CN111739660A - Parkinson disease non-motor symptom monitoring platform and application thereof - Google Patents
Parkinson disease non-motor symptom monitoring platform and application thereof Download PDFInfo
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Abstract
The invention provides a non-motor symptom monitoring platform for Parkinson's disease and application thereof, belonging to the technical field of online medical treatment. The monitoring platform comprises a patient module, a doctor module and an information processing module, the diagnosis and disease course monitoring of the doctor are assisted by the fact that the patient completes the Parkinson disease non-motor symptom visual scale on time, and information interaction is achieved through the form of app, a web page or a WeChat applet. The monitoring platform does not occupy the time of clinical communication, the patient can finish the evaluations at the terminal by himself, and the doctor can quantify the burden rating of the non-exercise symptom by calling the information and the analysis result of the patient during each visit, quickly and accurately grasp the current situation and the progress of the non-exercise symptom of the patient, and make a diagnosis timely and accurately.
Description
Technical Field
The invention belongs to the technical field of online medical treatment, and particularly relates to a non-motor symptom monitoring platform for Parkinson's disease and application thereof.
Background
Parkinson's disease is a nervous system degenerative disease commonly seen in the middle-aged and the elderly, and the average onset age is about 60 years old, and mainly manifests as slow movement of patients, involuntary tremor of hands, heads or mouths and muscle rigidity at rest. With the aging population coming, the Parkinson disease patients are also growing rapidly, and early discovery, early diagnosis and early treatment are particularly important for treating the Parkinson disease.
The non-motor symptoms comprise sensory disorder (olfactory disorder and pain), sleep disorder, neuropsychiatric disorder and autonomic dysfunction, have the characteristics of high incidence, low recognition rate, influence on life quality and treatment difficulty, can aggravate the movement disorder, shorten the life span and reduce the life quality, and sometimes has the influence on the life of patients and families far surpassing the influence of the movement disorder of the diseases per se. Currently, clinicians are more concerned about the observation and identification of motor symptoms for the diagnosis of parkinson's disease, while non-motor symptoms of parkinson's disease are not well identified in routine clinical visits. According to researches, the Parkinson's disease patients have 11 non-motor symptoms on average, but only 5 non-motor symptoms are recorded in medical records on average, and many non-motor symptoms are easy to overlook or ignore by clinicians, so that the diagnosis and treatment of the Parkinson's disease are delayed, and unnecessary losses are caused to the society and the patients.
Disclosure of Invention
Aiming at the problems existing in the current Parkinson disease diagnosis and treatment process, the invention provides a Parkinson disease non-motor symptom monitoring platform capable of being used for quickly and accurately diagnosing and treating Parkinson disease and application thereof.
In order to achieve the aim, the invention discloses a non-motor symptom monitoring platform for the Parkinson disease in one aspect, which comprises the following modules.
A patient module: the system comprises a patient information management unit, a medical information management unit and a medical information management unit, wherein the patient information management unit is used for registering personal identity information of a patient and uploading information such as doctor seeing information, clinic medical records, medication condition and the like; the patient monitoring unit is used for completing visual scale evaluation of the non-motor symptoms of the Parkinson's disease by the patient; and the information display unit is used for receiving the scheme issued by the doctor, reminding the patient to make a double-check in time, taking medicine on time and reminding the patient to perform scale evaluation on time.
A doctor module: the system comprises a doctor information management unit, a personal identification information registration unit and a personal identification information registration unit, wherein the doctor information management unit is used for registering personal identification information by a doctor; the information reading unit is used for calling basic information, diagnosis and treatment information and non-motor symptom visual scale evaluation results of the patients to be treated by the doctor; and the disease course monitoring unit is used for monitoring the disease course of the patient by the doctor according to the diagnosis and treatment information of the patient and the scale evaluation result and issuing a treatment scheme or suggestion.
An information processing module: the system comprises an information collecting and analyzing unit, a data processing unit and a data processing unit, wherein the information collecting and analyzing unit is used for collecting doctor and patient information, carrying out statistical analysis on the patient information and recommending the most suitable hospital and doctor for the patient; and the data storage module is used for counting, recording and storing the doctor-patient information.
Preferably, the parkinsonism non-motor symptom visual scale is an interactive scale matched with videos, pictures and voice explanations; the scale is one or more of a non-motor symptom complex scale, a PD autonomic nerve function scale, a PD sensory evaluation scale, a PD neuropsychiatric symptom scale, a PD sleep scale or a PD fatigue scale.
