CN106682439A - Investigational follow-up based medical record screening method - Google Patents
Investigational follow-up based medical record screening method Download PDFInfo
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- CN106682439A CN106682439A CN201611270995.9A CN201611270995A CN106682439A CN 106682439 A CN106682439 A CN 106682439A CN 201611270995 A CN201611270995 A CN 201611270995A CN 106682439 A CN106682439 A CN 106682439A
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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- 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
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Abstract
The invention discloses an investigational follow-up based medical record screening method. The method includes: initializing main dimensionalities and sub-dimensionalities for screening; allowing a user to set screening conditions according to demands, and adopting a keyword screening method to input to-be-screened keywords under corresponding dimensionalities so as to complete screening condition setup after confirmation; screening, to be more specific, firstly, importing historical medical records of a department into a medical record screening system through an interface; secondly, screening the imported medical records one by one according to the screening conditions set in the above step; thirdly, performing statistics of occurrence of hospitalization numbers under the main dimensionalities and the sub-dimensionalities, associating the hospitalization numbers with files of patients, regulating to generate a five-level summary table which includes complete information of the patients, and showing to users. According to different diagnosis and treatment way standards, electronic medical records in the system are analyzed to screen out medical records in accordance with research direction, and a follow-up list is obtained after regulation, so that medical record screening efficiency of researchers can be effectively improved, and the screening error rate is decreased.
Description
Technical field
The present invention relates to field of medical technology, particularly relates to a kind of case history screening technique based on research follow-up.
Background technology
Follow-up is a kind of important means in clinical research, refer to hospital to once the patient of hospital admission with communicate or other
Mode, periodically understood conditions of patients change and instructed a kind of observational technique of Rehabilitation.By follow-up, doctor can be with
Understand the recovery situation after patient discharge, grasp the firsthand information to carry out statistical analysiss, accumulate experience, judge the effect of diagnosis and treatment
Really, it is significant to clinical research.In order to draw follow-up list, doctor needs the purpose according to research, the history to section office
Case history is screened, and filters out the case history related to research and sick list, and then carries out follow-up.The current sieve to hospital's case history
Based on artificial operation, error rate is high, and inefficiency wastes time and energy, and needs a kind of method of computational screening case history for choosing.
Therefore, it is necessary to design a kind of new case history screening technique based on research follow-up, asked with solving above-mentioned technology
Topic.
The content of the invention
For problem present in background technology, it is an object of the invention to provide a kind of case history based on research follow-up is sieved
Choosing method, according to different diagnosis, therapeutic modality standard, is analyzed to the electronic health record in system, filters out and meets research
The case history in direction, arrangement draws follow-up list, can effectively improve screening efficiency of the research worker to case history, reduces screening error
Rate.
The technical scheme is that what is be achieved in that：A kind of case history screening technique based on research follow-up, including with
Xia Bu Sudden：(1) initialization operation：Each dimension for being screened of initialization, each dimension is divided into different main dimension and subordinate
The many sub- dimensions under each main dimension；(2) screening conditions arrange operation：User arranges according to demand screening conditions, using pass
Keyword screening method, is input into key word to be screened under corresponding dimension, screening conditions is completed after confirmation and arranges operation；
(3) screening operation：Firstly, it is necessary to by the history case history of this section office, Jing interfaces are imported in case history screening system；Subsequently, importing
Case history according to above-mentioned steps arrange screening conditions screen portionwise；(4) Classifying Sum operation：Statistics admission number is in main dimension
Situation about occurring under lower and sub- dimension, admission number is associated with patient files, is arranged and is generated the Pyatyi comprising patient's complete information
Summary sheet presents to user.
In above-mentioned technical proposal, the main dimension includes the main dimension of diagnosis and the main dimension of therapeutic modality.
In above-mentioned technical proposal, the main dimension of the diagnosis and the main dimension of therapeutic modality are divided into respectively 4 sub- dimensions.
In above-mentioned technical proposal, the main dimension of the diagnosis is divided into AD, discharge diagnosis, pathological diagnosis and inspection and examines
Disconnected sub- dimension.
In above-mentioned technical proposal, the main dimension of the therapeutic modality is divided into modus operandi, medicine, test mode and shield
The sub- dimension of reason mode.
In above-mentioned technical proposal, arranging key word under the main dimension of the diagnosis can count AD, discharge diagnosis, disease
Reason diagnosis and the sub- dimension dependency summary sheet of inspection diagnosis.
