WO2009092072A2 - Evaluating effectiveness of claims evaluation, assessment, and settlement processes - Google Patents
Evaluating effectiveness of claims evaluation, assessment, and settlement processes Download PDFInfo
- Publication number
- WO2009092072A2 WO2009092072A2 PCT/US2009/031406 US2009031406W WO2009092072A2 WO 2009092072 A2 WO2009092072 A2 WO 2009092072A2 US 2009031406 W US2009031406 W US 2009031406W WO 2009092072 A2 WO2009092072 A2 WO 2009092072A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- closed
- values
- candidate
- similar
- injury
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/18—Legal services; Handling legal documents
- G06Q50/188—Electronic negotiation
Definitions
- the present invention generally relates to systems and methods for evaluating the effectiveness and consistency of computer processes and systems used in insurance assessment and negotiation.
- Insurance companies have been processing and settling claims associated with bodily injury for a long time.
- the task of evaluating, analyzing or estimating the amount of damage associated with one or more types of bodily injuries, especially trauma-induced bodily injuries, can be very complex. Complexity in the evaluation process often arises out of the fact that concurrent expertise in legal, medical and insurance fields is often required to arrive at a particular decision involving a bodily injury claim.
- a knowledge -based claim-processing system may include an expert system which utilizes and builds a knowledge base to assist the user in decision making. Such a system may allow the insurance companies to define new business rules and/or use previously defined rules, in real-time.
- the business rules are generally written by industry experts to evaluate legal, medical, insurance conditions before arriving at a valuation of a claim.
- Various embodiments of assessing and evaluating processes for insurance claim estimation and settlement are disclosed.
- data is provided for closed claims that have been previously settled using an estimation and settlement process.
- Each closed claim in the data is treated as a candidate claim.
- a set of closed claims similar to the candidate closed claim is identified based on characteristics of the candidate closed claim.
- a representative value for the set of similar claims such as an arithmetic mean, is determined.
- the settlement values for the candidate closed claims are compared to the representative values for the sets of similar closed claims.
- the consistency of the claims estimation and settlement process is evaluated based on the comparison.
- a potential benefit of changing or improving the estimation and settlement process is projected based on the comparison.
- the projection may be used in benefit studies, quality assessments, or the like.
- a method of evaluating an insurance claim estimation and settlement process includes providing candidate claims, each having an associated general damages value. For each candidate claim, a set of claims that are similar to a candidate claim is identified based on characteristics of the candidate claim and the similar claims. A representative general damages value for the set of similar claims is determined. A total general damages value is calculated for all the candidate claims. A total representative general damages value is determined for the sets of similar claims associated with the candidate claims. A difference between the total general damages value for the candidate claims and total representative general damages value for the sets of similar claims is calculated.
- claims in a set of similar claims are grouped into two or more zones based on the values of the claims.
- a representative value for the set of similar claims may be based on values determined for claims in one or more of the zones, (such as an average value for the claims in a mid-zone).
- the representative value for the set of similar claims may be compared to the value for a candidate claim.
- FIG. 1 illustrates a computer system suitable for implementing various embodiments.
- FIG. 2 illustrates matching of candidate claims to precedent claims according to one embodiment.
- FIG. 3 illustrates a summary report for a set of precedent claims for a soft tissue injury according to one embodiment.
- FIG. 4 illustrates a summary report for a set of precedent claims for a fracture injury according to one embodiment.
- FIG. 5 illustrates grouping of a claim set into zones according to one embodiment.
- FIG. 6 illustrates determining an amount for use in settling an open claim using likelihood estimation according to one embodiment.
- FIG. 7 illustrates determining amounts for settling open claims using a likelihood function according to one embodiment.
- FIG. 8 shows a set of matches for an open claim.
- FIG. 9 is a graph of likelihood values for a data set for an open claim.
- FIG. 10 illustrates displaying likelihood values for a set of precedent claims matching an open claim according to one embodiment.
- FIG. 11 illustrates a display of likelihood values for a set of claims matching an open claim according to one embodiment.
- FIG. 12 illustrates displaying summary amounts to a user based on a display mode selected by the user.
- FIG. 13 illustrates determining equalization values based on defined equalization criteria for a system and processing open claims using the determined equalization values.
- FIG. 14 illustrates determining recommended settlement amounts and ranges with adjustments to adjusted general damages values for matching precedent claims.
- FIG. 15 illustrates determining an effectiveness of a process using a closed claim - to - closed claim comparison according to one embodiment.
- FIG. 16 illustrates evaluation of a claim estimation and settlement process in which evaluation includes determining differences between values for candidate closed claims and representative values for similar closed claims, according to one embodiment.
- FIG. 17 illustrates an example of results from a closed claim mathematical analysis.
- FIG. 18 illustrates a column chart reporting the matching frequency for a claim set according to one embodiment.
- FIG. 1 illustrates an embodiment of computer system 250 that may be suitable for implementing various embodiments of a system and method for processing claims.
- Each computer system 250 typically includes components such as CPU 252 with an associated memory medium such as disks 260.
- the memory medium may store program instructions for computer programs.
- the program instructions may be executable by CPU 252.
- Computer system 250 may further include a display device such as monitor 254, an alphanumeric input device such as keyboard 256, and a directional input device such as mouse 258.
- Computer system 250 may be operable to execute the computer programs to implement computer-implemented systems and methods for processing claims.
- Computer system 250 may include a memory medium on which computer programs according to various embodiments may be stored.
- memory medium is intended to include an installation medium, e.g., a CD-ROM, a computer system memory such as DRAM, SRAM, EDO RAM, Rambus RAM, etc., or a non-volatile memory such as a magnetic media, e.g., a hard drive or optical storage.
- the memory medium may also include other types of memory or combinations thereof.
- the memory medium may be located in a first computer, which executes the programs or may be located in a second different computer, which connects to the first computer over a network. In the latter instance, the second computer may provide the program instructions to the first computer for execution.
- Computer system 250 may take various forms such as a personal computer system, mainframe computer system, workstation, network appliance, Internet appliance, personal digital assistant ("PDA”), television system or other device.
- PDA personal digital assistant
- computer system may refer to any device having a processor that executes instructions from a memory medium.
- the memory medium may store a software program or programs operable to implement a method for processing insurance claims.
- the software program(s) may be implemented in various ways, including, but not limited to, procedure-based techniques, component-based techniques, and/or object-oriented techniques, among others.
- the software programs may be implemented using C#, ASP.NET, HTML, JavaScript, Java, ActiveX controls, C++ objects, JavaBeans, Microsoft
- a CPU such as host CPU 252 executing code and data from the memory medium may include a means for creating and executing the software program or programs according to the embodiments described herein.
- Various embodiments may use a service-oriented architecture.
- functions may be defined using a description language.
- Interfaces may be invoked to perform business processes.
- the interfaces may be independent of the platform on which the systems operate. Therefore, the services may be used regardless of the device, operating system, or communication protocol.
- a system includes a rule and calculation engine.
- the rule and calculation engine may also allow a user to configure the system to meet particular business needs.
- a system includes a thin-client common front end.
- the common front end may provide a single claims view for all types of claims. Views can be tailored to specific types of users, such as call center representatives, who handle notification and status calls, and back- office claims processors and adjudicators.
- a back office system may be provided. Back office users may handle more complex business processes and processes that remain active over a longer period of time.
- the back office may include access to management reports. Through the back office, managers may have access to all functions within their business unit in order to provide advice and to handle issues. In one embodiment, the back office may be provided as a thin client.
- FSO means financial services organization.
- An FSO may be an organization such as an insurance carrier or a bank.
- FSO also includes any company, organization, or other entity that covers risk and assesses claims, including entities that self-insure.
- general damages generally refers to general damages relating to an injury or accident. General damages may include damages relating to pain and suffering, permanent impairment, disability, loss of enjoyment of life, and disfigurement.
- a "closed” claim means a claim that has been settled.
- an "open” means to a claim that has yet to be settled.
- "precedents” generally refer to acts or instances that may be used as an example in dealing with subsequent similar instances. Applying this interpretation to bodily injury claims, precedent finding includes the act of comparing the facts of a bodily injury claim to bodily injury claims that have occurred previously, to find similar claims and to compare the "outcome” of these claims with each other. For this purpose, the "outcome" of a bodily injury claim can be the monetary settlement, or award in respect of general damages assessed or awarded for injuries suffered.
- a “candidate claim” includes a claim that being considered for adjustment, evaluation, estimation, assessment, or comparison.
- the candidate claim may be, for example, an open claim for which a process of estimation, negotiation, and settlement needs to be carried out by an insurer.
- a "match" includes a claim that is identified for a candidate claim based on one or more similarities to the candidate claim. For example, a closed claim relating to a broken radius bone may be found to match a candidate claim relating to a broken ulna bone. A match need not require that the characteristics of a claim be identical to the candidate claim. The degree of similarity that a system uses to produce a match may be controlled to produce a set of matching claims that are relevant to a claims negotiation process.
- monetary amount means an amount of money.
- a monetary amount may be expressed in any terms that indicate or correspond to financial value.
- a monetary amount may be expressed in the form of a currency, such as dollars, euros, or yen.
- “likelihood value” generally refers to a value corresponding to or representing the likelihood of a condition or event. For example, a likelihood value may provide a measure of the likelihood that the monetary value associated with a particular closed claim matching an open claim represents an appropriate value for use in settling the open claim.
- most likely value generally refers to a value derived from a set of two or more values that, based on an established set of criteria, is most likely to represent a good value for settlement of a claim.
- most likely range generally refers to a range of values derived from a set of two or more values that, based on an established set of criteria, is most likely to represent a good range for settlement of a claim.
- an “adjusted value” generally refers to a value that is adjusted (increased or decreased) from an original value based on one or more criteria. In some embodiments, an adjustment may be made for one or more differences between a candidate claim and a matching claim.
- equalization generally refers to a process of finding and/or accounting for relativities between settlement general damages amounts with different characteristics (e.g., for different jurisdictions or for different litigation types).
- a set of equalization values e.g., coefficient values
- the equalization values may be retrieved from the database and used to adjust the values of matching precedent claims to account for differences between the characteristics of the open claim and the characteristics of the matching precedent claims.
- equalization does not require that the value of any one claim be made equal to that of any other claim.
- a system allows an adjuster to compare each open and its relevant factors to other similar closed claims to determine common attributes so that the adjuster can better assess the value of each claim.
- the value of a claim may be, for example, a general damages value for a bodily injury claim.
- the system may include a database that covers all the closed claims data of a particular FSO. Details of such claims may be accessed by the adjuster to assist the adjuster in assessing values for new claims with the same or similar factors. Similar claims that significantly vary in value can be reviewed by the adjuster to understand what unique factors may have been present in the prior claim to determine whether that prior claim may have relevance to the current claim.
- FIG. 2 illustrates matching of candidate claims to precedent claims according to one embodiment.
- one or more claims are identified that are similar to a candidate claim based on one or more characteristics of the candidate claim.
- the identification of similar claims may be carried out automatically using a computer system.
- a claims matching process may be performed using PRECEDENT IDTM, available from Computer Sciences Corporation (CSC).
- information concerning the matching claims may be presented to an adjuster.
- the information may include information on individual claims, as well as information concerning the set of claims as a whole.
- statistical information concerning the matching claims may be presented to the adjuster.
- a value for the candidate claim is estimated.
- the value may be based on the value of one or more of the matching claims.
- the estimated value for the candidate claim may be the same as a particular matching claim.
- the estimated value may be based on statistical information (e.g., an average) for one or more of the matching claims.
- the value of the candidate claim may be used in a process for settling the claim.
- the negotiation process for a particular open claim may include more than one matching procedure. For example, an initial offer may be made to a claimant based on one matching procedure.
- a second matching process may be carried out to support an analysis of whether to accept the counter-offer or to formulate a response to the counter- offer.
- FIG. 3 illustrates an example summary for a set of precedent claims for a soft tissue injury according to one embodiment.
- FIG. 4 illustrates an example summary for a set of precedent claims for fracture injury according to one embodiment.
- Various characteristics of a candidate claim and/or precedent claims may be used in determining a matching set of claims.
- characteristics include the nature of any injuries, the treatment modalities, the injury stabilization period, the nature of any complications, the medical outcome and prognoses, and the degree of any residual permanent impairment.
- additional data including mitigating factors, attorney name, vehicle impact, and/or driving while under the influence, may be considered.
- a system or program for automatically identifying similar cases may be used in combination with a general assessment tool.
- an adjuster may use COLOSSUS®, available from Computer Sciences Corporation, as a general assessment tool.
- an adjuster may have a general assessment program and a catalog of precedent cases to assist the adjuster in determining an appropriate value for the claim and to aid in the negotiation process.
- the system collates and presents the outcome of closely similar finalized claims.
- An insurer's collection of finalized claims includes claims settled by negotiation, those determined by arbitration or mediation and those determined through the court process (verdicts).
- Finalized cases reflect the opinions and evaluations of adjusters and their peers, attorneys, injured parties, arbitrators and juries, and therefore collectively may be a fair and true reflection of the potential value of a given claim.
- relative values or severities of injuries and assessment behavior may be learned from a database of finalized claims.
- the relative difference between the contusion and fracture are exhibited in the finalized claims already present.
- the system may use data mining technologies to learn the relative values of such injuries and many others, from the tangle of injuries present in the finalized claims.
- This technology is also used to determine the impact that various treatments and complications have on the value of claims, as well as other medical and non-medical attributes. These include such things as the jurisdiction, i.e., how damages for particular injuries vary from state to state and county to county, and litigation stage, i.e., whether the claim was settled with or without attorney representation and whether a suit was filed.
- the system may determine for example that if there was both a contusion and a fracture in a claim that the contusion was not a key feature of the claim.
- the knowledge gained from data mining the finalized claims may form the basis of determining what is important and what is not in claims, and how this varies from claim to claim.
- Matching may include input of precise and comprehensive injury and claim data to successfully search for similar claims, including the nature of injuries, the treatment modalities, injury stabilization period, nature of any complication, the medical outcome and prognoses, and the degree of any residual permanent impairment or disability.
- other important information to be stored in the finalized claims database includes the financial outcome of each claim.
- the General Damages component for all settlements, arbitration awards and verdicts may be stored for each claim along with all the other components of the settlement.
- mathematical models may be applied to the information relating to matched claims.
- Statistical measures such as mean or median for the claim set may be determined and presented to the user.
- claims with similar adjusted general damages amounts are grouped into zones.
- determining the zones typically three are produced, but there may be fewer depending on how many claims are found as matches.
- the objective in determining zones can be expressed as determining where to place the dividing lines between the values in order to make three good clusters. Good clusters may be characterized by the 'closeness' of the values to each other in a cluster.
- FIG. 5 illustrates grouping of a claim set into zones according to one embodiment.
- claims are identified that are similar to a candidate claim.
- an initial grouping of the claims is made.
- the sum of the squared errors is calculated by taking the mean of the values in a cluster, finding the difference between each value and the mean, squaring the difference, and computing the sum for all of the claims.
- the dividing line is iteratively moved between values to determine the group of values with the lowest sum of squared errors.
- the precedent claims are divided in three groups - High, Medium and Low.
- the system calculates the minimum, maximum and weighted average value (e.g., general damages value) and the number of claims.
- the system also needs to derive the values which separate the groups.
- three bands may be calculated. However, there may be fewer bands. In this case the high band is discarded first, then the middle band. Values may be derived to separate the groups, or bands, in order to place the claims into these bands. In this case of three bands, the task is to find the two values that represent the dividing lines between the low and medium bands, and the dividing line between the medium and high bands. These two values may be found by regression (a stepwise process of refinement of the solution). The regression process starts by dividing the claims into three groups in increasing order of value. The value may be, for example, a General Damages amount or medicals amount, depending on which are being derived at the time.
- Claims are initially allocated with equal numbers in each group (as far as equal numbers can be achieved, the total number may not be exactly divisible by 3, e.g. 10 claims).