Preferably, the patient module further comprises an online inquiry unit for online consultation and inquiry of the patient; the doctor module also comprises an online diagnosis receiving unit for online diagnosis receiving of the patient by the doctor; the information processing module also comprises a fee settlement unit used for data statistics and fee settlement of online inquiry.
Preferably, the doctor module further comprises an online referral unit for allocating doctor resources for the patient needing referral or consultation.
Preferably, the information processing module further comprises an information sharing unit for realizing article pushing, knowledge retrieval, public lessons and communication between sick and friends.
Preferably, the information processing module further comprises an information printing unit, and the information printing unit is used for the patient to print the visual scale test result and the full-course monitoring data for use in the clinic.
The non-motor symptom monitoring platform for the Parkinson's disease is realized in the form of an app, a web page or a WeChat applet.
The invention also discloses application of the non-motor symptom monitoring platform for the Parkinson's disease in diagnosis and treatment of the Parkinson's disease.
The doctor and the patient establish contact on the non-motor symptom monitoring platform of the Parkinson disease through the patient terminal and the doctor terminal to carry out information interaction, and the system can be used for self-assessment and auxiliary diagnosis of the Parkinson disease in the prodromal stage, disease course monitoring and auxiliary treatment of the Parkinson disease in the advancing stage and provide support for scientific research work of the Parkinson disease.
The visual Parkinson disease non-motor symptom scale is used for evaluating potential high risk groups of Parkinson disease once every 3 to 6 months; for Parkinson's disease patients, particularly advanced Parkinson's disease patients, the assessment is performed once every 2-4 weeks or following a doctor's prescription.
Preferably, the patient can realize online consultation, online appointment registration, disease monitoring and diagnosis guidance, self-evaluation of precursor symptoms, knowledge retrieval, public classes and communication of disease friends through the monitoring platform; doctors can realize on-line inquiry, on-line referral, course management and auxiliary scientific research through the monitoring platform.
Compared with the prior art, the invention has the advantages and positive effects that:
1. the platform does not occupy the time of clinical communication, a patient can finish the evaluations at a terminal by himself, and a doctor can quantify the burden rating of the non-exercise symptoms by calling patient information and an analysis result during each visit, quickly and accurately grasp the current situation and progress of the non-exercise symptoms of the patient, and make a diagnosis timely and accurately; in addition, the patient information is integrated into the platform, and the whole course management of the patient can be realized.
2. The non-motor symptom evaluation scale is visualized, so that the friendliness of the platform is improved, and the Parkinson patients can master the evaluation scale.
3. The platform has the online diagnosis and treatment functions, can dispatch resources to the maximum extent, realizes seamless connection between a patient and a doctor, and can provide disease condition monitoring and diagnosis guidance for the patient outside a hospital.
4. The burden of scientific research personnel is reduced, and big data and technical support are provided for clinical scientific research.
5. The functions of article pushing, knowledge retrieval, class public offering and patient-friend communication are provided, doctor-patient communication modes are increased, and doctor-patient communication is strengthened to construct a harmonious doctor-patient relationship.
Drawings
FIG. 1 is a schematic diagram of an APP navigation page provided in an embodiment of the present invention;
FIG. 2 is a schematic diagram of an APP symptom test page provided by the embodiment of the present invention;
fig. 3 is a schematic diagram of an APP patient management page provided in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. 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.
The embodiment of the invention discloses a non-motor symptom monitoring platform for Parkinson's disease, which comprises the following modules.
A patient module: the system comprises a patient information management unit, a medical information management unit and a medical information management unit, wherein the patient information management unit is used for registering personal identity information of a patient and uploading information such as doctor seeing information, clinic medical records, medication condition and the like; the patient monitoring unit is used for completing visual scale evaluation of the non-motor symptoms of the Parkinson's disease by the patient; and the information display unit is used for receiving the scheme issued by the doctor, reminding the patient to make a double-check in time, taking medicine on time and reminding the patient to perform scale evaluation on time.