In above-mentioned technical proposal, the Pyatyi summary sheet includes the main dimension summary sheet of diagnosis of the first order, the second level
AD, discharge diagnosis, pathological diagnosis and each summary sheet of the sub- dimension of inspection diagnosis, the AD of the third level and discharge diagnosis
And pathological diagnosis and check the sub- dependency summary sheet of dimension of diagnosis, the main dimension summary sheet of therapeutic modality of the fourth stage and the
Any one sub- dimension summary sheet in the modus operandi of Pyatyi, medicine, test mode and the sub- dimension of nursing care mode.
In above-mentioned technical proposal, patient's complete information includes name corresponding with admission number, sex, age, electricity
Words number.
Comparing artificial screening method wastes time and energy, less efficient, needs to pay higher human cost, and the present invention is based on and grinds
The case history screening technique of the property studied carefully follow-up, by initializing each dimension screened, screening conditions arrange operation and screen behaviour
Make and Classifying Sum operation, the lengthy procedure of artificial screening check and correction can be exempted, it is according to different diagnosis, therapeutic modality mark
Standard, is directly analyzed by computer to the electronic health record in system, filters out the case history for meeting research direction, and arrangement draws
Follow-up list, can effectively improve screening efficiency of the research worker to case history, reduce screening error rate.
Description of the drawings
Fig. 1 is case history screening technique schematic flow sheet of the present invention based on research follow-up；
Fig. 2 is screening operation particular flow sheet in Fig. 1.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than the embodiment of whole.Based on this
Embodiment in invention, the every other reality that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example is applied, the scope of protection of the invention is belonged to.
As shown in figure 1, a kind of case history screening technique based on research follow-up of the present invention, comprises the following steps：
(1) initialization operation：Mainly initialize each dimension screened.Wherein, two main dimensions are divided into diagnosis master
Dimension and the main dimension of therapeutic modality, two main dimensions can proceed subdivision again, in the present embodiment, diagnose main dimension and control
The main dimension for the treatment of mode is divided into respectively 4 sub- dimensions, diagnoses main dimension and is divided into AD, discharge diagnosis, pathological diagnosis and inspection
Look into the sub- dimension of diagnosis；The main dimension of therapeutic modality is divided into the sub- dimension of modus operandi, medicine, test mode and nursing care mode, such as
Shown in table 1 below：
Table 1
(2) screening conditions arrange operation
User according to demand, arranges the condition of screening.Screening adopts key word screening method, and user is defeated under corresponding dimension
Enter key word to be screened, screening conditions are completed after confirmation operation is set.Screening conditions need not be arranged each, can be with
Arrange under diagnosis or therapeutic modality the two big dimensions, it is also possible to the setting in breakdown under two big dimensions.
Multiple key words can be screened under same dimension.It is as shown in table 2 below：
Table 2
(3) screening operation：
As shown in Figure of description 2, firstly, it is necessary to by the history case history of this section office, via certain interface, import case history
In screening system.After importing via interface, the various pieces of electronic health record can be recognized by case history screening system, so as to filter out pass
Keyword.
Subsequently, screen portionwise in the case history for importing.If in key word is arranged under " diagnosis " this main dimension, in son
Key word is not provided with dimension, then case history in AD, discharge diagnosis, pathological diagnosis and will be checked diagnosis four respectively
Individual part is screened respectively one time, is retrieved once in certain sub- dimension, and being in hospital for the case history is just recorded under corresponding sub- dimension
Number once.So as to each one table of self-generating of four sub- dimensions.After having screened a patient, into the case history of next patient
Screened, till whole case histories have been screened.
After having screened, four sublists are collected, as long as occurring in four dimensions, just record at summary table and be in hospital
Number, draw the related summary table of being in hospital of a diagnosis.If being not provided with key word under " diagnosis " this main dimension, only in sub- dimension
Degree is lower to arrange key word, then just in the corresponding part search key of each part case history, after retrieving key word, just in the sublist
Lower record admission number.Summary table need not be aggregated into after having screened.After " diagnosis " this dimension has been screened, enter " therapeutic modality " this
Dimension is screened.The screening of this dimension is on the basis of upper dimension, only to screen in upper dimension
Screen in case history.If in arranging key word under " therapeutic modality " main dimension, then will be by case history in modus operandi, treatment
Medicine, test mode, four parts of nursing care mode are retrieved respectively once, are retrieving once per individual sub- dimension, just corresponding
The admission number of the case history is recorded under sub- dimension once.So as to each one table of self-generating of four sub- dimensions.
