Abstract:
A machine-implemented method of assisting medical evidence collection for adjudication of a medical disability request is described. In some embodiments, the method includes providing an electronic medical record of a patient, the electronic medical record includes evidence of at least one claimable medical disability condition and locating in the electronic medical record at least one keyword associated with the at least one claimable medical disability condition. In some embodiments, the method further includes processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record and outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record.

Description:
REFERENCE TO RELATED APPLICATIONS 
       [0001]    The present application is a continuation of and claims priority benefit under 35 U.S.C. §120 from U.S. patent application Ser. No. 12/192,043, filed Aug. 14, 2008, which is hereby incorporated herein by reference in its entirety. 
     
    
     BACKGROUND OF THE INVENTION 
       [0002]    1. Field of the Invention 
         [0003]    Some embodiments of the present invention relates to methods and systems for gathering and processing medical data to support rating decisions in the adjudication of insurance and disability requests. 
         [0004]    2. Description of the Related Art 
         [0005]    Government agencies and insurance companies have developed rules for the adjudication of insurance or disability requests. Examples of insurance or disability programs include the Department of Veterans Affairs (VA) program, the Social Security Disability Insurance program, the Workers&#39; Compensation program, various property and casualty insurance programs, and so forth. 
         [0006]    In order to adjudicate a request made by a claimant, certain medical evidence is required. Medical evidence requirements refers to requirements of information about a claimant that is relevant to the medical conditions claimed by the claimant, such as the age and gender of the claimant, physical examination data, laboratory test data and medical history data pertinent to the claims, and so forth. The requirements are specified by rules developed by the government agency or by the insurance company, pertinent case law, government regulations, legislation and administrative decisions, and so forth. For example, the requirements may specify that if a claimant claims a certain medical condition, a medical provider must conduct certain physical examinations and laboratory tests on the claimant or ask certain questions. The requirements may also specify, for example, that a claimant must have a range of motions less than a certain degree to claim a limb disability. Requirements can also be specified by conventional medical knowledge, for example requiring a certain test to confirm a particular claimed condition. 
         [0007]    The rating rules are normally documented in manuals that may have many different titles, herein referred to as “rating books.” A rating code refers to a classification used by the government agency or insurance company that typically refers to a medical condition or a class of medical conditions in a rating book. The collection of rating rules, rating codes, pertinent legislation and case law for an insurance or disability program is herein referred to as the “rules collection” for that program. The rating rules may include rules on how to make a rating decision based on the collected medical evidence and the rating codes. For example, in a VA disability program, the rules collection typically specifies a disability percentage range based on rating codes and collected medical evidence. A VA rating personnel reviews the rating codes and medical evidence, and specifies a disability percentage within the range. 
         [0008]    In a disability or insurance request process, the claimant typically visits a hospital, clinic or medical office. A medical provider such as a physician or a nurse collects medical evidence from the claimant to support a rating decision. The rating decision is typically made by the government agency or the insurance company based on the medical evidence collected by the medical provider and based on the rules collection. The medical providers are typically provided with documents generally referred to as “physician&#39;s disability evaluation” or “medical examination handbooks” to assist them with collecting medical evidence. The handbooks are herein referred to as “medical handbooks.” The medical handbooks typically contain the medical evidence requirements for the rules collection. 
         [0009]    In many cases, a claimant makes claims for multiple medical conditions at different points in time. The conventional practice is to review a medical evidence document each time a condition is claimed. This results in significant duplication of effort as the analysis of portions of the medical evidence document might be conducted multiple times. 
         [0010]    To better illustrate the drawbacks of conventional practices and the need for better systems, the VA Compensation and Pension (C&amp;P) program is described as an example. This government program provides payments of benefits to military veterans for medical disability resulting from their military service. Multiple paper records form the basis for the analysis and adjudication of C&amp;P claims for veterans and transitioning active duty service member. In certain cases, sixty percent of all claims are reopened claims and require the paper record to be completely re-reviewed. 
       SUMMARY 
       [0011]    A system is disclosed for automatically relating rating requirements and other pertinent findings from a medical record to a claimed or potentially claimable condition. 