A doctor module: the system comprises a doctor information management unit, a personal identification information registration unit and a personal identification information registration unit, wherein the doctor information management unit is used for registering personal identification information by a doctor; the information reading unit is used for calling basic information, diagnosis and treatment information and non-motor symptom visual scale evaluation results of the patients to be treated by the doctor; and the disease course monitoring unit is used for monitoring the disease course of the patient by the doctor according to the diagnosis and treatment information of the patient and the scale evaluation result and issuing a treatment scheme or suggestion.
An information processing module: the system comprises an information collecting and analyzing unit, a data processing unit and a data processing unit, wherein the information collecting and analyzing unit is used for collecting doctor and patient information, carrying out statistical analysis on the patient information and recommending the most suitable hospital and doctor for the patient; and the data storage module is used for counting, recording and storing the information of the doctor and the patient.
The platform uses the assessment scale of the non-motor symptoms of the Parkinson's disease, combines the course record and the medication condition of the patient, integrates all data into a program, realizes the assessment of the state of the patient in the whole course, feeds back the result to the doctor through statistical analysis, and helps the doctor to diagnose accurately in time. In addition, the platform can realize the whole-course management of the patient, and the patient can be subjected to standardized whole-course monitoring no matter whether the patient is treated by following the same doctor all the time. The non-motor symptoms include sensory disorders (olfactory disorders and pain), sleep disorders, neuropsychiatric disorders, autonomic nerve dysfunction, and the like. Because the platform integrates the data of the patients, doctors can acquire the clinical data of the patients in the corresponding group according to different authorities, and the big data platform is used for providing clinical scientific research services.
In a preferred embodiment, the parkinsonism non-motor symptom visual scale is an interactive scale matched with videos, pictures and voice explanations. The existing international universal Parkinson disease assessment scale is converted into an interactive scale matched with video, picture and voice explanation. For example, UPDRS part I1.3 depression state evaluation is provided with video explanation to help patients judge whether relevant symptoms exist, the frequency and duration of symptom occurrence, and whether concomitant symptoms such as insomnia, anorexia, weight loss and the like exist. In addition, the scale also has a voice explanation function, can read the content of the options, and can make popular and understandable explanation for the professional nouns, so that the scale can be used by old patients, patient spouses and patients who are not skilled in using electronic equipment through proper training of doctors, and the test can be smoothly completed.
Such scales include, but are not limited to, the universal UPDRS, PDQ-39, etc., and scales for non-motor symptoms, listed below: 1) non-motor symptom complex scale: PD non-motor questionnaire (nmsqueest), non-motor rating scale (NMSS). 2) PD autonomic nervous function scale: PD prognosis scale-autonomic nerve (SCOPA-AUT). 3) PD sensory evaluation scale: PD dysosmia, 16 sminefin olfactory screening (SS-16); PD pain scale. 4) PD neuropsychiatric symptoms scale: 4.1 anxiety, depression: beck depression scale (BDI), hamilton depression scale (HAMD), HADS scale, beck anxiety scale (BAI) hamilton anxiety scale; 4.2 Impulse control disorder: PD impulse control obstacle scale (QUIP), BIS/BAS scale, BIS-11 scale; 4.3 cognitive disorders: MMSE, montreal cognitive assessment scale (MoCA). 5) PD sleep scale: PD sleep scale (PDSS), RBD screening scale (RBDSQ). 6) PD fatigue scale: fatigue Severity Scale (FSS).
In a preferred embodiment, the patient module further comprises an online inquiry unit for online consultation and inquiry of the patient; the doctor module also comprises an online diagnosis receiving unit for online diagnosis receiving of the patient by the doctor; the information processing module also comprises a fee settlement unit used for data statistics and fee settlement of online inquiry. The expert who resides in the platform may also provide on-line consulting services for the user. For the person who is suspected to be ill but has not yet been treated, the patient can check the historical introduction and the sitting treatment information of the expert and choose to consult the doctor on line or go out to the clinic for treatment. In addition, the platform can also cooperate with an online appointment registration system to realize autonomous appointment seeing a doctor.
In a preferred embodiment, the physician module further comprises an online referral unit for allocating physician resources for the patient requiring referral or consultation. Doctors are divided into special doctors and community doctors, community doctors can recommend patients to use the platform when managing the slow-disease patients in the community, transfer the patients in time when needed, the special doctors take the treatment, and then the patients return to the community for management.
