therein the computer program code means
for the processors.
Brief Description of the Drawings
The present invention will be explained in more detail, by way of example,
with reference to the drawings in which:
Figure 1 shows a block diagram illustrating schematically a n exemplary
parametric, event-driven critical illness insurance system based on a resource-pooling
system 1 according to the invention for risk sharing of critical illness risks associated with
elderly persons by providing a dynamic self-sufficient risk protection for a variable
number of risk exposure components 2 1, 22, 23, i.e. said elderly persons. The resourcepooling
system 1 comprises a n assembly module 5 to process risk- related component
data 211, 221 , 231 and to provide the likelihood 2 12, 222, 232 of said risk exposure for
one or a plurality of the pooled risk exposure components 2 1, 22, 23, wherein the risk
exposure components 2 1, 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 2 14, 224, 234 from the risk exposure components 2 1, 22, 23 for the
pooling of their risks, and wherein the resource-pooling system 1 comprises a n eventdriven
core engine 3 that comprises critical illness triggers 3 1, 32, 33, which trigger a
patient data flow pathway 2 13, 223, 233 to provide risk protection for a specific risk
exposure component 2 1, 22, 23. The patient data flow pathway 2 13, 223, 233 is
monitored by the resource-pooling system 1 in that patient measuring parameters of
the patient data flow pathway 213, 223, 233 are captured, wherein the patient data
flow pathway 2 13, 223, 233 is dynamically monitored and triggered for patient
measuring parameters of the patient data flow pathway 2 13, 223, 233, which is
transmitted from associated measuring systems.
Figure 2 shows a block diagram illustrating schematically exemplary trigger
stages of the resource-pooling system, wherein reference number 1001 is assigned to
the triggering of the critical illness, for example the malignant cancer. Reference
number 1002 designates the triggering of the treatment phase, such as, for example,
surgery, chemotherapy, radiotherapy or medications of drugs etc. Reference number
1003 designates the triggering of the recovery phase or the triggering of the terminal
illness and/or the aftercare phase. Finally, reference number 1004 designates the
triggering of additional support services. Reference number 1004 gives a n example of
additional trigger stages to the critical illness triggers 3 1, 32, 33 of the core engine
module 3.
Figure 3 shows a diagram illustrating schematically a n exemplary payment
drawdown a s it can be provided by the resource pooling system 1 in case of triggering
critical illness at a risk exposure component.
Figure 4 shows a block diagram illustrating schematically a n exemplary
parameterization of the risk exposure for critical illness of the risk exposure components
2 1, 22, 23. The reference numeral 520 gives the total transferred risk of a specific risk
exposure component 2 1, 22, 23 comprising at least a first risk contribution 5 11, 521 , 531
for a first occurrence of a critical illness. Further, it comprises a second risk contribution
512, 522, 532 related to a second occurrence of a critical illness. It also can comprise
third 513, 523, 533 and subsequent 5 1i, 52i, 53i risk contributions thereafter; i.e., "i" herein
denotes the i-†h risk distribution.
Figure 5 shows a diagram illustrating schematically the cumulative
incidence of all mortality and dementia for elderly ICU survivors over three years,
adjusting for mortality a s a competing risk. The dashed line is the cumulative incidence
of all mortality during follow-up. The solid line is the cumulative incidence of dementia
after adjusting for mortality a s a competing event.
Figure 6 shows a diagram illustrating schematically the cumulative
incidence of dementia by five year age categories. Cumulative incidence of
dementia, adjusted for mortality a s a competing event, by age.
Figure 7 shows a diagram illustrating schematically the cumulative
incidence of dementia, stratified by (A) infection or severe sepsis, (B) acute neurologic
dysfunction, (C) acute renal replacement therapy. Cumulative incidence (A. long
dashed line is for infection, short dashed line is for severe sepsis, solid line is for no
infection; B. dashed line is for neurologic dysfunction, solid line is for none; C. dashed
line is for acute RRT (renal replacement therapy), solid line is for none of dementia after
adjusting for mortality a s a competing event.
Figure 8 shows a flowchart illustrating schematically the exclusions of
patients with previous indications of cognitive impairment for whom dementia could
have been a n escalation of a pre-existing condition resulting in the final cohort
indicating the risk for related occurrence of dementia a s critical illness for elderly.
Detailed Description of the Preferred Embodiments
Figure 1 illustrates, schematically, a n architecture for a possible
implementation of a n embodiment of the parametric, event-driven resource-pooling
system 1 for risk sharing of critical illness risks associated with elderly persons. In Figure 1,
reference numeral 1 refers to the resource-pooling system for risk sharing of the risk
exposure components 2 1, 22, 23... 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 2 1, 22, 23, i.e.; persons or individuals, by its means.
The system 1 includes a t least one processor and associated memory modules. The
system 1 can also include one or more display units and operating elements, such a s a
keyboard, and/or graphical pointing devices a s a computer mouse. The resourcepooling
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 critical illness risks (CI) . The invention seeks to technically capture, handle and
automate complex related operations of the insurance industry. An other 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 n reproducible
operations with the desired technical, repetitious accuracy because it is completely
based o n technical means, process flow and process control/operation.
The resource-pooling system 1 comprises a n assembly module 5 to process
risk related component data 2 11, 221 , 231 and to provide the likelihood 2 12, 222, 232 of
said risk exposure for one or a plurality of the pooled risk exposure components 2 1, 22,
23, etc. based on the risk-related component data 2 11, 221 , 231 . The resource-pooling
system 1 can be implemented a s a technical platform, which is developed and
implemented to provide critical illness risk transfer through a plurality of (but at least
one) payment receiving module 4. The risk exposure components 2 1, 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 for the pooling of their risks in a payment data
store 6. The plurality of risk exposure components 2 1, 22, 23 from a cohort of selected
elderly persons, where during capturing the risk exposure components 2 1, 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 by means of a filter module, wherein by means of the filter
module only risk exposure components 2 1, 22, 23 associated with a n 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 e.g. be set to 50 years or a n
appropriate other age allowing to select specific cohort of elderly persons. As a n
embodiment variant, the selection criterion can comprise further parameters a s
gender, origin, habits, urban or rural conglomeration etc.
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 1 based on total risk
of the overall pooled risk exposure components 2 1, 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 2 1, 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 2 1, 22, 23 is
interrupted by the monitoring module 8, when the periodic transfer is no longer
detectable by means of the monitoring module 8. In one embodiment variant, 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 critical illness 7 1, 72,
73 is triggered 3 1 in the patient data flow pathway of a risk exposure component 2 1, 22,
23,... The resource-pooling system 1 further comprises a predefined searchable table 7
of acute and/or chronic critical illnesses 7 1, 72, 73 parameters indicating 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 Parkinson's
disease and/or paralysis of limb and/or terminal illness and/or other any definable and
measurable critical illnesses in the patient dataflow pathway 213, 223, 233. The triggers
3 1, 32, 33 are uni- or bidirectionally connected with the predefined searchable table 7
of acute or chronic critical illnesses 7 1, 72, 73, wherein the triggering 3 1, 32, 33 is
performed based on the acute and/or chronic critical illnesses 7 1, 72, 73 parameters
stored in the predefined searchable table 7. The critical illness triggers 3 1, 32, 33 can
comprise a trigger 3 1 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 critical illness
triggers 3 1, 32, 33 further can comprise a trigger 3 1 for triggering measuring parameters
indicating alcohol and/or drug abuse in the patient dataflow pathway 213, 223, 233,
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.
As also illustrated schematically in Figure 1, the resource-pooling system 1
includes a data storing module for capturing the risk-related component data and
multiple functional modules; e.g., namely the payment receiving modules 4, the core
engine 3 with the triggers 3 1, 32, 33, the assembly module 5 or the operating module 30.
