CN114155976A

CN114155976A - DRGs submission feedback method and system

Info

Publication number: CN114155976A
Application number: CN202111483545.9A
Authority: CN
Inventors: 陈强; 杨科春; 闵逸飞; 陆林
Original assignee: Changzhou Haoze Information Technology Co ltd
Current assignee: Changzhou Haoze Information Technology Co ltd
Priority date: 2021-12-07
Filing date: 2021-12-07
Publication date: 2022-03-08

Abstract

The invention belongs to the technical field of intelligent medical treatment, and particularly relates to a DRGs submission feedback method and a DRGs submission feedback system, wherein the DRGs submission feedback method comprises the following steps: constructing a DRGs knowledge base; optimizing the medical record of the patient; self-defining DRGs of a patient and acquiring a feedback result of the DRGs; and optimizing the DRGs knowledge base according to the feedback result of the DRGs, realizing that the most reasonable drg groups are calculated by a special algorithm through partial data counted by each department and the normal operation record of a doctor and recommended to the doctor, and comparing the DRGS in the event with the real-time feedback information of the medical insurance after the event so that the doctor has self-comparison and error summary.

Description

DRGs submission feedback method and system

Technical Field

The invention belongs to the technical field of intelligent medical treatment, and particularly relates to a DRGs submission feedback method and system.

Background

The Drgs group intelligent recommendation function is based on the subjective judgment of medical knowledge of doctors, because the content of the Drgs knowledge base is various, drg groups generated by different departments, different diagnoses and different operations are varied and have no fixed rules.

Therefore, a new DRGs submission feedback method and system need to be designed based on the above technical problems.

Disclosure of Invention

The invention aims to provide a DRGs submission feedback method and a DRGs submission feedback system.

In order to solve the above technical problem, the present invention provides a DRGs submission feedback method, which includes:

constructing a DRGs knowledge base;

optimizing the medical record of the patient;

self-defining DRGs of a patient and acquiring a feedback result of the DRGs; and

and optimizing the DRGs knowledge base according to the feedback result of the DRGs.

Further, the method for constructing the DRGs knowledge base comprises the following steps:

and storing the DRGs of all historical patients to construct a DRGs knowledge base.

Further, the method for optimizing the medical record of the patient comprises the following steps:

optimizing according to the bedside identification of the patient, the past history diagnosis and treatment plan, the transfer examination and examination, the transformation of the discharge summary, the prompt of the operation record, the special items of new technical and new projects and the medical record modification identification of the patient.

Further, the method for customizing DRGs of a patient comprises the following steps:

the doctor self-defines the DRGs of the patient according to the patient, wherein the self-defining of the DRGs comprises the following steps: a first diagnosis, a first operation and procedure, other diagnoses, other operations and procedures, gender, age, days of hospitalization, manner of discharge, referral, corresponding DRG group name, corresponding DRG group code, corresponding DRG group attribute, weight, DRG payment criteria, and rate for the year;

the other diagnosis is a diagnosis other than the first diagnosis;

the other surgery and procedure is a surgery and procedure other than the first surgery and procedure.

Further, the method for acquiring the feedback result of the DRGs includes:

comparing the self-defined DRGs with the medical insurance to obtain comparison information, and judging the comparison information as first feedback or final feedback;

the first feedback and the final feedback both comprise: feedback of outcome, health care DRG group, health care DRG code, health care weight, diagnosis, surgery or procedure, days of hospitalization, age, manner of discharge, outcome, other, cause of inconsistency, whether first diagnosis is adjusted, whether first surgery or procedure is adjusted, severe complications, and complications;

storing the self-defined DRGs when the first feedback result is consistent;

and updating the self-defined DRGs when the first feedback result is inconsistent.

Further, the method for optimizing the DRGs knowledge base according to the feedback result of the DRGs comprises the following steps:

comparing the self-defined DRGs with DRGs data stored in a DRGs knowledge base;

selecting comparison fields, and respectively acquiring the word frequency of each comparison field of the custom DRGs and the word frequency of each comparison field of DRGs data selected from a DRGs knowledge base for comparison;

acquiring the word frequency quantity of the custom DRGs and the DRGs data for comparison according to the word frequency of the comparison field, and judging the similarity degree according to the two word frequency quantities;

updating the DRGs knowledge base according to the similarity degree;

when there is no repetition, storing the self-defined DRGs in a DRGs knowledge base;

when the data is repeated, the custom-defined data of the hospitalization days, the sex, the outcome, the severe complications, the complications and the complications in the DRGs is stored in a DRGs knowledge base.

In a second aspect, the present invention further provides a DRGs submission feedback system, including:

the database module is used for constructing a DRGs knowledge base;

the medical record optimizing module is used for optimizing the medical record of the patient;

the feedback module is used for self-defining the DRGs of the patient and acquiring a feedback result of the DRGs; and

and the knowledge base optimization module is used for optimizing the DRGs knowledge base according to the feedback result of the DRGs.

The method has the beneficial effects that the DRGs knowledge base is constructed; optimizing the medical record of the patient; self-defining DRGs of a patient and acquiring a feedback result of the DRGs; and optimizing the DRGs knowledge base according to the feedback result of the DRGs, realizing that the most reasonable drg groups are calculated by a special algorithm through partial data counted by each department and the normal operation record of a doctor and recommended to the doctor, and comparing the DRGS in the event with the real-time feedback information of the medical insurance after the event so that the doctor has self-comparison and error summary.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a flow chart of the DRGs submission feedback method of the present invention;

FIG. 2 is a detailed flowchart of the DRGs submission feedback method of the present invention;

FIG. 3 is a flow chart of the present invention for custom feedback-with feedback results;

FIG. 4 is a flow chart of the custom feedback-no feedback result of the present invention;

FIG. 5 is a call checking/verification flow diagram of the present invention;