- the values which separate the groups are then calculated as the midpoints of the claims on either side. In other words, the separator value between the low and medium groups is calculated as half way between the highest claims in the low group and the lowest claim in the medium group.
- the next task is to see if the separator values can be changed in some way in order to derive more compact groups of values, or a tighter configuration of claims in the groups.
- To measure compactness, or tightness of values we use the sum of the squared errors - in this case the squared errors between each claim in a group and the average value for that group. If the sum of the squared errors decreases then the claims values in a group will form a tighter cluster.
- An iterative task is performed, which moves the separator values in the direction of the decreasing total squared error, for all the three groups combined. In other words, it modifies the separator values until it has the tightest fit for the three bands.
- Cluster A and cluster B may be divided into zones using the following approach:
- Table 1 is an example of a set of similar claims for which can be grouped into zones according to one embodiment.
- Table 2 is an example of a sequence of iterations used to group the claims in Table 1. To simplify the illustration, only two zones (Group A and Group B) are determined in the example.
- a first iteration is performed with the claims evenly divided — claims M, N, and O in Group A, and claims P, Q, and R in Group B.
- the sum squared error is calculated for Iteration 1.
- Subsequent iterations may be carried out until the grouping with the lowest sum squared error is found.
- Iteration 3 in which Group A includes claims M ($4,000) and N ($4,200) and Group B includes claims O ($5,000), P ($5,100), Q ($5,200), and R ($5,300), is associated with the lowest sum squared error (70,000) of all the iterations.
- This grouping may be used in mathematical models support claim assessment, process evaluation, or other purposes.
- an average for each zone is calculated using a weighted average calculation that considers the similarity (i.e., more similar attributes) of the precedent claims to the candidate claim.
- a weight is calculated for each claim, based on its similarity to the candidate claim, For example, an age of the claimant and the impairment as attributes to measure for claim similarity. For whiplash claims, duration of treatment, general practitioner visits, specialist visits, physical therapy, and chiropractic visits as attributes may be used to measure for claim similarity,
- a ratio is first developed which is calculated as the absolute difference between the candidate claim's attribute value and the precedent claim's attribute value, divided by the size of the zone used in the search for this attribute. For instance, if the candidate claim had a claimant age of 40 and the search used an age range of 30-50 (this range is purely hypothetical and will be influenced by search filters and algorithms) then the age band is 20. If the precedent claim had a claimant age of 45 then the age attribute ratio would be (45-40)/20 or 0.25. Ratios are calculated for all the relevant claim attributes. Then an average ratio is derived from all the relevant attribute ratios that have been calculated. The weight is then 1 minus the average ratio, all squared. Therefore, if the claim is very similar to the candidate claim then the weight will be close to 1, while if it has significant dissimilarities then the weight can be close to zero (e.g., 0.0025).
- the weighted average is then calculated by multiplying each precedent claim's value (e.g., adjusted General Damages) by its weight, giving its weighted value.
- the weighted values for all the claims in a cluster are summed and then divided by the sum of the weights for all precedent matches to the candidate claim. The result is the weighted average. Determining Amounts for Claims Settlement using Likelihood Values
- FIG. 6 illustrates determining an amount for use in settling an open claim using likelihood estimation according to one embodiment.
- an automated system may be used to identify one or more closed claims that match an open claim.
- Each of the closed claims may be associated with a corresponding monetary amount.
- the monetary amounts are general damages.
- a likelihood value is determined with respect to each of the closed claims.
- one or more amounts are determined for the open claim based on the likelihood values for the matching closed claims.
- the amounts may be monetary amounts.
- An adjuster may use the monetary amounts in settling the open claim.
- the monetary amount may be used as a proposed payout amount for the open claim.
- Monetary amounts may be representative of a value for any of various aspects of the claim.
- a monetary amount may represent a general damages value, a medicals value, a settled value, or a payout value.
- monetary amounts may be presented to an adjuster as a Most Likely Amount or Most Likely Range.
- likelihood values for the matching claims are displayed as a function of amount (e.g., in an x-y graph).
- likelihood values associated with the matching claims are graphically displayed. The amounts and likelihood values may be displayed simultaneously or on separate screens.
- likelihood values are determined using kernel density estimation. Kernel density estimations methods suitable for embodiments described herein may be found in "Very fast optimal bandwidth selection for univariate kernel density estimation” by Vikas Chandrakant Raykar and Ramani Duraiswami (Dec 20, 2005, CS-TR-4774/UMIACS-TR-2005-73). In certain embodiments, likelihood values for matching claims are determined using maximum likelihood estimation.
- FIG. 7 illustrates determining amounts for settling open claims using a likelihood function according to one embodiment.
- a set of claims e.g., closed claims
- a function is determined with respect to each of the matching claims in the set.
- a Gaussian function is derived for each claim in the set of claims.
- a Gaussian curve has a mean of 0 and a variance of 1.
- a suitable bandwidth is determined for the function.
- One method for determining bandwidth may be that given in the Raykar paper.
- a likelihood function is derived for the entire set of matching claims from the functions for the individual claims.
- the likelihood function is the sum of the functions for the individual claims.
- kernel density estimation is accomplished using a fast density derivative estimation. In other embodiments, kernel density estimation is accomplished using a solve-the-equation plug-in method. In one embodiment, a fast density derivative method is used for relatively large sets (e.g., 20 or more points), and a solve-the-equation plug-in method is used for smaller sets.
- likelihood values are determined with respect to each matching claim in the set.
- amounts for settling the open claim are determined based on the likelihood values of the matching claims.
- an amount for settling is the amount associated with the closed claim with the highest likelihood value.
- a rank or rating may be assigned to each of the matching claims based on the likelihood value.
- One or more ranges may be determined. Each range may include all claims falling within a specified portion of the likelihood curve. In one embodiment, a range is defined to include all the claims having values within about the top quartile of the likelihood curve. In another embodiment, a range is defined to include all claims within a specified percentage of a most likely value. In one embodiment, a range is defined to include all claims within about 10 % of a most likely value.
- FIG. 8 illustrates an example of a data set for an open claim.
- FIG. 9 is a graph of likelihood values for the data set shown in FIG. 8.
- Table 440 includes data for a set of claims that match a candidate claim.
- Column 442 indicates the candidate claim for which the matching claims are found. In this case, the candidate claim is identified as claim number CWWl 10001001.
- Column 444 indicates closed claims that were found to match claim CWWl 10001001.
- a unique claim number identifies each of the matching claims.
- Column 446 indicates a rating for each closed claim.
- Column 448 indicates an adjusted dollar value for each of the closed claims.
- Column 450 indicates a general damages value before adjustment.
- Column 452 indicates a likelihood value associated with each claim.
- the likelihood value may be based on a likelihood function determined as described above with respect to FIG. 7. In the data set shown in FIG. 8, the following is used for the kernel density estimate:
- N is the number of points
- x is the value of a point
- h is a bandwidth.
- Bandwidth may be selected by estimating an asymptotic mean integrated squared error (AMISE)-optimal bandwidth.
- AMISE asymptotic mean integrated squared error
- the rating shown in column 446 may provide an indicator of how useful the value for a claim might be in settling the open claim.
- the rating may reflect how close a match the candidate claim is to the matched claim in regards to data on the claim.
- claim number 0000017267001 has a rating of 1.
- Point 462 shown in FIG. 9, which is associated with claim number 0000017267001, is near the middle of the upper range of the likelihood curve.
- claim number 0000004399001 has a rating of 4.
- Point 464 shown in FIG. 9, which is associated with claim number 0000004399001, is on the lower fringe of the likelihood curve.
- a rating associated with a claim value may be based on the claim's position within a cluster of points. For example, points 463, 464, and 465 may be considered to form a cluster. The claim associated with point 465 may be given a relatively high rating because point 465 is in the middle of the cluster.
- a value e.g., dollar amount
- a representative value For example, $3,123.46, which is the amount associated with point 465, may be used as a representative value.
- FIG. 10 illustrates displaying likelihood values for a set of precedent claims matching an open claim according to one embodiment.
- precedent claims that match an open claim are identified.
- a likelihood value is determined with respect to each of the matching precedent claims.
- a graph of likelihood values associated with the matching precedent claims as a function of amount is displayed.
- one or more ranges of amounts are indicated on the graph.
- FIG. 11 illustrates a display of likelihood values for a set of claims matching an open claim according to one embodiment.
- Display 480 includes graph portion 482 and summary portion 484.
- Graph portion 482 of display 480 includes general damages graph 486.
- General damages graph 486 includes a curve showing likelihood values as a function of general damages. In the embodiment illustrated in FIG. 11, the curves are represented by specific discrete points (X' s). The curves may, however, be represented by a continuous curve or any other discrete or continuous symbology.
- General damages graph 486 and medicals graph 488 may provide a user with a visual representation of values for the matching claims.
- General damages graph 482 may allow an adjuster to identify a cluster of a values and select a value from the cluster, rather than for example, just picking a value from a textual list.
- General damages graph 486 includes mid band 490, lower range 492, and upper range 494.
- Mid band 490 corresponds to a most likely range for general damages.
- Mid band 490 and ranges 492 and 494 may serve as visual aids to assist an adjuster in choosing amounts for settling an open claim.
- mid band 490 may be shaded, hatched, highlighted, or colored, or the like. Such indicators may provide an additional visual cue to an adjuster for focusing on a most likely amount or range.
- a display may include only those values within a particular band. For example, an x-y graph may display only the portion of a curve associated with a mid-band, and not display any values associated with points in the lower or upper ranges.
- Summary portion 484 of display 480 includes numerical values of most likely amount and most likely range for general damages. Although in the display shown in FIG. 10, graph portion 482 and summary portion 484 relate to general damages, graphs may be directed to other amounts. In certain embodiments, a display may include a graph and summary for medicals instead of, or in addition, the graph and summary for general damages.
- graphs and summary information are each displayed on a separate screen. Switching between screens may be accomplished by selecting a tab or by toggling between a graph screen and a summary screen.
- a display may include other information associated with a matching claim set. For example, a History Dialog Window may include the following columns:
- the 'LkIy High/Low' amounts may correspond to the Most Likely Low and High amounts. These amounts may appear on Summary, Graphs, Compare With and/or Report screens.
- likelihood includes scale of values 0 through 5.
- values may be shown without any specific numerical values.
- likelihood values may be depicted graphically, relative to other likelihood values, rather than as an absolute value of likelihood.
- an adjuster may be provided with amounts for matching precedent claims that are derived using two or more different methods. For example, an adjuster may consider a recommended settlement amount based on both a kernel density estimate for the matching claims and a least squares analysis of the matching claims.
- FIG. 12 illustrates displaying summary amounts to a user based on a display mode selected by the user.
- closed claims are identified that match an open claim.
- likelihood values are determined with respect to the matching precedent claims.
- amounts and ranges for use in settling the open claim are determined based on the likelihood values for the matching precedent claims.
- one or more amounts and ranges are determined for settling the open claim based on least squares method. Amounts and ranges may be determined, for example, as described above with respect to FIG. 5.
- a display based on least squares method may include a mid-zone amount and a mid-zone range.
- a user may be prompted to select a display mode. If the user selects the likelihood display mode, summary amounts based on likelihood are displayed at 510. If the user selects the least squares display mode, summary amounts based on least squares are displayed at 512.
- the selection of a display mode may be by toggle, tab, or other user input.
- a default display mode may be established upon installation of a claims-matching program onto a computer system.
- a user may simultaneously view amounts and graphs based on more than one method. For example, a user may simultaneously view amounts and graphs based on a maximum likelihood method and amounts and graphs based on a least squares method.
- amounts are automatically computed for an open claim based on both likelihood and least squares methods regardless of the mode selected by the user.
- a system may compute amounts only when the user selects a particular mode. For example, if the system default is to display likelihood values, the system might not calculate least squares values unless and until the user selects a least squares display mode.
- Adjusting General Damages Values using Equalization Values general damages values for precedent claims are adjusted using predetermined equalization values to account for one or more differences between an open claim and matching precedent claims.
- the equalization values may be derived from a set of closed claim data and stored in a database when a system is first installed or configured for use process open claims. During processing of an open claim, the equalization values are retrieved from the database and used to adjust the general damages values of matching claims. An adjuster may use the adjusted general damages values for the matching precedent claims as basis for settling the open claim.
- FIG. 13 illustrates determining equalization values based on defined equalization criteria for a system and processing open claims using the determined equalization values.
- Equalization criteria may be configured or selected globally for all claims to be settled by an adjuster, group of adjusters, or an FSO. In one embodiment, equalization criteria are selected or configured when a claims- matching program is installed on an FSO computer system. Equalization criteria are then applied to all claims to be settled (or, alternately, to all claims that match predetermined criteria).
- equalization criteria are selected from a defined list. The defined list may be presented, for example, to an installer of a claims matching program when the program is installed. Equalization criteria may relate to various characteristics of a claim including locality, injury type, personal characteristics of a claimant, dominant injury, and claimant type.
- Equalization criteria may be based on a single characteristic or a combination of two or more characteristics. Equalization criteria may be selected using drop-down menus, check boxes, or similar methods. At 602, equalization values are determined based on the selected equalization criteria.
- the equalization values may be coefficients derived from a set of closed claim data. In alternate embodiments, the equalization values may be expressed as factors or multipliers. Coefficient values will vary as a function of the characteristics of the claims, such as jurisdiction, claim type, and/or secondary injury.
- the equalization values may be calculated in a batch process. In one embodiment, the batch process for determining the equalization values is run when a claims- matching program is first installed. The equalization values may be recalculated (e.g., by a subsequent batch process) at various times after the initial installation of a program. For example, the equalization values may be updated on a periodic basis, such as annually or quarterly.
- equalization values are determined based on the particular customer' s past claim data. For example, based on one customer's past data, baselined equalization values may produce an adjusted settlement amount for a claim in Louisiana that is 20 % less than a similar claim in New York City, while, based on another customer's past data, baselined equalization values may produce an adjusted settlement amount for a claim in Louisiana that is 22 % less than a similar claim in New York City. Beginning at 604, the system is placed into service to determine amounts for use in processing open claims. It will be understood that once the equalization values are determined at 602 (such as at the time the system is installed), any number of open claims may be processed without recalculating the equalization values.
- bodily injury data for an open claim is entered into the system.
- one or more precedent claims that match the open claim are identified by the system based on one or more characteristics of the open claim.
- a value of one or more of the matching precedent claims is adjusted based on the previously determined baselined equalization values. For example, for an open claim involving permanent impairment of a 20-year old male, the system may return an amount for a first matching closed claim settled for a 25- year old male and a second matching closed claim settled for a 30-year old male. Based on the baselined equalization values, the value for the closed claim relating to the 25-year old male may be increased by 4%, and the value for the closed claim relating to the 30-year old male may be increased by 8%.
- a value for a closed claim relating to a broken tibia might be adjusted upward for use in settling an open claim relating to a broken femur.
- an amount for use in settling the open claim is determined based on the adjusted values for the closed claims.
- the amounts for settling the claim are displayed.
- equalization criteria includes jurisdiction, claim type, and secondary injury (or a subset of one or more of these criteria). Other equalization criteria can be used, however.
- equalization criteria include personal characteristics of the claimants. Examples of personal characteristics to be used as equalization criteria include gender, age, or type or nature of the injury to the claimant, or type or nature of the impairment to the claimant.
- equalization criteria include whether a claimant's injury is a combination injury or not.
- one claim may relate to both a demonstrable and a soft tissue injury, while another claim may relate to only a soft tissue injury.
- a general damages value relating to the soft tissue-only claim may be adjusted using baselined equalization values to increase or decrease the value relative to a combination injury claim.
- equalization criteria include what a dominant injury of a claim is. For example, if a claim arises from a case where the dominant injury is demonstrable, the general damages value may be adjusted using equalization values to increase or decrease the value relative to a claim arising from a case where the dominant injury is a soft-tissue injury.