The functional modules can be implemented at least partly a s programmed software
modules stored on a computer readable medium, connected a s fixed or removable 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 implemented fully by
means of hardware components, units and/or appropriately implemented modules. As
illustrated in Figure 1, system 1 can be connected via a network, such a s 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 n UMTS network (Universal Mobile Telecommunications
System) and/or a WLAN (Wireless Local Region Network), and/or dedicated poin†-†opoint
communication lines. In any case, the technical electronic money schemes for
the present system comprises 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 comprises
further all necessary technical means for electronic money transfer and association e.g.
initiated by one or more associated payment receiving modules 4 over a n electronic
network. The monetary parameters can be based on all possible electronic and
transferable means a s e.g. 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 of the pooled risk
exposure components 2 1, 22, 23. The present invention can involve the use of the
mentioned network, such a s e.g. computer networks or telecommunication 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 a s financial
cryptography and technologies enabling the same. For the transaction of the
monetary parameters, it is preferable that hard electronic currency is used without the
technical possibilities for disputing or reversing any charges. The resource-pooling
system 1 supports, for example, 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 immediately to the system 1. This means that using hard electronic currency is
more akin to a cash transaction. However, also conceivable is the use of soft electronic
currency, such a s currency that allows for the reversal of payments, for example having
a "clearing time" of 72 hours, or the like. The way of the electronic monetary parameter
exchange applies to all connected systems and modules related to the resourcepooling
system 1 of the present invention, such a s e.g. 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 o n request of the resource-pooling system 1.
The resource-pooling system 1 comprises a n event-driven core engine 3
comprising critical illness triggers 3 1, 32, 33 for triggering component-specific measuring
parameters in the patient data flow pathway 213, 223, 233 of the assigned risk exposure
components 2 1, 22, 23 The patient data flow pathway 213, 223, 233 can e.g. be
monitored by the resource-pooling system 1, capturing patient-related measuring
parameters of the patient data flow pathway 213, 223, 233 a t least periodically and/or
within predefined time periods. The patient data flow pathway 2 13, 223, 233 can, for
example, also be dynamically monitored by the resource-pooling system 1, by
triggering patient-measuring parameters of the patient data flow pathway 213, 223,
233 transmitted from associated measuring systems. Triggering the patient data flow
pathway 213, 223, 233, which comprises dynamically recorded measuring parameters
of the concerned risk exposure components 2 1, 22, 23 the system 1 is able to
detect the occurrence of a critical illness and dynamically monitor the different stages
during the progress of the critical illness in order to provide appropriately adapted and
gradated risk protection for a specific risk exposure component 2 1, 22, 23 Such a risk
protection structure is based o n received and stored payments 214, 224, 234 from the
related risk exposure component 2 1, 22, 23 and/or related to the total risk of the
resource-pooling system , 1 based on the overall transferred critical illness risks of all
pooled risk exposure components 2 1, 22, 23
Figure 2 shows a block diagram with possible trigger stages, wherein
reference number 1001 is assigned to the triggering of the critical illness, for example
cancer; reference number 1002 designates the triggering of the treatment phase, such
as, for example, surgery, chemotherapy, radiotherapy or the administration of
medication, etc.; reference number 1003 designates the triggering of the recovery
phase or the triggering of the terminal illness and/or the aftercare phase.; and
reference number 1004 designates the triggering of additional support services.
Reference number 1004 gives a n example of additional trigger stages to the critical
illness triggers 3 1, 32, 33 of the core engine module 3. The critical illness triggers 3 1, 32, 33
can e.g. comprise a trigger 3 1 for triggering the occurrence 1001 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 data flow pathway 213, 223, 233. Further, the
critical illness triggers 3 1, 32, 33 can comprise a trigger 3 1 for triggering the occurrence
1001 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 a n operation, Parkinson's disease, paralysis of limb,
terminal illness in the patient data flow pathway 213, 223, 233. The majority of cases of
occurrences of critical illness are typically related to heart attack, stroke and cancer, a s
can be expected. The average age of individual 2 1, 22, 23, a t which a critical illness
can be detected in the patient data flow pathway 213, 223, 233, is ± 4 1 years; however,
this depends on the development of diagnostic and other medical means. These
statistics are common for all countries where statistics are maintained. However, it is of
great concern to observe the increasing number of critical illness occurrences -
particularly regarding cancer cases. In most countries, this observed increase is more
than 50%, and in some even 80%. 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 7 1, 72, 73
of critical illness in the trigger table 7 can be dynamically adapted based o n a
monitoring of changing risks in the risk exposure components 2 1, 22, 23. In particular, the
trigger parameters 7 1, 72, 73 can be region-specific, country-specific and/or specific of
the total pooled risk, adapted or changed. New critical illnesses 7 1, 72, 73 can be
added, while others can be deleted from the triggerable list of critical illnesses by the
resource-pooling system, owing to better treatments or other changed environmental
conditions. In one embodied variant, the critical illness triggers 3 1, 32, 33 can be
dynamically adapted by means of a n operating module 30, based o n time-correlated
incidence dates of a critical illness condition and/or diagnosis or treatment conditions
indicating improvements in diagnosis or treatment.
In addition to the adaptation of the triggers 3 1, 32, 33, the amount of
requested payments from the risk exposure components 2 1, 22, 23 can be accordingly
adjusted by the resource-pooling system 1.Therefore the receiving and preconditioned
storage 6 of payments 214, 224, 234 from risk exposure components 2 1, 22, 23, ... for the
pooling of their risks can be determined dynamically, based o n total risk 50 and/or the
likelihood of the risk exposure of the pooled risk exposure components 2 1, 22, 23, ... To
improve operational and functional security of the resource- pooling system 1 even
further, the number of pooled risk exposure components 2 1, 22, 23, ... 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 totally pooled risk exposure components 2 1, 22, 23, ...
a t a given time.
The total risk 50 of the pooled risk exposure components 2 1, 22, 23, ... can
comprise several risk contributions, a s it can comprise a first risk contribution 5 11, 521 ,
531 of each pooled risk exposure component 2 1, 22, 23, ... that is associated with risk
exposure in relation to a first diagnosis of a critical illness. The triggering parameters 7 1,
72, 73 of the covered critical illnesses is comprised and stored in a predefined
searchable table 7, such a s e.g. a n appropriately structured hash table, of critical
illnesses 7 1, 72, 73, respectively critical illness parameters 7 1, 72, 73. The critical illness
losses occur a s a consequence to the first diagnosis of risk exposure components 2 1, 22,
23, ... with regard to one of the searchable critical illnesses; i.e., the possible need of a
risk exposure components 2 1, 22, 23, ... to be covered by the pooled resources of the
resource-pooling system 1 is linked to the risk of the occurrence of a critical illness
requiring complex medical treatment and handling. The total risk 50 of the pooled risk
exposure components 2 1, 22, 23,... can further comprise a second risk contribution
5 12,522,523 and/or third or additional successional risk contributions
513/521/. ..51i/52i/53i; i.e., up to the i-†h risk contribution, associated with risk exposure in
relation to a second and/or successional critical illness(es). The critical illnesses 7 1, 72, 73
for triggering the second risk contribution 512, 522, 523 and/or third or additional
successional risk contributions 513/521/. ..51i/52i/53i are the same a s for the first risk
contribution and comprised in the predefined searchable table 7 of critical illness
parameters 7 1, 72, 73. However, in the primary embodiment variant, the total risk
contribution is only based on a single triggering of a n occurrence of a acute and/or
chronic critical illness, i.e. the primary scheme is designed to be a single occurrence
scheme following the diagnosis of specific condition, where there are multiple triggers
following each diagnosis, enabling the system to handle chronic critical illness.
Figure 4 shows a block diagram with a n exemplary parameterization of the
risk exposure for critical illness of the risk exposure components 2 1, 22, 23. The reference
numeral 520 gives the total transferred risk of a specific risk exposure component 2 1, 22,
23 comprising a † least a first risk contribution 511, 521 , 531 for a first occurrence of a
critical illness. Further comprised is a second risk contribution 512, 522, 532 related to a
second occurrence of a critical illness. Also comprised can be a third 513, 523, 533 and
subsequent 51i,52i,53i risk contribution; i.e., "i" denotes the i-†h risk distribution.
