WO2005104733A2 - Method for extracting and displaying healthcare history - Google Patents
Method for extracting and displaying healthcare history Download PDFInfo
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- WO2005104733A2 WO2005104733A2 PCT/US2005/014350 US2005014350W WO2005104733A2 WO 2005104733 A2 WO2005104733 A2 WO 2005104733A2 US 2005014350 W US2005014350 W US 2005014350W WO 2005104733 A2 WO2005104733 A2 WO 2005104733A2
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- 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
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- 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
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- 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
- G06Q50/22—Social work
Definitions
- the present invention relates to a system and method for automated extraction and display of past health care use to aid in predicting future health status. We assume that medical claim data is available for some individuals, that pharmacy claim data available for other individuals, and that both medical and pharmacy claim data is available for other individuals.
- the raw medical and pharmacy claims data is converted into Hierarchical Major Clinical Condition (HMCC) and Place of Treatment (POT) time-series data and displayed to facilitate the health assessment of a member's total clinical conditions and aid in predicting his or her future health status.
- HMCC Hierarchical Major Clinical Condition
- POT Place of Treatment
- Each medical and pharmacy claim of the member is mapped onto one or more HMCC/POT-time cells.
- HMCC/POT-time cells At the end of mapping, multiple entries in each HMCC-time cell are accumulated with the temporal resolution determined as a function of group size and temporal fidelity required for model building.
- Individual HMCC/POT-time maps can be rolled up to a group level to facilitate employer-by-employer or market-by-market comparison so that clinical strategies can be tailored to each employer or geographic region.
- the present invention is for a method for automated extraction and display of past health care use data to aid in predicting future health status, comprising the steps of: a. accessing a database containing insurance claim information; b. mapping the insurance claim information by individual and claim to at least one of a set of major clinical conditions to create a plurality of MCC claim mappings; c. associating each MCC claim mapping with an individual identifier, a time identifier, and a cost identifier; and, d.
- Figure 1 is a sample display of an individual's health care history over a selected time period based on medical and pharmacy claim information shown by major clinical condition and subsets thereof and by place of treatment.
- Figure 2 shows group-level rolled-up data for medical, pharmacy, and place-of-treatment or type-of-service (TOS) data for a selected group of individuals.
- TOS type-of-service
- Figure 3 shows group-level rolled-up data for medical, pharmacy, and place-of-treatment or type-of-service (TOS) data for two different selected groups for comparison.
- Figure 4A is a flow chart of member map data generation.
- Figure 4B is a flow chart showing how the data generated in Figure 4A is used to create the various member and group displays .
- DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT The predictive model uses features derived from multiple data sources that are fed to learning algorithms .
- One of the features used in this process is hierarchical categorization by Major Clinical Conditions or MCCs . Both medical and pharmacy claims data is mapped into these MCCs.
- MCCs Major Clinical Conditions
- ICD9-CM codes are used by hospitals and health care professionals to bill for charges and services. These codes identify the specific diagnosis assigned to each patient at the time of treatment. For each visit or service, there can be multiple diagnoses. Because there are approximately 12,000 ICD9-CM codes, the number of codes needed to be collapsed and categorized into cohesive broad groups or categories that made clinical sense, with flexibility in drill down into sub or sub-sub groups.
- Classifying the 12,000 ICD9-CM codes into 34 categories enables the predictive model to run more efficiently, and allows us to present a visual picture over time that follows the progression of illness and can be easily interpreted.
- the changed or revised codes can be easily mapped into the same 34 MCCs, thereby providing a method and system which the user of the visual picture sees as transparent to the changes and revisions.
- Within each major clinical condition there may be specific conditions or categories that are more definitive or may be clinically significant.
- MCC - Cancer CAN
- DIG sub-MCC Digestive
- UMI sub-sub MCC - Upper gastrointestinal
- LGI sub-sub MCC Lower gastrointestinal
- the pharmacy claim data is equally allocated among all MCCs that include the drug class related to the claim. While these drug classes are not as precise in identifying a disease or illness (some medications can be used for multiple disease processes) , they are of value in interpreting and evaluating a member's total health picture.
- MCC category #1 is CAD - coronary artery disease.
- the overall category has the following ICD9 Codes mapped thereto
- Drug classes mapped to this category are cardiotonics, anti-anginals, beta blockers, calcium channel blockers, cardiology supplies.
- Sub-MCCs for CAD are as follows: CABG - coronary artery bypass graft with ICD9 Code - V4581; PTCA - percutaneous transluminal coronary angioplasty with ICD9 Code - V4582; MI
- CAD has no Sub-sub-MCC categories.
- MCC category #2 is CHF - congestive heart failure with ICD9 Code 428 mapped thereto.
- Drug classes mapped to CHF are Beta Blockers, antihypertensive agents, and diuretics.
- CHF has no sub-MCCs or sub-sub-MCCs .
- MCC category #3 is HDZ - other heart disease.
- the overall category has the following ICD9 Codes mapped thereto - 394-3979, 424-4243, 426, 427, 420-422, 429, 4249, N151 , 425.
- One sub-MCC is VALV - valve diseases/disorders with ICD9 Codes 394 - 3979, 424 - 4243 and drug classes of Coumarin.
- Another sub-MCC is ARRH - arrhythmias/conduction disorders with ICD9 Codes 426,427 and drug classes of antiarrythirties and coumarin, with sub-sub-MCC SVI - supraventricular arrhythmia with ICD9 Codes 4270, 4272, 4273, and sub-sub-MCC VTC - ventricular arrhythmia with ICD9 Codes 4271, 4274, 4275.
- MCC category # 4 is CIR - circulatory.
- the overall category has the following ICD9 Codes mapped thereto - 390 - 459 785, 7943, 7892, V125, 79092.