FIG. 6 is a flowchart illustrating the operation of the present invention for recording the disease process;

FIG. 7 is a discharge summary flow chart of the present invention;

FIG. 8 is a flow chart of a past history diagnosis and treatment plan according to the present invention;

FIG. 9 is a flowchart specific to the new technology of the new project of the present invention;

FIG. 10 is a flow chart of DRGs criticizing according to the present invention.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1

As shown in fig. 1, this embodiment 1 provides a DRGs submission feedback method, which includes: constructing a DRGs knowledge base; optimizing the medical record of the patient; self-defining DRGs of a patient and acquiring a feedback result of the DRGs; and optimizing the DRGs knowledge base according to the feedback result of the DRGs, so that the most reasonable DRG group is calculated by a special algorithm through partial data counted by each department and the normal operation record of a doctor, and is recommended to the doctor for use, and the DRGS in the event can be compared with the real-time feedback information of the medical insurance after the event, so that the doctor has self-comparison and error summary.

In this embodiment, the method for constructing the DRGs knowledge base includes: and storing the DRGs of all historical patients to construct a DRGs knowledge base.

As shown in fig. 2-10, in this embodiment, the method for optimizing the medical record of the patient includes: optimizing according to the bedside identification of the patient, the past history diagnosis and treatment plan, the transfer examination and examination, the transformation of the discharge summary, the prompt of the operation record, the special items of new technical and new projects and the medical record modification identification of the patient.

The bedside card sign is: the bedside board displays resident medical insurance and employee medical insurance; description of the function: the bedside board displays resident medical insurance and employee medical insurance, and the resident medical insurance and the employee medical insurance are respectively distinguished by 'job' and 'resident'; the role of use of this function: physicians (doctors, etc.); inputting: when the patient pays for the medical insurance.

The history diagnosis and treatment plan is as follows: in order to adapt to and gradually guess the CC/MCC rules, the previous history node directly lists diagnosis in the diagnosis and treatment plan node when relating to the previous history diagnosis, but can be hidden, not written and not displayed; description of the function: when a product doctor records and diagnoses the past history of the first disease course, the diagnosis information is directly brought into a diagnosis and treatment plan, and the diagnosis information can be hidden, not written and not displayed; using roles: a physician; inputting: logging in diagnosis of the history node; description of the interface: the filled diagnosis is brought into the diagnosis plan, the diagnosis plan can be refined, the previous history diagnosis can be set to be visible or hidden, the specific diagnosis result is selected to be visible and printable, and otherwise, the diagnosis plan cannot be printed.

The call check checks are: and calling and checking to prevent omission of secondary diagnosis (complication complications), increasing analysis nodes for critical values and inspection abnormity during calling, prompting whether diagnosis needs to be increased or not, and preventing omission of secondary diagnosis (complication complications). When the examination is related, the analysis node is directly added after the examination conclusion, and doctors can not be stuck. Description of the function: when the inspection is called, the analysis of abnormal information is added; using roles: a physician; inputting: invoking a check; description of the drawings: (1) displaying the information of the current inspection and the previous inspection; (2) and (4) displaying fields: report date, institution, examination order number, examination item, impression visible, examination conclusion, analysis reason, diagnosis; (3) the analysis reason and diagnosis fields are editable; (4) supporting query by date; (5) supporting batch selection information and custom field information to be inserted into the current medical record; (6) after the analysis reason and the diagnosis are written on the current page, if the medical record is called and the current medical record is successfully stored, the analysis reason and the diagnosis data are stored, and the stored data are directly displayed when the medical record is called again to support editing. Description of the interface: 1. invoking a check; 2. checking the analysis reason or prompting when the corresponding information is not filled after diagnosis, and listing the corresponding unfilled categories in a prompt box to prompt characters: do the following check to see if a diagnosis or analysis reason is not filled in? Checking the analysis reason or diagnosis, when the analysis reason or diagnosis is not filled in, clicking a 'confirm' button to show that 'yes' in the prompt click prompt box, closing the prompt popup window, returning to the call check page to continuously fill the analysis reason or diagnose that 'no' in the click prompt box, closing the prompt popup window and calling the check page.

Function description of call verification: when the test is called, the abnormal information analysis and diagnosis are added; using roles: a physician; inputting: calling and checking; description of the drawings: (1) displaying the inspection and the past inspection information; (2) and (4) displaying fields: checking large item, specimen type, report date, organization, report item name, report item code, result, unit, normal reference value, analysis reason and diagnosis; (3) the analysis reason and diagnosis fields are editable. Description of the interface: 1. calling and checking; 2. checking the analysis reason or prompting when the corresponding information is not filled after diagnosis, and listing the corresponding unfilled categories in a prompt box to prompt characters: do the following check to see if a diagnosis or analysis reason is not filled in? Checking the analysis reason or diagnosis, when the analysis reason or diagnosis is not filled in, clicking a 'confirm' button to show that 'yes' in the prompt click prompt box, closing the prompt popup window, returning to the call check page to continuously fill the analysis reason or diagnosis and click 'no' in the prompt box, closing the prompt popup window and calling the check page.

The discharge summary is reformed as follows: all the operations of the intelligent doctor related to the required record are additionally provided with special record prompts for the operation course record, and the special record prompts can be automatically quoted in the discharge summary to prevent operation omission; and when the hospital discharge summary writing is finished and the storage is finished, the hospital discharge summary is popped out to remind whether no diagnosis and operation omission are confirmed. Function description of operation prompt record: all the operations of the intelligent doctor related to the required record are additionally provided with special record prompts for the operation course record, and the special record prompts can be automatically quoted in the discharge summary to prevent operation omission; using roles: a physician; description of the drawings: (1) clicking a prompt icon after the operation type medical advice to generate a disease course recording operation prompt; (2) clicking 'yes' goes to the template page where the operation is recorded, and specifically which set of templates automatically substitutes the initial data from the operation according to the operation concerned. Description of the interface: 1. prompting an entrance; 2. recording operation prompts, prompting characters: is the medical record forwarded to write the operation record? 3. If yes, jumping to a template writing interface of the record operation, specifically determining which template is according to the related operation, and automatically bringing the template writing page data into the template writing interface by the operation in the medical advice.