In case of triggering a n occurrence of a first (or in case of multiple
occurrence handling: second or successional) critical illness 71,72,73 on the patient
dataflow pathway 2 13,223,233 of a risk exposure component 2 1, 22, 23, i.e. if a
triggering of a n occurrence of a first or second or successional critical illness 7 1, 72, 73
goes into effect in the patient data flow pathway 2 13, 223, 233, a corresponding
trigger-flag is set by means of the resource-pooling system 1 and a parametric d raw
down or predefined transfer of payments is assigned to this corresponding trigger-flag.
A loss associated with the first or second or successional critical illness (es) 7 1, 72, 73 is
distinctly covered by the resource-pooling system 1, based o n the respective triggerflag
and based on the received and stored payment parameters 2 1 , 224, 234 from risk
exposure components 2 1, 22, 23 by the parametric draw-down or predefined transfer
from the resource-pooling system 1 to the risk exposure component 2 1, 22, 23,e†c. The
payment receiving module 4 can, a s a n input device, comprise one or more data
processing units, displays and other operating elements, such a s 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 2 1, 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
a s e.g. 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
comprise, e.g., a telecommunications network, such a s a wired or wireless network,
e.g., the internet, a GSM network (Global System for Mobile Communications) , a n UMTS
network (Universal Mobile Telecommunications System) and/or a WLAN (Wireless Local
Area Network) , a Public Switched Telephone Network (PSTN) and/or dedicated pointto-
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 a n embodied variant, the payment receiving module 4 can also be implemented a s
a n 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.
A first parametric payment 2 11 is transferred by triggering the occurrence
1001 of the critical illness 7 1, 72, 73 by means of the critical illness trigger 3 1 of the core
engine 3, thus triggering the measuring parameters of the specific risk exposure
component 2 1, 22, 23 in the related patient data flow pathway 2 13, 223, 233. The first,
second and third parametric payments are denoted in "units" in the examples
according to table 1 to 5 (see below). The amount of those units (table 1 to 5) are just
examples and can be either set a s 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, a s e.g.
medical or therapeutic cost, or based upon the total pooled resources by means of the
system 1. The changing of the environmental boundary conditions can by dynamically
triggered or captured by the system 1. One "unit" can be assigned to correspond to a n
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 a s e.g. 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, the first parametric
payment can be transferred by triggering 3 1 the occurrence 1001 of measuring
parameters indicating the critical illness 7 1, 72, 73 of malignant cancer and/or smaller
incidence of ductal carcinoma in situ (DCIS) and/or early prostate carcinoma. In the
case of dementia, the critical illness triggers 3 1, 32, 33 can comprise a trigger 3 1 for
triggering the occurrence of measuring parameters indicating dementia based o n
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 o n adrenal exhaustion factors and/or food and chemical reactions factors
and/or nutritional deficiencies factors and/or stress factors and/or depression factors, or
denial factors, indicating confirmed impairment of cognitive functions. In the case of
stroke, the critical illness triggers 3 1, 32, 33 can comprise a trigger 3 1 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 a n acute stroke episode in the patient dataflow pathway
213, 223, 233.
A second parametric payment 2 12 is transferred by triggering measuring
parameters in the patient data flow pathway 213, 223, 233 indicating the initiation of a n
acute or first treatment phase 1002 by means of the critical illness trigger 32 of the core
engine 3. This is achieved by triggering 32 in case of a n acute critical illness 7 1, 72, 73, of
a n acute treatment phase 1002 of the acute critical illness 7 1, 72, 73 or, in case of a
chronic critical illness 7 1, 72, 73, by triggering 32 of a first treatment phase 1002 of the
chronic critical illness 7 1, 72, 73. For example, acute or first treatment phase parameters
1002 indicating surgery and/or chemotherapy and/or radiotherapy and/or
reconstructive surgery can be triggered in patient data flow pathway 213, 223, 233 by
means of a critical illness trigger 32 of the core engine 3. For example, the second
parametric payment can only be transferred by triggering 32 acute or first treatment
phase parameters 1002, indicating surgery and/or chemotherapy and/or radiotherapy
and/or reconstructive surgery. In the example of dementia the critical illness triggers for
triggering 32 the first treatment phase 1002 of the chronic critical illness 7 1, 72, 73 can
comprise first treatment phase parame†erl002 indicating psychiatric or old-age inpatient
care associated with the risk exposure component 2 1, 22, 23, ... comprising
acute in-patient admission parameters a s a result of deterioration in dementia status
requiring for urgent treatment. In the example of stroke the critical illness triggers for
triggering 32 the first treatment phase 1002 of the chronic critical illness 7 1, 72, 73 can
comprise first treatment phase parameter 1002 indicating a measured time interval of
the risk exposure component 2 1, 22, 23, ... spend in hospital due to the triggered stroke.
Finally, a third parametric payment 213 is transferred, in the case of a n
acute critical illness 7 1, 72, 73, by a triggering 33 of a n aftercare phase 1003 linked to
terminal prognosis data of the acute critical illness 7 1, 72, 73. In case of a chronic
critical illness 7 1, 72, 73, the third parametric payment 2 13 is transferred by a triggering
33 a n ongoing care or management phase of the chronic critical illness 7 1, 72, 73. I.e.
the third parametric payment 2 13 is transferred in case of a n acute chronic illness by
triggering measuring parameters in the patient data flow pathway 213, 223, 233
indicating the initiation of a recovery phase 1003 linked to terminal prognosis data by
means of the critical illness trigger 33 by the core engine 3, and in case of a chronic
critical illness analogously. For example, recovery phase parameters 1003 linked to or
associated with terminal prognosis data are triggered in patient data flow pathway
213, 223, 233 by means of a critical illness trigger 33 by the core engine 3. As a variant,
the third parametric payment is only transferable by triggering 33 recovery phase
parameters and/or terminal prognosis parameters 1003 and/or ongoing care or
management phase. In case of dementia, the critical illness triggers 3 1,32,33 for
triggering a n ongoing care or management phase of the chronic critical illness 7 1, 72,
73 can comprise ongoing care or management phase parameters indicating
permanent cognitive and/or motor impairment requiring continuous supervision of
another person and/or ongoing care or management phase parameters indicating
permanent cognitive and/or motor impairment requiring constant supervision of
another person. In case of stroke, the critical illness triggers 3 1,32,33 for triggering a n
ongoing care or management phase of the chronic critical illness 7 1, 72, 73 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 of another person and/or permanent
cognitive and/or motor impairment requiring constant supervision of another person.
Therefore, if triggering 1001 takes effect, a n occurrence of a first critical
illness 7 1, 72, 73 in the patient dataflow pathway 2 13, 223, 233 of a risk exposure
component 2 1, 22, 23, any associated loss is covered by the resource-pooling system 1
based o n the received and stored payments 214, 224, 234 from risk exposure
components 2 1, 22, 23 by transferring a parametric diagnosis payment 2001 from the
resource-pooling system 1 to the risk exposure component 2 1, 22, 23, etc.; if triggering
1002 takes effect, a n occurrence of a n acute treatment phase or first treatment phase
in the patient data flow pathway 213, 223, 233 of a n associated loss is covered by the
resource-pooling system 1 based on the received and stored payments 214, 224, 234
from risk exposure components 2 1, 22, 23 by transferring a parametric treatment phase
payment 2002 from the resource-pooling system 1 to the risk exposure component 2 1,
22, 23, etc.; and if triggering 1003 takes effect, a n occurrence of a recovery phase
linked to terminal prognosis data or a n ongoing care or management phase in case of
a chronic critical illness in the patient data flow pathway and associated loss is covered
by the resource-pooling system based on the received and stored payments 214, 224,
234 from risk exposure components 2 1, 22, 23 by transferring a parametric recovery
phase payment 2003 or a n ongoing care or management phase payment 2003 from
the resource-pooling system 1 to the risk exposure component 2 1, 22, 23, etc. The first,
second and third parametric payments can, for example, be leveled by a predefined
total payment sum determined at least based on the risk-related component data 2 11,
221 , 231 and/or the likelihood of the risk exposure for one or a plurality of the pooled risk
exposure components 2 1, 22, 23, etc., based on the risk-related component data 2 11,
221 , 231 , wherein the first parametric payment is transferred up to 30% of said total
payment sum, and the second parametric payment is transferred up to 50% of said
total payment sum, and the third parametric payment is transferred up to the residual
part given by said total payment sum minus the actual first parametric payment and
the second parametric payment. Such a n exemplary payment draw-down a s it can be
provided by the resource-pooling system 1 in the event of a triggering of a critical illness
a t a risk exposure component is shown in the diagram of Figure 3.