- Drug classes mapped to this category are sclerosing agents and anticoagulants.
- HBP HBP - hypertension with ICD9 Codes 401 - 405, with drug classes of Beta Blockers, Calcium Channel Blockers, Antiarrhythimics, antihypertensives, diuretics, with sub-sub- MCCs EHBP - essential hypertension with ICD9 Codes 4011, 4019, and COMP - complicated hypertension with ICD9 Codes 4010, 402-405.
- MCC category #5 is BLD - blood and blood forming organs.
- This category has the following ICD9 Codes mapped thereto - 280 - 289, 7900-79009, V123.
- Drug classes mapped to this category are hematopoietic agents except EPO, GM-GSF) and Interleukins, Hemostatics, Platelet aggregation inhibitors, Hematorheological, Hemin, In vitro Hema agents, plasma expanders, plasma proteins, protamine, thrombolytic enzymes, hematologic 02 transporter assigned to the overall category.
- MCC category #6 is CAN - malignant neoplasms. This category has the following ICD9 Codes mapped thereto - 140 - 2089, 230 - 239, V10 - V109,V131, V581, V672. Drug classes mapped to this category are antineoplastics, erythropoeitins, GM-CSF, interleukins, immunosuppressive agents.
- One sub-MCCs is BRST - breast with ICD9 Codes 174 - 1759.
- Another sub-MCC is DIG - digestive and peritoneum with ICD9 Codes 150 -1599, with sub-sub-MCCs of UGI - upper gastrointestinal with ICD9 Codes 150-152, LGI - lower gastrointestinal with ICD9 codes 153-154, PBL - pancreas, liver with ICD9 Codes 155-157, and OTHR - other gastrointestinal with ICD9 Codes 158-159.
- Another sub-MCC is RES - respiratory with ICD9 Codes 160 - 165, with sub-sub-MCCs of UAIR - upper airway with ICD9 Codes 160-161, LAIR - lower airway with ICD9 Codes 162-163, and OTHR - other respiratory with ICD9 codes 164-165.
- Another sub-MCC is GU - genitourinary system with ICD9 Codes 179 - 1899, V131, with sub-sub-MCCs of FGEN - female genital with ICD9 Codes 179-184, V131, MGEN - male genital with ICD9 Codes 185-187, LGU - lower genito-urinary with ICD9 Code 188, and UGU - upper genitor-urinary with ICD9 Code 189.
- Additional sub-MCCs are LYMP - lymphatic and hematopoietic with ICD9
- Another sub-MCC is SKN - skin cancers with ICD9 Codes 173 - 1739, 172, with sub-sub-MCCs of MEL - malignant melanoma with ICD9 Code 172, and OTHR - other skin cancer with ICD9 Code 173.
- the remaining sub-MCCs are LEUK - leukemia with ICD9 Codes 2040, 2042 - 208 (excludes 2041) ; NER - nervous system with ICD9 Codes 191-192; END - endocrine system with ICD9
- MCC category #7 is BEN - benign neoplasms. This category has the following ICD9 Codes mapped thereto - 210 - 2299, V1241.
- MCC category #8 is DIA - diabetes.
- This category has the following ICD9 Codes mapped thereto - 250, 6480, (3572, 3371, 7135, 3540 - 3559, 3581), (3620) ' , (36641), (58381, 58181), (7854, 44381), 7902, 7915 - codes in parenthesis are secondary codes. These secondary codes are used in conjunction with a primary diagnosis; the primary diagnosis must be coded first as it is the underlying cause of the secondary illness. For example, nephropathy (kidney failure) is frequently a complication of diabetes, but it can also be caused by other diseases.
- ICD9 Codes mapped thereto - 250, 6480, (3572, 3371, 7135, 3540 - 3559, 3581), (3620) ' , (36641), (58381, 58181), (7854, 44381), 7902, 7915 - codes in parenthesis are secondary codes.
- diabetes would be coded primary (as it was the cause of nephropathy) and nephropathy would be coded as secondary.
- Drug classes mapped to DIA are antidiabetic agents, needles & syringes, diabetic supplies, wound care products, control reagents, Angiotensin Converting Enzyme Inhibitors (ACE) , ACE and thiazides,
- ICD9 Codes are mapped thereto - 27800, 27801.
- Drug classes mapped to OBE are nnorexiants, antiobesity agents. This category has no sub-MCCs or sub-sub-MCCs.
- MCC category #10 is END - endocrine.
- ICD9 Code/s 240- 279 7945, 7946, 7947, 7834-7839, 7994, V122, 7916, 70904, V150, V121, V691 are mapped to this category.
- MCC category #11 is GUS - genitourinary system.
- ICD9 Codes are mapped to this category - 580-629, 788, 7944, 7935, 7938, 7939, V130, 7910 - 7913, 7917 - 7919, 7922, 7950, 7951, V1329, V6701, 2564.
- Some of the sub-MCCs are KUB - kidneys, ureters, bladder with ICD9 codes 580-584, 587, 589-599, 7910 - 7913, 7917 - 7919, V130 and drug classes of Urinary anti-infectives, urinary antispasmodics, acidifiers, alkalinizers, urinary analgesics, cystinosis agents, interstitial cystits agents, urinary stone agents; GU irrigants, uroprotectant , GI_GU ostomy supplies; MALE - male genitourinary with ICD9 Codes 600 -608, 79093, 7922 and drug classes of androgen-anabolics, impotence agents, prostatic agents; and BRST - breast with ICD9 Codes 610-611.
- sub-MCC FEM - female with ICD9 Codes 614-629, 7950, 7951, V1329, V6701, 2564 and drug classes of estrogens, progestins, selective estrogen receptor modulators, fertility regulators, progesterone antagonists, menopausal sx suppressants, vaginal products, with sub-sub-MCC is as follows: PCOS - polycystic ovaries with drug class of oral antidiabetic agents.