The hospital discharge summary storage prompt function description: when the writing of the discharge summary is finished and the storage is finished, the discharge prompt is given to remind whether no diagnosis and operation omission are confirmed or not, all abnormal values of inspection and examination are displayed, and one-key top setting is supported; using roles: a physician; inputting: clicking and saving; description of the drawings: (1) checking the information of the abnormal value and the inspection information; (2) after the diagnosis is input in the discharge record popup window, if the diagnosis is newly added, a prompt of whether to synchronize the new diagnosis to the discharge record and the first page of the medical record appears, and the selection is to add the new diagnosis to the discharge record and the first page of the medical record; (3) checking that outlier information supports "one key set all unprocessed items"; (4) check outlier presentation field: status, test major, report time, report item code, report item name, result, unit, normal reference value, analysis cause, diagnosis: the state: dividing into treated and untreated; red entries indicate no processing, black entries indicate processing; thirdly, analyzing reasons and editing diagnosis support; fourthly, the large items to be tested and the report item names support the screening function, the large items to be tested (report item names) related to the current abnormal values are listed for the user to select, and multiple selections are supported; (5) when checking the abnormal value form, expanding the table, wherein the large item contains the small item; (6) checking an information display field: status, examination item, report time, content, analysis cause, diagnosis; analyzing reasons and diagnosing support editing; state II: dividing into treated and untreated; red entries indicate unprocessed and black entries indicate processed. Description of the interface: 1. checking abnormal value information; taking all abnormal or critical data from the data of the abnormal value detection information; the processed and unprocessed judgment criteria are filling in analysis reasons and diagnosis; prompting characters: is the following all the examination checks, please confirm whether there is no diagnosis or missing surgical operation? Clicking 'check abnormal value information' in tab key above the prompt box; clicking the icons after checking the large items and reporting the item names to support screening; after checking all unprocessed items by one key, setting all unprocessed abnormal values or critical values; click analysis reasons and diagnosis may be edited. 2. Screening and inspecting large items; 3. screening report item names; 4. taking all inspection records from the inspection information data, wherein the processed and unprocessed judgment standards are filling in analysis reasons and diagnosis; clicking 'check information' in tab keys above a prompt box to check 'one key to set all unprocessed items', setting all the checked items with unfilled diagnosis or analysis reasons on the top, and clicking the analysis reasons and the diagnosis to edit; 5. the items without diagnosis are prompted in real time under the inspection and examination, and buttons are operated: no omission and closing: no prompt is given when the user clicks 'no omission and closing' and then saves the data again; and (3) cancelling: closing the current prompt, and continuing to operate the discharge knot; temporary non-treatment: closing the current prompt, successfully storing the discharge summary, and reminding again when storing again; 6. after clicking a button of 'no omission and closing', the system judges whether the diagnosis input by the doctor in the 'diagnosis' column exists in the previous medical record or not, if not, the system is a new diagnosis, and a popup prompt appears; the diagnosis supports self-check, and the doctor clicks 'OK', and then inserts the checked new diagnosis into the position of the discharge diagnosis in the discharge record and the medical record first page, the serial number is extended, and the character splicing format is unchanged.

The new technology and new project establishment special item is as follows: the function of a five-pointed star label is added, a new technical project special item is created, and an electronic account is provided for a special case document medical record in the future. Description of functional points: creating a new technical and new project special item, and providing an electronic standing book for a special case document medical record in the future; using roles: a physician; inputting: selecting a new technical and new project special item after the right key of the five-pointed star; after the right key of the five-pointed star, the special item of the personal new technology and new project is deselected; description of the drawings: (1) labeling the current medical record, and storing the current medical record to a personal center-technical medical record; (2) the medical records are collected to the individual center to support the viewing of the corresponding medical records and also support the cancellation of marks; description of the interface: 1. marking a new technical new project special item by the five-pointed star, and right-clicking the five-pointed star; 2. personal center-technical case history-new technical project special item, operating button: and (6) viewing: checking the corresponding medical record; canceling the mark: canceling medical record labels; 3. and checking the corresponding medical record.

The summary of the medical advice comments is: and summarizing and displaying the related information of the medical advice comment. Description of functional points: the method comprises the following steps of supporting medical advice review in a DRGs module, wherein the function supports the summary of review information (review total number, review person and review submission time) of a single medical advice; using roles: a physician; inputting: judging a system and prompting an interface; description of the interface: adding an icon behind the single medical advice, only the medical advice with the comment content appears, and if the medical advice has an operation record prompt and a medical advice comment prompt at the same time, operating the record icon in front; and clicking the icon to display an advice comment summarizing page containing information such as the total number of comments, the comment persons and the comment time.

The medical record modification identifier is as follows: because each grouped medical record has a chance to be modified before being settled, but the modification needs to be authorized by a medical record room and an information department, the intelligent medical record is well controlled by authority, and the modified medical record is well marked and reminded. Description of the function: because each grouped medical record has a chance to be modified before being settled, but the modification needs to be authorized by a medical record room and an information department, the intelligent medical record is well controlled by authority, and the modified medical record is well marked and reminded. Using roles: a physician; inputting: and judging by a system and prompting by an interface.

The content of checking the medical advice comment is as follows: and the DRGs support medical advice review in self-defined feedback and grouping summarization, and after the review is submitted, data of a reviewer, review contents and submission time are stored and displayed on a medical advice page. When the medical advice is commented, a commenting icon appears behind the medical advice, and the commenting content of the medical advice is clicked and checked. The popup for viewing the order comments contains the following information: statistics of number of comments, head portrait of the comment person, department of the comment person, name of the comment person, submission time of the comment and contents of the comment (how much the comment contents are displayed and not collected).