After having screened a patient, the case history into next patient is screened, and has been screened until whole case histories and is
Only.After having screened, four sublists are collected, as long as occurring in four dimensions, admission number is just recorded at summary table, obtained
Go out the related summary table of being in hospital of a therapeutic modality.
If being not provided with key word under " therapeutic modality " this sub- dimension, and key word is set under sub- dimension, that
Just in the corresponding part search key of each part case history, after retrieving key word, just admission number is recorded under the sublist.Screening
Summary table need not be aggregated into after complete.Any key word can not be set in diagnosis dimension and only key word is set in therapeutic modality dimension,
Any key word can not also be set in therapeutic modality and only key word is set in diagnosis dimension.
(4) Classifying Sum operation：Two dimensions are divided into into different sub- dimensions, are numbered respectively, it is as shown in table 3 below：
Table 3
After the completion of previous action, 10 tables are at most generated, be respectively that A, A1, A2, A3, A4, B, B1, B2, B3, B4 are common
Table under 10 dimensions.If being to arrange key word under " diagnosis " main dimension, can generate under " diagnosis " dimension A, A1,
A2, A3, A4 totally five tables, if in key word is arranged under sub- dimension, can only generate the one or several sheets under the sub- dimension of correspondence
Table.It is as the same under " therapeutic modality " dimension.
If being that key word is arranged under " diagnosis " main dimension, system can statistic correlation.If an admission number
All occur in four sublists, then record admission number in " A1+A2+A3+A4 " table, if all gone out in tri- tables of A1, A2, A3
Show, then the admission number in " A1+A2+A3 " table.The rest may be inferred, and symbiosis is into 15 tables.
Because there is no comparability under " therapeutic modality " dimension between each project, correlation statistics are not carried out.Generate with
After upper form, enter and collect operation, collect for 5 levels：
I levels：A dimension summary tables.Under the key word that " diagnosis " main dimension is arranged, any subitem is related to the case history of key word
Admission number all can be recorded in this one-level table, if being not provided with key word under " diagnosis " main dimension, this grade of table is not deposited
.
II levels：Under " diagnosis " each sub- dimension, there is the admission number of the case history of key word, if in the main dimension of diagnosis
With any key word is not filled under sub- dimension, this one-level table is not present.
III level：Dependency table.This one-level has 15 tables, and the feelings that this key word occurs in each project are represented respectively
Condition, if not filling in any key word under the main dimension and sub- dimension of diagnosis, this one-level table is not present.
IV levels：B dimension summary tables.In screened case history inventory is diagnosed, it is related to " therapeutic modality " target critical
The admission number inventory of the case history of word, if not filling in any key word under the main dimension and sub- dimension of therapeutic modality, this
Level table is not present.
V levels：Under " therapeutic modality " each sub- dimension, there is the admission number of the case history of key word, if in therapeutic modality
Main dimension and sub- dimension under do not fill in any key word, this one-level table is not present.
After generating the table of above-mentioned five ranks, admission number is associated with patient files, sorts out name, the property of patient
Not, the information needed of contact method, generates the Pyatyi summary sheet comprising patient's complete information, presents to user.