- equalization criteria includes settlement characteristics for the claims. Examples of settlement characteristics that may form the basis for equalization include claim type (e.g., whether a lawsuit has been filed), whether a claimant is represented by an attorney, or the identity of an attorney representing the claimant.
- equalization criteria may include whether there is a particular type of evidence available with respect to the accident. For example, equalization values may be based on whether data for the accident is available from an electronic data recorder (EDR).
- EDR electronic data recorder
- equalization criteria may include whether EDR data for the accident indicates that an injury was a low-impact injury.
- claims for which EDR data suggests fraud may be adjusted or filtered out of the results.
- equalization criteria includes the locality of the claim.
- a locality may be a country, state, or a region thereof.
- a locality may be a sub-state locality (a portion of a state), such as a county, city, or zip code.
- a general damages value for a matching claim in Orange County, California may be adjusted for use in settling an open claim in Los Angeles County, California, or Dade County, Florida based on past data from a California insurer.
- a recommended settlement amount is determined by combining a value derived from precedent claims with one or more adjustments for the pending claim.
- a "pending claim adjustment” generally refers to an addition or subtraction based on one or more amounts associated with the pending claim.
- Pending claim adjustments can include any adjustment for the actual claim being settled. Examples of pending claim adjustments include specials, disfigurement, offsets, medical expenses (e.g., incurred expenses or expected expenses), wages (e.g., actual lost wages or expected lost wages), or a combination thereof.
- a recommended settlement may be calculated as follows:
- recommended settlement ranges may be determined in a similar manner as the recommended settlement amounts.
- FIG. 14 illustrates determining recommended settlement amounts and ranges with adjustments to adjusted general damages values derived from matching precedent claims.
- precedent claims that match an open claim are identified.
- a likelihood value is determined with respect to each of the matching precedent claims.
- likelihood values associated with matching precedent claims are displayed.
- an adjusted general damages amount for the open claim is determined based on the likelihood values for the matching precedent claims.
- a range of adjusted general damages amounts is determined for the open claim based on the likelihood values for the matching precedent claims.
- pending claim adjustments are made to an adjusted general damages amount and general damages range for the open claim, respectively. The pending claim adjustments may be made automatically, for example, by an FSO computer system.
- a most likely settlement amount and most likely settlement range for the open claim are determined.
- computed amounts and ranges are displayed to a user.
- the general damages amounts and ranges are determined based on likelihood values for the matching closed claims (see 702, 706, and 708). In other embodiments the general damages amounts and ranges may be determined from other methods, such as from a mid-zone calculation based on a least squares method.
- an "Adjusted Recommended Payout” amounts are calculated after the matching process has been completed and displayed on the Summary tab of the screen.
- the recommended payout amounts may be a combination of the adjusted general damages amounts of catalog claims (e.g., similar past claims) brought back in the matching process and the specials, offsets, adjustments, and disfigurement of the pending claim (i.e. the claim currently being entered into the system and adjusted).
- An example determination is as follows:
- Adjusted Settled GD amount of catalog claim may exclude specials and disfigurement, but include other offsets.
- the above formula may be applied to settlement values and ranges. For example, the above formula may be applied to a most likely settlement amount and a most likely settlement range. Least Squares Display
- the formula described above for Recommended Settlement Amount may be applied to the final high, average, and low amounts that are displayed in the Adjusted Generals column based on a least squares method. After the Recommended Settlement amounts have been calculated for the claims catalog, those amounts may be displayed in the Recommended Settlement column. The amounts can be calculated each time the user navigates to the screen if the specials, offsets, or disfigurement have been updated since the previous re -run. Any amounts that are calculated to be less than zero may be displayed as a '$0' in this column (i.e. negative amounts are not displayed). The following is an example display of values based on a least squares method: Adjusted General Damages: Recommended Settlement: High: $5,500 High: $7,500 Average: $3,500 Average: $5,500
- the display may contain fields named "Most Likely Settlement Amount” and "Most Likely Settlement Range” and appear in the corresponding locations as the current amount fields located in the Adjusted Generals section.
- the amounts can be calculated and stored each time the user navigates to the screen if the specials, offsets, or disfigurement have been updated since the previous re-run. Any amounts that are calculated to be less than zero may be displayed as a '$0' in this column (i.e. we will not display negative amounts).
- each candidate claim is an open claim for which an estimate of value is desired for purposes of settling the claim.
- the system provides an adjuster with access to data on closed claims that match the open claim.
- a claims-matching process is used to evaluate a claim estimation, negotiation and resolution process that has already been used by a company (i.e., a post "production" environment).
- each closed claim may be treated as a candidate claim and compared with other closed claims.
- Mathematical models may be used to determine the effectiveness of the process that has been used. For example, the system may be used to quantify how consistent a claim estimation and settlement process was.
- any of the methods used to match, identify, group, equalize, or display claims or claim data described with respect to FIGS. 6-14, including but not limited to kernel density estimation, may be used in assessing the effectiveness of claims evaluation, assessment, and settlement processes.
- any or all of the steps, including but not limited to matching or identifying claims or displaying data relating to claims may be carried out automatically using a computer system.
- an evaluation of a claims settlement process is performed using cross comparisons of an insurer's closed claim data for bodily injury claims.
- the data may reflect hundreds or thousands of closed claims.
- FIG. 15 illustrates determining an effectiveness of a process using a closed claim - to - closed claim comparison according to one embodiment.
- a set of closed claim data is provided.
- an insurer's closed claim data may be initially scrubbed to remove data that might skew the results, such as claims that have invalid or missing information.
- the closed claim data may be for a defined period (e.g., the preceding 3 years).
- the closed claim data may be limited by other attributes, such a jurisdiction, claim type, or dominant injury.
- precedent claims are identified for a closed claim in a defined set of claims.
- Each closed claim in the data set is considered a candidate claim when it is used as the claim at issue.
- the claim data for each candidate claim is used when searching for precedents (e.g., matches) of that candidate claim.
- a claims matching process is performed as described above with respect to FIG. 2, except that each candidate claim is a closed claim instead of an open claim.
- the system automatically excludes precedent claims from the set of matches if they exceed a defined amount of variation from some attribute of the set of precedent claims. For example, the system may automatically exclude precedent claims from the set of matches if they are greater than two standard deviations above or below the mean of the set of matches. Approximately 95 percent of all matching claims are within two standard deviations of the mean of all such matches to the candidate claim.
- a representative value is determined for the precedent claims associated with the candidate claim.
- the representative value may be based on a statistical value such as mean, median, or mid-zone value of the precedent claims.
- the system repeats the sequence of precedent claim identification (362) and determination of a representative value (364) for each of the candidate claims.
- one or more representative values of the precedent closed claims are compared with one or more values of the candidate closed claims.
- the comparison may include computing a difference between the representative value (e.g., mean, median, or mid-zone value) of the precedent claims and the value of the candidate closed claims.
- consistency of the claims estimation and settlement process is evaluated.
- the evaluation may be based on a comparison of the values of the candidate closed claims with representative values of the similar claims. For example, a small aggregate deviation between the values of the candidate claims and the representative values of the associated sets of precedent claims may indicate that the process used to arrive at the values of the candidate claims produces consistent results. Conversely, a large aggregate deviation between the values of the candidate claims and the representative values of the associated sets of precedent claims may indicate that the process used to arrive at the values of the candidate claims produces inconsistent results.
- determining a representative value may include kernel density estimation. In another embodiment, determining a representative value may include maximum likelihood estimation.
- FIG. 16 illustrates evaluation of a claim estimation and settlement process that includes determining differences between the general damages values for candidate closed claims and general damages values for similar closed claims according to one embodiment.
- claims in the data set that are similar to a candidate claim are identified based on characteristics of the candidate claim. Although the entire data set might include thousands of claims, the mathematical modeling is performed on each claim separately, treating each claim as the candidate claim.
- Each candidate claim will have a subset of precedent matches from the other claims. Therefore, the relevant data set size is represented by the number of precedent claims matched to the candidate claim.
- Each data set could be one precedent claim or many precedent claims.
- a representative general damages value is determined for the set of precedent claims associated with each of the candidate claims.
- the representative general damages value may be based on a statistical value for the entire set, or for a subset, of the similar claims.
- the mathematical analysis is successively performed using models and methods of increased complexity and sophistication. Initially, simple measures, such as median and mean, which do not require assumptions about the underlying set of matched general damages, may be used.
- the median is the number that splits the ordered set of precedent claims essentially in half. By using the median, effects of outliers are minimized without having to exclude any claims from the calculation.
- the mean is the average of all precedent matches.
- the median and mean are calculated using the set of precedent matches for each closed candidate claim. Once the median and mean are calculated, they are compared to the actual total general damages for the candidate closed claim.
- the system repeats the step of precedent claim identification (380) and calculation of a representative value (382) for each of the candidate claims.
- a total accumulated general damages value for the candidate claims is determined.
- the total accumulated general damages value may be the sum of the general damages values for all the candidate claims.
- a total accumulated representative general damages value for the sets of similar claims associated with the candidate claims is determined.
- the total representative general damages value may be the sum of the representative general damages value determined for the sets of precedent claims.
- the total accumulated difference (variance) between each candidate claim's general damages value and its corresponding representative general damages value is determined for all candidate closed claims.
- the total accumulated difference may be the difference between the sum of all the general damages values of the candidate claims and the sum of the representative general damages value for the associated sets of precedent claims.
- a difference is first computed between the value for each candidate claim and the representative value for the precedent claims, and then the accumulated difference is determined by taking the sum of these differences.
- an impact percentage is calculated based on the total accumulated difference.
- the impact percentage may be determined by dividing the total accumulated difference by the total accumulated general damages for the candidate claims.
- the impact percentage may be expressed in the followin *eg formula:
- the impact percentage may be used as a measure of consistency of the estimation and settlement process (with relatively larger impact percentage reflecting greater inconsistency in the estimation and settlement process). For example, an impact percentage less than 2 % may indicate that the process for establishing a value of the candidate claims was relatively consistent in producing values, while an impact percentage of greater than 10 % may indicate that the process was relatively inconsistent in producing values.
- Impact percentages may be used in benefit studies to project the impact of making a process change or improvement. For example, the impact percentages may be used to project a potential improvement to an insurer from implementing a new system and/or methodologies for evaluating and settling open claims.
- FIG. 17 illustrates a simple example of results for a closed claim mathematical analysis. For the sake of simplicity for illustrative purposes, only two candidate claims are included in the set. A closed claim evaluation might, however, include any number of candidate claims, and might include hundreds or thousands of candidate claims.
- each of the candidate claims information is provided for each of the candidate claims, including identification (ID), claim type, jurisdiction, dominant injury (e.g., soft tissue or demonstrable), and value.
- the value for each candidate claim may be a general damages value for the claim as determined by a claim adjuster during the evaluation and settlement of the claim.
- a set of matching closed claims is listed for each of the candidate closed claims.
- Each of the matching claims includes a corresponding value.
- the matching claims may be grouped into zones (e.g., low, mid, high).
- a mean, a median, and a mid-zone average are computed for each set of similar claims.
- FIG. 17 information is provided for each of the candidate claims, including identification (ID), claim type, jurisdiction, dominant injury (e.g., soft tissue or demonstrable), and value.
- the value for each candidate claim may be a general damages value for the claim as determined by a claim adjuster during the evaluation and settlement of the claim.
- a set of matching closed claims is listed for each of the candidate closed claims.
- the mid-zone average is an unweighted average of the mid-zone claims (i.e., claims O, P, Q, and R for candidate claim 1 and claims W, X, and Y for candidate 2).
- a mid-zone average may be a weighted average.
- each of claims O, P, Q, and R may each be given a different weight depending on their degree of similarity to candidate claim 1.
- the total of each value category is accumulated to yield the total associated with all candidate claims.
- the difference between the total representative value and the total value is calculated. Based on the difference for each representative value, the impact percentage is determined.
- an impact is determined for a subset of an insurer' s closed claim data that meets certain criteria.
- an impact may be determined for only the claims having a certain claim type, jurisdiction, or dominant injury.
- claim types include: unrepresented, unlitigated, and suit. "Unrepresented” are those claims without attorney representation. "Unlitigated” are those claims with attorney representation, but no suit has been filed. "Suit” are those claims in which some type of suit has been filed, but not necessarily a jury verdict outcome.
- a matching process may produce a different number of matches for each candidate claim. For example, candidate ID 1 has 8 matches, while candidate ID 2 has 5 matches. The frequency of the number of matching claims may be plotted for the candidate claims. The results may be presented to the user is graphical or textual format.
- FIG. 18 illustrates a column chart for reporting the matching frequency for a claim set according to one embodiment.
- the x-axis represents the number of matching claims for a candidate and the y-axis represents the number of candidate claims having a given number of matching claims.
- the legend at the base of each column represents a number of matching claims for a candidate.
- the height of the column indicates the total number of candidate claims in the claim set with that number of matches. For example, there were 800 candidate claims in the set for which 6 matching claims were identified.
- other statistical information such as mean and standard deviation may be reported, presented and/or used in evaluating an effectiveness of a claims assessment process. Identifying Similar Claims
- a claim may be defined to be predominantly demonstrable if it falls into any of the following categories: 1. It has no soft tissue spinal injuries
- Ligament injuries (but not a shoulder ligament injury) 4. It has any of the following, but no soft tissue spine injuries a. Lacerations b. Concussion c. Contusions d. Superficial injuries e. Sprain strain injuries
- Trivial injuries are defined as the injuries for which no matching priority rules exist. Injuries such as contusions, untreated lacerations, and superficial injuries are trivial injuries. If a claim contains only trivial injuries then the system may find matches for the most significant of the trivial injuries, as defined by the injury hierarchy, set out under "Injury Hierarchy" in the Section explaining rule priority considerations.
- the system may use the presence of the trivial injuries as matching criteria if the injury filter is set to "tight". This is explained in the injury section within "Filters” described below. Matching for Soft Tissue Spine
- the two broad classes of claim information that will be used in the matching are treatment duration and treatment level, there being a correlation between treatment duration and treatment level.
- Treatment time defines injury stabilization time or the time taken for an injury to reach maximum improvement.
- Treatment level can involve multiple types of therapeutic treatment. For instance, this can be any combination of chiropractic, physical therapy, other therapy, GP consultation and specialist doctor consultation. Other treatment can involve various forms of spinal immobilization and prescribed medication.
- Matching may involve setting some bounds around the values that are inherent in the current claim, in order to find claims that have similar, but not necessarily exactly the same values.
- the criteria used for matching similar claims is as described in the tables below.
- the table above may be based on a piecewise linear function approach. For example, a claim where the treatment time was 30 days will be addressed in the following manner. The 30 days treatment time is located in the first column, it is the second entry. The bounds then become from 30 days minus 25%, this being approximately 23 days, to 30 days plus 33%, this being approximately 37 days. Thus initially claims are looked for that had treatment times of 23 to 37 days, in this case. For treatment times which do not fall exactly on a value in the first column, which will be the case the vast majority of the time, a piecewise linear extrapolation may be used to determine the appropriate intermediate value. A worked example is contained for "Treatment Level" below. Exactly the same formula would be used. Treatment Level GP Treatment Consultations
- the second and third columns define the low and high bound of GP visits that will be searched for. For example, if the current claim had 5 actual GP visits search would be searched for claims that had between 4 and 7 GP visits (these being the values from the second and third columns for the fourth row, which has the 5 GP visits in the first column).
- y is the extrapolated value; x is the number of GP visits; xj is the value from the first column which is less than x; x 2 is the value from the first column which is greater than x; yj is the value from either the second or third columns (depending on whether we are predicting the lower or upper bound) which corresponds to the X 1 value from the first column; and similarly y 2 corresponds with
- Both the GP and specialist tables differ from the therapeutic treatment tables below, in that for the higher values in column 1 the corresponding bands (columns 2 and 3) are broader upwards more than downwards. For example, for 20 GP visits the band is between 15 and 30 visits, whereas for therapeutic treatment it is 15 to 25. Even for therapeutic treatment of 70 visits the band is equally distributed, being from 55 to 85 - a difference of 15 either side. For the GP and specialist it is regarded that there comes a point where additional treatment no longer impresses as to the severity of the injury, and it suggestive of over-servicing. For this reason the band is larger on the high side.