         [0012]    In some embodiments, a machine-implemented method of assisting medical evidence collection for adjudication of a medical disability request is disclosed. The method includes providing an electronic medical record of a patient, the electronic medical record includes evidence of at least one claimable medical disability condition and locating in the electronic medical record at least one keyword associated with the at least one claimable medical disability condition. The method further includes processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record and outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0013]    In some embodiments, the inference rule is processed if the at least one keyword is present in the electronic medical record. In some embodiments, the method further includes indexing the electronic medical record prior to the locating in the electronic medical record the at least one keyword. In some embodiments, the at least one keyword is selected from a plurality of keywords associated with the at least one claimable medical disability condition. In some embodiments, the method further includes determining, for each of the plurality of keywords, whether that keyword is included in the electronic medical record. In some embodiments, the inference rule includes searching, in the electronic medical record, for information associated with the at least one keyword. In some embodiments, the inference rule utilizes at least one of information on a category associated with the at least one keyword, a rating code, and a search query. In some embodiments, the information indicative of the evidence of the at least one claimable medical disability condition includes at least one of a secondary condition associated with the at least one claimable medical disability condition, a category associated with the at least one claimable medical disability condition, and a rating code associated with the at least one claimable medical disability condition. 
         [0014]    In some embodiments, a machine-implemented method of assisting medical evidence collection for adjudication of a medical disability request is disclosed. The method includes providing an electronic medical record of a patient, the electronic medical record includes evidence of at least one claimable medical disability condition and processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record. The method also includes outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0015]    In some embodiments, a machine-readable medium encoded with instructions for assisting medical evidence collection for adjudication of a medical disability request is disclosed. The instructions include code for locating in an electronic medical record at least one keyword associated with at least one claimable medical disability condition and processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record. The instructions also include code for outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0016]    In some embodiments, a machine-readable medium encoded with instructions for assisting medical evidence collection for adjudication of a medical disability request is disclosed. The instructions include code for processing an inference rule associated with at least one claimable medical disability condition, such that evidence of the at least one claimable medical disability condition is identified in the electronic medical record, and outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0017]    In some embodiments, a system, for assisting medical evidence collection for adjudication of a medical disability request, is disclosed. The system includes a searching module configured to locate in an electronic medical record at least one keyword associated with at least one claimable medical disability condition and a processing module configured to process an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record, the processing module further configured to send an output to an output module. The output includes computer-readable information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0018]    In some embodiments, a system, for assisting medical evidence collection for adjudication of a medical disability request, is disclosed. The system includes a processing module configured to process an inference rule associated with at least one claimable medical disability condition, such that the evidence of at least one claimable medical disability condition is identified in an electronic medical record, the processing module further configured to send an output to an output module. The output includes computer-readable information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0019]    In some embodiments, a system, for assisting medical evidence collection for adjudication of a medical disability request, is disclosed. The system includes means for providing an electronic medical record of a patient, the electronic medical record includes evidence of at least one claimable medical disability condition, and means for locating in the electronic medical record at least one keyword associated with the at least one claimable medical disability condition. The system also includes means for processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record, and means for outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0020]    In some embodiments, a system, for assisting medical evidence collection for adjudication of a medical disability request, is disclosed. The system includes means for providing an electronic medical record of a patient, the electronic medical record includes evidence of at least one claimable medical disability condition, and means for processing an inference rule associated with the at least one claimable medical disability condition, such that the evidence of the at least one claimable medical disability condition is identified in the electronic medical record. The system also includes means for outputting, to a computer-readable medium, information indicative of (1) the evidence of the at least one claimable medical disability condition, and (2) a location of the evidence in the electronic medical record. The processing an inference rule includes locating an indicator of a value in the electronic medical record that tends to confirm an existence of the claimable medical disability condition in the patient. 
         [0021]    In some embodiments, processing an inference rule consists essentially of locating in the electronic medical record at least one keyword associated with the at least one claimable medical disability condition. 