- MCC category #12 is CKD - chronic kidney disease.
- This category has the following ICD9 Codes mapped thereto - 5811, 58181, 5819, 582, 75312, 75313, 75314, 75316, 75319, 40301, 40311, 40391, 40402, 40403, 40412, V56 , 7925 , 40413 , 40492 , 40493, 585, 586, 588.
- Drug classes mapped to this MCC are erythropoietin, potassium removing resin, peritoneal dialysis solutions, hemodiialytics, and peritoneal dialysis supplies. CKD has no sub-MCCs or sub-sub-MCCs.
- MCC category #13 is PRE - pregnancy.
- ICD9 Codes 630 - 677, 7923, V1321, V137, V22 - V24, V27-V28 are mapped to this category.
- MCC #8 All codes found in MCC #8 are excluded from this MCC and its sub-MCCs. There are no sub-sub-MCCs for this category.
- MCC category #14 is NEO - neonates .
- ICD9 Codes 760 - 779, V29 - V39 are mapped thereto.
- MCC Category #15 is ANO - congenital anomalies.
- ICD9 Codes 740 - 759, V136 are mapped thereto.
- the sub-MCCs are as follows: CF - cystic fibrosis with ICD9 Code 2770 and drug class of cystic fibrosis agents; HEM - hemophilia with
- MCC category #17 is TRA - transplant.
- ICD9 Codes V420- V421, N426 , N427 , N428 - V4299, 9968 and drug class of immunosuppressants are mapped to this category.
- MCC category #18 is CER - cerebrovascular .
- the following ICD9 Codes are mapped thereto - 430 - 432, 433 - 434, 78002, 435, 438.
- the sub-MCCs are as follows: HEM - hemorrhage with ICD9 Codes 430 - 432; OCC - occlusions with
- ICD9 Codes 433 - 434 and drug class of coumarin agents TIA - transient ischemic attach with ICD9 Codes 78002, 435 and drug class of coumarin agents; and SEQ - late effects or sequelae of cerebrovascular accident with ICD9 Code 438.
- This category has no sub-sub-MCCs.
- MCC category #19 is ⁇ ER - nervous system. This MCC has the following ICD9 Codes mapped thereto - 320 - 359, 7810- 7814, 7816-7818, 78199, 7843, 7840, 7940, 79410, 79417, 79419, 7844-7846, 7920, V1240, V1249.
- ICD9 Codes 360 - 389, 79411 - 79416, 78193 are mapped to this MCC.
- the other sub- MCC for this category is EAR - ear with ICD9 Codes 380 - 389, 79415 -79416 with drug class of otic agents, with sub-sub- MCCs of XEAR - external ear with ICD9 Codes 380, MEAR - middle ear with ICD9 Codes 381 - 385, OTHR - other ear with ICD9 Code 388.
- MCC category #21 is TRM - trauma.
- ICD9 Codes 800 - 8049, 805 - 8069, 952 - 9529, 851 - 8541, 925 - 9252, 344- 3449, 808-8089, 820, 8181 - 819, 828 - 8281 are mapped thereto.
- the sub-MCCs are as follows: SKUL - skull fractures with ICD9 Codes 800 - 8049; SPFX - spinal cord fracture with ICD9 Codes 805 - 8069; SPNJ - spinal cord injury with ICD9 Codes 952 - 9529; BRN - brain laceration or contusion with ICD9 Codes 851 - 8541; F/N - crushing injury face/neck/scalp with ICD9 Codes 925 - 9252; PRLY - paralysis with ICD9 Codes 344-3449; HIP - hip/pelvis/neck of femur fractures with ICD9 Codes 808-8089, 820; FXU - multiple fracture upper limbs with ICD9 Codes 8181 - 819; FXUL - multiple fractures lower and/or upper limbs with ICD9 Codes 828 - 8281.
- MCC category #22 is MUS - musculo-skeletal and connective tissue.
- ICD9 Code/s 710 - 739, 7930, 7937, V134, V135, V674, 7815, 78191, 78192, 7842 are mapped thereto.
- Drug classes mapped to the overall category are analgesics, narcotic and non-narcotics, anti-inflammatory agents, neuromuscular agents, depolarizing and non-depolarizing muscle relaxants, musculoskeletal therapy agents.
- the sub- MCCs are as follows: OSTE - osteoporosis with ICD9 Code 7330; ARTH - arthritis (excludes rheumatoid arthritis) with ICD9 Codes 712, 713, 715, 720, 721, V134; BACK - back/neck pain with ICD9 Codes 722 - 724, 846, 847; ATRP - arthropathies with ICD9 Codes 712, 713, 715, 720, 721, V134; INF - infections with ICD9 Codes 711, 730; JNT - joint specific disorder with ICD9 Codes 717-719; SOFT - soft tissue disorders with ICD9 Codes 725-729; FORM - malformations with ICD9 Codes 7
- ICD9 Codes 001 - 1398, 7901, 7907, 7908, 7953-7956, V01-V02, V07,V09, V120, V1585 are mapped thereto.
- Drug class mapped to the MCC is anti-infective agents.
- MCC category #25 is RES - respiratory. ICD9 Codes 460 - 519, 786 (exclude 7865), 7942, 7931, 7932, V461, 7847 - 7849, 7841, 79091, 7991, 7990, V126, V1584 are mapped thereto.
- MCC category # 26 is DIG - digestive. ICD9 Codes 520 - 579, 787, 7933, 7934, 7891, 7895, 7948, 7905, V127, 7924, 7921, 04186, 7914 and drug class of ostomy supplies are mapped thereto.