As mentioned, the triggers 3 1,32, 33 are uni- or bidirectionally connected
with the predefined searchable table 7 of acute or chronic critical illnesses 7 1, 72, 73,
wherein the triggering 3 1, 32, 33 is performed based o n the acute or chronic critical
illnesses 7 1, 72, 73 parameters stored in the predefined searchable table 7. The
predefined searchable table 7 is multidimensionally structured, e.g. a s a
multidimensional hash-table. Each acute or chronic critical illnesses 7 1, 72, 73,
selectable in the multidimensional table has assigned to it triggerable measuring
parameters according to the trigger-step to be performed by means of the resourcepooling
system 1, i.e. trigger 3 1 and/or trigger 32 and/or trigger 33. The stored trigger
parameters of trigger 3 1, 32, 33 of the predefined searchable table 7 can for example
comprise the following trigger dependencies. Further, a s a n embodiment variant, the
predefined searchable table 7 can also comprise a predefined amount for the first,
second and/or third parametric payment assigned to the corresponding trigger 3 1, 32,
33. The amount can be fixed for a time-period contracted with the risk-exposed
component. However, in a preferred embodiment variant, the transferable parametric
payments from the pooled resources by means of the resource pooling system 1 are
dynamically adaptable by the system 1, for example based o n the pooled resources or
based upon dynamically checked changing medical conditions or other boundary
condition to the system 1 respectively to the associated and transferred risks.
Trigger 3 1 Trigger 32 Trigger 33 (aftercare trigger
(diagnosis trigger parameter) (treatment trigger parameter for parameter)
cancer diagnosis)
Cancer in situ or skin 2000 Radiotherapy - for 5000 Follow up surgery for 5000
cancer (other than Units conditions covered Units "cancer" - excluding Units
malignant melanoma) under cancer in situ surgery for conditions
- that is treated and main cancer covered under cancer in
definitions situ definition
Cancer, including 10Ό00 Radiotherapy - for 5000 Supportive/home 5000
invasive malignant Units conditions covered Units support (ADL's) - Units
melanoma (excluding under cancer in situ definition to be agreed
cancer in situ and other and main cancer
pre-malignant definitions
conditions)
Chemotherapy - for 10Ό00 Physiotherapy - for 1500
conditions covered Units conditions covered Units
under cancer in situ under cancer in situ and
and main cancer main cancer definitions
definitions
Long term drugs (>6 5000 Speech therapy - for 1500
months duration) Units conditions covered Units
licensed by EMA and under cancer in situ and
supported by the main cancer definitions
treating Oncologist a s
part of going
treatment (excludes
experimental drugs) -
for conditions covered
under cancer in situ
and main cancer
definitions
Table 1: Trigger parameter stored in searchable table 7 measured in the patient
data pathway related to cancer measuring parameters. As seen in table 1, the maximal
transferable units under trigger 3 1 are in this example 12Ό00 units, under trigger 32 25Ό00
units and under trigger 33 13Ό00 units
Trigger 3 1 Trigger 32 Trigger 33 (aftercare trigger
(diagnosis trigger parameter) (treatment trigger parameter for parameter)
coronary artery disease
diagnosis)
Heart Attack diagnosis 10Ό00 Medical management 3000 Continuing symptoms 5000
- based for example on Units only (after Ml Units needing further PCI Units
ABI (Association of (Myocardial Infarction)
British Insurers) definition or AMI (Acute
Myocardial Infarction)
diagnosis)
Percutaneous 5000 Heart failure needing 10Ό00
Coronary Intervention Units implantable defibrillator. Units
(PCI) - 1 coronary
artery (after Ml
diagnosis)
Percutaneous 8000
Coronary Intervention Units
(PCI) - 1 coronary
artery (after Ml
diagnosis)
Exclude 2 stents to the
same coronary artery -
they are covered by
the 5000 unit payment
transfer
Both procedures t o be
completed within a
period of x days/weeks
- and after Ml
diagnosis)
CABG (Coronary 9000
Artery Bypass Grafting) Units
- before o r after Ml
diagnosis
Table 2: Trigger parameter stored in searchable table 7 measured in the patient
data pathway related to coronary artery disease measuring parameters (including heart
attack). As seen in table 2, the maximal transferable units under trigger 3 1 are in this
example l O'OOO units, under trigger 32 25Ό00 units and under trigger 33 15Ό00 units
Table 3: Trigger parameter stored in searchable table 7 measured in the patient
data pathway related to stroke measuring parameters. As seen from table 3, the maximal
transferable units under trigger 3 1 are in this example l O'OOO units, under trigger 32 l O'OOO
units and under trigger 33 30Ό00 units
Trigger 3 1 Trigger 32 Trigger 33 (On-going care
(diagnosis trigger parameter) (On-going care trigger management trigger parameter)
parameter for dementia)
Diagnosis of dementia 10Ό00 Psychiatric or old-age 10000 Permanent cognitive o r 10000
by Consultant Units in-patient care: Acute Units motor impairment Units
Neurologist, in-patient admission a s requiring continuous
Gerontologist, o r a result of deterioration supervision of another
Neuropsychologist; with in dementia status, person
confirmed impairment resulting in behaviours
of cognitive function that challenge and
require urgent
treatment.
Permanent cognitive o r 20Ό00
motor impairment Units
requiring constant
supervision of another
person
Table 4: Trigger parameter stored in searchable table 7 measured in the patient data
pathway related to dementia measuring parameters. As seen from table 4, the maximal
transferable units under trigger 3 1 are in this example l O'OOO units, under trigger 32 l O'OOO
units and under trigger 33 30Ό00 units. The deterioration can b e measured in MMSE scores
(Mini-Mental-Status-Examination o r Mini-Mental-Status-Test). On average, persons with
Alzheimer's disease who are not receiving treatment lose two to four MMSE points each
year, cf. h††p://www.alzheimers.org.uk/si†e/scrip†s/documen†s_info.php?documen†ID=1 2 1.
Table 5: Trigger parameter stored in searchable table 7 measured in the patient data
pathway related to hip fracture measuring parameters. As seen from table 5, the maximal
transferable units under trigger 3 1 are in this example l O'OOO units, under trigger 32 and 33 no
units are transferred by means of the system 1. Table 5 is a n example, where not all triggers
are used, i.e. trigger 3 1 is the first and final trigger after triggering hip fracture measuring
parameters in the patient data pathway (no on-going triggers 32 and/or 33). In the example
of hip fracture, risk exposure persons having age 50+ ~ 25% die within 12/1 2.
As a further technical variant, the critical illness triggers 3 1, 32, 33 comprise
multi-dimensional trigger channels. Each of said trigger-flags is assigned to a first
dimension trigger channel comprising a first trigger-level triggering 3 1 o n occurrence
parameter 1001 of the acute or chronic critical illness 7 1, 72, 73, a second trigger-level
triggering 32 on acute or first treatment phase parameter 1002, and a third trigger-level
triggering 33 on recovery phase or ongoing care/management parameter 1003 linked
to or associated with terminal prognosis data; and each of said trigger-flags is assigned
to at least a second or higher dimension trigger channel and comprises additional
trigger-stages based on the first, second and/or third trigger-levels of the first dimension
trigger channel. The critical illness trigger 3 1, 32, 33 can e.g. comprise multi-dimensional
trigger channels, wherein each of said trigger-flags is assigned to a first dimension of a
trigger channel comprising a first trigger-level triggering 3 1 o n occurrence parameter
1001 of the critical illness 7 1, 72, 73, a second trigger-level triggering 32 on acute
treatment phase parameter 1002, and a third trigger-level triggering 33 on recovery
phase parameter 1003 linked to terminal prognosis data, and each of said trigger-flags
is assigned to a second dimension of a trigger channel comprising a first trigger-level
triggering 3 1 on a first stage of progression-measuring parameters of the occurrence
1001 with regard to critical illness 7 1, 72, 73, and one or more higher trigger-levels
triggering 32, 33 in higher stages of progression-measuring parameters of the
occurred critical illness 7 1, 72, 73.