In this embodiment, the method for customizing DRGs of a patient includes: the doctor self-defines the DRGs of the patient according to the patient, wherein the self-defining of the DRGs comprises the following steps: a first diagnosis, a first operation and procedure, other diagnoses, other operations and procedures, gender, age, days of hospitalization, manner of discharge, referral, corresponding DRG group name, corresponding DRG group code, corresponding DRG group attribute, weight, DRG payment criteria, and rate for the year; the other diagnosis is a diagnosis other than the first diagnosis; the other surgery and operation is a surgery and operation other than the first surgery and operation; the DRGs custom feedback is as follows: the doctor carries out DRGs editing and medical insurance real-time feedback DRGs group related information comparison and self-review on the patient. Patient list function point description: selecting a patient to perform a series of operations of DRGs custom feedback; using roles: a physician; inputting: inquiring fields; description of the drawings: (1) click DRGs management-custom feedback occurs; (2) the display logics of the patient list inside the medical record and the patient list outside the medical record are different, all patients are displayed outside the medical record, a doctor selects to perform subsequent operation, and the data in the first row of the patient list inside the medical record displays the current patient; (3) the patient list supports screening of patients which are customized and not customized, and the customized is that customized grouping and storage are performed in a customized feedback popup window. Description of the interface: 1. patient list, patient list supports screening, patient is checked according to department, and time screening (admission time) is added at the patient list; displaying the basic information of the patient and the character link of the patient list above the customized feedback main interface, clicking the character link of the patient list to return to a page of the patient list, customizing the patient information of the feedback page, and distinguishing colors of blue color of green residents of staff; 2. the internal part of the medical record is a DRGs main page, a navigation bar is added to a DRG entrance in the medical record on the page, and the self-defined feedback and the statistical analysis are selected in a pull-down mode. Clicking the user-defined feedback to generate a user-defined popup of the patient, and clicking the statistical analysis to directly jump to a DRG subsystem page.

DRGs customization, function point description: the doctor carries out DRGs prediction filling on the patient; using roles: a physician; inputting: first diagnosis, first operation and operation, other diagnosis, other operation and operation, gender, age, number of hospitalizations, discharge pattern, referral, corresponding DRG group name, corresponding DRG group code, corresponding DRG group attribute, weight, DRG payment criteria, current year rate; description of the drawings: (1) the fields of the first diagnosis, other diagnoses, the first operation or operation, other operations or operations, the corresponding DRG group name, the corresponding DRG group code, the corresponding DRG group attribute, the weight and the like can be edited and always keep an editable state; (2) when a first diagnosis, a first operation or an operation is filled, the corresponding DRGS group name, the corresponding code and the corresponding attribute are automatically matched with the corresponding content of the primary knowledge base; (3) binding data such as a corresponding DRG group name, a corresponding DRG group code, a corresponding DRG group attribute, a weight and the like, and automatically taking out other three data after selecting the name or the code; (4) the three fields of the number of hospitalization days, the discharge mode and the transfer are data automatically taken out after the discharge summary is filled; the field is not displayed if the discharge summary is not filled; (5) the first diagnosis, the first operation or the operation is data synchronized from the first page of the medical record, and pull-down selection is supported; (6) the sex and the age are automatically brought out from the medical record; (7) if the nurse submits the discharge summary (the discharge summary is necessarily submitted if feedback exists), editing the first diagnosis, other diagnoses, the first operation or operation, clicking a storage prompt to modify the discharge summary after other operations or operations, clicking a button of 'going to the discharge summary' to jump to a discharge summary page, and automatically substituting data; no prompt information appears when the corresponding DRG group name, the corresponding DRG group code, the corresponding DRG group attribute and the weight are modified; (8) if the nurse does not submit the discharge summary, editing the self-defined data without prompting; (9 if the case history is filed, clicking a 'save' button to prompt to go to an enterprise for WeChat cancel filing, and the cancel application can go to discharge after passing the cancel summary modification; (10) adding fields under 'relegation' in a feedback result, wherein the fields comprise DRG payment standard, upload fund, settlement fund (calculated according to a calculation formula of a normal group, a basic group, an ultra-high normal, an ultra-low normal, an ultra-high foundation, an ultra-low foundation, a non-group, a special case and the like), balance and settlement rate, the first feedback and the final feedback are required to be increased, and according to actual feedback display, interface description 1, DRGs are self-defined, the fields are in default approval editing state, the 'save' button and the 'go to discharge summary' button are grayed before the doctor is not modified, and are in a locking state, and if the first diagnosis, other diagnoses, the first operation or operation, other operations or operation fields in the self-defined state, the 'save' button and the 'go to discharge summary' button are changed into a clickable state, and the user-defined state is clicked Toast appears above the interface to remind, and suspension prompt appears above the button of 'go to discharge summary'. If the modified corresponding DRGs group name, the corresponding DRGs group code and the corresponding DRGs group attribute are obtained, the 'save' button and the 'go to discharge bar' button are both lightened, but no prompt appears above the 'go to discharge bar' button. 2. And (5) discharging a small knot. 3. Prompting to go to enterprise WeChat to cancel modification, prompting characters: the patient's medical record is filed and please go to the enterprise to apply for revocation of filing! The system judges whether the medical record is filed or not, if yes, clicking 'save' to enable the prompt popup window, and clicking 'confirm' or 'x' in the popup window to close the prompt popup window.