         [0022]    For purposes of summarizing the invention, certain aspects, advantages, and novel features of the invention have been described herein. It is to be understood that not necessarily all such advantages may be achieved in accordance with any particular embodiment of the invention. Thus, the invention may be embodied or carried out in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0023]    A general architecture that implements the various features of the invention will now be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention. Throughout the drawings, reference numbers are re-used to indicate correspondence between referenced elements. 
           [0024]      FIG. 1  illustrates a general overview of one embodiment of a medical record inference index system. 
           [0025]      FIG. 2  illustrates sample inference rules associated with a claim condition. 
           [0026]      FIG. 3  is one embodiment of a process for identifying disability benefits claims. 
           [0027]      FIG. 4  is one embodiment of processing an electronic medical record (EMR) using the medical record inference index system of  FIG. 1 . 
           [0028]      FIGS. 5A-5B  illustrate values associated with a sample entry in an evidence repository for an EMR. 
           [0029]      FIGS. 6A-6C  illustrate pages of a sample EMR. 
       
    
    
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
       [0030]      FIG. 1  illustrates a general overview of one embodiment of a medical record inference index system  100 . The medical record inference index system  100  includes rules collection  105 , pertinent medical knowledge  106 , keyword and inference library  107 , at least one indexed patient EMR  104 , and an index of potential patient claims in the EMR  108 . 
         [0031]    Rules collection  105  and pertinent medical knowledge  106  are organized into a keyword and inference library  107 . Based on an indexed patient EMR  104 , which was created by applying text indexer  103  to a patient EMR  102  selected from EMR storage  101 , and based on the keywords and inference rules in the keyword and inference library  107 , an index of potential claims  108  present in indexed patient EMR  104  is generated. The index of potential claims is stored in evidence repository  109 . 
         [0032]    EMR storage  101  is electronic data storage configured to store at least one EMR (e.g., EMR  104 ). As used herein, an electronic medical record includes, without limitation, medical information stored in an electronic format. The medical information can include, for example, notes from a patient&#39;s medical history, family and social history, complaints, office visits, staff observations, laboratory tests, X-rays, prescription and drug allergy information, social history, diagnoses, data from charts, radiological study results, nuclear medicine laboratory results, present medication, allergy and chronic condition lists (e.g., from medical alert bracelets), histories of a present illness, a review of systems, physical exams, interviews with friends and family of the claimant, interviews of the claimant&#39;s prior medical providers, and other medical records of the patient. For example, an EMR can be an electronic Veteran&#39;s Health Administration (VHA) record or a Department of Defense (DoD) record. The electronic data storage may comprise any type of computer-readable media, including hard disk drives, removable magnetic disks, removable optical disks, magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, random access memories, read-only memories, and the like, and may be configured as a file server, database, or other data object. Electronic formats include, but are not limited to, scanned documents, such as scanned paper records, or documents originally generated and subsequently stored electronically, such as text files. 
         [0033]    Text indexer  103  is configured to index EMR  102  in order to provide indexed patient EMR  104 , an indexed version of EMR  102 . As a result, in certain embodiments, indexed information in indexed patient EMR  104  can be located in sublinear, logarithmic, or constant time. In one embodiment, text indexer  103  provides a full-text indexing of EMR  102 . In certain embodiments, text indexer  103  includes optical character recognition of content in EMR  102  when indexing EMR  102 . Any conventional algorithm known to those of skill in the art may be used to implement text indexer  103 . 
         [0034]    Still referring to  FIG. 1 , rule collection  105  represents a rules collection for the insurance or disability program, typically embodied in rating books, legislation, administrative decisions and case law. For example, rule collection  105  can include the “Schedule for Ratings Disabilities” from Title 38 of the Code of Federal Regulations (CFR) (hereinafter “Schedule for Ratings Disabilities”). Medical knowledge  106  represents pertinent medical knowledge, such as instructions to a physician, lab technician or nurse for performing a physical exam or laboratory test, and information from a contractor&#39;s extensive disability examination experience and its experience supporting the Veteran&#39;s Benefit Administration with C&amp;P examinations. 