In addition, the resource-pooling system 1 can be realized such that it
transfers critical illness data in the patient data flow pathway 213, 223, 233 of the
related risk exposure component 2 1, 22, 23, etc., after triggering the occurrence of a
critical illness 7 1, 72, 73, to a n automated employee assistance system (EAP: Employee
Assistance Program) providing automated support to the risk exposure component 2 1,
22, 23, etc. Analogously, by triggering the occurrence of a n acute or chronic critical
illness 7 1, 72, 73 by means of the critical illness trigger 3 1 by the core engine 3, critical
illness data in the patient data flow pathway 213, 223, 233 of the related risk exposure
component 2 1, 22, 23, etc. can be transferred to a n alert system of a n Citizens Advice
Bureau (CAB) to activate automated or a t least semi-automated CAB actions.
Finally, in a further specified embodied variant, a n independent verification
critical illness trigger of the resource-pooling system 1 can be activated in the event of
a triggering of the occurrence 1001 of indicators for critical illness 7 1, 72, 73 in the
patient data flow pathway 2 13, 223, 233 of a risk exposure component 2 1, 22, 23, etc.
by means of the critical illness trigger 3 1, and wherein the independent verification
critical illness trigger additionally is triggering with regard to the occurrence 1001
indicators for critical illness 7 1, 72, 73 in a n alternative patient data flow pathway 2 15,
225, 235 with independent measuring parameters from the primary patient data flow
pathway 213, 223, 233 to verify the occurrence 1001 of the critical illness 7 1, 72, 73 at
the risk exposure component 2 1, 22, 23, etc. As a variant, the parametric draw-down or
predefined transfer of payments is only assigned to the corresponding trigger-flag, if the
occurrence 1001 of the critical illness 7 1, 72, 73 at the risk exposure component 2 1, 22,
23, etc. is verified by the independent verification critical illness trigger.
Claims
1. An event-driven critical illness insurance system based o n a resourcepooling
system ( 1 ) for risk sharing of critical illness risks associated with elderly persons by
providing a dynamic self-sufficient risk protection for a variable number risk exposure
components (21 , 22, 23, ...) by means of the resource-pooling system ( 1 ) , 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) 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 resources, and wherein the resource-pooling system ( 1 )
comprises a n event-driven core engine (3) comprising critical illness triggers (31 , 32, 33)
triggering in a patient dataflow pathway (213, 223, 233) to provide risk protection for a
specific risk exposure component (21 , 22, 23, ...) based o n received and stored
payments (214, 224, 234) of the risk exposure components (21 , 22, 23, ...), characterized
in that the resource-pooling system ( 1 ) comprises a filter-module for
capturing age-related parameters of risk exposure components (21 , 22, 23, ...) and for
filtering risk exposure components (21 , 22, 23, ...) associated with a n age-related
parameter greater than a predefined age-threshold value by means of the predefined
age-threshold value,
in that the resource-pooling system ( 1 ) comprises a predefined searchable
table (7) of acute and/or chronic critical illnesses (71 , 72, 73) parameters indicating 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 a n operation and/or Parkinson's
disease and/or paralysis of limb and/or terminal illness in the patient dataflow pathway
(21 3, 223, 233),
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a critical illness risk contribution (51 1, 521 , 531 ) of each pooled risk
exposure components (21 , 22, 23,...) associated to risk exposure in relation to a
diagnosis of a n acute or chronic critical illness, wherein the acute or chronic critical
illness (71 , 72, 73) is comprised in a predefined searchable table (7) of critical illnesses
(71 , 72, 73) and wherein critical illness losses occur a s a consequence to the first
diagnosis of risk exposure components (21 , 22, 23, ...) with one of the searchable critical
illnesses,
in that in case of a triggering of a n occurrence of a n acute or chronic
critical illness (71 , 72, 73) in the patient data flow pathway (21 3, 223, 233) of a risk
exposure component (21 , 22, 23), a corresponding trigger-flag is set by means of the
resource-pooling system ( 1 ) and a parametric transfer of payments is assigned to this
corresponding trigger-flag, wherein a loss associated with the acute or chronic critical
illness (71 , 72, 73) is distinctly covered by the resource pooling system ( 1 ) based o n the
respective trigger-flag and based o n the received and stored payment parameters
(21 , 224, 234) from risk exposure components (21 , 22, 23) by the parametric transfer
from the resource-pooling system ( 1 ) to the risk exposure component (21 , 22, 23, ...),
and
in that a first parametric payment (21 1) is transferred by triggering (31 ) the
occurrence (1001 ) of the acute or chronic critical illness (71 , 72, 73), a second
parametric payment (212) is transferred, in case of a n acute critical illness (71 , 72, 73),
by a triggering (32) of a n acute treatment phase (1002) of the acute critical illness (71 ,
72, 73) or, in case of a chronic critical illness (71 , 72, 73), by triggering (32) of a first
treatment phase (1002) of the chronic critical illness (71 , 72, 73), and a third parametric
payment (213) is transferred, in the case of a n acute critical illness (71 , 72, 73), by a
triggering (33) of a n aftercare phase (1003) linked to terminal prognosis data of the
acute critical illness (71 , 72, 73) or, in case of a chronic critical illness (71 , 72, 73), by a
triggering (33) a n ongoing care or management phase of the chronic critical illness (71 ,
72, 73).
2. The system ( 1 ) according to claim 1, wherein the critical illness triggers (31 ,
32, 33) comprise a trigger (31 ) 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).
3. The system ( 1 ) according to claim 2, wherein the triggering 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 reactions factors and/or
nutritional deficiencies factors and/or stress factors and/or depression factors, or denial
factors, indicating confirmed impairment of cognitive functions.
4. The system ( 1 ) according to one of the claims 1 to 3, wherein the critical
illness triggers triggering (32) the first treatment phase (1002) of the chronic critical illness
(71 , 72, 73) comprise first treatment phase parame†er(1002) indicating psychiatric or
old-age in-patient care associated with the risk exposure component (21 , 22, 23, ...)
comprising acute in-patient admission parameters a s a result of deterioration in
dementia status requiring for urgent treatment.
5. The system ( 1 ) according to one of the claims 1 to 4, wherein the critical
illness triggers (31 ,32,33) triggering a n ongoing care or management phase of the
chronic critical illness (71 , 72, 73) comprise ongoing care or management phase
parameters indicating permanent cognitive and/or motor impairment requiring
continuous supervision of another person and/or ongoing care or management phase
parameters indicating permanent cognitive and/or motor impairment requiring
constant supervision of another person.
6. The system ( 1 ) according to one of the claims 1 to 5, wherein the critical
illness triggers (31 , 32, 33) comprise a trigger (31 ) 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).
7. The system ( 1 ) according to one of the claims 1 to 6, wherein the critical
illness triggers triggering (32) the first treatment phase (1002) of the chronic critical illness
(71 , 72, 73) comprise first treatment phase parame†er(1002) indicating a measured
time interval of the risk exposure component (21 , 22, 23, ...) spend in hospital due to the
triggered stroke.
8. The system ( 1 ) according to one of the claims 1 to 7, wherein the critical
illness triggers (31 ,32,33) triggering a n ongoing care or management phase of the
chronic critical illness (71 , 72, 73) 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 of
another person and/or permanent cognitive and/or motor impairment requiring
constant supervision of another person.