- the above table entries can be altered to reflect a particular company's experience or as new trends emerge.
- this table defines the low and high bounds for chiropractic treatment used in matching. Physical therapy and other therapy are processed in the same manner using the respective tables below. However, each therapeutic treatment type is used distinctly in the matching process, and matched claims must satisfy all the derived bounds. For example, if the current claim had 10 chiropractic visits and 10 physical therapy visits then matched claims must have between 7 and 14 chiropractic visits and also between 7 and 14 physical therapy visits.
- Other therapy includes treatment given by practitioners of osteopathy, naturopathy, homeopathy or other "alternative medical practices” such as acupuncture, herbal medicine, faith healing, massage or any other non-orthodox therapeutic practices.
- the tables have different values associated even with the same actual observed value. In other words, if our claim has no GP visits the bounds become up to 1 GP visit. The difference between none and one GP visit may not be significant. However, the difference between a claim for which a specialist opinion was sought and one where it was not required has more significance as an indicator of severity, simply because of the fact that a specialist opinion was required. Most soft tissue injuries would not involve a specialist referral.
- matching similar cases may include, in the first instance, matching similar injuries.
- Injuries as defined by the program include traumatic amputations, fracture dislocations, dislocations, fractures, intra-abdominal injuries, intra-thoracic injuries, intra-pelvic injuries, vertebral disc injuries, ligament injuries, lacerations, sprains and strains and trivial injuries such as contusions and superficial injuries.
- a fractured skull is not an insignificant injury; but an intracranial hematoma is both life threatening and potentially can lead to residual brain damage; which required an invasive operative procedure to drain the hematoma (craniotomy).
- a fractured skull would not generally require any operative treatment. In this case the craniotomy alters the nature of the case, making it a more severe head injury.
- the complication of the intracranial hematoma transcends both the initial injury and the operative treatment, and becomes the dominant medical feature of this claim. Determining the most severely injured body part therefore takes into account all three of these considerations - injuries, treatments and complications, or a combination of these.
- the dominant medical feature of a case can be specified by the adjuster using the system's user interface, or failing this, can be determined by the system.
- the system can perform this function. In order to do this the system:
- the major body parts include the head, chest, abdomen, pelvic area, the spine, arms and legs. • Determining the dominant medical feature of the most injured body part
- Each case can have any number of medical attributes associated with it. These can be a number of injuries, treatments and complications, in any combination. For each of these instances there is a corresponding character code (there is a seventh character denoting sidedness), which is constrained to be from a list of treatment, or complication codes predefined with each injury code tracked by the system.
- predefined treatment and complication codes may be derived from a series of mappings within the system.
- Injury may be mapped to treatment
- injury may be mapped to complication
- complication may be mapped to treatment.
- the system may have a list of treatments the injury may require, these are sorted as "expected" and "possible” treatments. For example if the injury were an open fracture of the tibia, the treatment list might contain:
- the list can include treatments for potential complications which will vary depending on the type of complication that occurred. This might include such procedures as fasciotomy, osteoarthrotomy, nerve or vascular repair. Medical procedures are considered only as past and future procedures, there is no notion of initial treatment or subsequent treatment, and these are considered simply as past treatment. Similarly, for each injury code, the system can have a list of potential complications that might arise from the injury. In the case of our fractured tibia this would include:
- Complication and treatment mapping may be derived from medical references including:
- a table may be accessed which defines a number of attributes for each medical code.
- the pain and suffering severity scale is used to derive overall medical severity for each injured body part, given the medical facts regarding the case being considered.
- a pain and suffering severity scale can represent relative severity between injuries, treatments and complications respectively.
- the severity applied may be in isolation to the particular injury, treatment or complication it is applied to.
- the severity applied to an open fracture of the femur can be for the relative trauma of the fracture alone, and not include the treatment or any other considerations.
- the relative severity applied to an open reduction of the femur might not take into account the trauma for the fracture.
- the scale may not include severity for implied impairment. For example procedures such as amputation and arthrodesis leave permanent impairments but these may be ignored in the assigned value.
- the pain and suffering severity scale may be refined through a calibration process described below. Calculating Major Body Part Relative Pain and Suffering Severity
- agglomeration algorithms are used to derive a combined value for a body part when more than one medical code is present. For example, if a case consisted of a fractured humerus and a fractured scaphoid, both being to the same arm, then the agglomeration algorithm can derive an overall value for the arm in question, comprising both injuries. The system can do this for every body part described above.
- the determination of the combined value may not be a simple summation of the medical codes. Doing so would result in unconstrained total values. For example, even if a case involves a fracture of the middle finger, which on average settles for $5,000, this does not mean that a case involving three fractured fingers should settle for $15,000. For example, the proximity of the fingers may obviate the combined value being three times the value of one, thus the value for the three- finger injury should be less than three times that of the one-finger injury.
- a set of rules may be utilized, one set for each major body part.
- Each rule detects a particular medical feature. For example, one rule, within the leg detects a femur fracture with osteomyelitis, another with avascular necrosis, yet another for nonunion of the femur.
- the rules may be run which correspond to body parts representing the dominant medical features. For example, if the user had nominated a fractured tibia and a fractured humerus as dominant, then the rules may be run for the leg and those for the arm respectively. In running these rules the system may be restricted to seeing only the dominant medical features nominated by the user - other medical codes which may be present on the case but not made dominant will not be considered by the rules.
- Cases can have a number of medical features, even for the same body part. This can result in more than one rule potentially being considered. For example, in a case where there is a fractured humerus with delayed union and an uncomplicated fractured thumb, then two different rules could be executed - one for the humeral fracture and its complication and another for the thumb. In these cases rule priority determines which will have precedence when it come to searching for matching cases. In this example it will be the fractured humerus with delayed union that will have precedence owing to the higher priority assigned to its rule. In one embodiment, the rule priorities are as defined in the section "Rule Prioritization Considerations" below. Rule Prioritization Considerations
- Reference sources may include:
- Brain complications such as intracranial hematoma - subdural, subarachnoid or epidural hematoma, cerebral edema or posttraumatic epilepsy
- Cranial nerve involvement such as vertigo, tinnitus or loss of smell and taste
- Bone complications such as osteomyelitis, avascular necrosis, bony union difficulties or limb deformities 8.
- Joint complications such as osteoarthritis, synovitis, joint stiffness or joint laxity
- a treatment hierarchy includes, but is not limited to: 1. Amputation
- Bone surgery such as fracture reductions, sequestrectomy or osteotomy 10. Ligament and tendon repairs
- the above hierarchy is a guide as to the severity of treatments. For instance the amputation of the arm at the shoulder is far more severe than the amputation of the little finger. Accordingly there will be considerable overlap between treatments in the hierarchy in terms of where medical severities could be allocated.
- dislocations of the knee are an orthopedic emergency, with the loss of the limb possible unless it is treated promptly and professionally. Even then the outcome will be guarded.
- dislocations will be hip dislocations for instance. These latter dislocations do not present the same orthopedic emergency nor are they likely to have the same medical outcome. So in this case, dislocations of the knee would be regarded as the most severe form of dislocation and would rate as a more severe injury in the overall hierarchy of injury than it would have otherwise.
- a combination of medical features can have significant implications for the matching process.
- a laceration of the upper arm requiring nerve repair implies that a 3 rd degree peripheral injury is present. Such nerve injuries can lead to significant impairment of the limb.
- a laceration to the upper arm with vascular repair is also a significant injury but is unlikely to have the same pessimistic outcome or associated impairment of the limb.
- the first combination of injury and complication could be more serious than the second.
- filters are used to constrain, refine or relax the criteria that are used in finding matching closed claims.
- the starting settings of the filters can be specified on a company wide basis, at a user level, or at a specific claim level (once set by the user).
- Example filter settings are:
- Example filter values are:
- the state/county filter can take the values "tight”, "loose” and "ignore".
- the "tight” setting will constrain the search to ensure that all claims returned match the county of the current claim.
- a "tight” setting for a 40 year old may be from age 30 to 45
- a "loose” setting for a 40 year old may be from 25 to 55.
- Example settings include:
- the table has entries for ages 0 and 120. Though few claimants will have these particular ages, they are included to provide lower and upper bounds of theoretical potential ages. For claimants whose age falls in between two values in the first column, such as age 9, then the values used representing the age range will be intermediate values from the other columns. For example, if the setting for age is "tight" then, since age 9 is half way between ages 8 and 10 (which appear in the claimant age column), the derived low age value will be 6 (half way between 5 and 7 - which are the corresponding value for ages 8 and 10) and the high bound will be 13 (between 12 and 14 from the high column). Gender
- the gender settings are “enable” and “ignore”, which correspond to matching the claimant's gender or returning claims involving both sexes respectively. Injuries The settings for injuries are “tight” and “loose” only
- the "tight" setting constrains the matching to include precedent claims whose medical attributes match all the medical attributes of the current claim, excluding any trivial injuries. These medical attributes are governed by the medical rules as specified below. A “loose” setting widens the matching to claims which have the same dominant medical feature as the current claim (the dominant medical feature is described elsewhere in this document).
- a "tight” setting may constrain the matching to only return claims which have at least one of the whiplash type injuries of the current claim, and which have trivial demonstrable injuries if the current claim also has them or that do not have any trivial injuries if the current claim also does not have them.
- the cases returned will include any that have a cervical sprain and another trivial demonstrable injury (not necessarily a chest contusion).
- a "loose” setting may remove the constraint of requiring to include or exclude the trivial demonstrable injuries. For the above example, claims would be returned which had a cervical sprain, but regardless of whether they also had any trivial demonstrable injuries. Impairment
- Example settings include:
- potential values for litigation stage are "direct", “unlitigated” and “suit”.
- the values for the filter are "enable” and "ignore”.
- a setting of “enable” constrains the matching to return claims which have the same litigation stage, as the current claim.
- a setting of "ignore” will return claims regardless of their litigation stage.
- a filter may be applied depending on whether a claimant is represented by an attorney. In another embodiment, a filter may be applied depending on whether a claimant is represented by a particular attorney or a defined set of particular attorneys.
- a filter may be applied depending on whether EDR data is available for the accident that gave rise to the claim. In an embodiment, a filter may be applied depending on whether EDR data for the accident indicates that an injury was a low-impact injury. Fallback
- the filters may be relaxed in order to expand the search. In order of priority the filters are relaxed in the following order, assuming filters are originally set at tightest setting
- Age is set to "ignore"
- one or more of any of the characteristics used for filters described herein may be used as equalization criteria.
- Such equalization criteria may be used instead of, or in addition to, the application of various filters.
- the system might filter claims based gender and adjust values using equalization values based on age.
- the minimum number of claims used in the filter optimization is set to 6.
- matching claims are ranked on a numerical scale. For example, Rank 1 matches may be the best fit, but claims of Rank 4 are still similar claims. It is the number of claim attributes and to what degree they differ between a matched claim and the current claim that determine the rating a matched claim receives.
- Example attributes considered when determining ranking level are:
- Treatment time Number of GP visits
- the system also adjusts for differences in litigation stage. For instance, settlements for claims already in suit are generally at higher monetary damages than for unlitigated claims, and direct claims respectively.
- the current claim involved a fractured humerus and a fractured sternum and a matching humerus fracture claim involved a sprained wrist
- the current claim has a more serious secondary injury than the matched claim. Therefore, the projected value of the current claim should be higher than the settlement value of the matched claim. Learning How to Adjust for Secondary Medical Features
- each medical code used by the system may be assigned a Pain and Suffering severity which represents the General Damages severity relativity. These relativities follow in general the injury, treatment and complication hierarchies described above.
- Each medical code may also been assigned a medical scale relativity parameter value (e.g., from 0 to 10). A higher the value may correspond to a more serious medical feature belonging to the code.
- F or instance, the complication of flail chest, a life threatening respiratory complication may be assigned a medical scale of 8, while a facial wound infection is assigned 0.5.
- Other serious complications such as epidural, subdural or subarachnoid hematomas may be assigned a medical scale of 9.
- the medical scale values reflect the seriousness of a medical condition (whether this is an injury, treatment or complication) and its relationship to the General Damages settled. In the example above a flail chest would contribute more to the settlement than a facial wound infection
- each medical sub body part is assigned a rank.
- the injuries with same ranks have the same Pain and Suffering severities.
- the radius and ulna have the same rank and the system considers fracture ulna and fracture radius as the same injuries in terms of severity.
- the system may aggregate all medical codes with the same major body part, injury code and rank, to form a set of injury categories.
- the categories are constructed by aggregation of the codes with the same medical scale. The system derives the contribution of each category of medical codes to the settlement values of the claims. Once the values of the medical codes categories have been derived then the Pain and Suffering severities assigned to every medical code are adjusted accordingly.
- Prioritizing Medical Features for Each Body Part Within each body part the medical features, being injuries, treatments and complications, may be listed in decreasing priority order. The first entry may be the highest priority - it is the most severe case and will be searched for instead of any others, if it exists.
- Skull fractures include open or closed fracture to the base of vault or the skull.
- Facial fractures also include open and closed fractures.
- Fractured jaw mandible or maxilla
- Fractured facial bone zygoma or orbit
- Loss of sight may be the highest level of severity, followed by head injuries with accompanying intracranial hemorrhage such as epidural, subdural and subarachnoid hemorrhage. While recovery from intracranial hemorrhage may take place, some residual cerebral dysfunction may also exist.
- Posttraumatic epilepsy is a serious consequence of head injury which depending on its severity may have a profound affect on an individuals ability to lead a normal life style. Head injuries with associated cranial nerve trauma may result in sensory loss (hearing, smell and taste). Injuries to the acoustic nerve may produce vertigo or tinnitus or both, again these complications depending on the severity of the symptoms can seriously affect a person's ability to lead a normal life.
- Skull surgery is an indication that some serious brain or vascular injury or complication was involved. Facial fractures may have both a functional and disfiguring aftermath. Jaw fractures (mandible or maxilla) can heal with dysfunction to mastication and may even be disfiguring. Zygoma and orbit fractures may heal with disfigurement, similarly nasal fractures. The main implication for lacerations to the head region is disfigurement. Eye lacerations can be simple or extremely serious. The severity order described above is not absolute, for example, an eye laceration with visual impairment clearly would be a more serious injury than where it currently lies within this hierarchy. Debilitating epilepsy or vertigo or tinnitus would also be higher in the hierarchy than suggested above. Chest 1. Thoracic injuries involving open thoracic or abdominal surgery
- Intercostal neuralgia Fractured ribs or sternum a. Fractures of five or more ribs
- Fractures to 5, 6, 7 or 8 or more rib fractures b. Fractures of 4 ribs Fractures to 3 to 6 ribs c. Fractures of 3 ribs
- Abdominal hierarchy is generally reflected by removal or repair or reconstruction to major abdominal organs and trauma or surgical complications. Removal of a kidney (nephrectomy) would be seen as the most serious abdominal injury because of its potential to be life threatening should the remaining kidney be injured or become diseased in the future. Removal of the spleen (splenectomy) puts the individual (particularly if he or she is young) at risk of very serious infection (post- splenectomy sepsis) and requires ongoing medication to prevent against infection. Injuries to the small or large bowel requiring surgery indicate serious abdominal injuries. Peritonitis heads the severity for abdominal complications. Fistula, abscess, cyst, adhesions and incisional hernia are all suggestive of possible further surgery. Abdominal injury with repair by laparotomy is considered more invasive than repair by laparoscope.