- a sub-MCCs is: UGI - upper gastrointestinal with ICD9 Codes 520 - 537, 5301, 04186, 7924, with sub-sub-MCCs of PUD - peptic ulcer disease/gastro-esophageal reflux disease with ICD9 Codes 520 - 537, 5301, 04186, 7924 and drug class of antacids, ulcer drugs, prostaglandins, MOU - mouth with ICD9 Codes 520-529, 7924 and drug class of local mouth and throat agents, ESO - esophagus with ICD9 Codes 5300, 5303-5307, 53083-5309, and STOM - stomach with ICD9 Codes 536-537 and drug class of antiemitics, digestive aids.
- LGI - lower gastro-intestinal with ICD9 Codes 540-569, 7921 and drug class of anorectal agents, laxatives, antidiarrheals, antiflatulent combos, gi stimulants, intestinal acidifiersrs irritable bowel agents, (IBS) agents; P/B - pancreas/biliary with ICD9 Codes 574-577, 7914 with drug class of gallstone agents; LIV - liver with ICD9 Codes 570 - 573 and drug class of hepatropic agents; and OTHR sum of MCC - sub-MCC with drug class of miscellaneous GI , phosphate binders .
- MCC category #27 is SKN - skin and subcutaneous tissue.
- ICD9 Codes 680- 709, 700-709, 7820-7822, 7827-7829, V133, V820 are mapped thereto.
- MCC 16 All codes found within MCC 16 are excluded from this MCC and its sub-MCCs. There are no sub- sub-MCCs for this category. MCC category #28 is INJ - Injury and poisoning. ICD9 Codes 800 - 999, E800 - E807, E820 - E888, E900 - E929, E950- E999, V155-V156, V1586, V14 are mapped thereto.
- MCC category #30 is MVA - motor vehicle accident. ICD9 Codes E810 - E819 are mapped thereto. This category has no sub-MCCs or sub-sub-MCCs.
- MCC category #31 is MEN - mental/behavioral disorders.
- MCC category #32 is SNS - signs and symptoms with ICD9 Codes 780-799.
- MCC category #33 is VCO - V-codes with ICD9 Codes V01 - V83 with drug classes of vaccines and toxoids .
- One sub-MCC is EXAM - examination and screening with ICD9 Codes V70 - V83, with sub-sub-MCCs of CAD - screening for ischemic heart disease with ICD9 Codes V810, V7791, HDZ - screening for other heart disease with ICD9 Code V812, BLD - screening for blood disorders with ICD9 Codes V780-781, V783-V789; CAN - screening for cancer with ICD9 Code V76, DIA - screening for diabetes with ICD9 Code V771, OBE - screening for obesity with ICD9 Code V778, END - screening for endocrine disorders with ICD9 Codes V770, V773-V775, V777, V772, V7799, GUS - screening genitourinary with ICD9 Codes V815, V157, V723, V816, V25-26, V724, ANO - screening for anomalies with ICD9 Codes V823-824, RAR - screening for rare diseases with I
- MCC category # 34 is CHR - chronic MCCs. This category includes items in prior detailed MCC categories or sub-MCCs that are considered chronic or long term.
- MCCs are listed first, followed by sub-MCCs; all acronyms have been previously detailed.
- POT place of treatment
- eleven POT categories are used. These POT categories are HI - hospital inpatient, 01 - other facility inpatient, HS - hospital outpatient surgery, HE - hospital emergency, HO - hospital outpatient other, 00 - other facility outpatient other, PI - physician service inpatient, PO - physician service outpatient, PP - physician service office visit, PX - physician service all other, and
- OP - other providers OP - other providers .
- the following example will explain the system as could be used by a healthcare insurance company with its various health plans.
- members of the various plans who will have provided member information and have been assigned a unique member identifier ("member ID") . These members may be enrolled for medical care, for prescription services, or both.
- member ID a unique member identifier
- advance authorization may be required.
- Some of the member data, authorization data, pharmacy data, and medical claim data is submitted electronically and some is submitted by other means, such as, for example, by the submission on paper of a claim seeking reimbursement. However, all of the relevant data, whether submitted electronically or not, is established in an electronic database.
- This database will generally contain more information than is needed for displaying the information used in the prediction system of the present invention. While other data relationships are possible to accomplish the same result, the system of the present invention extracts the desired data from the database and converts it so that it is included in four relational database tables, pharmacy claims, medical claims, authorizations, and membership, all related by member ID. For example, in the preferred embodiment, it is desired to display medical and pharmacy claim information and place of treatment information over time for each individual. It is also desired in the preferred embodiment to display similar information by groups of members, for example, for all members of one PPO, or for all members in a geographic area. It is also desirable in the preferred embodiment to be able to compare similar information for different member groupings.
- the membership database table will include at least the unique member ID, the PPO identifier, and the geographic area identifier or identifiers, for example, city, state, and zip code. If other comparison is desired, that additional needed information can be extracted from the electronic database and included in the appropriate relational database table. As it is preferred to display medical, pharmacy, and place of treatment information over time and based on cost, the information relevant to map medical claim and pharmacy claim costs to MCC and to map where treatment was received to POT is extracted and included in the appropriate relational database table. Using the data in the relational database tables, a transformation algorithm converts the ICD9 codes in the medical claims to MCC, Sub-MCC, and Sub-sub-MCC and associates time and cost information with each claim.
- a transformation algorithm converts the pharmacy claim information by drug class to MCC, Sub-MCC, and Sub-sub-MCC and associates time and cost information with each claim. Where there is a corresponding medical claim, and multiple possible MCCs for a drug class, the pharmacy claim is associated with the medical claim in the same MCC. Where there is no corresponding medical claim and where there are multiple possible MCCs for the drug class, the cost is equally divided among the possible drug classes. Further, a transformation algorithm converts the medical claim claimant information to one of the eleven place of treatment categories and associates time, utilization, and amount information with each claim. For display of the information, cost amount over time is important. For a color display of cost amount, a "hot to cold" color scheme can be employed for each cost event.
- Figure 1 is a sample information display for one unique individual. Item 1 identifies the member ID, for example, in this case, 123678903. Any unique identifier can be used. Item 2 is a mapping over a time period (January 2001 - February 2003) of the medical claim costs by MCC, Sub-MCC, and Sub-sub-MCC using the primary ICD9 diagnosis code associated with the medical claim.
- the costs are displayed at the MCC level only, but the display user can expand the display to include the Sub-MCC and Sub-sub-MCC information by clicking on the MCC category the user wishes to expand.
- item 2 has had MCC category #6 CAN (Malignant Neoplasm) expanded to show the thirteen secondary or sub- MCCs, namely BRST (Breast) , DIG (Digestive & Peritoneum) , RES (Respiratory) , GU (Genitourinary Organs) , LYMP (Lymph & Hema) , SEC (Secondary) , H&N (Head & Neck) , SKN (Skin Cancer) , LEUK (Leukemia) , NER (Nervous System) , END (Endocrine) , H/O (V Codes) and OTHR (All Other) .
- MCC category #6 CAN Malignant Neoplasm
- DIG has four tertiary MCCs - UGI (Upper Gastrointestinal) , LGI (Lower Gl) , PBL (Pancreas/Bile ducts/Liver) and OTHR (Other) .
- RES has three tertiary MCCs - UAIR (Upper Airway) , LAIR (Lower Airway) and OTHR (Other) .
- GU has 4 tertiary MCCs - FGEN (Female Genital) , MGEN (Male Genital) , LGU (Lower Urinary) and UGU (Upper Urinary) .
- SKN has two tertiary MCCs - MEL (Melanoma) and OTHR (Other) .
- the main or primary MCC categories are shown down the left side of the display as three letters without a dash in front of them, for example, item 10 is CAN.
- the Sub-MCCs are displayed with a "_" before the letters representing the Sub- MCC, for example, item 11 is _DIG.
- the Sub-sub-MCCs are displayed with a " " " " before the letters representing the
- Sub-sub-MCC for example, item 12 is LGI.
- member 123678903 has medical claims related to the sixth primary MCC CAN (Malignant Neoplasm) . More specifically, these claims are classified under the secondary or sub-MCC DIG (Digestive &
- Peritoneum Peritoneum
- tertiary or sub-sub-MCC UGI Upper Gl
- Item 13 identifies a darker black mark than the lighter gray item 14. This identifies that the cost associated with medical claim item 13 was greater than the cost associated with medical claim item 14.
- Item 3 is a mapping over a time period (January 2001 - February 2003) of the medical claim costs by MCC, Sub-MCC, and Sub-sub-MCC using the secondary ICD9 diagnosis code associated with the medical claim.
- the costs are displayed at the MCC level only, but the display user can expand the display to include the Sub-MCC and Sub-sub-MCC information by clicking on the MCC category the user wishes to expand and selecting one of the context menus .
- item 3 has had MCC category #22 MUS (Musculoskeletal and Connective Tissues) expanded to show nine secondary or Sub-MCC categories. There are no Sub-sub- MCCs under MCC #22 MUS.
- this member under the primary MCC MUS, this member has claims more particularly associated with the secondary or Sub-MCCs BACK (Back/Neck pain) and SOFT (Soft Tissue Disorders) .
- Item 4 is a mapping over a time period (January 2001 - February 2003) of the pharmacy claim costs by MCC, Sub-MCC, and Sub-sub-MCC using the drug class associated with the pharmacy claim. Again, as with items 2 and 3, in the initial display of the preferred embodiment, the costs are displayed at the MCC level only, but the user can expand the display to include the Sub-MCC and Sub-sub-MCC information by clicking on the MCC category the user wishes to expand. As shown, item 4 has MCC category #4 CIR (Other
- this member has pharmacy claims that are especially related to Hypertension (secondary MCC HBP or high blood pressure) .
- Item 5 is a mapping over a time period (January 2001 - February 2003) of the place of treatment (POT) utilization profile and item 6 is a mapping over the same time period of the place of treatment paid cost profile, using the eleven POT categories previously explained. As shown, this member has a lot of procedures done in an outpatient setting. These individual displays have many uses. For example, an individual member may want to have a copy when going to a doctor. Also, members may be enrolled in clinical programs or other services which assist the members in managing their healthcare.
- Figure 1 This is a display over time of the primary ICD9 information mapped to the MCC categories, but showing cumulative information for all members of group 20. Again, the darker the shade of gray, the more the cost.
- Item 31 parallels item 30 and shows the total amount for group 20 per MCC over the total time period reflected in item 30.
- Item 32 reflects the total amount over all MCCs for group 20 over the same time period.
- items 33, 34, and 35 form a related display group. These items show pharmacy claim information for group 20.
- the item 33 display is similar to the item 4 display in Figure 1. This is a display over time of the pharmacy claim information mapped to the MCC categories, but showing cumulative information for all members of group 20.
- Item 34 parallels item 33 and shows the total amount for group 20 per MCC over the total time period reflected in item 33.
- Item 35 reflects the total amount over all MCCs for group 20 over the same time period.
- Items 36, 37, and 38 relate to types of services (TOS) received by group 20.
- the TOS codes shown, HI, 01, HS, HE, HO, 00, PI, PO, PP, PX, and OP are the same as the POT codes previously explained.
- Item 36 shows the number of encounters over time for group 20 by TOS code.
- Item 37 shows total encounters for group 20 per TOS code for the time period of item 36.
- Item 38 shows the total encounters for group 20 for all of the TOS codes combined over the same time period as in item 36.
- Items 39, 40, and 41 are similar to items 36, 37, and 38, as they also show TOS information over time for group 20. However, instead of showing information based on encounters, they reflect cost paid information. Additional group displays and comparisons are desired in advanced embodiments.
- Figure 3 shows group- level rolled-up data for medical, pharmacy, and place-of- treatment (POT) or type-of-service (TOS) data for two different selected groups 20 and 21 for comparison. As with Figure 2 , the data shown in Figure 3 covers the period February 2001 - January 2004.
- Items 50, 51, and 52 show medical claim information for group 20 and 21.
- Item 50 display is similar to the item 30 display in Figure 2.
- the group 20 information shown in item 30 of Figure 2 has been compressed for the display of Figure 3 so that the data for group 20 can be shown adjacent to the data for group 21 for side by side comparison of the information displayed. Again, the darker the shade of gray, the more the cost.
- Item 51 parallels item 50 and shows the total amount per group 20 and group 21 per MCC over the total time period reflected in item 50.
- Item 52 reflects the total amount over all MCCs for each of group 20 and group 21 over the same time period.
- TOS types of services
- Item 56 shows the number of encounters over time for each of groups 20 and 21 by TOS code.
- Item 57 shows total encounters by group per TOS code for the time period of item 56.
- Item 58 shows the total encounters by group for all of the TOS codes combined over the same time period as in item 56.
- Items 59, 60, and 61 are similar to items 56, 57, and 58, as they also show TOS information over time for each of groups 20 and 21. However, instead of showing information based on encounters, they reflect cost paid information.
- Figure 4A is a flow chart of member map data generation.
- Figure 4B is a flow chart showing how the data generated in Figure 4A is used to create the various member and group displays.
- EDW Enterprise Data Warehouse
- the boxes in Figures 4A-4B have numbers in parenthesis, which are referred to in the below description.
- Box (1) With reference to Figure 4A, EDW is the Enterprise Data Warehouse where the medical, pharmacy, and member information is retained, for example, by an insurance company having members and processing medical and pharmacy claims .
- Box (2) From the Enterprise Data Warehouse (EDW) , we fetch the most recent one-year membership and pharmacy and medical claims data for each active member at the end of each month. This process is repeated monthly.
- Box (3) The raw relational database records are converted into all-numeric binary files for fast retrieval by computational engines.
- the string variables, such as ICD9 and other alphanumeric codes are also converted into numeric codes with each numeric code representing unique alphanumeric code in the code look-up table.
- Matlab (MATrix Laboratory) is a high-level object-oriented, scientific programming language produced by the Mathworks in Natick, MA. It has a number of built-in graphical visualization and scientific algorithms that facilitate rapid transition from concept formulation to prototyping. It also has real-time code generation capabilities that allow Matlab programs to be converted into embeddable and standalone applications through the use of C/C++ and Java compilers working in concert with Windows/Unix components.
- the embedded applications can be generated in Windows Common Object Model (COM) module or Dynamic Linked Library (DLL) that can be called from external programs written in Visual Basic (VB) , C/C++, or Java.
- Matlab format is simply the way Matlab stores data in binary format, so Matlab can efficiently fetch data.
- Box (4) This box represents the data files in binary and Matlab format, and ICD9 LUT.
- Box (5) Retrieve just the required fields from the binary claims data for speed and memory.
- PGK person gen key, a unique identification assigned to each member.
- Box (6) Here we map the ICD9 codes to MCCs and associate with service dates and cost to create medical MCC time series data.
- Box (8) Here, we write the member id, medical MCC and TOS data to data file.
- the TOS and MCC maps are written to a set of binary and matlab files for both storage efficiency and fast retrieval of member-specific maps later.
- Box (9) This box represents the data file in binary and Matlab format for medical MCC and TOS.
- Box (10) Each Rx prescription is mapped to an appropriate MCC. If there is one-to-many mapping for drugs that can be prescribed to treat multiple MCC conditions, we refer to the medical MCC-time map for the member. We compare all the possible Rx MCCs with the appropriate medical MCCs. If there is only one medical MCC present, then we assign the entire Rx cost to that MCC.
- Box (14) represents the data files in binary and Matlab format which are refreshed monthly.
- the Visual Basic (VB) program [Box (17) ] gets the input of the member id [Box (16)] from the user [Box (15)] and passes it to the Matlab COM [Box (18)], the Matlab COM generates an output portable network graphics or png file [Box (20)] .
- the VB program then displays the image stored in the output file [Box (21)]. Inserting item numbers from Figures 1-3 as examples only, the present invention is for a method for automated extraction and display of past health care use data to aid in predicting future health status, comprising the steps of: a. accessing a database containing insurance claim information; b.
- the step of mapping the insurance claim information can further include mapping by individual and claim to at least one of a set of place of treatment identifiers to create a plurality of POT claim mappings; the step of associating each MCC claim mapping with an individual identifier, a time identifier, and a cost identifier, can further include associating each MCC claim mapping to each POT claim mapping; and, the step of creating at least one • display can further include creating an additional display (6, 39, 59) showing by each of the place of treatment identifiers over said time period a representation of the POT claim mappings, each POT claim mapping weighted by its respective cost identifier.
- the step of creating at least one display can further include creating an additional display (5, 36, 56) showing by each of said place of treatment identifiers over said time period a representation of the POT claim mappings, each POT claim mapping weighted by a utilization identifier.
- the step of mapping can include mapping primary diagnosis codes, secondary diagnosis codes, and/or pharmacy information contained in the insurance claim information to the set of major clinical conditions.
- the display created can be a color display where different colors are used to identify different cost identifiers or a shades of gray display where different shades of gray are used to identify different cost identifiers .
- the major clinical conditions may include hierarchical code levels, or sub or sub-sub levels, with mapping to the hierarchical code levels, where the step of creating at least one display includes providing the capability to expand the display to additionally show the MCC claim mappings by each of the set of major clinical conditions (10) and by any hierarchical code levels (11, 12) .
- the step of creating at least one display can create the display (2, 3, 4 of Figure 1) for an individual (1), the display (30, 33 of Figure 2) for a single group (20), or the display (50, 53 of Figure 3) for multiple groups (20, 21) .
- the present invention is for a method for automated extraction of past health care use data to aid in predicting future health status, comprising the steps of: a.
Abstract
Description
Claims
Priority Applications (4)
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EP05740293A EP1782345A2 (en) | 2004-04-27 | 2005-04-26 | System and method for automated extraction and display of past health care use to aid in predicting future health status |
JP2007510903A JP2007535078A (en) | 2004-04-27 | 2005-04-26 | Systems and methods for automated extraction and display of past medical receipts to help predict future health conditions |
AU2005237562A AU2005237562A1 (en) | 2004-04-27 | 2005-04-26 | Method for extracting and displaying healthcare history |
KR1020067024812A KR20070033340A (en) | 2004-04-27 | 2005-04-26 | Methods and systems for automated extraction and display of past healthcare uses to help predict future health conditions |
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US10/832,915 US7676379B2 (en) | 2004-04-27 | 2004-04-27 | System and method for automated extraction and display of past health care use to aid in predicting future health status |
US10/832,915 | 2004-04-27 |
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Families Citing this family (35)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7895062B2 (en) | 2001-12-31 | 2011-02-22 | Genworth Financial, Inc. | System for optimization of insurance underwriting suitable for use by an automated system |
US8005693B2 (en) | 2001-12-31 | 2011-08-23 | Genworth Financial, Inc. | Process for determining a confidence factor for insurance underwriting suitable for use by an automated system |
US7844477B2 (en) | 2001-12-31 | 2010-11-30 | Genworth Financial, Inc. | Process for rule-based insurance underwriting suitable for use by an automated system |
US7844476B2 (en) | 2001-12-31 | 2010-11-30 | Genworth Financial, Inc. | Process for case-based insurance underwriting suitable for use by an automated system |
US8793146B2 (en) | 2001-12-31 | 2014-07-29 | Genworth Holdings, Inc. | System for rule-based insurance underwriting suitable for use by an automated system |
US7818186B2 (en) | 2001-12-31 | 2010-10-19 | Genworth Financial, Inc. | System for determining a confidence factor for insurance underwriting suitable for use by an automated system |
US7899688B2 (en) | 2001-12-31 | 2011-03-01 | Genworth Financial, Inc. | Process for optimization of insurance underwriting suitable for use by an automated system |
US7383239B2 (en) | 2003-04-30 | 2008-06-03 | Genworth Financial, Inc. | System and process for a fusion classification for insurance underwriting suitable for use by an automated system |
US7801748B2 (en) | 2003-04-30 | 2010-09-21 | Genworth Financial, Inc. | System and process for detecting outliers for insurance underwriting suitable for use by an automated system |
US7813945B2 (en) | 2003-04-30 | 2010-10-12 | Genworth Financial, Inc. | System and process for multivariate adaptive regression splines classification for insurance underwriting suitable for use by an automated system |
US7698159B2 (en) | 2004-02-13 | 2010-04-13 | Genworth Financial Inc. | Systems and methods for performing data collection |
US10248951B2 (en) | 2004-12-01 | 2019-04-02 | Metavante Corporation | E-coupon settlement and clearing process |
US20060252600A1 (en) * | 2004-12-22 | 2006-11-09 | Grogan Troy J | System and method for integrated health promotion, injury prevention, and management |
US20070239492A1 (en) * | 2006-04-10 | 2007-10-11 | Sweetland Christopher L | Estimating benefit plan costs |
US7739129B2 (en) * | 2006-04-10 | 2010-06-15 | Accenture Global Services Gmbh | Benefit plan intermediary |
US20080016023A1 (en) * | 2006-07-17 | 2008-01-17 | The Mathworks, Inc. | Storing and loading data in an array-based computing environment |
US7801749B2 (en) * | 2007-06-07 | 2010-09-21 | Ingenix, Inc. | System and method for grouping claim records associated with a procedure |
US8682696B1 (en) * | 2007-11-30 | 2014-03-25 | Intuit Inc. | Healthcare claims navigator |
US20090228301A1 (en) * | 2008-01-28 | 2009-09-10 | Youngblood Ernest T | Insurance plan design, reporting and analysis of healthcare data using global filters |
US11562323B2 (en) * | 2009-10-01 | 2023-01-24 | DecisionQ Corporation | Application of bayesian networks to patient screening and treatment |
US20110079451A1 (en) * | 2009-10-01 | 2011-04-07 | Caterpillar, Inc. | Strength Track Bushing |
US20130246097A1 (en) * | 2010-03-17 | 2013-09-19 | Howard M. Kenney | Medical Information Systems and Medical Data Processing Methods |
ITRM20120018U1 (en) * | 2012-02-06 | 2013-08-07 | Alessio Biancheri | IT SYSTEM FOR THE MEMORIZATION, PROCESSING AND CONSULTATION ON REQUEST OF CLINICAL AND ANAMNESTIC INFORMATION |
US20160358290A1 (en) * | 2012-04-20 | 2016-12-08 | Humana Inc. | Health severity score predictive model |
US20140081659A1 (en) | 2012-09-17 | 2014-03-20 | Depuy Orthopaedics, Inc. | Systems and methods for surgical and interventional planning, support, post-operative follow-up, and functional recovery tracking |
US20160357929A1 (en) * | 2012-11-21 | 2016-12-08 | Humana Inc. | System for drug interaction alerts |
US10650116B2 (en) | 2013-04-25 | 2020-05-12 | Aver Informatics Inc. | User-definable episodes of activity and graphical user interface for creating the same |
US9282008B2 (en) * | 2013-06-11 | 2016-03-08 | General Electric Company | Systems and methods for monitoring system performance and availability |
CN103513991B (en) * | 2013-10-17 | 2017-04-12 | 杭州安恒信息技术有限公司 | Method for establishing bi-directional mapping among sequences under condition of difference limitation |
US10349918B2 (en) | 2015-12-22 | 2019-07-16 | Samsung Medison Co., Ltd. | Method and apparatus for displaying ultrasound images |
KR101869438B1 (en) * | 2016-11-22 | 2018-06-20 | 네이버 주식회사 | Method and system for predicting prognosis from diagnostic histories using deep learning |
AU2018313853A1 (en) | 2017-08-08 | 2020-01-02 | Fresenius Medical Care Holdings, Inc. | Systems and methods for treating and estimating progression of chronic kidney disease |
KR102216689B1 (en) * | 2018-11-23 | 2021-02-17 | 네이버 주식회사 | Method and system for visualizing classification result of deep neural network for prediction of disease prognosis through time series medical data |
CN111105316B (en) * | 2019-11-13 | 2023-06-09 | 泰康保险集团股份有限公司 | Data processing method and device for long-term care insurance, medium and electronic equipment |
US20210407629A1 (en) * | 2020-06-24 | 2021-12-30 | F. Hoffmann-La Roche Ltd. | Compromised-system assessments based on key translation |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020026332A1 (en) * | 1999-12-06 | 2002-02-28 | Snowden Guy B. | System and method for automated creation of patient controlled records |
US6453297B1 (en) * | 1993-11-02 | 2002-09-17 | Athena Of North America, Inc. | Medical transaction system |
US20020161609A1 (en) * | 2000-10-23 | 2002-10-31 | Zizzamia Frank M. | Commercial insurance scoring system and method |
US20030120515A1 (en) * | 2001-11-05 | 2003-06-26 | Jacob Geller | Method and system for managing health |
US6915265B1 (en) * | 1997-10-29 | 2005-07-05 | Janice Johnson | Method and system for consolidating and distributing information |
Family Cites Families (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5018067A (en) * | 1987-01-12 | 1991-05-21 | Iameter Incorporated | Apparatus and method for improved estimation of health resource consumption through use of diagnostic and/or procedure grouping and severity of illness indicators |
US5253164A (en) * | 1988-09-30 | 1993-10-12 | Hpr, Inc. | System and method for detecting fraudulent medical claims via examination of service codes |
US5324077A (en) * | 1990-12-07 | 1994-06-28 | Kessler Woodrow B | Medical data draft for tracking and evaluating medical treatment |
US5225976A (en) * | 1991-03-12 | 1993-07-06 | Research Enterprises, Inc. | Automated health benefit processing system |
US5301105A (en) * | 1991-04-08 | 1994-04-05 | Desmond D. Cummings | All care health management system |
US5307262A (en) * | 1992-01-29 | 1994-04-26 | Applied Medical Data, Inc. | Patient data quality review method and system |
US5835897C1 (en) * | 1995-06-22 | 2002-02-19 | Symmetry Health Data Systems | Computer-implemented method for profiling medical claims |
US5970463A (en) * | 1996-05-01 | 1999-10-19 | Practice Patterns Science, Inc. | Medical claims integration and data analysis system |
US6059724A (en) * | 1997-02-14 | 2000-05-09 | Biosignal, Inc. | System for predicting future health |
US6110109A (en) * | 1999-03-26 | 2000-08-29 | Biosignia, Inc. | System and method for predicting disease onset |
US20020116387A1 (en) * | 2001-02-05 | 2002-08-22 | Azadeh Farahmand | Translation devices, methods and software for moving information between a database file, and a source or destination file |
JP3563394B2 (en) * | 2002-03-26 | 2004-09-08 | 株式会社日立製作所 | Screen display system |
-
2004
- 2004-04-27 US US10/832,915 patent/US7676379B2/en active Active
-
2005
- 2005-04-26 JP JP2007510903A patent/JP2007535078A/en not_active Withdrawn
- 2005-04-26 WO PCT/US2005/014350 patent/WO2005104733A2/en active Application Filing
- 2005-04-26 EP EP05740293A patent/EP1782345A2/en not_active Withdrawn
- 2005-04-26 AU AU2005237562A patent/AU2005237562A1/en not_active Abandoned
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- 2005-04-26 KR KR1020067024812A patent/KR20070033340A/en not_active Application Discontinuation
-
2006
- 2006-11-23 ZA ZA200609781A patent/ZA200609781B/en unknown
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6453297B1 (en) * | 1993-11-02 | 2002-09-17 | Athena Of North America, Inc. | Medical transaction system |
US6915265B1 (en) * | 1997-10-29 | 2005-07-05 | Janice Johnson | Method and system for consolidating and distributing information |
US20020026332A1 (en) * | 1999-12-06 | 2002-02-28 | Snowden Guy B. | System and method for automated creation of patient controlled records |
US20020161609A1 (en) * | 2000-10-23 | 2002-10-31 | Zizzamia Frank M. | Commercial insurance scoring system and method |
US20030120515A1 (en) * | 2001-11-05 | 2003-06-26 | Jacob Geller | Method and system for managing health |
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US7676379B2 (en) | 2010-03-09 |
CN101076817A (en) | 2007-11-21 |
JP2007535078A (en) | 2007-11-29 |
ZA200609781B (en) | 2007-11-28 |
KR20070033340A (en) | 2007-03-26 |
WO2005104733A3 (en) | 2007-03-29 |
AU2005237562A1 (en) | 2005-11-10 |
US20050240447A1 (en) | 2005-10-27 |
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