9. The system ( 1 ) according to one of the claims 1 to 8, wherein the critical
illness triggers (31 , 32, 33) further comprise a trigger (31 ) for triggering measuring
parameters indicating alcohol and/or drug abuse in the patient dataflow pathway
(21 3, 223, 233), 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 ) .
10. The system ( 1 ) according to one of the claims 1 to 7, wherein the critical
illness triggers of the acute critical illness (71 , 72, 73) triggering (32) acute treatment
phase parameters (1002) indicating surgery and/or chemotherapy and/or radiotherapy
and/or reconstructive surgery in the patient dataflow pathway (213, 223, 233).
11. The system ( 1 ) according to one of the claims 1 to 10, wherein the first
and second and third transferred portion of payment are generatable to sum up to the
allocated total parametric payment.
12. The system ( 1 ) according to one of the claims 1 to 11, wherein the
resource-pooling system ( 1 ) comprises a n assembly module (5) to process risk-related
component data (21 1, 221 , 231 ) and to provide the likelihood (21 2, 222, 232) of said risk
exposure for one or a plurality of the pooled risk exposure components (21 , 22, 23, ...)
based o n the risk-related component data (21 1, and wherein the receiving and
preconditioned storage (6) of payments (214, 224, 234) from risk exposure components
(21 , 22, 23, ...) for the pooling of their risks is dynamically determinable based on total
risk (50) and/or the likelihood of the risk exposure of the pooled risk exposure
components (21 , 22, 23, ...).
13. The system ( 1 ) according to one of the claims 1 to 12, wherein the
number of pooled risk exposure components (21 , 22, 23, ...) is dynamically adaptable
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 totally pooled risk exposure components (21 , 22, 23, ...) at a given time.
14. The system ( 1 ) according to one of the claims 1 to 13, wherein the
critical illness triggers (31 , 32, 33) are dynamically adapted by means of a n operating
module (30) based o n time-correlated incidence data for a critical illness conditions
and/or diagnosis or treatment conditions indicating improvements in diagnosis or
treatment.
15. The system ( 1 ) according to one of the claims 1 to 14, wherein the
allocated total parametric payment is determined a t least based o n the risk-related
components data (21 1, 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, ...) based on the risk
related components data 2 11, 221 , 231 and wherein the first portion is transferred up to
30% of said total payments sum and the second portion is transferred up to 50% of said
total payments sum and the third portion is transferred up to the residual part given by
said total payment sum minus the actual portion and the second portion.
1 . The system ( 1 ) according to one of the claims 1 to 15, wherein the
resource-pooling system ( 1 ) comprises a monitoring module (8) requesting a periodic
payment transfer from the risk exposure components (21 , 22, 23, ...) to the resourcepooling
system ( 1 ) by means of a plurality of payment receiving modules (2), wherein
the risk protection for the risk exposure components (21 , 22, 23, ...) is interrupted by the
monitoring module (8) when the periodic transfer is no longer detectable by means of
the monitoring module (8).
17. The system ( 1 ) according to claim 1 , wherein the request for periodic
payment transfer is interrupted or waived by the monitoring module (8) when the
occurrence (1001 ) of indicators for critical illness (71 ,72,73) is triggered (31 ) in a patient
data flow pathway of a risk exposure component (21 , 22, 23, ...).
18. The system (1) according to one of the claims 1 to 17, wherein the
resource-pooling system ( 1 ) comprises a n independent verification critical illness trigger,
which is activated in the event of a triggering of the occurrence (1001 ) of indicators for
critical illness in the patient dataflow pathway (213, 223, 233) of a risk exposure
component (21 , 22, 23, ...) by means of the critical illness trigger (31 ) and which
additionally, is a triggering for the occurrence (1001 ) of indicators for critical illness (71 ,
72, 73) in a n alternative patient dataflow pathway (215, 225, 235) with independent
measuring parameters from the primary patient data flow pathway (213, 223, 233) to
verify the occurrence of the critical illness (71 ,72,73) at the risk exposure component (21 ,
22, 23, ...).
19. The system ( 1 ) according to claim 17, wherein the parametric transfer of
payments is only assigned to the corresponding trigger-flag, if the occurrence (1001 ) of
the critical illness (71 ,72,73) at the risk exposure component (21 , 22, 23, ...) is verified by
the independent verification critical illness trigger.
20. The system ( 1 ) according to one of the claims 1 to 19, wherein critical
illness data of the patient dataflow pathway (213, 223, 233) of the risk exposure
component (21 , 22, 23, ...) are transferred to a n automated employee assistance
system (EAP: Employee Assistance Program) providing automated support to the risk
exposure component (21 , 22, 23, ...).
2 1. The system ( 1 ) according to one of the claims 1 to 20, wherein the
patient dataflow pathway (213, 223, 233) is monitored by the resource-pooling system
( 1 ) by capturing patient measuring parameter of the patient dataflow pathway (213,
223, 233) a t least periodically and/or within predefined time frames.
22. The system ( 1 ) according to one of the claims 1 to 2 1, wherein the
patient dataflow pathway (213, 223, 233) is dynamically monitored by the resourcepooling
system ( 1 ) by a triggering of patient measuring parameters of the patient
dataflow pathway (213, 223, 233) transmitted from associated measuring systems.
23. An event-driven critical illness insurance system based o n a resourcepooling
system ( 1 ) for risk sharing of critical illness risks associated with elderly persons by
providing a dynamic self-sufficient risk protection for a variable number risk exposure
components (21 , 22, 23, ...) by means of the resource-pooling system ( 1 ) , 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) 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 resources, and wherein the resource-pooling system ( 1 )
comprises a n event-driven core engine (3) comprising critical illness triggers (31 , 32, 33)
triggering in a patient dataflow pathway (213, 223, 233) to provide risk protection for a
specific risk exposure component (21 , 22, 23, ...) based on received and stored
payments (214, 224, 234) of the risk exposure components (21 , 22, 23, ...), characterized
in that the resource-pooling system ( 1 ) comprises a filter-module for
capturing age-related parameters of risk exposure components (21 , 22, 23, ...) and for
filtering risk exposure components (21 , 22, 23, ...) associated with a n age-related
parameter greater than a predefined age-threshold value by means of the predefined
age-threshold value,
in that the resource-pooling system ( 1 ) comprises a predefined searchable
table (7) of acute and/or chronic critical illnesses (71 , 72, 73) parameters indicating 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 a n operation and/or Parkinson's
disease and/or paralysis of limb and/or terminal illness in the patient dataflow pathway
(21 3, 223, 233),
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a first risk contribution (51 1, 521 , 531 ) of each pooled risk exposure
components (21 , 22, 23,...) associated to risk exposure in relation to a first diagnosis of a
critical illness, wherein the critical illness (71 , 72, 73) is comprised in a predefined
searchable table (7) of critical illnesses (71 , 72, 73) and wherein critical illness losses
occur a s a consequence to the first diagnosis of risk exposure components (21 , 22, 23,
...) with one of the searchable critical illnesses,
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a t least a second and/or successional risk contributions (512/522/...,
513/521/...) associated to risk exposure in relation to a second and/or successional
critical illnesses, wherein the critical illnesses (71 , 72, 73) are comprised in the predefined
searchable table (7) of critical illness parameters (71 , 72, 73), and wherein a critical
illness loss losses occurs a s a consequence †o the second and/or successional diagnosis
of risk exposure components (21 , 22, 23, ...) with one of the searchable critical illnesses,
in that in case of a triggering of a n occurrence of a first or second or
successional critical illness (71 , 72, 73) in the patient data flow pathway (213, 223, 233)
of a risk exposure component (21 , 22, 23), a corresponding trigger-flag is set by means
of the resource-pooling system ( 1 ) and a parametric draw-down transfer of payments is
assigned to this corresponding trigger-flag, wherein a loss associated with the first or
second or successional critical illness(es) (71 , 72, 73) is distinctly covered by the resource
pooling system ( 1 ) based on the respective trigger-flag and based on the received and
stored payment parameters (214, 224, 234) from risk exposure components (21 , 22, 23)
by the parametric draw-down transfer from the resource-pooling system ( 1 ) to the risk
exposure component (21 , 22, 23, ...), and
in that a first parametric payment (21 1) is transferred by triggering (31 ) the
occurrence (1001 ) of the acute or chronic critical illness (71 , 72, 73), a second
parametric payment (212) is transferred, in case of a n acute critical illness (71 , 72, 73),
by a triggering (32) of a n acute treatment phase (1002) of the acute critical illness (71 ,
72, 73) or, in case of a chronic critical illness (71 , 72, 73), by triggering (32) of a first
treatment phase (1002) of the chronic critical illness (71 , 72, 73), and a third parametric
payment (213) is transferred, in the case of a n acute critical illness (71 , 72, 73), by a
triggering (33) of a n aftercare phase (1003) linked to terminal prognosis data of the
acute critical illness (71 , 72, 73) or, in case of a chronic critical illness (71 , 72, 73), by a
triggering (33) a n ongoing care or management phase of the chronic critical illness (71 ,
72, 73).