- Pelvic fracture includes both open and closed fractures. 1. Internal pelvic surgery or laparotomy 2. Intra-pelvic laceration of internal organs (bladder, ureter, urethra)
- Lacerations of the penis 11. Lacerations to the scrotum
- Lacerations to the bladder, ureter or urethra requiring surgical repair or reconstruction are considered to be the most severe pelvic injuries, followed by complications such as fistula or stricture of the ureter or urethra.
- Pelvic fractures are serious injuries but not considered as serious as injuries to the urinary system aforementioned.
- Genital lacerations can be minor or serious injuries, this would be determined by any residual impairment that resulted.
- this severity hierarchy is not inflexible and the order shown can change depending on factual circumstances of a claim.
- Spinal fractures include open and closed fractures of the spine. Fractures, dislocations and fracture dislocations to any spinal region include such injuries to any specific level within the spinal region. 1. Fracture dislocations or dislocations of the cervical spine
- Nonunion of the carpal bones (scaphoid, lunate, pisiform, hamate, capitate, triquetral, trapeziod, trapezium) 29.
- Nonunion of metacarpal, thumb or finger 29.
- Osteoarthritis of shoulder, elbow or wrist 29.
- Delayed Union of the shoulder bones (scapula or clavicle) 34. Delayed Union of the carpal bones (scaphoid, lunate, pisiform, hamate, capitate, triquetral, trapeziod, trapezium)
- Fracture dislocation or dislocation of the elbow 41. Fracture dislocation or dislocation of the elbow 42. Fracture dislocation or dislocation of the wrist
- Fracture dislocations or dislocations of the knee 8. Fracture dislocations or dislocations of the hip
- Avascular necrosis of femur, patella, tibia or fibula 16.
- Avascular necrosis of tarsal bones (calcaneus, cuboid, navicular, talus or cuneiforms)
- Fracture dislocations or dislocations of the ankle 35. Fracture dislocations or dislocations of the foot 36. Fractures of the hind foot (talus and calcaneus)
- Embodiments of a subset or all (and portions or all) of the above may be implemented by program instructions stored in a memory medium or carrier medium and executed by a processor.
- a memory medium may include any of various types of memory devices or storage devices.
- the term "memory medium” is intended to include an installation medium, e.g., a Compact Disc Read Only Memory (CD-ROM), floppy disks, or tape device; a computer system memory or random access memory such as Dynamic Random Access Memory (DRAM), Double Data Rate Random Access Memory (DDR RAM), Static Random Access Memory (SRAM), Extended Data Out Random Access Memory (EDO RAM), Rambus Random Access Memory (RAM), etc.; or a non-volatile memory such as a magnetic media, e.g., a hard drive, or optical storage.
- the memory medium may comprise other types of memory as well, or combinations thereof.
- the memory medium may be located in a first computer in which the programs are executed, or may be located in a second different computer that connects to the first computer over a network, such as the Internet. In the latter instance, the second computer may provide program instructions to the first computer for execution.
- the term "memory medium" may include two or more memory mediums that may reside in different locations, e.g., in different computers that are connected over a network.
- a computer system at a respective participant location may include a memory medium(s) on which one or more computer programs or software components according to one embodiment of the present invention may be stored.
- the memory medium may store one or more programs that are executable to perform the methods described herein.
- the memory medium may also store operating system software, as well as other software for operation of the computer system.
- users may access or operate elements of a computer system via a network such as a WAN or LAN.
- users may have web-enabled access to a system (e.g., via internet browser).
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP09703022A EP2252966A2 (en) | 2008-01-18 | 2009-01-19 | Evaluating effectiveness of claims evaluation, assessment, and settlement processes |
AU2009205960A AU2009205960A1 (en) | 2008-01-18 | 2009-01-19 | Evaluating effectiveness of claims evaluation, assessment, and settlement processes |
CA2715378A CA2715378C (en) | 2008-01-18 | 2009-01-19 | Evaluating effectiveness of claims evaluation, assessment, and settlement processes |
Applications Claiming Priority (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US2214008P | 2008-01-18 | 2008-01-18 | |
US61/022,140 | 2008-01-18 | ||
US5355608P | 2008-05-15 | 2008-05-15 | |
US61/053,556 | 2008-05-15 | ||
US12/134,977 | 2008-06-06 | ||
US12/134,977 US20090187428A1 (en) | 2008-01-18 | 2008-06-06 | Evaluating effectiveness of claims evaluation, assessment, and settlement processes |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2009092072A2 true WO2009092072A2 (en) | 2009-07-23 |
Family
ID=40877155
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2009/031406 WO2009092072A2 (en) | 2008-01-18 | 2009-01-19 | Evaluating effectiveness of claims evaluation, assessment, and settlement processes |
Country Status (5)
Country | Link |
---|---|
US (5) | US8244558B2 (en) |
EP (1) | EP2252966A2 (en) |
AU (1) | AU2009205960A1 (en) |
CA (1) | CA2715378C (en) |
WO (1) | WO2009092072A2 (en) |
Families Citing this family (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8244558B2 (en) * | 2008-01-18 | 2012-08-14 | Computer Sciences Corporation | Determining recommended settlement amounts by adjusting values derived from matching similar claims |
US20100299161A1 (en) * | 2009-05-22 | 2010-11-25 | Hartford Fire Insurance Company | System and method for administering subrogation related transactions |
US20110077977A1 (en) * | 2009-07-28 | 2011-03-31 | Collins Dean | Methods and systems for data mining using state reported worker's compensation data |
US10387175B2 (en) * | 2009-10-23 | 2019-08-20 | Autodesk, Inc. | Method and system for providing software application end-users with contextual access to text and video instructional information |
US8352292B2 (en) * | 2009-12-31 | 2013-01-08 | Hampton Thurman B | Personal injury valuation systems and method |
US20130085769A1 (en) * | 2010-03-31 | 2013-04-04 | Risk Management Solutions Llc | Characterizing healthcare provider, claim, beneficiary and healthcare merchant normal behavior using non-parametric statistical outlier detection scoring techniques |
US20110320223A1 (en) * | 2010-06-28 | 2011-12-29 | Hartford Fire Insurance Company | System and method for analysis of insurance claims |
WO2013067117A1 (en) * | 2011-11-01 | 2013-05-10 | Willis Hrh | System and method for selecting an insurance carrier |
US8600863B2 (en) * | 2012-01-16 | 2013-12-03 | International Business Machines Corporation | Financial services card that provides visual indicator according to available balance defined policies |
US20130198091A1 (en) * | 2012-01-31 | 2013-08-01 | Daniel Jahnsen | System of alternative dispute resolution implemented through a global computer network and methods thereof |
WO2013172852A1 (en) * | 2012-05-18 | 2013-11-21 | Jpmorgan Chase Bank, N.A. | Dynamic management and netting of transactions using executable rules |
US10445697B2 (en) | 2012-11-26 | 2019-10-15 | Hartford Fire Insurance Company | System for selection of data records containing structured and unstructured data |
US20150073834A1 (en) * | 2013-09-10 | 2015-03-12 | Europa Reinsurance Management Ltd. | Damage-scale catastrophe insurance product design and servicing systems |
US20150348202A1 (en) * | 2014-05-29 | 2015-12-03 | Fair Isaac Corporation | Insurance Claim Outlier Detection with Kernel Density Estimation |
US20190236712A1 (en) * | 2018-01-26 | 2019-08-01 | Michael Horowitz | Secure dispute settlement system |
CA3121190C (en) * | 2018-11-29 | 2022-05-24 | Clara Analytics, Inc. | Systems and methods for implementing search and recommendation tools for attorney selection |
US11410260B2 (en) * | 2019-02-11 | 2022-08-09 | Daniel S. Gunsberg | Online transaction platform system and method |
US11645344B2 (en) | 2019-08-26 | 2023-05-09 | Experian Health, Inc. | Entity mapping based on incongruent entity data |
US20220230254A1 (en) * | 2021-01-15 | 2022-07-21 | Life & Specialty Ventures, Llc | Cross policy single claim insurance management system |
Family Cites Families (343)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4166599A (en) * | 1977-06-21 | 1979-09-04 | General Signal Corporation | Wayside oriented moving block |
US4525780A (en) | 1981-05-22 | 1985-06-25 | Data General Corporation | Data processing system having a memory using object-based information and a protection scheme for determining access rights to such information |
DE3405757A1 (en) * | 1983-02-26 | 1984-10-04 | Edmund 7016 Gerlingen Zottnik | ACCIDENT RECORDER |
US4553206A (en) * | 1983-10-03 | 1985-11-12 | Wang Laboratories, Inc. | Image storage and retrieval |
US4656585A (en) * | 1984-02-03 | 1987-04-07 | Sundstrand Data Control Inc. | Aircraft flight data recorder data acquisition system |
JPS61120275A (en) * | 1984-11-16 | 1986-06-07 | Toshiba Corp | Japanese word processor |
US4648062A (en) | 1985-02-01 | 1987-03-03 | International Business Machines Corporation | Method for providing an on line help facility for interactive information handling systems |
US5099422A (en) * | 1986-04-10 | 1992-03-24 | Datavision Technologies Corporation (Formerly Excnet Corporation) | Compiling system and method of producing individually customized recording media |
US4831526A (en) * | 1986-04-22 | 1989-05-16 | The Chubb Corporation | Computerized insurance premium quote request and policy issuance system |
US4878167A (en) * | 1986-06-30 | 1989-10-31 | International Business Machines Corporation | Method for managing reuse of hard log space by mapping log data during state changes and discarding the log data |
EP0280773A3 (en) | 1987-01-09 | 1989-12-20 | International Business Machines Corporation | Method for recovery enhancement in a transaction-oriented data processing system |
US4837693A (en) * | 1987-02-27 | 1989-06-06 | Schotz Barry R | Method and apparatus for facilitating operation of an insurance plan |
JP2718031B2 (en) * | 1987-07-17 | 1998-02-25 | 株式会社日立製作所 | History information acquisition method |
US4839822A (en) * | 1987-08-13 | 1989-06-13 | 501 Synthes (U.S.A.) | Computer system and method for suggesting treatments for physical trauma |
US4964077A (en) * | 1987-10-06 | 1990-10-16 | International Business Machines Corporation | Method for automatically adjusting help information displayed in an online interactive system |
DE3853512T2 (en) | 1987-11-09 | 1995-11-23 | Sharp Kk | Device for computers or computer-controlled systems for generating a help display. |
US4992972A (en) | 1987-11-18 | 1991-02-12 | International Business Machines Corporation | Flexible context searchable on-line information system with help files and modules for on-line computer system documentation |
US5008853A (en) * | 1987-12-02 | 1991-04-16 | Xerox Corporation | Representation of collaborative multi-user activities relative to shared structured data objects in a networked workstation environment |
US4962468A (en) * | 1987-12-09 | 1990-10-09 | International Business Machines Corporation | System and method for utilizing fast polygon fill routines in a graphics display system |
US4945474A (en) | 1988-04-08 | 1990-07-31 | Internatinal Business Machines Corporation | Method for restoring a database after I/O error employing write-ahead logging protocols |
US4975840A (en) * | 1988-06-17 | 1990-12-04 | Lincoln National Risk Management, Inc. | Method and apparatus for evaluating a potentially insurable risk |
US4931793A (en) * | 1988-07-01 | 1990-06-05 | Solitron Devices, Inc. | System for providing a warning when vehicles approach a common collision point |
US5434963A (en) * | 1988-09-03 | 1995-07-18 | Hitachi, Ltd. | Method and system of help-information control method and system |
CA2003418A1 (en) * | 1988-12-29 | 1990-06-29 | Louis A. Winans | Computer message & screen communications in a multi-lingual network |
US5155806A (en) * | 1989-03-15 | 1992-10-13 | Sun Microsystems, Inc. | Method and apparatus for displaying context sensitive help information on a display |
US5157768A (en) | 1989-03-15 | 1992-10-20 | Sun Microsystems, Inc. | Method and apparatus for displaying context sensitive help information on a display |
US4987538A (en) * | 1989-04-27 | 1991-01-22 | Western Medical Consultants | Automated processing of provider billings |
US5287448A (en) * | 1989-05-04 | 1994-02-15 | Apple Computer, Inc. | Method and apparatus for providing help information to users of computers |
US5748953A (en) | 1989-06-14 | 1998-05-05 | Hitachi, Ltd. | Document search method wherein stored documents and search queries comprise segmented text data of spaced, nonconsecutive text elements and words segmented by predetermined symbols |
US5557515A (en) * | 1989-08-11 | 1996-09-17 | Hartford Fire Insurance Company, Inc. | Computerized system and method for work management |
US5093911A (en) * | 1989-09-14 | 1992-03-03 | International Business Machines Corporation | Storage and retrieval system |
US5241671C1 (en) * | 1989-10-26 | 2002-07-02 | Encyclopaedia Britannica Educa | Multimedia search system using a plurality of entry path means which indicate interrelatedness of information |
US5870724A (en) | 1989-12-08 | 1999-02-09 | Online Resources & Communications Corporation | Targeting advertising in a home retail banking delivery service |
US5233513A (en) | 1989-12-28 | 1993-08-03 | Doyle William P | Business modeling, software engineering and prototyping method and apparatus |
US5191522A (en) * | 1990-01-18 | 1993-03-02 | Itt Corporation | Integrated group insurance information processing and reporting system based upon an enterprise-wide data structure |
US5170464A (en) * | 1990-01-26 | 1992-12-08 | International Business Machines Corporation | Method for rolling back an expert system |
JP2844240B2 (en) | 1990-03-15 | 1999-01-06 | 本田技研工業株式会社 | Automatic traveling device |
US5201044A (en) * | 1990-04-16 | 1993-04-06 | International Business Machines Corporation | Data processing method for file status recovery includes providing a log file of atomic transactions that may span both volatile and non volatile memory |
DE69126066T2 (en) | 1990-06-29 | 1997-09-25 | Oracle Corp | Method and device for optimizing logbook usage |
CA2025201C (en) * | 1990-09-12 | 1992-09-01 | Dominic Carbone | Electronic accident estimating system |
US5180309A (en) * | 1990-12-04 | 1993-01-19 | United States Of America As Represented By The Secretary Of The Navy | Automated answer evaluation and scoring system and method |
US5172281A (en) * | 1990-12-17 | 1992-12-15 | Ardis Patrick M | Video transcript retriever |
AU1427492A (en) * | 1991-02-06 | 1992-09-07 | Risk Data Corporation | System for funding future workers' compensation losses |
US5432904A (en) * | 1991-02-19 | 1995-07-11 | Ccc Information Services Inc. | Auto repair estimate, text and graphic system |
US5504674A (en) * | 1991-02-19 | 1996-04-02 | Ccc Information Services, Inc. | Insurance claims estimate, text, and graphics network and method |
US5225976A (en) * | 1991-03-12 | 1993-07-06 | Research Enterprises, Inc. | Automated health benefit processing system |
US5386566A (en) | 1991-03-20 | 1995-01-31 | Hitachi, Ltd. | Inter-processor communication method for transmitting data and processor dependent information predetermined for a receiving process of another processor |
US5566330A (en) | 1991-08-20 | 1996-10-15 | Powersoft Corporation | Method for forming a reusable and modifiable database interface object |
US5410648A (en) | 1991-08-30 | 1995-04-25 | International Business Machines Corporation | Debugging system wherein multiple code views are simultaneously managed |