In a preferred embodiment, the information processing module further includes an information sharing unit, which is used to implement article pushing, knowledge retrieval, class disclosure and communication between patients and friends. The platform invites Parkinson disease experts to write articles related to relevant knowledge such as illness state introduction, reasonable medication and the like to be pushed to patients periodically, the patients can also search medical knowledge related to the Parkinson disease on the platform, the experts are invited to record courses for disease course management periodically, and a platform for online communication and mutual assistance of disease friends is established.
In a preferred embodiment, in order to facilitate the patient to see a doctor, the information processing module further comprises an information printing unit, the information printing unit is used for the patient to print the visual scale test result and the whole course monitoring data by himself/herself, the visual scale test result and the whole course monitoring data are put together with other auxiliary examination results such as CT and MRI to see a doctor, the doctor and the patient do not need to use electronic equipment in a consulting room, the doctor and the patient can practice diagnosis and treat time, and the doctor can log in the doctor end by himself/herself to inquire the patient course data through the identification code after the doctor.
The non-motor symptom monitoring platform for the Parkinson's disease is realized in the form of an app, a web page or a WeChat applet. According to the using habits of different users, the platform can be realized in the form of app, WeChat applet or web pages so as to meet different requirements of different users.
The invention also discloses application of the non-motor symptom monitoring platform for the Parkinson's disease in diagnosis and treatment of the Parkinson's disease. The doctor and the patient establish contact on the Parkinson disease non-motor symptom monitoring platform through the patient terminal and the doctor terminal to carry out information interaction, and diagnosis and treatment of the Parkinson disease and disease course monitoring are achieved. The patient terminal and the doctor terminal are mobile phones, tablet computers or computers. The doctor and the patient establish contact on the non-motor symptom monitoring platform of the Parkinson disease through the patient terminal and the doctor terminal to carry out information interaction, and the system can be used for self-assessment and auxiliary diagnosis of the Parkinson disease in the prodromal stage, auxiliary treatment of the Parkinson disease in the progressive stage and support scientific research work of the Parkinson disease.
In a preferred embodiment, the patient can realize online consultation and online appointment registration, disease monitoring and treatment guidance, self-evaluation of precursor symptoms, knowledge retrieval, public classes and communication of patients and friends through the monitoring platform; doctors can realize on-line inquiry, on-line referral, course management and auxiliary scientific research through the monitoring platform.
For patients suspected of suffering from Parkinson's disease but not diagnosed yet, the platform can evaluate the progression of non-motor symptoms of the patients, and is beneficial to the early detection of suspicious conditions and the timely re-diagnosis of the patients. For example, when depression is accompanied by hyposmia and constipation, the specificity of progression to Parkinson's disease can reach 89% even if no motor symptoms appear, and thus, people having the above symptoms are alerted to the onset of Parkinson's disease. Namely, the non-motor symptoms can also be used as precursor symptoms of the Parkinson disease, and are 2-3 years earlier than the currently accepted motor symptoms in the precursor stage of the Parkinson disease, and the part of patients need to be enhanced with regular follow-up, early diagnosis and timely intervention.
Further, for a patient suspected of having the Parkinson's disease, the patient monitoring unit in the platform patient module can also automatically calculate the disease probability according to the early warning factors of the Parkinson's disease in the precursor stage, so as to better guide the patient to see a doctor. Early warning factors of the Parkinson disease in the prodromal stage are as follows: predisposition, genetic factors, and prodromal phase symptoms and adjuvant tests. The final individual likelihood ratio is obtained by multiplying the likelihood ratios of all the following pre-warning factors (if the patient is present). The susceptibility factors comprise part of information in the past history, personal history and family history of the patient (app is input when the patient fills in the information), such as whether the past history has a history of brain trauma and a history of medicine taking (such as NSAIDs (aspirin and the like); age and sex in personal history, whether pesticide and chemical solvent are contacted, whether habit of drinking tea, coffee and milk exists, smoking history and drinking history; family history, particularly family history of first degree relatives. Genetic factors include the results of gene testing before or during the visit, whether there is a mutation in the parkinsonism-related gene (PARK gene). The prodromal phase symptoms and the auxiliary examinations included all non-motor symptoms, imaging results (mainly transcranial ultrasound) as described herein.