24. The system ( 1 ) according to one of the claims 1 to 23, wherein the
system comprises more than said three trigger stages (31 , 32, 33), the first three trigger
stages (31 , 32, 33) associated with said trigger parameters in the patient dataflow
pathway (213, 223, 233) and associated with said first, second and third draw-down
payment (21 1, 2 12, 2 13), and wherein the subsequent trigger stages are associated
with measurable trigger parameters and gradated parametric payments, indicating
further gradation in the patient dataflow pathway (2 13, 223, 233) .
25. An method for risk sharing of critical illness risks associated with elderly
persons by providing a dynamic self-sufficient risk protection for a variable number of
risk exposure components (21 , 22, 23, ...) by means of the resource-pooling system ( 1 ) ,
wherein the risk exposure components (21 , 22, 23, ...) are connected to the resourcepooling
system ( 1 ) by means of a plurality of payment receiving modules (4) and
payment data (214, 224, 234) are received and stored by means of a payment data
store (6) from the risk exposure components (21 , 22, 23, ...) for the pooling of their risks,
and wherein the resource-pooling system ( 1 ) triggers a patient dataflow pathway (213,
223, 233) by means of critical illness triggers (31 , 32, 33) of a n event-driven core engine
(3) in order to provide risk protection for a specific risk exposure component (21 , 22, 23,
...) based on received and stored payments (214, 224, 234) from the risk exposure
components (21 , 22, 23, ...), characterized
in that risk exposure components (21 , 22, 23, ...) associated with a n agerelated
parameter greater than a predefined age-threshold value are filtered and
captured by means of a filter-module and the predefined age-threshold value,
in that acute or chronic critical illnesses (71 , 72, 73) parameters indicating
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 a n operation and/or
Parkinson's disease and/or paralysis of limb and/or terminal illness in the patient
dataflow pathway (213, 223, 233), are stored by means of a predefined searchable
table (7),
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a critical illness risk contribution (51 1, 521 , 531 ) of each pooled risk
exposure components (21 , 22, 23,...) associated to risk exposure in relation to a
diagnosis of a n acute or chronic critical illness, wherein the acute or chronic critical
illness (71 , 72, 73) is comprised in a predefined searchable table (7) of critical illnesses
(71 , 72, 73) and wherein critical illness losses occur a s a consequence to the first
diagnosis of risk exposure components (21 , 22, 23, ...) with one of the searchable critical
illnesses,
in that in case of a triggering of an occurrence of a n acute or chronic
critical illness (71 , 72, 73) in the patient data flow pathway (213, 223, 233) of a risk
exposure component (21 , 22, 23), a corresponding trigger-flag is set by means of the
resource-pooling system ( 1 ) and a parametric transfer of payments is assigned to this
corresponding trigger-flag, wherein a loss associated with the acute or chronic critical
illness (71 , 72, 73) is distinctly covered by the resource pooling system ( 1 ) based on the
respective trigger-flag and based on the received and stored payment parameters
(21 , 224, 234) from risk exposure components (21 , 22, 23) by the parametric transfer
from the resource-pooling system ( 1 ) to the risk exposure component (21 , 22, 23, ...),
and
in that a first parametric payment (21 1) is transferred by triggering (31 ) the
occurrence (1001 ) of the acute or chronic critical illness (71 , 72, 73), a second
parametric payment (212) is transferred, in case of an acute critical illness (71 , 72, 73),
by a triggering (32) of an acute treatment phase (1002) of the acute critical illness (71 ,
72, 73) or, in case of a chronic critical illness (71 , 72, 73), by triggering (32) of a first
treatment phase (1002) of the chronic critical illness (71 , 72, 73), and a third parametric
payment (213) is transferred, in the case of an acute critical illness (71 , 72, 73), by a
triggering (33) of an aftercare phase (1003) linked to terminal prognosis data of the
acute critical illness (71 , 72, 73) or, in case of a chronic critical illness (71 , 72, 73), by a
triggering (33) a n ongoing care or management phase of the chronic critical illness (71 ,
72, 73).
26. The method according to claim 25, wherein 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) are triggered by means of a trigger (31 ) of the critical illness
triggers (31 , 32, 33).
27. The method according to claim 26, wherein the triggering 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 reactions factors and/or
nutritional deficiencies factors and/or stress factors and/or depression factors, or denial
factors, indicating confirmed impairment of cognitive functions.
28. The method according to one of the claims 25 to 27, wherein the critical
illness triggers triggering (32) the first treatment phase (1002) of the chronic critical illness
(71 , 72, 73) comprise first treatment phase parame†er(1002) indicating psychiatric or
old-age in-patient care associated with the risk exposure component (21 , 22, 23, ...)
comprising acute in-patient admission parameters a s a result of deterioration in
dementia status requiring for urgent treatment.
29. The method according to one of the claims 25 to 28, wherein the critical
illness triggers (31 ,32,33) triggering a n ongoing care or management phase of the
chronic critical illness (71 , 72, 73) comprise ongoing care or management phase
parameters indicating permanent cognitive and/or motor impairment requiring
continuous supervision of another person and/or ongoing care or management phase
parameters indicating permanent cognitive and/or motor impairment requiring
constant supervision of another person.
30. The method according to one of the claims 25 to 29, wherein the critical
illness triggers (31 , 32, 33) comprise a trigger (31 ) 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).
3 1. The method according to one of the claims 25 to 30, wherein the critical
illness triggers triggering (32) the first treatment phase (1002) of the chronic critical illness
(71 , 72, 73) comprise first treatment phase parame†er(1002) indicating a measured
time interval of the risk exposure component (21 , 22, 23, ...) spend in hospital due to the
triggered stroke.
32. The method according to one of the claims 25 to 3 1, wherein the critical
illness triggers (31 ,32,33) triggering a n ongoing care or management phase of the
chronic critical illness (71 , 72, 73) 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 of
another person and/or permanent cognitive and/or motor impairment requiring
constant supervision of another person.
33. The method according to one of the claims 25 to 32, wherein the critical
illness triggers (31 , 32, 33) further comprise a trigger (31 ) for triggering measuring
parameters indicating alcohol and/or drug abuse in the patient dataflow pathway
(21 3, 223, 233), 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 ) .
34. The method according to one of the claims 25 to 33, wherein the critical
illness triggers of the acute critical illness (71 , 72, 73) triggering (32) acute treatment
phase parameters (1002) indicating surgery and/or chemotherapy and/or radiotherapy
and/or reconstructive surgery in the patient dataflow pathway (213, 223, 233).
35. The method according to one of the claims 25 to 34, wherein the first
and second and third transferred portion of payment are generatable to sum up to the
allocated total parametric payment.
36. The method according to one of the claims 25 to 35, wherein by means
of a n assembly module (5) risk-related component data (21 1, 221 , 231 ) are processed
and the likelihood (212, 222, 232) of said risk exposure for one or a plurality of the pooled
risk exposure components (21 , 22, 23, ...) is provided based o n the risk-related
component data (21 1, and wherein the receiving and preconditioned storage (6) of
payments (214, 224, 234) from risk exposure components (21 , 22, 23, ...) for the pooling
of their risks is dynamically is determined based on total risk (50) and/or the likelihood of
the risk exposure of the pooled risk exposure components (21 , 22, 23, ...).