US6604080B1 (en) | 1991-10-30 | 2003-08-05 | B&S Underwriters, Inc. | Computer system and methods for supporting workers' compensation/employers liability insurance |
US5359509A (en) * | 1991-10-31 | 1994-10-25 | United Healthcare Corporation | Health care payment adjudication and review system |
US5471575A (en) | 1992-01-03 | 1995-11-28 | Home Equity Software, Inc. | Interactive parameter driven iterative financial spreadsheet analysis with context and layout sensitive help screen |
US5307262A (en) * | 1992-01-29 | 1994-04-26 | Applied Medical Data, Inc. | Patient data quality review method and system |
US5481667A (en) * | 1992-02-13 | 1996-01-02 | Microsoft Corporation | Method and system for instructing a user of a computer system how to perform application program tasks |
US5732397A (en) * | 1992-03-16 | 1998-03-24 | Lincoln National Risk Management, Inc. | Automated decision-making arrangement |
US5732221A (en) * | 1992-03-27 | 1998-03-24 | Documation, Inc. | Electronic documentation system for generating written reports |
US5317503A (en) * | 1992-03-27 | 1994-05-31 | Isao Inoue | Apparatus for calculating a repair cost of a damaged car |
US6254127B1 (en) | 1992-05-05 | 2001-07-03 | Automotive Technologies International Inc. | Vehicle occupant sensing system including a distance-measuring sensor on an airbag module or steering wheel assembly |
US5446885A (en) | 1992-05-15 | 1995-08-29 | International Business Machines Corporation | Event driven management information system with rule-based applications structure stored in a relational database |
JP2758311B2 (en) * | 1992-05-28 | 1998-05-28 | 富士通株式会社 | Log file control method in complex system |
US5535323A (en) | 1992-06-29 | 1996-07-09 | Digital Equipment Corporation | Method of and system for displaying context sensitive and application independent help information |
CA2100893A1 (en) | 1992-08-06 | 1994-02-07 | Michael E. Stickney | Interactive computerized witness interrogation recording tool |
US5673402A (en) * | 1992-08-17 | 1997-09-30 | The Homeowner's Endorsement Plan Incorporated | Computer system for producing an illustration of an investment repaying a mortgage |
US5655085A (en) | 1992-08-17 | 1997-08-05 | The Ryan Evalulife Systems, Inc. | Computer system for automated comparing of universal life insurance policies based on selectable criteria |
GB2273183A (en) * | 1992-12-04 | 1994-06-08 | Ibm | Replicated distributed databases. |
US5550976A (en) * | 1992-12-08 | 1996-08-27 | Sun Hydraulics Corporation | Decentralized distributed asynchronous object oriented system and method for electronic data management, storage, and communication |
US5394555A (en) | 1992-12-23 | 1995-02-28 | Bull Hn Information Systems Inc. | Multi-node cluster computer system incorporating an external coherency unit at each node to insure integrity of information stored in a shared, distributed memory |
JP2521024B2 (en) * | 1993-04-20 | 1996-07-31 | 淡路フェリーボート株式会社 | Traffic accident data recorder and traffic accident reproduction system |
US5446653A (en) * | 1993-05-10 | 1995-08-29 | Aetna Casualty And Surety Company | Rule based document generation system |
US5950169A (en) | 1993-05-19 | 1999-09-07 | Ccc Information Services, Inc. | System and method for managing insurance claim processing |
US5689706A (en) * | 1993-06-18 | 1997-11-18 | Lucent Technologies Inc. | Distributed systems with replicated files |
JPH0717347A (en) * | 1993-07-07 | 1995-01-20 | Mazda Motor Corp | Obstacle detecting device for automobile |
US5913198A (en) | 1997-09-09 | 1999-06-15 | Sbp Services, Inc. | System and method for designing and administering survivor benefit plans |
US5940811A (en) | 1993-08-27 | 1999-08-17 | Affinity Technology Group, Inc. | Closed loop financial transaction method and apparatus |
US5499330A (en) * | 1993-09-17 | 1996-03-12 | Digital Equipment Corp. | Document display system for organizing and displaying documents as screen objects organized along strand paths |
US5359660A (en) * | 1993-10-07 | 1994-10-25 | International Business Machines Corporation | Local area network peripheral lock method and system |
US5517405A (en) | 1993-10-14 | 1996-05-14 | Aetna Life And Casualty Company | Expert system for providing interactive assistance in solving problems such as health care management |
US5644778A (en) * | 1993-11-02 | 1997-07-01 | Athena Of North America, Inc. | Medical transaction system |
FR2712101B1 (en) | 1993-11-05 | 1996-01-05 | Socs Holding | System for controlling a relational database according to an object-oriented access logic limiting the number of accesses to the database, and corresponding method. |
US5550734A (en) * | 1993-12-23 | 1996-08-27 | The Pharmacy Fund, Inc. | Computerized healthcare accounts receivable purchasing collections securitization and management system |
US5524489A (en) * | 1994-02-18 | 1996-06-11 | Plan B Enterprises, Inc. | Floating mass accelerometer |
US5600831A (en) | 1994-02-28 | 1997-02-04 | Lucent Technologies Inc. | Apparatus and methods for retrieving information by modifying query plan based on description of information sources |
US5652842A (en) * | 1994-03-01 | 1997-07-29 | Healthshare Technology, Inc. | Analysis and reporting of performance of service providers |
US5537315A (en) | 1994-03-23 | 1996-07-16 | Mitcham; Martin K. | Method and apparatus for issuing insurance from kiosk |
US5523942A (en) * | 1994-03-31 | 1996-06-04 | New England Mutual Life Insurance Company | Design grid for inputting insurance and investment product information in a computer system |
US6810382B1 (en) | 1994-04-04 | 2004-10-26 | Vaughn A. Wamsley | Personal injury claim management system |
US5581677A (en) * | 1994-04-22 | 1996-12-03 | Carnegie Mellon University | Creating charts and visualizations by demonstration |
US5434994A (en) * | 1994-05-23 | 1995-07-18 | International Business Machines Corporation | System and method for maintaining replicated data coherency in a data processing system |
US5806078A (en) * | 1994-06-09 | 1998-09-08 | Softool Corporation | Version management system |
US5483442A (en) * | 1994-07-12 | 1996-01-09 | Investigator Marketing Inc. | Accident documentation system |
EP0702322B1 (en) | 1994-09-12 | 2002-02-13 | Adobe Systems Inc. | Method and apparatus for identifying words described in a portable electronic document |
JP3402412B2 (en) | 1994-09-20 | 2003-05-06 | 株式会社リコー | Process simulation input data setting device |
US5627886A (en) * | 1994-09-22 | 1997-05-06 | Electronic Data Systems Corporation | System and method for detecting fraudulent network usage patterns using real-time network monitoring |
US5768506A (en) | 1994-09-30 | 1998-06-16 | Hewlett-Packard Co. | Method and apparatus for distributed workflow building blocks of process definition, initialization and execution |
US5745901A (en) | 1994-11-08 | 1998-04-28 | Kodak Limited | Workflow initiated by graphical symbols |
US6073104A (en) | 1994-11-09 | 2000-06-06 | Field; Richard G. | System for invoice record management and asset-backed commercial paper program management |
US6029195A (en) | 1994-11-29 | 2000-02-22 | Herz; Frederick S. M. | System for customized electronic identification of desirable objects |
US5504675A (en) | 1994-12-22 | 1996-04-02 | International Business Machines Corporation | Method and apparatus for automatic selection and presentation of sales promotion programs |
US5839112A (en) | 1994-12-28 | 1998-11-17 | Automatic Data Processing | Method and apparatus for displaying and selecting vehicle parts |
US5717913A (en) * | 1995-01-03 | 1998-02-10 | University Of Central Florida | Method for detecting and extracting text data using database schemas |
US5798949A (en) | 1995-01-13 | 1998-08-25 | Kaub; Alan Richard | Traffic safety prediction model |
US6658568B1 (en) | 1995-02-13 | 2003-12-02 | Intertrust Technologies Corporation | Trusted infrastructure support system, methods and techniques for secure electronic commerce transaction and rights management |
US5918208A (en) | 1995-04-13 | 1999-06-29 | Ingenix, Inc. | System for providing medical information |
US6405132B1 (en) | 1997-10-22 | 2002-06-11 | Intelligent Technologies International, Inc. | Accident avoidance system |
US5835897C1 (en) | 1995-06-22 | 2002-02-19 | Symmetry Health Data Systems | Computer-implemented method for profiling medical claims |
US6092049A (en) | 1995-06-30 | 2000-07-18 | Microsoft Corporation | Method and apparatus for efficiently recommending items using automated collaborative filtering and feature-guided automated collaborative filtering |
US5742820A (en) | 1995-07-06 | 1998-04-21 | Novell, Inc. | Mechanism for efficiently synchronizing information over a network |
US6065000A (en) | 1996-07-19 | 2000-05-16 | Star Solutions & Consulting Services | Computer-implemented process of reporting injured worker information |
US5696705A (en) * | 1995-08-29 | 1997-12-09 | Laser Technology, Inc. | System and method for reconstruction of the position of objects utilizing a signal transmitting and receiving distance determining device |
US5899998A (en) | 1995-08-31 | 1999-05-04 | Medcard Systems, Inc. | Method and system for maintaining and updating computerized medical records |
US5652705A (en) * | 1995-09-25 | 1997-07-29 | Spiess; Newton E. | Highway traffic accident avoidance system |
US5809478A (en) | 1995-12-08 | 1998-09-15 | Allstate Insurance Company | Method for accessing and evaluating information for processing an application for insurance |
US6584467B1 (en) | 1995-12-08 | 2003-06-24 | Allstate Insurance Company | Method and apparatus for obtaining data from vendors in real time |
US5870711A (en) | 1995-12-11 | 1999-02-09 | Sabre Properties, Inc. | Method and system for management of cargo claims |
US5768505A (en) | 1995-12-19 | 1998-06-16 | International Business Machines Corporation | Object oriented mail server framework mechanism |
US6065047A (en) | 1996-01-24 | 2000-05-16 | America Online, Inc. | System for providing subscriber with access to a content area customized for the combination of subscriber's responses to topic prompt, subtopic prompt, and action prompt |
US5797134A (en) | 1996-01-29 | 1998-08-18 | Progressive Casualty Insurance Company | Motor vehicle monitoring system for determining a cost of insurance |
US5862325A (en) | 1996-02-29 | 1999-01-19 | Intermind Corporation | Computer-based communication system and method using metadata defining a control structure |
US5991733A (en) | 1996-03-22 | 1999-11-23 | Hartford Fire Insurance Company | Method and computerized system for managing insurance receivable accounts |
US5850442A (en) | 1996-03-26 | 1998-12-15 | Entegrity Solutions Corporation | Secure world wide electronic commerce over an open network |
US6003007A (en) | 1996-03-28 | 1999-12-14 | Dirienzo; Andrew L. | Attachment integrated claims system and operating method therefor |
US5862500A (en) | 1996-04-16 | 1999-01-19 | Tera Tech Incorporated | Apparatus and method for recording motor vehicle travel information |
US5930759A (en) | 1996-04-30 | 1999-07-27 | Symbol Technologies, Inc. | Method and system for processing health care electronic data transactions |
US5864301A (en) | 1996-05-13 | 1999-01-26 | Jackson; Jerome D. | Systems and methods employing a plurality of signal amplitudes to identify an object |
EP0979459A4 (en) | 1996-05-23 | 2005-04-06 | Citibank Na | Global financial services integration system and process |
US5903873A (en) | 1996-05-31 | 1999-05-11 | American General Life And Accident Insurance Company | System for registering insurance transactions and communicating with a home office |
US5987434A (en) | 1996-06-10 | 1999-11-16 | Libman; Richard Marc | Apparatus and method for transacting marketing and sales of financial products |
US5787429A (en) | 1996-07-03 | 1998-07-28 | Nikolin, Jr.; Michael A. | Potential hazard and risk-assessment data communication network |
CA2261262C (en) | 1996-07-22 | 2007-08-21 | Cyva Research Corporation | Personal information security and exchange tool |
US5815093A (en) | 1996-07-26 | 1998-09-29 | Lextron Systems, Inc. | Computerized vehicle log |
US5895461A (en) | 1996-07-30 | 1999-04-20 | Telaric, Inc. | Method and system for automated data storage and retrieval with uniform addressing scheme |
US6016504A (en) | 1996-08-28 | 2000-01-18 | Infospace.Com, Inc. | Method and system for tracking the purchase of a product and services over the Internet |
US5915241A (en) | 1996-09-13 | 1999-06-22 | Giannini; Jo Melinna | Method and system encoding and processing alternative healthcare provider billing |
US5832508A (en) | 1996-09-18 | 1998-11-03 | Sybase, Inc. | Method for deallocating a log in database systems |
US6029150A (en) | 1996-10-04 | 2000-02-22 | Certco, Llc | Payment and transactions in electronic commerce system |
US6104874A (en) | 1996-10-15 | 2000-08-15 | International Business Machines Corporation | Object oriented framework mechanism for order processing including pre-defined extensible classes for defining an order processing environment |
US5933816A (en) | 1996-10-31 | 1999-08-03 | Citicorp Development Center, Inc. | System and method for delivering financial services |
US5907705A (en) | 1996-10-31 | 1999-05-25 | Sun Microsystems, Inc. | Computer implemented request to integrate (RTI) system for managing change control in software release stream |
US5937189A (en) | 1996-11-12 | 1999-08-10 | International Business Machines Corporation | Object oriented framework mechanism for determining configuration relations |
US5884274A (en) | 1996-11-15 | 1999-03-16 | Walker Asset Management Limited Partnership | System and method for generating and executing insurance policies for foreign exchange losses |
US6021202A (en) | 1996-12-20 | 2000-02-01 | Financial Services Technology Consortium | Method and system for processing electronic documents |
US5956691A (en) | 1997-01-07 | 1999-09-21 | Second Opinion Financial Systems, Inc. | Dynamic policy illustration system |
US5877707A (en) | 1997-01-17 | 1999-03-02 | Kowalick; Thomas M. | GPS based seat belt monitoring system & method for using same |
US5873066A (en) | 1997-02-10 | 1999-02-16 | Insurance Company Of North America | System for electronically managing and documenting the underwriting of an excess casualty insurance policy |
US5717391A (en) * | 1997-02-13 | 1998-02-10 | Rodriguez; Otto M. | Traffic event recording method and apparatus |
US5835914A (en) | 1997-02-18 | 1998-11-10 | Wall Data Incorporated | Method for preserving and reusing software objects associated with web pages |
US5809496A (en) | 1997-02-20 | 1998-09-15 | International Business Machines Corporation | Hybrid search |
CA2198189C (en) | 1997-02-21 | 2001-05-29 | Ibm Canada Limited-Ibm Canada Limitee | Internet browser based data entry architecture |
JPH10247252A (en) | 1997-03-04 | 1998-09-14 | Sharp Corp | Collision judging processor |
US5907848A (en) | 1997-03-14 | 1999-05-25 | Lakeview Technology, Inc. | Method and system for defining transactions from a database log |
US6064983A (en) | 1997-03-21 | 2000-05-16 | Koehler Consulting, Inc. | System for performing tax computations |
US5914714A (en) | 1997-04-01 | 1999-06-22 | Microsoft Corporation | System and method for changing the characteristics of a button by direct manipulation |
US5956687A (en) | 1997-04-04 | 1999-09-21 | Wamsley; Vaughn A. | Personal injury claim management system |
US5982369A (en) | 1997-04-21 | 1999-11-09 | Sony Corporation | Method for displaying on a screen of a computer system images representing search results |
US6173284B1 (en) | 1997-05-20 | 2001-01-09 | University Of Charlotte City Of Charlotte | Systems, methods and computer program products for automatically monitoring police records for a crime profile |
US5877757A (en) | 1997-05-23 | 1999-03-02 | International Business Machines Corporation | Method and system for providing user help information in network applications |
US5999940A (en) | 1997-05-28 | 1999-12-07 | Home Information Services, Inc. | Interactive information discovery tool and methodology |