         [0035]    Keyword and inference library  107  includes claimable medical disability conditions relating to medical disabilities, a collection of keywords associated with the claimable medical disability conditions relating to medical disabilities, and a collection of inference rules associated with the keywords. According to certain embodiments, keyword and inference library  107  is organized according to the claimable medical disability conditions. A keyword as discussed herein includes, without limitation, either a single or multiple letters, words, acronyms, abbreviations, or numerals. For example, “diabetes mellitus,” “insulin dependent diabetes,” “adult onset diabetes,” “insulin dependent diabetes mellitus,” “IDDM,” “vision loss,” “nephropathy,” “amputation,” “renal failure,” “diabetic ketoacidosis,” “antibiotic therapy,” “impaired fasting glucose,” and “IFG” may be keywords associated with the claimable medical disability condition of diabetes mellitus. 
         [0036]    Inference rules as discussed herein include, without limitation, values and/or parameters to be applied to an EMR (e.g., indexed patient EMR  104 ) to determine if the EMR satisfies the values and/or contains the values, and actions to be taken if the EMR satisfies the values and/or contains the values. In certain embodiments, the actions include assigning a rating code based on available rating books, such as the Schedule for Ratings Disabilities. In certain embodiments, inference rules may be associated with additional claim conditions, such as related claim conditions. For example, inference rules that assist in locating evidence of diabetes mellitus may also assist in locating evidence of heart disease. 
         [0037]    For example,  FIG. 2  illustrates sample inference rules associated with the claimable medical disability condition of diabetes mellitus. The sample inference rules include an inference rule  201 , with a “RULEID” value of 3. Inference rule  201 , if processed on an EMR, determines that if the EMR contains the string “plasma glucose” within five words distance from a value greater than 199 mg/d, then a record (e.g., index of potential claims in EMR  108 ) is created and stored (e.g., in evidence repository  109 ) in which (1) the EMR (e.g., EMR  102  or indexed patient EMR  104 ) is identified as containing evidence of the claimable medical disability condition with which the inference rule is associated, diabetes mellitus, (2) the page number containing the subject matter satisfying the inference rule is stored, (3) the category “diagnosis” is set to “diabetes,” and (4) the rating code is assigned a value of “7913,” which is the rating code for diabetes in the Schedule for Ratings Disabilities. The record can be supplemented with additional information on the same or different claimable medical disability conditions that are found in the same EMR using other inference rules. In certain embodiments, relevant portions of the EMR may be tagged in order to facilitate referencing of the EMR, such as by tagging a portion of the EMR identified as containing evidence of the claimable medical disability condition with which the inference rule is associated. Additional records can also be created and stored in evidence repository  109 , which may also be electronic storage, for other EMRs. For example, in an object-oriented arrangement, a claimable medical disability condition can be associated with an object that includes various fields for “RULEID,” “RULEID OPERATOR,” “REQUIREMENT,” “REQUIREMENT OPERATOR,” “CATEGORY,” “CATEGORY KEYWORD,” and “RATING CODE.” 
         [0038]    In certain embodiments, inference rules are generated based on the units of data that may be required by rules collection  105  for assigning a rating code. For example, an inference rule can correspond to a medical evidence requirement specified by rules collection  105  or by medical knowledge  106 . 
         [0039]    A collection of potential claimable medical disability conditions found in an EMR for a patient can thus be generated and stored, and later reviewed to assist a physician, rating specialist, nurse or technician to confirm actual claimable medical disability conditions for the patient. Furthermore, the collection can be recalled and re-reviewed at any time without having to retrieve voluminous paper or electronic files. For example, if an EMR for a patient is reviewed by the medical record inference index system  100  a first time, and after the first review the EMR is supplemented with additional information, the medical record inference index system  100  may highlight or otherwise differentiate new information during a second review that was not present during the first review. In certain embodiments, the medical record inference index system  100  is configured to differentiate between actual claimed conditions by a patient and potentially claimable conditions by a patient. 