The relevant probability model for automatically calculating the disease probability is a naive Bayes classification method, and the disease probability of a research object is calculated by multiplying the prior probability (prior probability) and the Likelihood Ratio (LR) after conversion. Where the prior probability is the probability of developing a disease without taking any factors into account, i.e. the prevalence of pre-stage parkinson's disease in the present strategy at different ages, and the likelihood ratio is the ratio of the probability of a certain result of the diagnostic test appearing in the diseased group to the probability of appearing in the non-diseased group. In addition, because the prevalence rate of the Parkinson disease in the precursor stage of each age group is fixed, the individual likelihood ratio threshold value can also be independently used as the judgment standard of high-risk individuals in a certain age group, and the probability of the individual appearing in the diseased group is far higher than that in the non-diseased group.
According to a naive Bayes classification method, when a certain individual has a plurality of early warning factors of the precursor stage Parkinson's disease at the same time, a plurality of LRs can be multiplied continuously to obtain the final individual LR. Each early warning factor LR can be calculated through sensitivity and specificity. The likelihood ratio can also be calculated by drawing a four-table through the prevalence rate, positive predictive value, dominance ratio, relative risk, queue research data and the like of the early warning factors.
After the patient data is collected, the current condition of the patient can be evaluated according to a relevant probability model made by a naive Bayesian classification method. When the product of the likelihood ratio of a certain individual and the prior probability after conversion is more than 80%, the possibility that the individual is in the precursor stage of the Parkinson disease is more than 80%, and the individual is defined as a high-risk individual. The patient may then be recommended to visit the relevant hospital.
For patients diagnosed with Parkinson's disease, the platform provides the patient with a self-test every 2-4 weeks, monitoring the patient's progression of non-motor symptoms throughout. In practical work, because the diagnosis and treatment time of each patient in a consulting room is 10 minutes on average, and the basic scale test and the scale test aiming at the non-motor symptoms need to be completed for the patient for at least 1 hour, the non-motor symptoms are ignored in clinic, the patient can complete all scale tests before visiting the doctor and repeat the test at intervals by the monitoring platform, and great help is provided for judging whether the patient has the non-motor symptoms and the symptom progress when the doctor visits the doctor.
For patients diagnosed with Parkinson's disease and already presenting with motor complications and non-motor symptoms, the effect of the medication on the motor complications and non-motor symptoms can be evaluated, and the medication scheme can be adjusted according to the medication effect, so that the patients can obtain the maximum benefit.
In order to more clearly and specifically describe the non-motor symptom monitoring platform for parkinson disease and the application thereof provided by the embodiments of the present invention, the following description will be made with reference to specific embodiments.
Example 1
Parkinson's disease non-motor symptom monitoring platform comprises the following modules: a patient module: the system comprises a patient information management unit, a patient monitoring unit, an information display unit and an online inquiry unit; a doctor module: comprises a doctor information management unit, an information reading unit, an online referral unit, an online reception unit and a course monitoring unit; an information processing module: the system comprises an information collecting and analyzing unit, a data storage unit, an information sharing unit, a fee settlement unit and an information printing unit.
As shown in fig. 1, the functions of the non-motor symptom monitoring platform for parkinson's disease can be integrated into the app, including interfaces for symptom assessment, disease understanding, online inquiry, medical record, appointment registration, and more management. After the patient downloads the app through the mobile phone, the app needs to be opened, an account is registered in the patient information management unit, and personal information and medical history information including name, sex, age, past history, personal history, family history and the like are filled in.
The Parkinson disease patient who is not diagnosed can be evaluated through the platform, and medical advice is obtained.
If the patient has not been diagnosed, the patient can be evaluated by using the app before the visit, the platform firstly selects a non-motor symptom comprehensive scale, such as a PD non-motor symptom questionnaire (NMSQuest) and a non-motor symptom evaluation scale (NMSS), to test, according to the test result, such as a higher depression sub-item score, the patient can be recommended to evaluate a depression scale, such as a Becker depression scale (BDI) and a Hamilton depression scale (HAMD), and after the evaluation is finished, the disease probability can be automatically displayed, so that whether the patient is recommended to be diagnosed in a relevant hospital or not is determined. As shown in fig. 2, the self-test questionnaire is a symptom of the patient, the case of the depression state is exemplified to be tested, the video playing area is arranged on the upper part of the interface, the expressions of the depression states with different degrees are explained, the patient can easily distinguish the condition of the patient, other tests are presented in a mode of being harmonious, and the patient can successfully complete the required tests.