US6301621B1 (en) | 1997-06-19 | 2001-10-09 | International Business Machines Corporation | Web server with direct mail capability |
US6012053A (en) | 1997-06-23 | 2000-01-04 | Lycos, Inc. | Computer system with user-controlled relevance ranking of search results |
US6119093A (en) | 1997-07-01 | 2000-09-12 | Walker Asset Management Limited Partnership | System for syndication of insurance |
US5950196A (en) | 1997-07-25 | 1999-09-07 | Sovereign Hill Software, Inc. | Systems and methods for retrieving tabular data from textual sources |
US6009402A (en) | 1997-07-28 | 1999-12-28 | Whitworth; Brian L. | System and method for predicting, comparing and presenting the cost of self insurance versus insurance and for creating bond financing when advantageous |
US20010020229A1 (en) | 1997-07-31 | 2001-09-06 | Arnold Lash | Method and apparatus for determining high service utilization patients |
EP0895173A3 (en) | 1997-08-02 | 2003-02-12 | Fujitsu Services Limited | Computer system for delivery of financial services |
US5987430A (en) | 1997-08-28 | 1999-11-16 | Atcom, Inc. | Communications network connection system and method |
US6038668A (en) | 1997-09-08 | 2000-03-14 | Science Applications International Corporation | System, method, and medium for retrieving, organizing, and utilizing networked data |
US5970464A (en) | 1997-09-10 | 1999-10-19 | International Business Machines Corporation | Data mining based underwriting profitability analysis |
US5995947A (en) | 1997-09-12 | 1999-11-30 | Imx Mortgage Exchange | Interactive mortgage and loan information and real-time trading system |
JP3314686B2 (en) | 1997-09-18 | 2002-08-12 | トヨタ自動車株式会社 | Vehicle shortest stopping distance prediction method and vehicle shortest stopping distance prediction device |
DE19741631B4 (en) | 1997-09-20 | 2013-08-14 | Volkswagen Ag | Method and device for avoiding and / or minimizing conflict situations in road traffic |
US6038393A (en) | 1997-09-22 | 2000-03-14 | Unisys Corp. | Software development tool to accept object modeling data from a wide variety of other vendors and filter the format into a format that is able to be stored in OMG compliant UML representation |
US6076026A (en) | 1997-09-30 | 2000-06-13 | Motorola, Inc. | Method and device for vehicle control events data recording and securing |
US6088710A (en) | 1997-10-29 | 2000-07-11 | R.R. Donnelley & Sons Company | Apparatus and method for producing fulfillment pieces on demand in a variable imaging system |
US5991756A (en) | 1997-11-03 | 1999-11-23 | Yahoo, Inc. | Information retrieval from hierarchical compound documents |
US5953526A (en) | 1997-11-10 | 1999-09-14 | Internatinal Business Machines Corp. | Object oriented programming system with displayable natural language documentation through dual translation of program source code |
US6112986A (en) | 1997-12-08 | 2000-09-05 | Berger; Richard S. | Method and apparatus for accessing patient insurance information |
US6067031A (en) | 1997-12-18 | 2000-05-23 | Trimble Navigation Limited | Dynamic monitoring of vehicle separation |
US6237035B1 (en) | 1997-12-18 | 2001-05-22 | International Business Machines Corporation | System and method for preventing duplicate transactions in an internet browser/internet server environment |
US6016477A (en) | 1997-12-18 | 2000-01-18 | International Business Machines Corporation | Method and apparatus for identifying applicable business rules |
US6115690A (en) | 1997-12-22 | 2000-09-05 | Wong; Charles | Integrated business-to-business Web commerce and business automation system |
DE69822283T2 (en) | 1997-12-24 | 2004-07-29 | Nortel Networks Ltd., St. Laurent | Distributed persistent storage for user-provider systems with sometimes broken connections |
US6249905B1 (en) | 1998-01-16 | 2001-06-19 | Kabushiki Kaisha Toshiba | Computerized accounting system implemented in an object-oriented programming environment |
CA2260622C (en) | 1998-02-04 | 2007-04-24 | Biodynamic Research Corporation | System and method for determining post-collision vehicular velocity changes |
US6452607B1 (en) | 1998-02-04 | 2002-09-17 | Hewlett-Packard Company | Context sensitive user interface help feature |
US6470303B2 (en) | 1998-02-04 | 2002-10-22 | Injury Sciences Llc | System and method for acquiring and quantifying vehicular damage information |
US6456303B1 (en) | 1998-02-09 | 2002-09-24 | Microsoft Corporation | Method and system for access of online information |
US6308187B1 (en) | 1998-02-09 | 2001-10-23 | International Business Machines Corporation | Computer system and method for abstracting and accessing a chronologically-arranged collection of information |
US6061657A (en) | 1998-02-18 | 2000-05-09 | Iameter, Incorporated | Techniques for estimating charges of delivering healthcare services that take complicating factors into account |
US6088702A (en) | 1998-02-25 | 2000-07-11 | Plantz; Scott H. | Group publishing system |
US6208973B1 (en) | 1998-02-27 | 2001-03-27 | Onehealthbank.Com | Point of service third party financial management vehicle for the healthcare industry |
US6560592B1 (en) | 1998-03-19 | 2003-05-06 | Micro Data Base Systems, Inc. | Multi-model computer database storage system with integrated rule engine |
US6134582A (en) | 1998-05-26 | 2000-10-17 | Microsoft Corporation | System and method for managing electronic mail messages using a client-based database |
US6239798B1 (en) | 1998-05-28 | 2001-05-29 | Sun Microsystems, Inc. | Methods and apparatus for a window access panel |
US6950013B2 (en) | 1998-06-01 | 2005-09-27 | Robert Jeffery Scaman | Incident recording secure database |
US6148297A (en) | 1998-06-01 | 2000-11-14 | Surgical Safety Products, Inc. | Health care information and data tracking system and method |
JP2002517860A (en) | 1998-06-08 | 2002-06-18 | ケイシーエスエル インク. | Method and system for retrieving relevant information from a database |
JPH11348695A (en) | 1998-06-09 | 1999-12-21 | Nec Corp | Detection device for rear vehicle |
US6098070A (en) | 1998-06-09 | 2000-08-01 | Hipersoft Corp. | Case management for a personal injury plaintiff's law office using a relational database |
US6505176B2 (en) | 1998-06-12 | 2003-01-07 | First American Credit Management Solutions, Inc. | Workflow management system for an automated credit application system |
US6343271B1 (en) | 1998-07-17 | 2002-01-29 | P5 E.Health Services, Inc. | Electronic creation, submission, adjudication, and payment of health insurance claims |
US6330551B1 (en) | 1998-08-06 | 2001-12-11 | Cybersettle.Com, Inc. | Computerized dispute resolution system and method |
US7249114B2 (en) | 1998-08-06 | 2007-07-24 | Cybersettle Holdings, Inc. | Computerized dispute resolution system and method |
US6272482B1 (en) | 1998-08-14 | 2001-08-07 | International Business Machines Corporation | Managing business rules using jurisdictions |
US6163770A (en) | 1998-08-25 | 2000-12-19 | Financial Growth Resources, Inc. | Computer apparatus and method for generating documentation using a computed value for a claims cost affected by at least one concurrent, different insurance policy for the same insured |
US6473748B1 (en) | 1998-08-31 | 2002-10-29 | Worldcom, Inc. | System for implementing rules |
US6266645B1 (en) | 1998-09-01 | 2001-07-24 | Imetrikus, Inc. | Risk adjustment tools for analyzing patient electronic discharge records |
US6236975B1 (en) | 1998-09-29 | 2001-05-22 | Ignite Sales, Inc. | System and method for profiling customers for targeted marketing |
US6253203B1 (en) | 1998-10-02 | 2001-06-26 | Ncr Corporation | Privacy-enhanced database |
US6336096B1 (en) * | 1998-10-09 | 2002-01-01 | Donald V. Jernberg | System and method for evaluating liability |
JP4159674B2 (en) | 1998-10-22 | 2008-10-01 | 富士通株式会社 | Object-oriented business system and method |
US6314415B1 (en) | 1998-11-04 | 2001-11-06 | Cch Incorporated | Automated forms publishing system and method using a rule-based expert system to dynamically generate a graphical user interface |
US6141611A (en) | 1998-12-01 | 2000-10-31 | John J. Mackey | Mobile vehicle accident data system |
US6502233B1 (en) | 1998-11-13 | 2002-12-31 | Microsoft Corporation | Automated help system for reference information |
US6260024B1 (en) | 1998-12-02 | 2001-07-10 | Gary Shkedy | Method and apparatus for facilitating buyer-driven purchase orders on a commercial network system |
US6341265B1 (en) | 1998-12-03 | 2002-01-22 | P5 E.Health Services, Inc. | Provider claim editing and settlement system |
US6532459B1 (en) | 1998-12-15 | 2003-03-11 | Berson Research Corp. | System for finding, identifying, tracking, and correcting personal information in diverse databases |
US6523172B1 (en) | 1998-12-17 | 2003-02-18 | Evolutionary Technologies International, Inc. | Parser translator system and method |
US6397334B1 (en) | 1998-12-17 | 2002-05-28 | International Business Machines Corporation | Method and system for authenticating objects and object data |
US6272472B1 (en) | 1998-12-29 | 2001-08-07 | Intel Corporation | Dynamic linking of supplier web sites to reseller web sites |
US6449652B1 (en) | 1999-01-04 | 2002-09-10 | Emc Corporation | Method and apparatus for providing secure access to a computer system resource |
US6525672B2 (en) | 1999-01-20 | 2003-02-25 | International Business Machines Corporation | Event-recorder for transmitting and storing electronic signature data |
US6389588B1 (en) | 1999-02-04 | 2002-05-14 | Relativity Technologies | Method and system of business rule extraction from existing applications for integration into new applications |
US20010037223A1 (en) | 1999-02-04 | 2001-11-01 | Brian Beery | Management and delivery of product information |
US6223125B1 (en) | 1999-02-05 | 2001-04-24 | Brett O. Hall | Collision avoidance system |
US6513019B2 (en) | 1999-02-16 | 2003-01-28 | Financial Technologies International, Inc. | Financial consolidation and communication platform |
US6161071A (en) | 1999-03-12 | 2000-12-12 | Navigation Technologies Corporation | Method and system for an in-vehicle computing architecture |
US6185490B1 (en) | 1999-03-15 | 2001-02-06 | Thomas W. Ferguson | Vehicle crash data recorder |
US7337121B1 (en) | 1999-03-30 | 2008-02-26 | Iso Claims Services, Inc. | Claim assessment model |
US6938029B1 (en) | 1999-03-31 | 2005-08-30 | Allan Y. Tien | System and method for indexing recordings of observed and assessed phenomena using pre-defined measurement items |
US6570609B1 (en) | 1999-04-22 | 2003-05-27 | Troy A. Heien | Method and apparatus for monitoring operation of a motor vehicle |
US7013284B2 (en) | 1999-05-04 | 2006-03-14 | Accenture Llp | Component based interface to handle tasks during claim processing |
US6633316B1 (en) | 1999-05-13 | 2003-10-14 | International Business Machines Corporation | Method and apparatus for implementing direct link selection of cached, previously visited links in nested web pages |
US6594697B1 (en) | 1999-05-20 | 2003-07-15 | Microsoft Corporation | Client system having error page analysis and replacement capabilities |
US6473794B1 (en) | 1999-05-27 | 2002-10-29 | Accenture Llp | System for establishing plan to test components of web based framework by displaying pictorial representation and conveying indicia coded components of existing network framework |
US7035812B2 (en) | 1999-05-28 | 2006-04-25 | Overture Services, Inc. | System and method for enabling multi-element bidding for influencing a position on a search result list generated by a computer network search engine |
US6314419B1 (en) | 1999-06-04 | 2001-11-06 | Oracle Corporation | Methods and apparatus for generating query feedback based on co-occurrence patterns |
US6952741B1 (en) | 1999-06-30 | 2005-10-04 | Computer Sciences Corporation | System and method for synchronizing copies of data in a computer system |
US6446086B1 (en) | 1999-06-30 | 2002-09-03 | Computer Sciences Corporation | System and method for logging transaction records in a computer system |
US7124088B2 (en) | 1999-07-30 | 2006-10-17 | Progressive Casualty Insurance Company | Apparatus for internet on-line insurance policy service |
US6272471B1 (en) * | 1999-08-02 | 2001-08-07 | Jeffrey J. Segal | Method and apparatus for deterring frivolous professional liability claims |
US6961708B1 (en) | 1999-08-27 | 2005-11-01 | Computer Sciences Corporation | External interface for requesting data from remote systems in a generic fashion |
US6970844B1 (en) | 1999-08-27 | 2005-11-29 | Computer Sciences Corporation | Flow designer for establishing and maintaining assignment and strategy process maps |
US6636242B2 (en) | 1999-08-31 | 2003-10-21 | Accenture Llp | View configurer in a presentation services patterns environment |
US6473084B1 (en) | 1999-09-08 | 2002-10-29 | C4Cast.Com, Inc. | Prediction input |
US6363360B1 (en) | 1999-09-27 | 2002-03-26 | Martin P. Madden | System and method for analyzing and originating a contractual option arrangement for a bank deposits liabilities base |
US6401079B1 (en) | 1999-10-01 | 2002-06-04 | Inleague, Inc. | System for web-based payroll and benefits administration |
US6925468B1 (en) | 1999-10-29 | 2005-08-02 | Computer Sciences Corporation | Configuring systems for generating business transaction reports using processing relationships among entities of an organization |
US6246933B1 (en) | 1999-11-04 | 2001-06-12 | BAGUé ADOLFO VAEZA | Traffic accident data recorder and traffic accident reproduction system and method |
US20020082877A1 (en) | 1999-12-03 | 2002-06-27 | Schiff Martin R. | Systems and methods of matching customer preferences with available options |
US6351893B1 (en) | 1999-12-07 | 2002-03-05 | Garrick St. Pierre | Self squaring accident diagramming template |
US6408304B1 (en) | 1999-12-17 | 2002-06-18 | International Business Machines Corporation | Method and apparatus for implementing an object oriented police patrol multifunction system |
US20030074353A1 (en) | 1999-12-20 | 2003-04-17 | Berkan Riza C. | Answer retrieval technique |
US6775658B1 (en) | 1999-12-21 | 2004-08-10 | Mci, Inc. | Notification by business rule trigger control |
US6751657B1 (en) | 1999-12-21 | 2004-06-15 | Worldcom, Inc. | System and method for notification subscription filtering based on user role |
US6484178B1 (en) | 1999-12-30 | 2002-11-19 | The Merallis Company | Universal claims formatter |
US6643652B2 (en) | 2000-01-14 | 2003-11-04 | Saba Software, Inc. | Method and apparatus for managing data exchange among systems in a network |
US6493650B1 (en) | 2000-01-27 | 2002-12-10 | Optimus Corporation | Device for automatic documentation of crash scenes |
US20010037224A1 (en) | 2000-01-31 | 2001-11-01 | Eldridge James A. | Method and system for submitting and tracking insurance claims via the internet |
US20010041993A1 (en) | 2000-02-03 | 2001-11-15 | Campbell Richard L. | Automated claim processing and attorney referral and selection |
US6681380B1 (en) | 2000-02-15 | 2004-01-20 | International Business Machines Corporation | Aggregating constraints and/or preferences using an inference engine and enhanced scripting language |
US20010041992A1 (en) | 2000-03-10 | 2001-11-15 | Medorder, Inc. | Method and system for accessing healthcare information using an anatomic user interface |
US7953615B2 (en) | 2000-04-03 | 2011-05-31 | Mitchell International, Inc. | System and method of administering, tracking and managing of claims processing |
US20020002475A1 (en) | 2000-04-13 | 2002-01-03 | Joel Freedman | Automated insurance system and method |
US7426474B2 (en) | 2000-04-25 | 2008-09-16 | The Rand Corporation | Health cost calculator/flexible spending account calculator |
US20020004729A1 (en) | 2000-04-26 | 2002-01-10 | Christopher Zak | Electronic data gathering for emergency medical services |
US20010044735A1 (en) | 2000-04-27 | 2001-11-22 | Colburn Harry S. | Auditing and monitoring system for workers' compensation claims |
US6728769B1 (en) | 2000-05-04 | 2004-04-27 | Sun Microsystems, Inc. | Method and apparatus for providing a highly interactive transaction environment in a distributed network |