37. The method according to one of the claims 25 to 36, wherein the
number of pooled risk exposure components (21 , 22, 23, ...) is 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 totally pooled risk exposure components (21 , 22, 23, ...) a t a given time.
38. The method according to one of the claims 25 to 37, wherein the critical
illness triggers (31 , 32, 33) are dynamically adapted by means of a n operating module
(30) based on time-correlated incidence data for a critical illness conditions and/or
diagnosis or treatment conditions indicating improvements in diagnosis or treatment.
39. The method according to one of the claims 25 to 38, wherein the
allocated total parametric payment is determined a t least based o n the risk-related
components data (21 1, 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, ...) based on the risk
related components data 2 11, 221 , 231 and wherein the first portion is transferred up to
30% of said total payments sum and the second portion is transferred up to 50% of said
total payments sum and the third portion is transferred up to the residual part given by
said total payment sum minus the actual portion and the second portion.
40. The method according to one of the claims 25 to 39, wherein by means
of a monitoring module (8) a periodic payment transfer is requested from the risk
exposure components (21 , 22, 23, ...) to the resource-pooling system ( 1 ) by means of a
plurality of payment receiving modules (2), wherein the risk protection for the risk
exposure components (21 , 22, 23, ...) is interrupted by the monitoring module (8) when
the periodic transfer is no longer detectable by means of the monitoring module (8).
4 1. The method according to claim 40, wherein the request for periodic
payment transfer is interrupted or waived by the monitoring module (8) when the
occurrence (1001 ) of indicators for critical illness (71 ,72,73) is triggered (31 ) in a patient
data flow pathway of a risk exposure component (21 , 22, 23, ...).
42. The method according to one of the claims 25 to 4 1, wherein a n
independent verification critical illness trigger is activated in the event of a triggering of
the occurrence (1001 ) of indicators for critical illness in the patient dataflow pathway
(21 3, 223, 233) of a risk exposure component (21 , 22, 23, ...) by means of the critical
illness trigger (31 ) and which additionally, is a triggering for the occurrence (1001 ) of
indicators for critical illness (71 , 72, 73) in a n alternative patient dataflow pathway (21 5,
225, 235) with independent measuring parameters from the primary patient data flow
pathway (21 3, 223, 233) to verify the occurrence of the critical illness (71 ,72,73) a t the
risk exposure component (21 , 22, 23, ...).
43. The method according to claim 42, wherein the parametric transfer of
payments is only assigned to the corresponding trigger-flag, if the occurrence (1001 ) of
the critical illness (71 ,72,73) a t the risk exposure component (21 , 22, 23, ...) is verified by
the independent verification critical illness trigger.
44. The method according to one of the claims 25 to 43, wherein critical
illness data of the patient dataflow pathway (213, 223, 233) of the risk exposure
component (21 , 22, 23, ...) are transferred to a n automated employee assistance
system (EAP: Employee Assistance Program) providing automated support to the risk
exposure component (21 , 22, 23, ...).
45. The method according to one of the claims 25 to 44, wherein the
patient dataflow pathway (213, 223, 233) is monitored by the resource-pooling system
( 1 ) by capturing patient measuring parameter of the patient dataflow pathway (21 3,
223, 233) a t least periodically and/or within predefined time frames.
46. The method according to one of the claims 25 to 45, wherein the
patient dataflow pathway (21 3, 223, 233) is dynamically monitored by the resourcepooling
system ( 1 ) by a triggering of patient measuring parameters of the patient
dataflow pathway (213, 223, 233) transmitted from associated measuring systems.
47. An event-driven critical illness insurance method based o n a resourcepooling
system ( 1 ) for risk sharing of critical illness risks associated with elderly persons by
providing a dynamic self-sufficient risk protection for a variable number risk exposure
components (21 , 22, 23, ...) by means of the resource-pooling system ( 1 ) , 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) 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 resources, and wherein the resource-pooling system ( 1 )
comprises a n event-driven core engine (3) comprising critical illness triggers (31 , 32, 33)
triggering in a patient dataflow pathway (213, 223, 233) to provide risk protection for a
specific risk exposure component (21 , 22, 23, ...) based on received and stored
payments (214, 224, 234) of the risk exposure components (21 , 22, 23, ...), characterized
in that by means of a filter-module age-related parameters of risk exposure
components (21 , 22, 23, ...) are captured and risk exposure components (21 , 22, 23, ...)
associated with a n age-related parameter greater than a predefined age-threshold
value by means of the predefined age-threshold value are filtered,
in that the resource-pooling system ( 1 ) comprises a predefined searchable
table (7) of acute and/or chronic critical illnesses (71 , 72, 73) parameters indicating 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 a n operation and/or Parkinson's
disease and/or paralysis of limb and/or terminal illness in the patient dataflow pathway
(21 3, 223, 233),
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a first risk contribution (51 1, 521 , 531 ) of each pooled risk exposure
components (21 , 22, 23,...) associated to risk exposure in relation to a first diagnosis of a
critical illness, wherein the critical illness (71 , 72, 73) is comprised in a predefined
searchable table (7) of critical illnesses (71 , 72, 73) and wherein critical illness losses
occur a s a consequence to the first diagnosis of risk exposure components (21 , 22, 23,
...) with one of the searchable critical illnesses,
in that the total risk (50) of the pooled risk exposure components (21 , 22, 23,
...) comprises a t least a second and/or successional risk contributions (512/522/...,
513/521/...) associated to risk exposure in relation to a second and/or successional
critical illnesses, wherein the critical illnesses (71 , 72, 73) are comprised in the predefined
searchable table (7) of critical illness parameters (71 , 72, 73), and wherein a critical
illness loss losses occurs a s a consequence to the second and/or successional diagnosis
of risk exposure components (21 , 22, 23, ...) with one of the searchable critical illnesses,
in that in case of a triggering of a n occurrence of a first or second or
successional critical illness (71 , 72, 73) in the patient data flow pathway (213, 223, 233)
of a risk exposure component (21 , 22, 23), a corresponding trigger-flag is set by means
of the resource-pooling system ( 1 ) and a parametric draw-down transfer of payments is
assigned to this corresponding trigger-flag, wherein a loss associated with the first or
second or successional critical illness(es) (71 , 72, 73) is distinctly covered by the resource
pooling system ( 1 ) based on the respective trigger-flag and based on the received and
stored payment parameters (214, 224, 234) from risk exposure components (21 , 22, 23)
by the parametric draw-down transfer from the resource-pooling system ( 1 ) to the risk
exposure component (21 , 22, 23, ...), and
in that a first parametric payment (21 1) is transferred by triggering (31 ) the
occurrence (1001 ) of the acute or chronic critical illness (71 , 72, 73), a second
parametric payment (212) is transferred, in case of a n acute critical illness (71 , 72, 73),
by a triggering (32) of a n acute treatment phase (1002) of the acute critical illness (71 ,
72, 73) or, in case of a chronic critical illness (71 , 72, 73), by triggering (32) of a first
treatment phase (1002) of the chronic critical illness (71 , 72, 73), and a third parametric
payment (213) is transferred, in the case of a n acute critical illness (71 , 72, 73), by a
triggering (33) of a n aftercare phase (1003) linked to terminal prognosis data of the
acute critical illness (71 , 72, 73) or, in case of a chronic critical illness (71 , 72, 73), by a
triggering (33) a n ongoing care or management phase of the chronic critical illness (71 ,
72, 73).
48. The method according to one of the claims 1 to 47, wherein the method
processes more than said three trigger stages (31 , 32, 33), the first three trigger stages
(31 , 32, 33) associated with said trigger parameters in the patient dataflow pathway
(213, 223, 233) and associated with said first, second and third draw-down payment
(21 1, 212, 213), and wherein the subsequent trigger stages are associated with
measurable trigger parameters and gradated parametric payments indicating further
gradation in the patient dataflow pathway (21 3, 223, 233).