If the patient has been treated, the patient can finish the evaluation of the related non-motor symptom visual scale according to the medical advice home and upload the evaluation result for the doctor to use during the consultation; meanwhile, if the patient is diagnosed with the Parkinson's disease after the return visit, the information display unit can synchronously receive the scheme issued by the doctor, remind the patient of return visit in time, take medicine on time and evaluate the scale on time.
After the doctor downloads the app, the personal identity information is registered in the information management unit, then the basic information, the diagnosis and treatment information and the non-motor symptom visual scale evaluation result of the patient can be called in the information reading unit, and a treatment scheme or suggestion can be issued according to the result.
The patient can also consult and ask for consultation on line through the on-line inquiry unit, and the doctor receives a consultation on line through the on-line inquiry unit, so that the platform encourages the doctor to actively answer questions of the sick and friends, and a certain reward is given through the fee settlement unit.
The patient information and the diagnosis and treatment information are collected and statistically analyzed through the information processing module, so that the Parkinson patients are monitored in the whole disease course.
The online referral unit can allocate doctor resources for patients needing referral or consultation, and the Parkinson's disease belongs to chronic diseases and needs long-term treatment and rehabilitation, so that the joint efforts of primary community doctors and specialist doctors are needed. The platform can realize the bidirectional communication between primary community doctors and clinical specialist doctors. Clinical specialist doctors can give the relevant guidance of primary community doctors to better serve community Parkinson's disease patients and carry out more accurate Parkinson's disease screening, the primary community doctors can feed back the diagnosis and treatment conditions of the Parkinson's disease patients to a large hospital in time so as to assist doctors to improve diagnosis and treatment schemes, up-and-down linkage is realized, the operation of medical health system is effectively promoted, and diagnosis and treatment efficiency and effect are improved.
As further shown in fig. 3, in the information sharing unit, the platform periodically invites the parkinson's disease experts to write articles related to the related knowledge such as introduction of illness state, rational medication and the like to be pushed to the patient, the patient can also retrieve the medical knowledge related to parkinson's disease on the platform, periodically invites the experts to record courses for disease course management, and establishes a platform for online communication and mutual assistance of the patients.
The information printing unit is used for the patient to print the visual scale test result and the whole course of disease monitoring data by oneself, and is put together with other supplementary inspection results such as CT, MRI and see a doctor, does not need the doctor and the patient both sides to use electronic equipment in the consulting room, practices thrift the time that the doctor diagnosed, and the doctor can log in the doctor end by oneself after the doctor and inquire patient's course of disease data through the identification code.
Example 2
Parkinson's disease non-motor symptom monitoring platform comprises the following modules: a patient module: the system comprises a patient information management unit, a patient monitoring unit, an information display unit and an online inquiry unit; a doctor module: comprises a doctor information management unit, an information reading unit, an online referral unit, an online reception unit and a course monitoring unit; an information processing module: the system comprises an information collecting and analyzing unit, a data storage unit, an information sharing unit, a fee settlement unit and an information printing unit.
Besides the functions of embodiment 1, the confirmed Parkinson patients can also realize full-course monitoring and adjuvant therapy through the monitoring platform.
For patients with confirmed diagnosis, a corresponding scale is selected to perform regular assessment and monitoring according to non-motor symptoms, such as constipation and prominent cognitive impairment, and the assessment of the PD autonomic nerve function scale and the cognitive impairment scale is performed regularly according to medical advice. Meanwhile, the non-motor symptom comprehensive scale is evaluated at intervals, and whether other non-motor symptoms appear or not is judged along with the progress of the disease. And regularly upload the condition of oneself, make things convenient for the doctor to carry out real-time supervision, help the doctor to obtain the first hand data of patient's state of an illness progress to adjust follow-up treatment scheme.
For patients diagnosed with motor complications or non-motor symptoms already, the platform can help doctors comprehensively understand the relationship between motor symptoms, motor complications and non-motor symptoms of the patients when managing the part of patients, and avoid aggravating certain non-motor symptoms when trying to increase the types and dosage of anti-Parkinson drugs to relieve the motor disorders.
In addition, the doctor can be helped to adjust the medication according to the feedback of the patient to the treatment condition, so that the patient can obtain the maximum benefit. The treatment regimen for patients presenting with partial non-motor symptoms during treatment is now presented in table 1.