In this embodiment, the method for acquiring the feedback result of the DRGs includes: comparing the self-defined DRGs with the medical insurance to obtain comparison information, and judging the comparison information as first feedback or final feedback; the first feedback and the final feedback both comprise: feedback of outcome, health care DRG group, health care DRG code, health care weight, diagnosis, surgery or procedure, days of hospitalization, age, manner of discharge, outcome, other, cause of inconsistency, whether first diagnosis is adjusted, whether first surgery or procedure is adjusted, severe complications, and complications; storing the self-defined DRGs when the first feedback result is consistent; updating the self-defined DRGs when the first feedback result is inconsistent;

the method for optimizing the DRGs knowledge base according to the feedback result of the DRGs comprises the following steps: comparing the self-defined DRGs with DRGs data stored in a DRGs knowledge base; selecting comparison fields, and respectively acquiring the word frequency of each comparison field of the custom DRGs and the word frequency of each comparison field of DRGs data selected from a DRGs knowledge base for comparison; acquiring the word frequency quantity of the custom DRGs and the DRGs data for comparison according to the word frequency of the comparison field, and judging the similarity degree according to the two word frequency quantities;

updating the DRGs knowledge base according to the similarity degree; when there is no repetition, storing the self-defined DRGs in a DRGs knowledge base; when the data is repeated, the custom-defined data of the hospitalization days, the sex, the outcome, the severe complications, the complications and the complications in the DRGs is stored in a DRGs knowledge base.

First feedback/final feedback, functional point description: the DRGs and the medical insurance comparison information are fed back in real time, and the medical record can be examined and approved by self; using roles: a physician; inputting: click first feedback/final feedback, including information: feedback of outcome, health care DRG group, health care DRG code, health care weight, diagnosis, surgery or procedure, days of hospitalization, age, manner of discharge, outcome, other, cause of inconsistency, whether first diagnosis is adjusted, whether first surgery or procedure is adjusted, severe complications, complications; description of the drawings: (1) when feedback exists, adding a mark reminding on the DRGs management big module; (2) displaying the part of content when a feedback result exists; (3) the system judges whether the feedback is the first feedback or the final feedback and shows the feedback on the title; (4) the fields of the inconsistency reason, whether the first diagnosis is adjusted or not, whether the first operation or operation is adjusted or not, serious complications, complications and the like can be edited and can be kept in an editable state all the time; (5) when diagnosis, operation or operation modification is involved, after the 'storage' is clicked, the information in the DRGs self-definition is updated in real time; (6) when the first feedback result is consistent, storing filling data, extracting data and comparing the data with a knowledge base (no repeatedly adding a piece of knowledge base data, and repeatedly and directly adding the hospitalization days, sex, outcome, severe complications and complications data), wherein eleven points in each day of night are used for counting and recording feedback information from eleven points in the previous day to eleven points in the same day of night; (7) when the final feedback result filling information is stored, extracting data and comparing the data with a knowledge base (no repeatedly adding a piece of knowledge base data, and repeatedly and directly adding the days of hospitalization, sex, outcome, severe complications and complications data) — counting and recording feedback information from eleven points in the previous day to eleven points in the same day every night; the comparison method comprises the following steps: an existing piece of data is retrieved from the knowledge base. The fields of hospital days, sex, outcome, severe complications, complications and complications are taken as the comparison fields. The fields in the two pieces of data are merged. And then respectively calculating the field word frequency of each piece of data.

For example:

data a 3 days, male, cured, diabetes, acute myocardial infarction, heart failure;

data B8 days, male, transfer, hypertension, acute myocardial infarction, coronary atherosclerosis/thrombosis/occlusion;

the more similar the words of the two words, the more similar their contents should be. Therefore, the similarity degree of the words can be calculated by starting from the word frequency; list all words 3 days, male, cured, diabetes, acute myocardial infarction, heart failure, 8 days, transfer, hypertension, coronary atherosclerosis/thrombosis/occlusion; calculating word frequency: data a:3 days 1, male 1, cure 1, diabetes 1, acute myocardial infarction 1, heart failure 1, 8 days 0, transfer 0, hypertension 0, coronary atherosclerosis/thrombosis/occlusion 0; data B: day 3 0, male 1, cure 0, diabetes 0, acute myocardial infarction 1, heart failure 0, day 8 1, transfer 1, hypertension 1, coronary atherosclerosis/thrombosis/occlusion 1; writing out word frequency quantity: data A: (1, 1, 1, 1, 1, 1, 0,0, 0, 0); data B: (0, 1, 0,0, 1, 0, 1, 1, 1, 1); they can be thought of as two line segments in space, both pointing from the origin ([0, 0. ]) in different directions. An included angle is formed between the two line segments, if the included angle is 0 degree, the direction is the same, the line segments are overlapped, and the fact that the texts represented by the two vectors are completely equal is shown; if the included angle is 90 degrees, the right angle is formed, and the directions are completely dissimilar; if the angle is 180 degrees, it means the direction is exactly opposite. Therefore, the similarity degree of the vectors can be judged according to the size of the included angle. The smaller the angle, the more similar.

According to the formula

The degree of similarity of the two data was calculated:

cos(θ)＝(1*0+1*1+1*0+1*0+1*1+1*0+0*1+0*1+0*1+0*1)/(√(1²+1²+1²+1²+1²+1²+0²+0²+0²+0²)×√(0²+1²+0²+0²+1²+0²+1²+1²+1²+1²) 0.33); the cosine value of the angle in the calculation result is 0.33 not close to 1, so the above data a and data B are not similar.

And when the final feedback result filling information is stored, extracting data and comparing the data with a knowledge base (no repeatedly adding a piece of knowledge base data, and repeatedly and directly adding the days of stay, sex, outcome, severe complications and complications data) — counting and recording the feedback information from eleven points in the previous day to eleven points in the current day every night.