It is as follows an instantiation explanation：Now three parts of case histories are had in the case history storehouse of Digestive System Department, its diagnosis and treatment situation is such as
Shown in table 4 below：
Table 4
The key word of setting is as shown in table 5 below：
Table 5
Key word " digestive tract hemorrhage " is set in " diagnosis " main dimension, following four sublists and a summary table is obtained：
A1：
| 10002 | 10003 |
A2：
| 10002 |
A3：
A4：
| 10002 | 10003 |
A：
| 10002 | 10003 |
Dependency table：
A1+A2+A4：
| 10002 |
A2+A4：
| 10003 |
(other 13 tables are sky, omit herein)
B：
| 10002 |
B2：
| 10002 |
It is collated and associate with patient files and can obtain Pyatyi table：
One-level：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | … | …… | |
| 10003 | …… | …… | …… | …… | |
| …… |
Two grades：
AD：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
| 10003 | …… | …… | …… | …… | |
Discharge diagnosis：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
Pathological diagnosis：
| Admission number | Name | Sex | Age | Telephone number | …… |
Check diagnosis：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
| 10003 | …… | …… | …… | …… | |
Three-level：
AD+discharge diagnosis+inspection diagnosis：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
AD+inspection diagnosis：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10003 | …… | …… | …… | …… | |
Level Four：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
Pyatyi：
Medicine：
| Admission number | Name | Sex | Age | Telephone number | …… |
| 10002 | …… | …… | …… | …… | |
To sum up：Comparing artificial screening method wastes time and energy, less efficient, needs to pay higher human cost, the present invention
Based on the case history screening technique of research follow-up, by initializing each dimension screened, screening conditions arrange operation and
Screening operation and Classifying Sum are operated, and can exempt the lengthy procedure of artificial screening check and correction, and it is according to different diagnosis, treatment
Mode standard, is directly analyzed by computer to the electronic health record in system, filters out the case history for meeting research direction, whole
Reason draws follow-up list, can effectively improve screening efficiency of the research worker to case history, reduces screening error rate.
Presently preferred embodiments of the present invention is the foregoing is only, not to limit the present invention, all essences in the present invention
Within god and principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.
Claims (8)
1. a kind of case history screening technique based on research follow-up, it is characterised in that：Bao includes Yi Xia Bu Sudden：
(1) initialization operation：Each dimension that initialization is screened, each dimension is divided into different main dimensions and belongs to each with
Many sub- dimensions under main dimension；
(2) screening conditions arrange operation：User arranges according to demand screening conditions, using key word screening method, ties up accordingly
Degree lower input key word to be screened, completes screening conditions and arranges operation after confirmation；
(3) screening operation：Firstly, it is necessary to by the history case history of this section office, Jing interfaces are imported in case history screening system；Subsequently, exist
The screening conditions arranged according to above-mentioned steps in the case history of importing are screened portionwise；
(4) Classifying Sum operation：The situation that statistics admission number occurs under main dimension and under sub- dimension, by admission number and patient's shelves
Case is associated, and is arranged Pyatyi summary sheet of the generation comprising patient's complete information and is presented to user.
2. the case history screening technique based on research follow-up according to claim 1, it is characterised in that：The main dimension bag
Include the main dimension of diagnosis and the main dimension of therapeutic modality.
3. the case history screening technique based on research follow-up according to claim 2, it is characterised in that：It is described to diagnose main dimension
Degree and the main dimension of therapeutic modality are divided into respectively 4 sub- dimensions.
4. the case history screening technique based on research follow-up according to claim 3, it is characterised in that：It is described to diagnose main dimension
Degree is divided into AD, discharge diagnosis, pathological diagnosis and checks the sub- dimension of diagnosis.
5. the case history screening technique based on research follow-up according to claim 4, it is characterised in that：The therapeutic modality
Main dimension is divided into the sub- dimension of modus operandi, medicine, test mode and nursing care mode.
6. the case history screening technique based on research follow-up according to claim 4, it is characterised in that：It is described to diagnose main dimension
The lower key word that arranges of degree can count AD, discharge diagnosis, pathological diagnosis and check the sub- dimension dependency summary sheet of diagnosis.
7. the case history screening technique based on research follow-up according to claim 6, it is characterised in that：The Pyatyi collects
Table includes the main dimension summary sheet of diagnosis, the AD of the second level, discharge diagnosis, pathological diagnosis and inspection diagnosis of the first order
The dependency of each summary sheet of dimension, the AD of the third level and discharge diagnosis and pathological diagnosis and the sub- dimension of inspection diagnosis converges
Summary table, the modus operandi of the main dimension summary sheet of therapeutic modality of the fourth stage and level V, medicine, test mode and nursing
Any one sub- dimension summary sheet in the sub- dimension of mode.