Table 1 partial non-motor symptom treatment protocol
Claims (10)
1. Parkinson's disease non-motor symptom monitoring platform is characterized by comprising the following modules:
a patient module: the system comprises a patient information management unit, a medical information management unit and a medical information management unit, wherein the patient information management unit is used for registering personal identity information of a patient and uploading information such as doctor seeing information, clinic medical records, medication condition and the like; the patient monitoring unit is used for completing visual scale evaluation of the non-motor symptoms of the Parkinson's disease by the patient; the information display unit is used for receiving the scheme issued by the doctor, reminding the patient to make a double-check in time, taking medicine on time and reminding the patient to perform scale evaluation on time;
a doctor module: the system comprises a doctor information management unit, a personal identification information registration unit and a personal identification information registration unit, wherein the doctor information management unit is used for registering personal identification information by a doctor; the information reading unit is used for calling basic information, diagnosis and treatment information and non-motor symptom visual scale evaluation results of the patients to be treated by the doctor; the disease course monitoring unit is used for monitoring the disease course of the patient by a doctor according to the diagnosis and treatment information of the patient and the scale evaluation result and issuing a treatment scheme or suggestion;
an information processing module: the system comprises an information collecting and analyzing unit, a data processing unit and a data processing unit, wherein the information collecting and analyzing unit is used for collecting doctor and patient information, carrying out statistical analysis on the patient information and recommending the most suitable hospital and doctor for the patient; and the data storage module is used for counting, recording and storing the information of the doctor and the patient.
2. The monitoring platform of claim 1, wherein the parkinson's disease non-motor symptom visual scale is an interactive scale that coordinates video, picture, voice interpretation;
the scale is one or more of a non-motor symptom complex scale, a PD autonomic nerve function scale, a PD sensory evaluation scale, a PD neuropsychiatric symptom scale, a PD sleep scale or a PD fatigue scale.
3. The monitoring platform of claim 1 or 2, wherein the patient module further comprises an online consultation unit for online consultation and consultation of the patient; the doctor module also comprises an online diagnosis receiving unit for online diagnosis receiving of the patient by the doctor; the information processing module also comprises a fee settlement unit used for data statistics and fee settlement of online inquiry.
4. The monitoring platform of claim 1 or 2, wherein the physician module further comprises an online referral unit for allocating physician resources for patients requiring referral or consultation.
5. The monitoring platform according to claim 1 or 2, wherein the information processing module further comprises an information sharing unit for realizing article pushing, knowledge retrieval, public classes and communication between patients and friends.
6. The monitoring platform of claim 1 or 2, wherein the information processing module further comprises an information printing unit for self-printing the visual scale test result and the full-course monitoring data for the patient to use in the clinic.
7. The monitoring platform of any one of claims 1-6, wherein the monitoring platform is implemented in the form of an app, a wechat applet, or a web page.
8. The application of the non-motor symptom monitoring platform of the Parkinson's disease in diagnosing and treating the Parkinson's disease.
9. The application of claim 8, wherein the doctor and the patient establish a connection on the non-motor symptom monitoring platform of the Parkinson's disease through the patient terminal and the doctor terminal to perform information interaction, and the application can be used for self-assessment and auxiliary diagnosis of the Parkinson's disease in the prodromal stage, auxiliary treatment of the Parkinson's disease in the progressive stage and support for scientific research work of the Parkinson's disease;
the visual Parkinson disease non-motor symptom scale is used for evaluating potential high risk groups of Parkinson disease once every 3 to 6 months; for Parkinson's disease patients, particularly advanced Parkinson's disease patients, the assessment is performed once every 2-4 weeks or following a doctor's prescription.
10. The use of claim 8, wherein the patient can use the monitoring platform to perform online consultation and online appointment registration, disease monitoring and medical instruction, self-assessment of precursor symptoms, knowledge retrieval, public classes, and communication with the patients and friends; doctors can realize on-line inquiry, on-line referral, course management and auxiliary scientific research through the monitoring platform.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112687378A (en) * | 2020-12-31 | 2021-04-20 | 中国科学院合肥物质科学研究院 | Parkinson's disease dyskinesia symptom monitoring platform and application thereof |
| CN115148330A (en) * | 2022-05-24 | 2022-10-04 | 中国医学科学院北京协和医院 | POP treatment scheme forming method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2938629A1 (en) * | 2014-02-04 | 2015-08-13 | The Medical Research, Infrastructure and Health Services Fund of the Tel Aviv Medical Center | