CN111986038A - Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease - Google Patents
Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease Download PDFInfo
- Publication number
- CN111986038A CN111986038A CN202010900114.7A CN202010900114A CN111986038A CN 111986038 A CN111986038 A CN 111986038A CN 202010900114 A CN202010900114 A CN 202010900114A CN 111986038 A CN111986038 A CN 111986038A
- Authority
- CN
- China
- Prior art keywords
- information
- sample
- diagnosis
- formula
- auditing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003745 diagnosis Methods 0.000 title claims abstract description 123
- 201000010099 disease Diseases 0.000 title claims abstract description 55
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000006399 behavior Effects 0.000 title claims abstract description 37
- 239000003814 drug Substances 0.000 claims abstract description 108
- 238000012550 audit Methods 0.000 claims abstract description 71
- 238000004364 calculation method Methods 0.000 claims abstract description 31
- 229940079593 drug Drugs 0.000 claims description 46
- 238000013507 mapping Methods 0.000 claims description 25
- 238000000605 extraction Methods 0.000 claims description 19
- 238000004590 computer program Methods 0.000 claims description 13
- 239000000463 material Substances 0.000 claims description 11
- 230000002457 bidirectional effect Effects 0.000 claims description 8
- 238000003062 neural network model Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 238000012549 training Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 238000012795 verification Methods 0.000 claims description 4
- 230000009471 action Effects 0.000 claims description 3
- 238000001356 surgical procedure Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 10
- 239000013598 vector Substances 0.000 description 10
- KVUAALJSMIVURS-ZEDZUCNESA-L calcium folinate Chemical compound [Ca+2].C1NC=2NC(N)=NC(=O)C=2N(C=O)C1CNC1=CC=C(C(=O)N[C@@H](CCC([O-])=O)C([O-])=O)C=C1 KVUAALJSMIVURS-ZEDZUCNESA-L 0.000 description 8
- 235000008207 calcium folinate Nutrition 0.000 description 8
- 239000011687 calcium folinate Substances 0.000 description 8
- 238000007726 management method Methods 0.000 description 8
- DWAFYCQODLXJNR-BNTLRKBRSA-L oxaliplatin Chemical compound O1C(=O)C(=O)O[Pt]11N[C@@H]2CCCC[C@H]2N1 DWAFYCQODLXJNR-BNTLRKBRSA-L 0.000 description 7
- 229960001756 oxaliplatin Drugs 0.000 description 7
- GHASVSINZRGABV-UHFFFAOYSA-N Fluorouracil Chemical compound FC1=CNC(=O)NC1=O GHASVSINZRGABV-UHFFFAOYSA-N 0.000 description 6
- 229960002949 fluorouracil Drugs 0.000 description 6
- 238000012552 review Methods 0.000 description 6
- 206010009944 Colon cancer Diseases 0.000 description 5
- 208000001333 Colorectal Neoplasms Diseases 0.000 description 5
- 238000013528 artificial neural network Methods 0.000 description 5
- IWEDIXLBFLAXBO-UHFFFAOYSA-N dicamba Chemical compound COC1=C(Cl)C=CC(Cl)=C1C(O)=O IWEDIXLBFLAXBO-UHFFFAOYSA-N 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000014509 gene expression Effects 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 241000894007 species Species 0.000 description 4
- 230000006978 adaptation Effects 0.000 description 3
- 125000004122 cyclic group Chemical group 0.000 description 3
- 230000003444 anaesthetic effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 208000035474 group of disease Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000002547 new drug Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 208000002177 Cataract Diseases 0.000 description 1
- 208000025174 PANDAS Diseases 0.000 description 1
- 208000021155 Paediatric autoimmune neuropsychiatric disorders associated with streptococcal infection Diseases 0.000 description 1
- 240000000220 Panda oleosa Species 0.000 description 1
- 235000016496 Panda oleosa Nutrition 0.000 description 1
- 108010001267 Protein Subunits Proteins 0.000 description 1
- 238000009098 adjuvant therapy Methods 0.000 description 1
- 230000002924 anti-infective effect Effects 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000000586 desensitisation Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000857 drug effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000003862 health status Effects 0.000 description 1
- 238000002513 implantation Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 238000012954 risk control Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 229940126680 traditional chinese medicines Drugs 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 210000004127 vitreous body Anatomy 0.000 description 1
- 229940126673 western medicines Drugs 0.000 description 1
Images
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
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Abstract
The application relates to the field of digital medical treatment, is applied to wisdom medical treatment, provides a method, device, equipment and storage medium of examining and verifying of behavior is diagnose to single disease kind, the method includes: generating an audit formula group and acquiring medical record information; the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information; determining an auditing formula set according to the diagnosis information; wherein the audit formula set at least comprises an audit formula; judging whether the variable of each audit formula exists or not; determining the value of each variable according to the existence condition; and inputting the values of the auditing formula and the variables into an automator engine for calculation, and outputting an auditing result. By the method, the device, the equipment and the storage medium for examining and verifying the diagnosis and treatment behaviors of the single disease, the examination and the treatment behaviors of the single disease can be automatically and accurately carried out, and unreasonable diagnosis and treatment behaviors are prevented.
Description
Technical Field
The application relates to the technical field of digital medical treatment, in particular to a method, a device, equipment and a storage medium for auditing diagnosis and treatment behaviors of single disease.
Background
In the field of medical insurance payment, single-disease payment refers to paying per-disease medical expenses for partial diseases. The single disease charge is one of the medical insurance charge payment modes, and is divided into a medical insurance fund payment amount and a participator self-payment amount, and the participator needs to pay the self-payment amount and the medical service charge which is not listed in the disease charge self-payment amount according to the regulation when the participator is discharged; the medical insurance fund can be used for payment, and the settlement is declared to the medical insurance agency after the fixed-point hospital accounts. The payment is made in accordance with the specified payment amount regardless of whether the actual cost is higher or lower than the specified payment amount. However, in the payment process of a single disease category, in order to save cost and improve profit, unreasonable diagnosis and treatment behaviors are generally existed in the medical institution. For example, the examination items are reduced, the use of some medicine consumables is reduced, the diagnosis and treatment effect is reduced, and the contradiction between doctors and patients is further increased.
Disclosure of Invention
The application mainly aims to provide a method, a device, equipment and a storage medium for auditing diagnosis and treatment behaviors of single disease, and aims to solve the technical problem that unreasonable diagnosis and treatment behaviors occur in order to save cost in medical institutions.
In order to achieve the above object, the present application provides an auditing method for diagnosis and treatment behaviors of a single disease species, comprising the following steps:
acquiring a plurality of sample electronic medical records;
acquiring sample diagnosis information, sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of each sample electronic medical record;
grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
analyzing the logical relationship among the sample medicine information, the sample consumable information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records, and generating an auditing formula group according to the logical relationship;
acquiring medical record information, wherein the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information;
determining an audit formula set according to the diagnostic information, wherein the audit formula set at least comprises an audit formula;
judging whether variables of the auditing formulas exist or not according to the medicine information, the consumable information, the diagnosis and treatment service information and the operation information;
determining the value of each variable according to the existence condition;
and inputting the values of the auditing formula and the variables into an automator engine for calculation, and outputting an auditing result.
Further, the step of inputting the values of the audit formula and the variables into an ariator engine for calculation and outputting an audit result includes:
mapping variables in the audit formula into codes through a code-code mapping table in a basic database;
mapping logic in the audit formula into a logic operator;
and inputting the coding and logic operator into an argument engine in sequence for calculation, and outputting an auditing result.
Further, the step of obtaining medical record information, wherein the medical record information includes diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information, includes:
acquiring an electronic medical record;
preprocessing the electronic medical record to obtain a target medical record;
and inputting the target medical record into a preset information extraction model to extract the medical record information, wherein the information extraction model is formed by training based on a bidirectional circulation neural network model.
Further, after the step of inputting the values of the audit formula and the variables into an ariator engine for calculation and outputting an audit result, the method includes:
judging whether the audit result is qualified;
if the first variable is not qualified, extracting a first unqualified variable in the auditing formula;
detecting whether a second variable which is not in the auditing formula exists in the medicine information, the consumable information or the operation information;
judging whether the second variable can replace the first variable or not;
if the variable is replaceable, the second variable is marked and displayed.
Further, the step of analyzing the logical relationship among the sample drug information, the sample consumable information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records, and generating an auditing formula set according to the logical relationship includes:
dividing the sample electronic medical records with the same sample drug information into a group to obtain a plurality of drug groups;
connecting sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of the sample electronic medical records in each medicine group in a logical relationship to obtain a plurality of first examination formulas;
analyzing whether the sample consumable material information, the sample diagnosis and treatment service information or the sample operation information among the first examination formulas has substitutability or not;
if so, connecting the replaceable sample consumable material information, the sample diagnosis and treatment service information or the sample operation information in an OR logical relationship to obtain a second examination formula;
and collecting the second auditing formula to obtain the auditing formula group.
The application still provides a single disease species diagnoses examination and verification device of action, includes:
the first acquisition unit is used for acquiring a plurality of sample electronic medical records;
the second acquisition unit is used for acquiring sample diagnosis information, sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of each sample electronic medical record;
the grouping unit is used for grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
the analysis unit is used for analyzing the logical relationship among the sample medicine information, the sample consumable material information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records and generating an auditing formula group according to the logical relationship;
the third acquisition unit is used for acquiring medical record information, wherein the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information;
the first determining unit is used for determining an auditing formula group according to the diagnosis information, wherein the auditing formula group at least comprises an auditing formula;
the judging unit is used for judging whether variables of the auditing formulas exist or not according to the medicine information, the consumable information, the diagnosis and treatment service information and the operation information;
the second determining unit is used for determining the value of each variable according to the existence condition;
and the calculation unit is used for inputting the values of the auditing formula and the variables into an ariator engine for calculation and outputting an auditing result.
Further, the calculation unit includes:
the first mapping subunit is used for mapping the variables in the audit formula into codes through a code-code mapping table in a basic database;
a second mapping subunit, configured to map the logic in the audit formula into a logic operator;
and the calculation subunit is used for inputting the coding and logic operator into an argument engine in sequence for calculation and outputting an audit result.
Further, the third obtaining unit includes:
the acquisition subunit is used for acquiring the electronic medical record;
the pretreatment unit is used for pretreating the electronic medical record to obtain a target medical record;
and the extraction subunit is used for inputting the target medical record into a preset information extraction model to extract the medical record information, and the information extraction model is formed by training based on a bidirectional circulation neural network model.
The application also provides computer equipment which comprises a memory and a processor, wherein the memory stores computer programs, and the processor realizes the steps of the single disease diagnosis and treatment behavior auditing method when executing the computer programs.
The application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for auditing diagnosis and treatment behaviors of single disease species is implemented.
According to the auditing method, the auditing device, the equipment and the storage medium for single disease diagnosis and treatment behaviors, the corresponding auditing formula group is determined through the diagnosis information, whether the variable of the auditing formula group exists or not is determined, the value of the variable is determined according to the existence condition, the auditing formula and the value of the variable are input into an aviator engine for calculation, the single disease can be automatically and quickly audited, and unreasonable diagnosis and treatment behaviors are prevented.
Drawings
Fig. 1 is a schematic diagram illustrating a procedure of an auditing method for a single disease diagnosis and treatment behavior according to an embodiment of the present application;
fig. 2 is a block diagram of an auditing apparatus for single disease diagnosis and treatment behaviors according to an embodiment of the present application;
fig. 3 is a block diagram illustrating a structure of a computer device according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Referring to fig. 1, an embodiment of the present application provides an auditing method for diagnosis and treatment behaviors of a single disease category, including the following steps:
step S1, obtaining a plurality of sample electronic medical records;
step S2, obtaining sample diagnosis information, sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of each sample electronic medical record;
step S3, grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
step S4, analyzing the logical relationship among the sample drug information, the sample consumable information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records, and generating an auditing formula group according to the logical relationship;
step S5, acquiring medical record information, wherein the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information;
step S6, determining an auditing formula set according to the diagnosis information; wherein the audit formula set includes at least one audit formula;
step S7, judging whether the variables of the auditing formulas exist according to the medicine information, the consumable information, the diagnosis and treatment service information and the operation information;
step S8, determining the value of each variable according to the existence condition;
and step S9, inputting the values of the auditing formula and the variables into an ariator engine for calculation, and outputting an auditing result.
In this embodiment, as described in step S1, a plurality of sample electronic medical records are obtained, and the plurality of sample electronic medical records should include all electronic medical records of a single disease type.
As described in step S2, sample diagnosis information of each sample electronic medical record is obtained, and specifically, the sample electronic medical record may be input into a preset information extraction model to extract sample diagnosis information of the sample electronic medical record, where the sample diagnosis information includes a disease name of the sample and a corresponding ICD (international Classification of diseases) -10 code. The sample consumable information comprises information of consumed medical instruments, the sample operation information comprises operation names and corresponding operation codes, and the sample medicine information comprises medicines adopted in the treatment process, including traditional Chinese medicines and western medicines.
As described in step S3, the plurality of sample electronic medical records are grouped according to the sample diagnostic information, such that the sample electronic medical records corresponding to the same sample diagnostic information are grouped into one group, and if the sample diagnostic information is a group of diseases a, the sample diagnostic information is a group of diseases B, a plurality of sample groups are obtained.
As described in the step S4, the logical relationship between the sample drug information, the sample consumable information, the sample diagnosis and treatment service information, and the sample operation information is analyzed, specifically, if the disease a can be treated with western medicine or traditional Chinese medicine, the sample electronic medical record a is treated with western medicine P, the sample electronic medical record b is treated with western medicine Q, and the sample electronic medical record c is treated with traditional Chinese medicine X, the logical relationship between P, Q and X is "or", and if some diseases require western medicine and operation for adjuvant therapy, the logical relationship between western medicine and operation is "and". And generating a checking formula group according to the logical relationship, wherein the checking formula of the disease A can be 'P or Q or W', and a corresponding checking formula group can be generated for each disease, wherein all reasonable treatment schemes are included. Specifically, a variable library related to diagnosis and treatment behaviors is input into a basic data maintenance module in advance; the basic information of diagnosis, medicine, consumables, diagnosis and treatment service, operation and the like can be modified at any time so as to deal with the change of diagnosis and treatment modes and update the auditing formula set corresponding to each disease in real time.
As described in the foregoing steps S5-S6, the medical record information is obtained, and the corresponding review formula set is determined according to the diagnosis information, where the review formula set corresponding to each disease includes all reasonable treatment schemes for the disease, each disease has a corresponding reasonable treatment scheme, and the reasonable treatment schemes may include a plurality of ones, and a review formula is formed according to the reasonable treatment scheme for each disease, where each formula represents a reasonable treatment behavior, for example, a review formula for a disease a is "P or Q or W", which means that the disease a can be treated by a western medicine P, a western medicine Q, or a traditional medicine W, and the western medicine P, the western medicine Q, or the traditional medicine W is a variable of the review formula. If the disease A can be treated by 3 modes of operation treatment, traditional Chinese medicine treatment and western medicine treatment, a plurality of reasonable auditing formulas can be configured by using related treatment means in each treatment mode, and if the colorectal cancer needs to be treated by oxaliplatin, fluorouracil and calcium folinate, the auditing formula can be determined to be 'oxaliplatin, fluorouracil and calcium folinate'.
As described in step S7, it is determined whether the variables in each audit formula exist, and if a single colorectal cancer is audited, the drug information in the consumable information is extracted, and it is determined whether the colorectal cancer is treated with oxaliplatin, fluorouracil, and calcium folinate in the treatment stage, and if oxaliplatin, fluorouracil, and calcium folinate are all used, each variable in the audit formula of the colorectal cancer exists.
As described in step S8 above, the value of each variable is determined according to the existence of the variable, specifically, in the audit formula of colorectal cancer, if oxaliplatin exists, the value of the variable is set to TRUE, otherwise, the value is set to FALSE.
As described in step S9, the values of the respective audit formulas and the corresponding variables are input to the Aviator engine for calculation, and an audit result is output, where the Aviator is a high-performance and lightweight expression evaluation engine implemented in java language, and is mainly used for dynamic evaluation of various expressions.
In an embodiment, the step S9 of inputting the audit formula and the value of the variable to an ariator engine for calculation and outputting an audit result includes:
step S91, mapping the variables in the auditing formula into codes through a code-code mapping table in a basic database;
step S92, mapping the logic in the auditing formula into a logic operator;
and step S93, inputting the coding and logic operator into an argument engine in sequence for calculation, and outputting an audit result.
In this embodiment, as described in step S91, the variables in the audit formula are mapped into codes, specifically, basic information such as drugs, consumables, and operations is stored in a basic database, the drugs, consumables, and operations have corresponding codes, a code-code mapping table is generated, and codes of the variables are determined according to the mapping table, where the codes can be supported by an aviator engine.
As described in step S92 above, the logical operation in each audit formula includes and or, mapping the logical operator to a logical operator, such as or |, and &.
As described in the above step S93, the coding and logic operators are input into the averager engine for calculation according to the order of the coding and logic operators in the audit formula, where the audit formula is as follows: anti-infective 3 and (cataract extraction or lens implantation or other operations of the lens or vitreous body operations) and (anesthetic 3.1 or diagnosis and treatment items containing anesthetic), the variables are assigned according to the existence condition, and the expression input to the averager engine after mapping is as follows: true & (false | | true | | false | | false) & (false | | false). In this embodiment, by the examination method for the single disease diagnosis and treatment behavior provided above, the diagnosis and treatment scheme provided by the doctor can be automatically and accurately examined, and unreasonable diagnosis and treatment behaviors are prevented.
In one embodiment, the medical record information is acquired; step S5, in which the medical record information includes diagnosis information, medicine information, consumable information, diagnosis and treatment service information, and operation information, includes:
step S51, acquiring an electronic medical record;
step S52, preprocessing the electronic medical record to obtain a target medical record;
step S53, inputting the target medical record into a preset information extraction model to extract the medical record information; the information extraction model is trained on the basis of a bidirectional cyclic neural network model.
In this embodiment, as described in step S51, an electronic medical record is obtained, where the electronic medical record includes the original record of the whole process of diagnosis and treatment of the patient in the hospital.
As described in the above step S52, the acquired electronic medical record is preprocessed, for example, by preprocessing text and cleaning data with numpy, pandas, jieba and other tools, including word segmentation in chinese, word deletion, removal of useless symbols, etc., and information desensitization may be performed on privacy in the text of the electronic medical record, and then patient privacy is removed, where the privacy includes: the key privacy information such as name, bed number, hospital number, address and the like which are easy to be identified by others.
As described in step S53, since the context information can be extracted well by the information extraction model trained by the bidirectional recurrent neural network, the medical record information of the electronic medical record, such as the medicine and the operation, used in the electronic medical record, can be extracted accurately. Specifically, when the information extraction model is trained, each sentence of the target medical record is mapped into a sentence vector with fixed dimensions, specifically, the sentence can be mapped into the vector with fixed dimensions through an encoder of a neural network (which can be a convolutional neural network, a cyclic neural network, a transormer, and the like), and then the vector representation of a single sentence passing through the neural network can be obtained. Thus, each sentence in the target medical record is input into the neural network, a vector representation of each sentence can be obtained, and thus, a complete target medical record can be represented by the sentence vectors of all sentences. Inputting sentence vectors into a bidirectional circulation neural network model according to the sequence of sentences corresponding to the sentence vectors in a target case for iterative training, and calculating the output result after training by softmax, wherein the softmax can map any real number vector of one K-dimension into a real number vector of another K-dimension, the value of each element in the vector is between (0 and 1), and the functional expression of the softmax is as follows:
wherein K represents the number of classes of the classification, j represents a certain class of the K classes, and j belongs to (0, K)]，zjThe value of the classification is expressed, and medical record information is extracted. Further, a loss value is calculated using cross entropy.
In an embodiment, after the step S9 of inputting the audit formula and the value of the variable to the avertor engine for calculation and outputting the audit result, the method includes:
step S9A, judging whether the audit result is qualified;
step S9B, if not, extracting the first variable which is not qualified in the auditing formula;
step S9C, detecting whether a second variable which is not in the auditing formula exists in the medicine information, the consumable information or the operation information;
step S9D, judging whether the second variable can replace the first variable;
and step S9E, if the variable can be replaced, marking the second variable and displaying the second variable.
In this embodiment, as described in step S9A, it is determined whether the audit result is qualified, the output audit result is generally displayed as true or false, where true indicates that the audit result is qualified, that is, the treatment plan provided by the doctor is reasonable, and false indicates that the treatment plan provided by the doctor is not qualified, that is, there is a case where there is no inspection item or medicine in the treatment plan provided by the doctor.
As described in the above step S9A, if the test result is not qualified, a first variable that is not qualified in the verification formula is extracted, and if oxaliplatin and fluorouracil in the verification formula and calcium folinate both exist and calcium folinate is absent, calcium folinate is the first variable.
As described in step S9B, if other drugs not contained in oxaliplatin, fluorouracil, or calcium folinate are present in the acquired medical record information, the other drugs are used as the second variable.
As described in the foregoing steps S9C-S9E, the update of the drug is fast, when the new drug has the same drug effect as the original drug but is not in the variables provided by the audit formula, the audit result is not qualified, but the new drug and the original drug are replaceable, the replaceable second variable is labeled and displayed, so that the personnel at the audit post can know the drug, and the drug is added to the corresponding audit formula by the basic data maintenance module, thereby improving the accuracy. Specifically, relevant documents recording the new medicine are obtained according to the name of the new medicine, whether the medicine effect between the new medicine and the original medicine is the same or not is analyzed according to the relevant documents, and whether the replaceability between the new medicine and the original medicine exists or not is determined according to the medicine effect.
In an embodiment, the step S4 of analyzing the logical relationship among the sample drug information, the sample consumable information, the sample medical service information, and the sample surgery information among the sample electronic medical records, and generating an audit formula set according to the logical relationship includes:
step S41, dividing the sample electronic medical records with the same sample drug information into a group to obtain a plurality of drug groups;
step S42, connecting sample drug information, sample consumable information, sample diagnosis and treatment service information and sample operation information of the sample electronic medical records in each drug group in a logical relationship to obtain a plurality of first examination formulas;
step S43, analyzing whether the sample consumable information, the sample diagnosis and treatment service information or the sample operation information among the first examination formulas has substitutability;
step S44, if yes, connecting the replaceable sample consumable material information, the sample diagnosis and treatment service information or the sample operation information in an OR logical relationship to obtain a second examination formula;
and step S45, collecting the second auditing formula to obtain the auditing formula group.
In this embodiment, as described in step S41, the sample electronic medical records with the same sample drug information are divided into one group, for example, all the sample electronic medical records using western drug a are divided into one group, and all the sample electronic medical records using western drug B are divided into one group, so as to obtain a plurality of drug groups.
As described in step S42, each sample electronic medical record can provide a treatment plan, where the drugs or operations used in the treatment plan are unique, and the doctor can only choose one of the two drugs with the same efficacy without prescribing two drugs with the same efficacy, so that the sample drug information, the sample consumable information, the sample medical service information, or the sample operation information in each sample electronic medical record can be linked in a logical relationship, for example, the first checking formula in the sample electronic medical record 1 can be: drug a and procedure B and consumable C; the second review formula in the sample electronic medical record 2 can be: drug a and surgery b and consumable c; each sample electronic medical record can be subjected to a first audit formula.
As described in the above steps S43-S44, it is analyzed whether the sample consumable information, the sample diagnosis and treatment service information, or the sample operation information are substitutable, specifically, the analysis can be performed from the aspect of their efficacy, and when the efficacies of the two are the same, the substitution is performed. If there are alternatives, then the logical relationship of OR can be used to connect, as described above for sample electronic case 1 and sample electronic case 2, alternatives for procedures B and B, and alternatives for consumables C and C, then the second checking formula can be obtained: drugs a and (procedure B or procedure B) and (consumable C or consumable C).
As described in the above step S45, all the second audit formulas are collected to obtain the audit formula set. In this embodiment, the electronic medical records of samples using the same drugs are divided into a group, and the auditing formula group is determined based on the same drugs, and when the electronic medical records of samples using the same drugs are used, one auditing formula group may be determined according to the diagnostic information, a second auditing formula with the same drugs may be determined according to the drug information, and a closest auditing formula may be determined according to the second auditing formula.
The auditing method for the single disease diagnosis and treatment behavior can be applied to the field of block chains, and the medical record information is stored in a block chain network, wherein the block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product services layer, and an application services layer.
The block chain underlying platform can comprise processing modules such as user management, basic service, intelligent contract and operation monitoring. The user management module is responsible for identity information management of all blockchain participants, and comprises public and private key generation maintenance (account management), key management, user real identity and blockchain address corresponding relation maintenance (authority management) and the like, and under the authorization condition, the user management module supervises and audits the transaction condition of certain real identities and provides rule configuration (wind control audit) of risk control; the basic service module is deployed on all block chain node equipment and used for verifying the validity of the service request, recording the service request to storage after consensus on the valid request is completed, for a new service request, the basic service firstly performs interface adaptation analysis and authentication processing (interface adaptation), then encrypts service information (consensus management) through a consensus algorithm, transmits the service information to a shared account (network communication) completely and consistently after encryption, and performs recording and storage; the intelligent contract module is responsible for registering and issuing contracts, triggering the contracts and executing the contracts, developers can define contract logics through a certain programming language, issue the contract logics to a block chain (contract registration), call keys or other event triggering and executing according to the logics of contract clauses, complete the contract logics and simultaneously provide the function of upgrading and canceling the contracts; the operation monitoring module is mainly responsible for deployment, configuration modification, contract setting, cloud adaptation in the product release process and visual output of real-time states in product operation, such as: alarm, monitoring network conditions, monitoring node equipment health status, and the like.
Referring to fig. 2, an embodiment of the present application further provides an auditing apparatus for diagnosis and treatment of a single disease category, including:
a first obtaining unit 10, configured to obtain a plurality of sample electronic medical records;
the second obtaining unit 20 is configured to obtain sample diagnosis information, sample drug information, sample consumable information, sample diagnosis service information, and sample operation information of each sample electronic medical record;
the grouping unit 30 is used for grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
the analysis unit 40 is configured to analyze a logical relationship between sample drug information, sample consumable information, sample diagnosis and treatment service information and sample operation information among the sample electronic medical records, and generate an audit formula set according to the logical relationship;
a third acquiring unit 50, configured to acquire medical record information, where the medical record information includes diagnosis information, medicine information, consumable information, diagnosis and treatment service information, and operation information;
a first determining unit 60, configured to determine an audit formula set according to the diagnosis information, where the audit formula set at least includes an audit formula;
a judging unit 70, configured to judge whether a variable of each audit formula exists according to the drug information, the consumable information, the diagnosis and treatment service information, and the operation information;
a second determining unit 80 for determining the value of each of the variables according to the presence;
and the calculating unit 90 is configured to input the values of the audit formula and the variable to an ariator engine for calculation, and output an audit result.
In one embodiment, the computing unit 90 includes:
the first mapping subunit is used for mapping the variables in the audit formula into codes through a code-code mapping table in a basic database;
a second mapping subunit, configured to map the logic in the audit formula into a logic operator;
and the calculation subunit is used for inputting the coding and logic operator into an argument engine in sequence for calculation and outputting an audit result.
In an embodiment, the third obtaining unit 50 includes:
the acquisition subunit is used for acquiring the electronic medical record;
the pretreatment unit is used for pretreating the electronic medical record to obtain a target medical record;
the extraction subunit is used for inputting the target medical record into a preset information extraction model to extract the medical record information; the information extraction model is trained on the basis of a bidirectional cyclic neural network model.
In an embodiment, the auditing device for diagnosis and treatment behaviors of a single disease type further includes:
the first judging unit is used for judging whether the auditing result is qualified or not;
the extracting unit is used for extracting the unqualified first variable in the auditing formula if the unqualified first variable is not qualified;
the detection unit is used for detecting whether a second variable which is not in the auditing formula exists in the medicine information, the consumable information or the operation information;
the second judging unit is used for judging whether the second variable can replace the first variable or not;
and the marking unit is used for marking the second variable and displaying the second variable if the second variable can be replaced.
In an embodiment, the analyzing unit 40 includes:
the grouping subunit is used for grouping the sample electronic medical records with the same sample drug information into a group to obtain a plurality of drug groups;
the first auditing formula subunit is used for connecting the sample medicine information, the sample consumable material information, the sample diagnosis and treatment service information and the sample operation information of the sample electronic medical record in each medicine group in a logical relationship to obtain a plurality of first auditing formulas;
the analysis subunit is used for analyzing whether the sample consumable material information, the sample diagnosis and treatment service information or the sample operation information among the first examination and check formulas has substitutability or not;
the second examination and check formula subunit is used for connecting the substitutable sample consumable material information, the sample diagnosis and treatment service information or the sample operation information in an OR logical relationship to obtain a second examination and check formula if the substitutable sample consumable material information, the sample diagnosis and treatment service information or the sample operation information exists;
and the set subunit is used for collecting the second audit formula to obtain the audit formula group.
In this embodiment, please refer to the above method embodiment for the specific implementation of each unit and sub-unit, which is not described herein again.
Referring to fig. 3, a computer device, which may be a server and whose internal structure may be as shown in fig. 3, is also provided in the embodiment of the present application. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer designed processor is used to provide computational and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing medical record data and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by the processor to realize the auditing method of single disease diagnosis and treatment behaviors.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is only a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects may be applied.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for auditing diagnosis and treatment behaviors of a single disease type is implemented.
In summary, for the auditing method, apparatus, device and storage medium for single disease diagnosis and treatment behavior provided in the embodiment of the present application, an auditing formula group is generated, and medical record information is obtained; the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information; determining an auditing formula set according to the diagnosis information; wherein the audit formula set at least comprises an audit formula; judging whether the variable of each audit formula exists or not; determining the value of each variable according to the existence condition; and inputting the values of the auditing formula and the variables into an automator engine for calculation, and outputting an auditing result. According to the auditing method, the auditing device, the equipment and the storage medium for single disease diagnosis and treatment behaviors, the corresponding auditing formula group is determined through the diagnosis information, whether the variable of the auditing formula group exists or not is determined, the value of the variable is determined according to the existence condition, the auditing formula and the value of the variable are input into an aviator engine for calculation, the single disease can be automatically and quickly audited, and unreasonable diagnosis and treatment behaviors are prevented.
The application provides a method, a device, equipment and a storage medium for auditing diagnosis and treatment behaviors of single disease species, which can be applied to the field of intelligent medical treatment to accelerate the construction of digital medical treatment, thereby promoting the construction of smart cities.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware associated with instructions of a computer program, which may be stored on a non-volatile computer-readable storage medium, and when executed, may include processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
The above description is only for the preferred embodiment of the present application and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are intended to be included within the scope of the present application.
Claims (10)
1. A method for auditing diagnosis and treatment behaviors of single disease species is characterized by comprising the following steps:
acquiring a plurality of sample electronic medical records;
acquiring sample diagnosis information, sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of each sample electronic medical record;
grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
analyzing the logical relationship among the sample medicine information, the sample consumable information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records, and generating an auditing formula group according to the logical relationship;
acquiring medical record information, wherein the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information;
determining an audit formula set according to the diagnostic information, wherein the audit formula set at least comprises an audit formula;
judging whether variables of the auditing formulas exist or not according to the medicine information, the consumable information, the diagnosis and treatment service information and the operation information;
determining the value of each variable according to the existence condition;
and inputting the values of the auditing formula and the variables into an automator engine for calculation, and outputting an auditing result.
2. The examination method for the single disease diagnosis and treatment behavior according to claim 1, wherein the step of inputting the examination formula and the value of the variable into an ariator engine for calculation and outputting an examination result comprises:
mapping variables in the audit formula into codes through a code-code mapping table in a basic database;
mapping logic in the audit formula into a logic operator;
and inputting the coding and logic operator into an argument engine in sequence for calculation, and outputting an auditing result.
3. The method for auditing diagnosis and treatment activities of a single disease category according to claim 1, wherein the step of obtaining medical record information including diagnosis information, drug information, consumable information, diagnosis and treatment service information, and surgery information comprises:
acquiring an electronic medical record;
preprocessing the electronic medical record to obtain a target medical record;
and inputting the target medical record into a preset information extraction model to extract the medical record information, wherein the information extraction model is formed by training based on a bidirectional circulation neural network model.
4. The examination method for single-disease diagnosis and treatment behavior according to claim 1, wherein after the step of inputting the examination formula and the value of the variable into an ariator engine for calculation and outputting the examination result, the method comprises:
judging whether the audit result is qualified;
if the first variable is not qualified, extracting a first unqualified variable in the auditing formula;
detecting whether a second variable which is not in the auditing formula exists in the medicine information, the consumable information or the operation information;
judging whether the second variable can replace the first variable or not;
if the variable is replaceable, the second variable is marked and displayed.
5. The examination method for single-disease diagnosis and treatment behaviors of claim 1, wherein the step of analyzing the logical relationship among the sample drug information, the sample consumable information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records, and generating an examination formula group according to the logical relationship comprises the steps of:
dividing the sample electronic medical records with the same sample drug information into a group to obtain a plurality of drug groups;
connecting sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of the sample electronic medical records in each medicine group in a logical relationship to obtain a plurality of first examination formulas;
analyzing whether the sample consumable material information, the sample diagnosis and treatment service information or the sample operation information among the first examination formulas has substitutability or not;
if so, connecting the replaceable sample consumable material information, the sample diagnosis and treatment service information or the sample operation information in an OR logical relationship to obtain a second examination formula;
and collecting the second auditing formula to obtain the auditing formula group.
6. The utility model provides a single disease species diagnoses examination and verification device of action which characterized in that includes:
the first acquisition unit is used for acquiring a plurality of sample electronic medical records;
the second acquisition unit is used for acquiring sample diagnosis information, sample medicine information, sample consumable information, sample diagnosis and treatment service information and sample operation information of each sample electronic medical record;
the grouping unit is used for grouping the sample electronic medical records according to the sample diagnosis information to obtain a plurality of sample groups;
the analysis unit is used for analyzing the logical relationship among the sample medicine information, the sample consumable material information, the sample diagnosis and treatment service information and the sample operation information among the sample electronic medical records and generating an auditing formula group according to the logical relationship;
the third acquisition unit is used for acquiring medical record information, wherein the medical record information comprises diagnosis information, medicine information, consumable information, diagnosis and treatment service information and operation information;
the first determining unit is used for determining an auditing formula group according to the diagnosis information, wherein the auditing formula group at least comprises an auditing formula;
the judging unit is used for judging whether variables of the auditing formulas exist or not according to the medicine information, the consumable information, the diagnosis and treatment service information and the operation information;
the second determining unit is used for determining the value of each variable according to the existence condition;
and the calculation unit is used for inputting the values of the auditing formula and the variables into an ariator engine for calculation and outputting an auditing result.
7. The examination unit for single-disease diagnosis and treatment behavior according to claim 6, wherein the calculation unit comprises:
the first mapping subunit is used for mapping the variables in the audit formula into codes through a code-code mapping table in a basic database;
a second mapping subunit, configured to map the logic in the audit formula into a logic operator;
and the calculation subunit is used for inputting the coding and logic operator into an argument engine in sequence for calculation and outputting an audit result.
8. The examination device for single-disease diagnosis and treatment behavior according to claim 6, wherein the third obtaining unit comprises:
the acquisition subunit is used for acquiring the electronic medical record;
the pretreatment unit is used for pretreating the electronic medical record to obtain a target medical record;
and the extraction subunit is used for inputting the target medical record into a preset information extraction model to extract the medical record information, and the information extraction model is formed by training based on a bidirectional circulation neural network model.
9. A computer device comprising a memory and a processor, the memory having a computer program stored therein, wherein the processor when executing the computer program implements the steps of the method for auditing individual medical actions of any one of claims 1 to 5.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for auditing monomial clinical behaviors of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010900114.7A CN111986038A (en) | 2020-08-31 | 2020-08-31 | Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010900114.7A CN111986038A (en) | 2020-08-31 | 2020-08-31 | Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111986038A true CN111986038A (en) | 2020-11-24 |
Family
ID=73447248
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010900114.7A Pending CN111986038A (en) | 2020-08-31 | 2020-08-31 | Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111986038A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114724693A (en) * | 2022-06-07 | 2022-07-08 | 武汉金豆医疗数据科技有限公司 | Method and device for detecting abnormal diagnosis and treatment behaviors, electronic equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106372432A (en) * | 2016-08-31 | 2017-02-01 | 杭州逸曜信息技术有限公司 | Medicine combination information processing method |
| CN109256186A (en) * | 2018-10-30 | 2019-01-22 | 平安医疗健康管理股份有限公司 | Medication checking method, device, server and storage medium based on audit model |
| CN109712684A (en) * | 2018-11-06 | 2019-05-03 | 闽江学院 | A kind of recommended method and device of composition of medicine |
| CN111241806A (en) * | 2019-12-23 | 2020-06-05 | 望海康信(北京)科技股份公司 | Method and system for checking consistency of diagnosis of electronic medical record and medical record home page |
-
2020
- 2020-08-31 CN CN202010900114.7A patent/CN111986038A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106372432A (en) * | 2016-08-31 | 2017-02-01 | 杭州逸曜信息技术有限公司 | Medicine combination information processing method |
| CN109256186A (en) * | 2018-10-30 | 2019-01-22 | 平安医疗健康管理股份有限公司 | Medication checking method, device, server and storage medium based on audit model |
| CN109712684A (en) * | 2018-11-06 | 2019-05-03 | 闽江学院 | A kind of recommended method and device of composition of medicine |
| CN111241806A (en) * | 2019-12-23 | 2020-06-05 | 望海康信(北京)科技股份公司 | Method and system for checking consistency of diagnosis of electronic medical record and medical record home page |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114724693A (en) * | 2022-06-07 | 2022-07-08 | 武汉金豆医疗数据科技有限公司 | Method and device for detecting abnormal diagnosis and treatment behaviors, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111339126B (en) | Medical data screening method and device, computer equipment and storage medium | |
| Kimura et al. | Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage | |
| Waghade et al. | A comprehensive study of healthcare fraud detection based on machine learning | |
| US8688607B2 (en) | System and method for detecting healthcare insurance fraud | |
| CN110910976A (en) | Medical record detection method, device, equipment and storage medium | |
| US20080052128A1 (en) | Medical billing auditing method and system | |
| CN106650256A (en) | Precise medical platform for molecular diagnosis and treatment | |
| CN1853194A (en) | Computer-based data capturing system | |
| CN112016279A (en) | Electronic medical record structuring method and device, computer equipment and storage medium | |
| WO2022041722A1 (en) | Hospital guidance data acquisition method and apparatus, and computer device and storage medium | |
| CN112216361A (en) | Follow-up plan list generation method, device, terminal and medium based on artificial intelligence | |
| CN112734202A (en) | Medical capability evaluation method, device, equipment and medium based on electronic medical record | |
| CN112035618A (en) | Medical expense analysis method and device, computer equipment and storage medium | |
| US7742933B1 (en) | Method and system for maintaining HIPAA patient privacy requirements during auditing of electronic patient medical records | |
| CN113936762A (en) | Intelligent medical treatment data storage method and platform based on block chain | |
| CN110729054B (en) | Abnormal diagnosis behavior detection method and device, computer equipment and storage medium | |
| CN112036749A (en) | Method and device for identifying risk user based on medical data and computer equipment | |
| Biswas et al. | Disease diagnosis system | |
| CN111986038A (en) | Examination method, device, equipment and storage medium for diagnosis and treatment behaviors of single disease | |
| CN113948172A (en) | Inspection result sharing mutual recognition system | |
| US20080140599A1 (en) | System and method for detecting healthcare insurance fraud | |
| US20160253770A1 (en) | Systems and methods for genetic testing algorithms | |
| CN112086175A (en) | Medical price charge monitoring method, system, computer equipment and storage medium | |
| CN115938608A (en) | Clinical decision early warning method and system based on prompt learning model | |
| McDougall et al. | Predicting Opioid Overdose Readmission and Opioid Use Disorder with Machine Learning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20220602 Address after: 518000 China Aviation Center 2901, No. 1018, Huafu Road, Huahang community, Huaqiang North Street, Futian District, Shenzhen, Guangdong Province Applicant after: Shenzhen Ping An medical and Health Technology Service Co.,Ltd. Address before: Room 12G, Block H, 666 Beijing East Road, Huangpu District, Shanghai 200000 Applicant before: PING AN MEDICAL AND HEALTHCARE MANAGEMENT Co.,Ltd. |