Description of the interface: 1. a feedback result mark is provided; 2. the feedback results are inconsistent, the filling data are stored when the first feedback result is consistent, the extracted data are compared with the knowledge base (a knowledge base data is not repeatedly added, the number of days of hospitalization, sex, outcome, severe complications, complications and complications are repeatedly and directly added), and the extracted data are compared with the knowledge base (a knowledge base data is not repeatedly added, the number of days of hospitalization, sex, outcome, severe complications, complications and complications are repeatedly and directly added) when the feedback result filling information is stored; 3. the feedback results are consistent, the 'DRGs feedback' items under the click customization are expanded, and the items are clicked again for collection; and when the content is not modified, the save button is grayed, after the content is modified, the save button is lightened and can be clicked, and the customized first diagnosis, other diagnoses, the first operation or operation is synchronously updated after clicking. And after the modified content is clicked and stored, the storage button is grayed again, and then is lightened when modified, and the logic is the same as that of the above.

Feedback result notification, functional point description: when a feedback result exists, adding a reminder in the system; using roles: a physician; inputting: feeding back a result; description of the drawings: (1) adding marks on the DRGs management headlines; (2) adding DRGs feedback in a message notification module; description of the interface: 1. DRGS manages large title identification; 2. a DRGs feedback module is added in the message center;

and (4) viewing medical records, and describing function points: providing medical record reference when filling in DRGs; using roles: a physician; inputting: searching for key words; description of the drawings: (1) supporting keyword search and intelligent recommendation search; (2) counting search results, and supporting one-by-one check; (3) highlighting a search result; (4) and linking and positioning the search result to the medical record, and when the search result page clicks the 'custom feedback' again, the jumped-out DRGs management page is in a state of expanding the medical record. Description of the interface: 1. viewing a medical record; clicking a self-defined medical record entry to expand, clicking and retracting again, inputting a keyword by a search box, starting to inquire by a keyboard entry key or a click query button, highlighting a query result, distinguishing the currently viewed search result from other search results in colors, clicking a left marked directory column or a right search result page to jump to a medical record page, and adding underlines when a mouse moves into a clickable link; 2. the medical record is linked to the medical record, the search result is linked to a page corresponding to the medical record, the search result is highlighted, and when the page of the search result is clicked again for DRGs management-custom feedback, the page is a page which is fed back to the medical record link (namely, a page for selecting the patient and expanding the medical record);

checking medical orders and describing function points: providing advice reference when filling in DRGs; using roles: a physician; inputting: searching for key words; description of the drawings: (1) supporting keyword search and intelligent recommendation search; (2)

counting search results, and supporting one-by-one check; (3) highlighting a search result; (4) clicking any field to support medical advice comment; the recommendation query is carried out through association rules, the association rules reflect the interdependency and the association between one thing and other things, and if a certain association relationship exists between two or more things, one thing can be predicted through other things. For example, if a doctor writes a cold diagnosis for a patient, a cold medicine is generally prescribed, or a patient with fever is generally prescribed a blood routine test. Therefore, the combined data of the diagnosis and the medical advice of each patient can be inquired through background data to calculate the medical advice which is most suitable for recommendation;

specific analysis results are as follows: first scanning: counting each candidate combination to obtain C1, deleting { D } to obtain a frequent 1-item set L1 because the support count of the candidate { D } is 1< the minimum support count of 2; and (3) second scanning: generating candidate C2 from L1 and counting the candidates C2, comparing the candidate support count with the minimum support count of 2-term frequent sets L2; and (3) third scanning: the process of concatenating and pruning L2 to produce the candidate 3 item set C3 is as follows: 1, C3 ═ L2 (link)

Then) L2 { { a, C }, { B, E }, { C, E } } { { a, B, C }, { a, C, E } } { { B, C, E }; 2, { a, B, C } and { B, C }, wherein { a, B } is not the 2-item subset L2, and therefore is not frequent, is deleted from C3; the 2 item subsets of { A, C, E } { A, C }, { A, E } and { C, E }, where { A, E } is not the 2 item subset L2 and is therefore not frequent, are deleted from C3; the 2 item subsets of { B, C, E } { B, C }, { B, E } and { C, E }, all of its 2 item subsets being elements of L2, are reserved in C3. After the L2 is connected and pruned, the set of candidate 3 item sets is generated as C3 ═ { B, C, E }. when the candidate set is counted, the 3-item set L3 is frequent since it is equal to the minimum support metric number of 2, and at the same time, C4 is an empty set since there are only 1 of 4-item sets, the algorithm terminates. The frequent item set is divided into two subsets which are respectively used as a front piece and a back piece, and the frequent item set is converted into a rule with enough confidence; if the rule R: x ═ Y satisfies support (X ═ Y) > _ supmin (minimum support, which is used to measure the minimum importance that the rule needs to satisfy) and confidence (X ═ Y) > _ confmin (minimum confidence, which represents the minimum reliability that the association rule needs to satisfy) call the association rule X ═ Y as a strong association rule, otherwise call the association rule X ═ Y as a weak association rule. The existing A, B, C, D, E patient record tables of five orders are used to find out all frequent item sets, assuming that the minimum support > is 50% and the minimum confidence > is 50%. For the association rule R: a > B, then: support (support): is the ratio of the number of combinations in the set that contain both A and B to all combinations. Support (a ═ B) ═ P (a ═ B) ═ count (a ═ B)/| D |; confidence (confidence): is the ratio of the number of combinations comprising A and B to the number of combinations comprising A. Configence (a ═ B) ═ P (B | a) ═ support (a ═ u B)/support (a); the calculation procedure is as follows, and when K is 1, the term set { a } appears 2 times in T1 and T3 for 4 combinations, so that the support degree is 2/4 is 50%, which are calculated in sequence. Where the set of terms { D } occurs at T1 with a support of 1/4-25% and less than 50% of the minimum support, so removed to yield L1. And combining the item sets L1 pairwise, and calculating the support degrees respectively, wherein the item sets { A, B } appear 1 time in T3, the support degree is 1/4-25%, and is less than the minimum support degree by 50%, so that the L2 item sets are obtained by the same method. The set of items in L2 is combined, with more than three items being filtered, and the final calculation yields the L3 set of items { B, C, E }. Description of the interface: 1. viewing the medical order, and displaying the field content of the medical order comprises the following steps: start time, type, content, usage, frequency, notes; clicking a self-defined medical record entry to expand, clicking again to retract, inputting a keyword into a search box, starting to inquire by clicking an enter key or a query button on a keyboard, highlighting a query result, and distinguishing the currently viewed search result from other search results in colors; 2. the method comprises the steps of commenting the medical advice, clicking fields such as the type, the content, the usage, the frequency and the remarks of the medical advice to display the commenting content, adding underlines to the content when a mouse moves in, clicking to cancel and close a commenting frame, clicking to confirm and close if no comment content page displays a comment input prompt, clicking to confirm and close the commenting frame if the comment exists, and storing the commenting content into a database.