US20020022976A1 (en) | 2000-05-19 | 2002-02-21 | Hartigan William R. | Method and system for providing online insurance information |
AU2001265006A1 (en) | 2000-05-24 | 2001-12-03 | The Haley Enterprises, Inc. | A system for enterprise knowledge management and automation |
US7668738B2 (en) | 2000-06-01 | 2010-02-23 | Blue Cross And Blue Shield Of South Carolina | Insurance claim filing system and method |
US7398219B1 (en) | 2000-06-23 | 2008-07-08 | Computer Sciences Corporation | System and method for displaying messages using a messages table |
US7418400B1 (en) | 2000-06-23 | 2008-08-26 | Computer Sciences Corporation | Internet-enabled system and method for assessing damages |
US7430515B1 (en) * | 2000-06-23 | 2008-09-30 | Computer Sciences Corporation | System and method for externalization of formulas for assessing damages |
US7024418B1 (en) | 2000-06-23 | 2006-04-04 | Computer Sciences Corporation | Relevance calculation for a reference system in an insurance claims processing system |
US7430514B1 (en) | 2000-06-23 | 2008-09-30 | Computer Sciences Corporation | System and method for processing insurance claims using a table of contents |
US7095426B1 (en) | 2000-06-23 | 2006-08-22 | Computer Sciences Corporation | Graphical user interface with a hide/show feature for a reference system in an insurance claims processing system |
US7343307B1 (en) | 2000-06-23 | 2008-03-11 | Computer Sciences Corporation | Dynamic help method and system for an insurance claims processing system |
US20020161597A1 (en) | 2000-06-28 | 2002-10-31 | Alexander Klibaner | System and method for interactively establishing a dispute resolution procedure |
JP2002014950A (en) | 2000-06-29 | 2002-01-18 | Tokio Marine & Fire Insurance Co Ltd | Presentation file preparation system and method |
US6832205B1 (en) | 2000-06-30 | 2004-12-14 | General Electric Company | System and method for automatically predicting the timing and costs of service events in a life cycle of a product |
US20020007289A1 (en) | 2000-07-11 | 2002-01-17 | Malin Mark Elliott | Method and apparatus for processing automobile repair data and statistics |
US6850922B1 (en) | 2000-07-14 | 2005-02-01 | International Business Machines Corporation | Business logic support |
US6684388B1 (en) | 2000-08-22 | 2004-01-27 | International Business Machines Corporation | Method for generating platform independent, language specific computer code |
US20020035491A1 (en) | 2000-09-21 | 2002-03-21 | Access Transport Services, Inc. | System and associated methods for providing claimant services with increased quality assurance |
US20030093302A1 (en) | 2000-10-04 | 2003-05-15 | Francis Quido | Method and system for online binding of insurance policies |
US20020055861A1 (en) | 2000-11-08 | 2002-05-09 | King Daniel A. | Claiming system and method |
JP4823448B2 (en) | 2000-11-24 | 2011-11-24 | トヨタ自動車株式会社 | Alarm device |
US7020869B2 (en) | 2000-12-01 | 2006-03-28 | Corticon Technologies, Inc. | Business rules user interface for development of adaptable enterprise applications |
US7720698B1 (en) * | 2000-12-20 | 2010-05-18 | Guaranty Fund Management Services | Method and apparatus for performing assessments |
US20020091818A1 (en) | 2001-01-05 | 2002-07-11 | International Business Machines Corporation | Technique and tools for high-level rule-based customizable data extraction |
US20020116254A1 (en) * | 2001-02-16 | 2002-08-22 | Stein Larry L. | Apparatus and method for estimating damage to a building |
US20020133362A1 (en) | 2001-03-13 | 2002-09-19 | Elliot Karathanasis | Computerized dispute resolution system |
WO2002077759A2 (en) | 2001-03-20 | 2002-10-03 | Dealigence Inc. | Negotiating platform |
US6862573B2 (en) | 2001-03-22 | 2005-03-01 | Clear Technology, Inc. | Automated transaction management system and method |
US6868413B1 (en) | 2001-05-10 | 2005-03-15 | Networks Associates Technology, Inc. | System and method for customizing and processing business logic rules in a business process system |
US7328212B2 (en) | 2001-05-31 | 2008-02-05 | Oracle International Corporation | Generalized method for modeling complex ordered check constraints in a relational database system |
US20020194023A1 (en) | 2001-06-14 | 2002-12-19 | Turley Troy A. | Online fracture management system and associated method |
US6856980B2 (en) | 2001-06-25 | 2005-02-15 | Exigen Group | Hybrid use of rule and constraint engines |
US7051046B2 (en) | 2001-08-01 | 2006-05-23 | Roy F. Weston, Inc. | System for managing environmental audit information |
US6675074B2 (en) | 2001-08-21 | 2004-01-06 | Robert Bosch Gmbh | Method and system for vehicle trajectory estimation |
US6850843B2 (en) | 2001-09-06 | 2005-02-01 | Wdt Technologies, Inc. | Accident evidence recording method |
US20030200123A1 (en) | 2001-10-18 | 2003-10-23 | Burge John R. | Injury analysis system and method for insurance claims |
US20030120528A1 (en) | 2001-10-23 | 2003-06-26 | Kruk Jeffrey M. | System and method for managing compliance with strategic business rules |
JP2003182508A (en) | 2001-12-18 | 2003-07-03 | Denso Corp | Occupant protecting device for vehicle |
JP3925188B2 (en) | 2001-12-20 | 2007-06-06 | 日本電気株式会社 | Application layer multicast method and relay node system |
US20040205562A1 (en) * | 2001-12-27 | 2004-10-14 | G.E. Information Services, Inc. | System and method for transforming documents to and from an XML format |
US20030125991A1 (en) | 2001-12-31 | 2003-07-03 | Logan Andrew J. | Computerized locus investigation system for motor vehicle claims adjusters |
US20030158759A1 (en) | 2002-01-24 | 2003-08-21 | Robert Kannenberg | Method of modifying software by defining business rules |
US7424715B1 (en) | 2002-01-28 | 2008-09-09 | Verint Americas Inc. | Method and system for presenting events associated with recorded data exchanged between a server and a user |
US7720699B2 (en) | 2002-04-22 | 2010-05-18 | Employers Reinsurance Corporation | Critical injury insurance systems and methods |
US20030221184A1 (en) | 2002-05-22 | 2003-11-27 | Gunjal Atul Narayan | Template-based application development system |
US7885829B2 (en) * | 2002-08-07 | 2011-02-08 | Metropolitan Property And Casualty Insurance Company | System and method for identifying and assessing comparative negligence in insurance claims |
US20040054557A1 (en) * | 2002-09-09 | 2004-03-18 | Stefan Wahlbin | Computerized method and system for estimating premises liability for an accident |
US7672860B2 (en) * | 2002-09-09 | 2010-03-02 | Computer Sciences Corporation | Computerized method and system for determining the contribution of defenses to premises liability for an accident |
US20040054556A1 (en) | 2002-09-09 | 2004-03-18 | Stephan Wahlbin | Computerized method and system for determining causation in premises liability for an accident |
US20040054558A1 (en) * | 2002-09-09 | 2004-03-18 | Stefan Wahlbin | Computerized method and system for determining claimant status in premises liability for an accident |
US7702528B2 (en) | 2002-09-09 | 2010-04-20 | Computer Sciences Corporation | Computerized method and system for determining breach of duty in premises liability for an accident |
US7451148B2 (en) | 2002-10-31 | 2008-11-11 | Computer Sciences Corporation | Method of modifying a business rule while tracking the modifications |
US20040102984A1 (en) | 2002-11-27 | 2004-05-27 | Stefan Wahlbin | Computerized method and system for estimating liability using recorded vehicle data |
US7725334B2 (en) | 2002-11-27 | 2010-05-25 | Computer Sciences Corporation | Computerized method and system for estimating liability for an accident using dynamic generation of questions |
US7792690B2 (en) * | 2002-11-27 | 2010-09-07 | Computer Sciences Corporation | Computerized method and system for estimating an effect on liability of the speed of vehicles in an accident and time and distance traveled by the vehicles |
US7805321B2 (en) | 2002-11-27 | 2010-09-28 | Computer Sciences Corporation | Computerized method and system for estimating liability for an accident from an investigation of the accident |
US7895063B2 (en) * | 2002-11-27 | 2011-02-22 | Computer Sciences Corporation | Computerized method and system for creating pre-configured claim reports including liability in an accident estimated using a computer system |
US7660725B2 (en) * | 2002-11-27 | 2010-02-09 | Computer Sciences Corporation | Computerized method and system for estimating an effect on liability based on the stopping distance of vehicles |
US7702529B2 (en) * | 2002-11-27 | 2010-04-20 | Computer Sciences Corporation | Computerized method and system for estimating an effect on liability using claim data accessed from claim reporting software |
US7809586B2 (en) | 2002-11-27 | 2010-10-05 | Computer Sciences Corporation | Computerized method and system for estimating an effect on liability using a comparison of the actual speed of a vehicle in an accident and time and distance traveled by the vehicles in a merging vehicle accident |
US7818187B2 (en) | 2002-11-27 | 2010-10-19 | Computer Sciences Corporation | Computerized method and system for estimating liability |
US20040103005A1 (en) | 2002-11-27 | 2004-05-27 | Stefan Wahlbin | Computerized method and system for estimating monetary damages due to injuries in an accident from liability estimated using a computer system |
US7020593B2 (en) * | 2002-12-04 | 2006-03-28 | International Business Machines Corporation | Method for ensemble predictive modeling by multiplicative adjustment of class probability: APM (adjusted probability model) |
US20070214020A1 (en) * | 2003-03-18 | 2007-09-13 | Balaji Srinivasan | Modeling of insurance product data |
US20040215494A1 (en) * | 2003-04-24 | 2004-10-28 | Wahlbin Stefan L. | Method and system for determining monetary amounts in an insurance processing system |
US20050038682A1 (en) * | 2003-08-14 | 2005-02-17 | Gandee Gregory M. | Method and systems for virtual insurance adjusting |
US20050060205A1 (en) * | 2003-09-02 | 2005-03-17 | Woods Randall K. | Systems and methods for a graphical input display in an insurance processing system |
US7895064B2 (en) * | 2003-09-02 | 2011-02-22 | Computer Sciences Corporation | Graphical input display in an insurance processing system |
US8516123B2 (en) | 2004-02-12 | 2013-08-20 | Oracle International Corporation | Runtime validation of messages for enhanced web service processing |
US20050192850A1 (en) | 2004-03-01 | 2005-09-01 | Lorenz Scott K. | Systems and methods for using data structure language in web services |
US20060089861A1 (en) * | 2004-10-22 | 2006-04-27 | Oracle International Corporation | Survey based risk assessment for processes, entities and enterprise |
US20060111993A1 (en) * | 2004-11-23 | 2006-05-25 | International Business Machines Corporation | System, method for deploying computing infrastructure, and method for identifying an impact of a business action on a financial performance of a company |
AU2006335151A1 (en) * | 2005-12-30 | 2007-07-19 | Steven Kays | Genius adaptive design |
US8645162B2 (en) * | 2006-05-01 | 2014-02-04 | Envoy Llc | Method and system for estimating the financial liability of a patient for a medical service |
US8229767B2 (en) * | 2006-10-18 | 2012-07-24 | Hartford Fire Insurance Company | System and method for salvage calculation, fraud prevention and insurance adjustment |
US20070226018A1 (en) * | 2007-03-01 | 2007-09-27 | Paul Gross | System and method for managing an insurance claim |
US8244558B2 (en) | 2008-01-18 | 2012-08-14 | Computer Sciences Corporation | Determining recommended settlement amounts by adjusting values derived from matching similar claims |
-
2008
- 2008-06-06 US US12/134,997 patent/US8244558B2/en not_active Expired - Fee Related
- 2008-06-06 US US12/134,977 patent/US20090187428A1/en not_active Abandoned
- 2008-06-06 US US12/135,009 patent/US7991630B2/en active Active
- 2008-06-06 US US12/135,004 patent/US20090187431A1/en not_active Abandoned
- 2008-06-06 US US12/134,991 patent/US8219424B2/en not_active Expired - Fee Related
-
2009
- 2009-01-19 WO PCT/US2009/031406 patent/WO2009092072A2/en active Application Filing
- 2009-01-19 CA CA2715378A patent/CA2715378C/en active Active
- 2009-01-19 AU AU2009205960A patent/AU2009205960A1/en not_active Abandoned
- 2009-01-19 EP EP09703022A patent/EP2252966A2/en not_active Withdrawn
Also Published As
Publication number | Publication date |
---|---|
US8244558B2 (en) | 2012-08-14 |
US20090187430A1 (en) | 2009-07-23 |
US20090187428A1 (en) | 2009-07-23 |
CA2715378C (en) | 2018-03-13 |
EP2252966A2 (en) | 2010-11-24 |
AU2009205960A1 (en) | 2009-07-23 |
US8219424B2 (en) | 2012-07-10 |
US20090187432A1 (en) | 2009-07-23 |
US20090187429A1 (en) | 2009-07-23 |
CA2715378A1 (en) | 2009-07-23 |
US20090187431A1 (en) | 2009-07-23 |
US7991630B2 (en) | 2011-08-02 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CA2715378C (en) | Evaluating effectiveness of claims evaluation, assessment, and settlement processes | |
US7337121B1 (en) | Claim assessment model | |
Yang et al. | Epidemiological survey of orthopedic joint dislocations based on nationwide insurance data in Taiwan, 2000-2005 | |
Leahy | Rational Health Policy and the Legal Standard of Care: A Call for Judicial Deference to Medical Practice Guidelines | |
Shwartz et al. | Do severity measures explain differences in length of hospital stay? The case of hip fracture. | |
Sarmiento et al. | Malpractice litigation in plastic surgery: can we identify patterns? | |
Patterson et al. | Lawsuits after primary and revision total knee arthroplasty: a malpractice claims analysis | |
Ali | A decade of clinical negligence in ophthalmology | |
Bergman et al. | Lobbying physicians: Payments from industry and hospital procurement of medical devices | |
AU2014274609A1 (en) | Evaluating effectiveness of claims evaluation, assessment, and settlement processes | |
Makhni et al. | The use of patient-reported outcome measures in clinical practice and clinical decision making | |
Kohring et al. | Pattern of recovery and outcomes of patient reported physical function and pain interference after ankle fusion: a retrospective cohort study | |
Christensen et al. | Hospital revenue, cost, and contribution margin in inpatient versus outpatient primary total joint arthroplasty | |
Midgley et al. | Evaluation of an evidence-based patient pathway for non-surgical and surgically managed metacarpal fractures | |
Fontánez et al. | Musculoskeletal conditions in the emergency room: a teaching opportunity for medical students and residents | |
Park et al. | Measuring case-mix complexity of tertiary care hospitals using DRGs | |
Kotha et al. | National disparities in insurance coverage of comprehensive craniomaxillofacial trauma care | |
GB2460922A (en) | Determining amounts for claims settlements using likelihood values | |
Shapiro et al. | Health policy in hand surgery: evaluating what works | |
Works | Health Policy in Hand Surgery | |
Tavolaro et al. | Post-operative follow-up care after acute spinal trauma: What is the reality? | |
Grennan et al. | Lobbying Physicians: Payments from Industry and Hospital Procurement of Medical Devices | |
Miles | Gender and Health Insurance | |
Anitelea et al. | The outcomes of patients returned to general practitioner after being declined hip and knee replacement | |
Crespin et al. | Claims-Based Reporting of Post-Operative Visits for Procedures with 10-or 90-Day Global Periods |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 09703022 Country of ref document: EP Kind code of ref document: A2 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2009205960 Country of ref document: AU |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2715378 Country of ref document: CA |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2009703022 Country of ref document: EP |
|
ENP | Entry into the national phase |
Ref document number: 2009205960 Country of ref document: AU Date of ref document: 20090119 Kind code of ref document: A |