8. the case history screening technique based on research follow-up according to claim 1, it is characterised in that：The patient is complete
Information includes name corresponding with admission number, sex, age, telephone number.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109243549A (en) * | 2018-07-11 | 2019-01-18 | 腾讯科技（深圳）有限公司 | A kind of intelligent follow-up method, device and server |
| CN109841285A (en) * | 2017-11-28 | 2019-06-04 | 北京市眼科研究所 | A kind of clinical research cooperative system and method |
| CN110400613A (en) * | 2019-06-10 | 2019-11-01 | 南京医基云医疗数据研究院有限公司 | A kind of follow-up patient screening method, apparatus, readable medium and electronic equipment |
| CN111192689A (en) * | 2018-11-15 | 2020-05-22 | 零氪科技（北京）有限公司 | Patient identification method based on medical data |
| CN113643778A (en) * | 2021-10-14 | 2021-11-12 | 山东大学齐鲁医院 | In-hospital cardiac arrest screening method and system based on electronic medical record data |
| CN113643777A (en) * | 2021-10-12 | 2021-11-12 | 山东大学齐鲁医院 | Out-of-hospital cardiac arrest data processing method and system |
| CN117251556A (en) * | 2023-11-17 | 2023-12-19 | 北京遥领医疗科技有限公司 | Patient screening system and method in registration queue |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070156757A1 (en) * | 2005-12-21 | 2007-07-05 | Xiaofeng Tang | computer-implemented method and system for enabling the automated selection of keywords for rapid keyword portfolio expansion |
| US20080162393A1 (en) * | 1993-12-29 | 2008-07-03 | Clinical Decision Support, Llc | Computerized medical diagnostic and treatment advice system |
| CN104598740A (en) * | 2015-01-26 | 2015-05-06 | 曹庆恒 | Method, system and equipment for intelligent medication guidance |
| CN105488228A (en) * | 2016-01-08 | 2016-04-13 | 复旦大学附属华山医院 | Method and device for presenting medical information of visiting users |
| CN105488231A (en) * | 2016-01-22 | 2016-04-13 | 杭州电子科技大学 | Self-adaption table dimension division based big data processing method |
| CN105574030A (en) * | 2014-10-16 | 2016-05-11 | 腾讯科技（深圳）有限公司 | Information search method and device |
-
2016
- 2016-12-30 CN CN201611270995.9A patent/CN106682439A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080162393A1 (en) * | 1993-12-29 | 2008-07-03 | Clinical Decision Support, Llc | Computerized medical diagnostic and treatment advice system |
| US20070156757A1 (en) * | 2005-12-21 | 2007-07-05 | Xiaofeng Tang | computer-implemented method and system for enabling the automated selection of keywords for rapid keyword portfolio expansion |
| CN105574030A (en) * | 2014-10-16 | 2016-05-11 | 腾讯科技（深圳）有限公司 | Information search method and device |
| CN104598740A (en) * | 2015-01-26 | 2015-05-06 | 曹庆恒 | Method, system and equipment for intelligent medication guidance |
| CN105488228A (en) * | 2016-01-08 | 2016-04-13 | 复旦大学附属华山医院 | Method and device for presenting medical information of visiting users |
| CN105488231A (en) * | 2016-01-22 | 2016-04-13 | 杭州电子科技大学 | Self-adaption table dimension division based big data processing method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109841285A (en) * | 2017-11-28 | 2019-06-04 | 北京市眼科研究所 | A kind of clinical research cooperative system and method |
| CN109243549A (en) * | 2018-07-11 | 2019-01-18 | 腾讯科技（深圳）有限公司 | A kind of intelligent follow-up method, device and server |
| CN111192689A (en) * | 2018-11-15 | 2020-05-22 | 零氪科技（北京）有限公司 | Patient identification method based on medical data |
| CN111192689B (en) * | 2018-11-15 | 2023-11-24 | 零氪科技（北京）有限公司 | Patient identification method based on medical data |
| CN110400613A (en) * | 2019-06-10 | 2019-11-01 | 南京医基云医疗数据研究院有限公司 | A kind of follow-up patient screening method, apparatus, readable medium and electronic equipment |
| CN113643777A (en) * | 2021-10-12 | 2021-11-12 | 山东大学齐鲁医院 | Out-of-hospital cardiac arrest data processing method and system |
| CN113643778A (en) * | 2021-10-14 | 2021-11-12 | 山东大学齐鲁医院 | In-hospital cardiac arrest screening method and system based on electronic medical record data |
| CN113643778B (en) * | 2021-10-14 | 2022-01-21 | 山东大学齐鲁医院 | In-hospital cardiac arrest screening method and system based on electronic medical record data |
| CN117251556A (en) * | 2023-11-17 | 2023-12-19 | 北京遥领医疗科技有限公司 | Patient screening system and method in registration queue |
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Application publication date: 20170517 |