Checking a settlement list, and describing function points: providing settlement list reference when filling in DRGs; using roles: a physician; inputting: searching for key words; description of the drawings: (1) if feedback exists, the part of the content exists; (2) supporting keyword search and conditional query; (3) and highlighting a search result. Description of the interface: 1. viewing a settlement list, wherein the field of displaying the settlement list comprises: item type, pricing date, item name, specification, unit, quantity, unit price, amount, valuator, executive department, billing department, accounting source; clicking the 'settlement list' item under the self-definition to expand, clicking again to retract, inputting a keyword into the search box, starting to inquire by clicking an 'enter' key or a 'inquiry' button, and displaying category information meeting the inquiry condition after inquiring.

Checking, function point description: providing inspection information reference when filling in DRGs; using roles: a physician; inputting: searching for key words; description of the drawings: (1) supporting keyword search and intelligent recommendation search; (2) counting search results, and supporting one-by-one check; (3) and highlighting a search result. Description of the interface: 1. viewing a check, displaying a check field comprising: examination item, report time, content, analysis reason; clicking the self-defined 'check' item to expand, clicking again to retract, inputting a keyword into the search box, starting to inquire by clicking an 'enter' key or a 'inquiry' button on the keyboard, highlighting and prompting the inquiry result, and distinguishing the currently viewed search result from other search results in colors.

Checking and checking, and describing a function point: providing inspection information reference when filling in DRGs; using roles: a physician; inputting: searching for key words; description of the drawings: (1) supporting keyword search and intelligent recommendation search; (2) counting search results, and supporting one-by-one check; (3) and highlighting a search result. Description of the interface: 1. viewing a check, displaying a check field comprising: checking large items, report time, report item codes, report item names, results, units, normal reference values, analysis reasons and diagnosis; clicking the self-defined 'check' item to expand, clicking again to retract, inputting a keyword into the search box, starting to inquire by clicking an 'enter' key or a 'inquiry' button on the keyboard, highlighting and prompting the inquiry result, and distinguishing the currently viewed search result from other search results in colors.

Reference, functional point description: when filling in DRG information, providing data references such as specification files and the like; using roles: a physician; inputting: searching for key words; description of the drawings: (1) clicking a 'reference data' text link at the upper left corner of the user-defined feedback page to appear; (2) the file supports preview, addition, batch downloading and batch deletion; (3) the preview file supports the query function and highlights the prompt; (4) the file list displays uploading time, file names (including file types) and operations; (5) the files are stored in different categories. Description of the interface: 1. the files are stored in different categories, when the files are deleted or downloaded in batches, the selected number is marked on the button, and the button is operated: local uploading: uploading a local file to a system; downloading: downloading files to the local to support batch downloading; and (3) deleting: deleting files from the system, and supporting batch deletion; and (3) cancelling: and closing the pop-up window. 2. Previewing the file, supporting the query function and displaying the information of the uploader; clicking a file preview page with a file name appearing, keeping the size of a pop-up window unchanged, inputting a keyword into a search box, starting to inquire by using an enter key or a query button of a keyboard, highlighting a query result, and distinguishing the color of the currently viewed search result from the color of other search results; click downloading: and downloading the preview file to the local.

The enterprise wechat examination and approval is that each entered medical record has a chance to be modified before being settled, but the modification needs to be authorized by a medical record room and an information department, authority control is performed in the intelligent medical record, and obvious identification reminding is performed on the modified medical record. DRGs archive revocation, functional point description: and (4) carrying out revocation application on medical records filed by the DRGs by using enterprise WeChat. Using roles: a physician; inputting: the physician approves; and (3) treatment: the physician fills out the approval application form and submits it to the chief deputy. The department is approved by a long time, and the functional points are described as follows: and (4) carrying out revocation application and verification on medical records filed by the DRGs by using enterprise WeChat. Using roles: the clinical department takes charge of the principal and subordinate; inputting: checking the clinical department director; and (3) treatment: the clinical department master enters the examination and approval function module.