         [0040]    In certain embodiments, claimable medical disability conditions and associated information can be specific to the claimant or specific to the type of claim. For example, information associated with a claimable medical disability condition can be associated with information relevant or specific to the claimant (e.g., claimed medical conditions, name, age, gender) and/or to the type of claim (e.g., leg pain, chest pain, head pain). Examples of claim-specific, claimant-specific, and claim-type specific information can be found in U.S. patent application Ser. No. 10/279,759, filed Oct. 23, 2002, U.S. patent application Ser. No. 11/155,908, filed Jun. 20, 2005, and U.S. patent application Ser. No. 11/157,125, filed on Jun. 20, 2005, each of which is hereby incorporated herein by reference in its entirety 
         [0041]      FIG. 3  is one embodiment of a process for identifying disability benefits claims. The process begins in step  301 , and proceeds to step  302 , in which a loop is entered for each EMR  102  in EMR storage  101 . In the first step of the loop, step  303 , EMR  102  is received. For example, EMR  102  may be actively retrieved by a module, or received from another module that sends EMR  102 . EMR  102  is processed in step  304  using the medical record inference index system  100  of  FIG. 1 , as further described in  FIG. 4 . Claim information identified in EMR  102  is output to an output device in step  305 , such as by printing a record of claimable medical disability conditions found in EMR  102 . Output devices may include but are not limited to, a display monitor, a printer, paper, the human voice, computer memory, volatile (such as RAM) or non-volatile (such as a hard disk drive), an electronically generated voice, and output computer languages, specifications, or formats such as the Extensible Markup Language (XML) or Comma Separated Values (CSV) format, or standards such as Health Level Seven (HL7). The process then moves to end-of-loop step  306 , in which another EMR in EMR storage  101  is retrieved, and steps  203 - 205  are repeated for the EMR. If no EMR remains in EMR storage  101  in step  306 , the process ends in step  307 . In certain embodiments, the identified claim information output in step  305  can be reviewed by a human reviewer to ensure the accuracy of the information. 
         [0042]      FIG. 4  is one embodiment of processing an electronic medical record (EMR) using the medical record inference index system of  FIG. 1 , and provides further elaboration for step  304  of  FIG. 3 . 
         [0043]    The process begins in step  401 , and proceeds to step  402 , in which the EMR (e.g., EMR  102 ) is optionally indexed, to generate the indexed EMR (e.g., indexed EMR  104 ). For example, in addition to word-indexing the EMR, as described above, the EMR may be indexed by patient name, page, date, location, physician, record type, page number, case related information such as claim number or claim conditions. In certain embodiments, the EMR is already indexed, and step  402  is skipped. In certain embodiments, the EMR does not need to be indexed to proceed with the process, and the system  100  is configured to provide an index of potential claims from a non-indexed EMR. 
         [0044]    In step  403 , a loop is entered for each claim condition in a keyword and inference library (e.g., keyword and inference library  107 ). A sub-loop is further entered in step  404  for each keyword associated with each claim condition. In the sub-loop, which proceeds to step  405 , the indexed EMR is processed to determine whether the keyword of step  403  is present in the indexed EMR. The process proceeds to step  406 , in which the sub-loop is repeated for each keyword associated with the claim condition. In certain embodiments (not illustrated), the sub-loop of steps  404 - 406  may end when any keyword associated with the claim condition is determined to be present in the indexed EMR. 
         [0045]    In step  407 , if any keywords associated with the claim condition were determined to be present in the indexed EMR during the sub-loop of steps  404 - 406 , then the process proceeds to step  408 . If no keywords associated with the claim condition were determined to be present in the indexed EMR, then the process proceeds to step  413 , in which the loop of step  403  either returns to step  403  if another claim condition remains in the keyword and inference library, or ends in state  414  if no claim conditions remain in the keyword and inference library. 
         [0046]    In step  408 , i.e., if a keyword associated with the claim condition is present in the indexed EMR, then steps  409 - 411  are repeated for each inference rule associated with the claim condition. In step  409 , the inference rule is processed on the indexed EMR to locate values (or indicators of values) in the indexed EMR satisfying the inference rule. The values can include, without limitation, numeric values, such as a value of 130 indicating a blood sugar level, binary values, such as a yes or no value indicating a history of cancer, character values, string values, or other values. 