Grouping and summarizing DRGs grouping conditions; description of the function: gathering DRGs grouping conditions to embody feedback state information; using roles: a physician; inputting: when the user-defined information is stored; description of the drawings: (1) clicking the DRGs management-grouping summary of the upper navigation bar; (2) and (4) displaying fields: first feedback, final feedback, hospital number, patient name, patient gender, patient age, department, attending physician, diagnosis, surgery or procedure, discretionary DRG group name, discretionary DRG group code, discretionary RW, medicare DRG group name, medicare DRG group code, medicare RW; (3) displaying field support customization; (4) first feedback and final feedback: the method is divided into consistent feedback, medium feedback and consistent feedback. If no feedback result shows 'none'; (5) click expansion is carried out, and advanced query is supported; (6) clicking the hospital number to support checking details, checking medical records, checking medical advice and checking a settlement list; viewing an advice support review function; (7) all fields support sorting; (8) exporting the data support, generating an EXCEL file and storing the EXCEL file to the local; (9) data is taken from all patients with customized grouping information; (10) grouping summaries add data for the expected balance: support viewing of predicted balance of department or doctor or disease group. Description of the interface: 1. grouping and summarizing, wherein when data is displayed, the position is frozen in the first row; 2. grouping summaries add data for the expected balance: the system supports the viewing of the predicted balance condition of a department, a doctor or a disease group, the data of the predicted balance needs to be subjected to mutual exclusion processing, namely, only one data is needed, the system judges, the data fed back finally is subjected to judgment if the two times of feedback exist, and the data fed back firstly is subjected to judgment if the two times of feedback exist. Clicking the field of the predicted balance to jump out of a pop-up window, and displaying the respective predicted balance conditions of the department, the disease group and the main doctor. 2. Advanced query, clicking and expanding, wherein the search conditions displayed by the advanced search are based on fields displayed by self definition of a doctor, the doctor selects which rows of data to view, and then searches corresponding to which rows of data appear, and the drop-down list box item comprises all drop-down list boxes by default and all drop-down list boxes support input query: feeding back for the first time: all, consistent feedback and inconsistent feedback; and (3) final feedback: all, consistent feedback and inconsistent feedback; department: all, all department names; the name and the hospitalization number are input boxes supporting fuzzy query; sex of the patients: male, female, unknown gender; the patient age is an input box; the attending physician: all, all physician names; a first diagnosis: all, all diagnostic names; a first procedure or operation: all, all surgery or procedure names; self-selecting DRGs group name: all, all DRGs group names in the own library; self-selecting DRGs codes: DRGs group codes in all and all owned libraries; selecting RW: RW weights corresponding to DRGs groups in all and all owned libraries; medical insurance DRGs group name: DRGs group names of all medical insurance feedbacks; medical insurance DRGs codes: DRGs group codes of all medical insurance feedbacks; medical insurance RW: and all RW weights corresponding to the DRGs groups fed back by the medical insurance. 3. Export is supported, the survival EXCEL file is stored to the local, and when data is not selected, an export button is in a locked state and cannot be clicked. 4. And customizing the display field, and clicking the corresponding key to appear. 5. Clicking the patient number of hospitalization to select to view details, viewing medical records, viewing medical advice and viewing settlement lists, and clicking the patient number of hospitalization again or other blanks to pack. 6. Reviewing details, showing the medical insurance DRG group, medical insurance DRG codes, medical insurance weights, diagnoses, operations or procedures, days of hospitalization, age, manner of discharge, others, outcome, reasons for compliance (inconsistency), whether a first diagnosis is adjusted, whether a first operation or procedure is adjusted, severe complications, complications; and (3) storing and displaying the data twice with the two feedback results: the header position freezing (i.e. the content in the green frame) only feeds back the result once; and feeding back results twice. 7. The medical record checking method comprises the steps of checking medical advice, 8, 9, checking the medical advice-comment function, clicking fields such as the type, content, usage, frequency and remarks of the medical advice on a page of the checked medical advice to evaluate, adding underlines to the content when a mouse moves in, clicking to cancel a comment closing frame, clicking to confirm if no comment content page is clicked to input a comment prompt, clicking to confirm if the comment exists, closing the comment frame, and storing the comment content in a database. 9.1 comment box component, 1, the current comment doctor name, 2, comment content writing area, 3, operation button cancel: closing the pop-up window and commenting: and submitting the comment content. 10. And checking the settlement list.

Example 2

On the basis of embodiment 1, this embodiment 2 further provides a DRGs submission feedback system, which includes: the database module is used for constructing a DRGs knowledge base; the medical record optimizing module is used for optimizing the medical record of the patient; the feedback module is used for self-defining the DRGs of the patient and acquiring a feedback result of the DRGs; and the knowledge base optimization module is used for optimizing the DRGs knowledge base according to the feedback result of the DRGs.

In this embodiment, specific functions of each module have been described in detail in embodiment 1, and are not described in detail in this embodiment.

In conclusion, the invention constructs the DRGs knowledge base; optimizing the medical record of the patient; self-defining DRGs of a patient and acquiring a feedback result of the DRGs; and optimizing the DRGs knowledge base according to the feedback result of the DRGs, realizing partial data counted by each department and the ordinary operation record of the doctor, calculating the most reasonable drg groups by using a special algorithm, recommending the information to the doctor, comparing the DRGS in the event with the real-time feedback information of the medical insurance after the event, and leading the doctor to have self-comparison and error summary

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims

1. A DRGs submission feedback method is characterized by comprising the following steps:

constructing a DRGs knowledge base;

optimizing the medical record of the patient;

2. The DRGs submission feedback method of claim 1 wherein,

the method for constructing the DRGs knowledge base comprises the following steps:

3. The DRGs submission feedback method of claim 2 wherein,

the method for optimizing the medical record of the patient comprises the following steps:

4. The DRGs submission feedback method of claim 3, wherein the step of receiving the feedback information from the DRGs submission engine,

the method for customizing DRGs of a patient comprises the following steps:

the other diagnosis is a diagnosis other than the first diagnosis;

5. The DRGs submission feedback method of claim 4 wherein,

the method for acquiring the feedback result of the DRGs comprises the following steps:

storing the self-defined DRGs when the first feedback result is consistent;

6. The DRGs submission feedback method of claim 5 wherein,

the method for optimizing the DRGs knowledge base according to the feedback result of the DRGs comprises the following steps:

comparing the self-defined DRGs with DRGs data stored in a DRGs knowledge base;

updating the DRGs knowledge base according to the similarity degree;

7. A DRGs submission feedback system, comprising:

the database module is used for constructing a DRGs knowledge base;