         [0047]    In decision step  410 , if such values are located in the indexed EMR, then the process proceeds to step  411 . If, however, in decision step  410 , if such values are not located in the indexed EMR, then the process proceeds to end-of-loop step  412 . 
         [0048]    In step  411 , an entry corresponding to the located value is added to a record (e.g., index of potential claims in EMR  108 ) associated with the indexed EMR stored in an evidence repository (e.g., evidence repository  109 ). In step  412 , if any inference rules remain which are associated with the claim condition of step  403 , then the process returns to beginning-of-loop step  408 . Otherwise, if no inference rules remain which are associated with the claim condition of step  403 , then the process proceeds to step  413 . 
         [0049]    In step  413 , if any claim conditions remain in the keyword and inference library, then the process returns to beginning-of-loop step  403 . Otherwise, if no claim conditions remain in the keyword and inference library, then the process ends in step  414 . 
         [0050]    In certain embodiments, after step  403 , steps  404 - 407  may be skipped, and the process may proceed immediately to step  408 . As a result, inference rules associated with each claim condition may be processed on an EMR in order to add entries corresponding to located values to a record for the EMR in the evidence repository. 
         [0051]    According to one embodiment,  FIGS. 5A-5B  illustrate a sample record (e.g., index of potential claims in EMR  108 ) associated with a sample EMR (e.g., patient the EMR) which includes information on potential claims located in an indexed version of the EMR (e.g., index of potential claims in EMR  108 ).  FIGS. 6A-6C  illustrate selected pages from the sample EMR. 
         [0052]      FIG. 5A  illustrates the sample record before the record has been populated with any information related to the sample EMR. For example, the illustrated sample record may represent a record during steps  401 - 410  of the process illustrated in  FIG. 4 . The sample record is configured to store information on a claimed condition, as well as any keywords, page numbers, secondary conditions, and rating codes associated with a diagnosis, secondary condition, symptomatology, treatment, and diagnostic test(s) of the claimed condition. In certain embodiments, a record can be configured to store other information. 
         [0053]      FIG. 5B  illustrates the sample record of  FIG. 5A  after inference processing has occurred. For example, the sample record may represent a record after at least step  411  of the process illustrated in  FIG. 4  is processed on the sample EMR illustrated in  FIGS. 6A-6C  using the sample inference rule of  FIG. 3 . Because sample inference rule  201  is satisfied by the sample EMR, i.e., the sample EMR contains the phrase “plasma glucose” within five words distance of a value greater than 199 mg/dl at  201  in  FIG. 6A , the “claimed condition” value of the sample record is set to “diabetes mellitus”  501  and the “diagnosis” category of the record is set to “diabetes”  504  with a rating code of 7913 and the appropriate page number, according to the parameters of sample inference rule  201 . Likewise, additional inference rules associated with the entries of “ketoacidosis”  502  (the phrase being located at  502  in  FIG. 6B ) and “diabetic retinopathy”  503  (the phrase being located at  503  in  FIG. 6C ) are also recorded in the sample record. 
         [0054]    The sample record illustrated in  FIG. 5A  listing potential claims found in an EMR can be displayed after the process of  FIG. 3  is complete. For example, the list of potential claims and associated information can be displayed to a medical provider on the screen of an electronic device, and the medical provider can then have easy access to potential claim information for a patient without having to identify or otherwise locate information in the EMR first. 
         [0055]    According to one aspect of the disclosure, a machine-readable medium is a computer-readable medium encoded or stored with instructions and is a computing element, which defines structural and functional interrelationships between the instructions and the rest of the system, which permit the instructions&#39; functionality to be realized. Instructions may be executable, for example, by a medical record inference index system or by a processor of a medical record inference index system. Instructions can be, for example, a computer program including code. A machine-readable medium may comprise one or more media. 
         [0056]    While certain aspects and embodiments of the invention have been described, these have been presented by way of example only, and are not intended to limit the scope of the invention. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms without departing from the spirit thereof. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the invention.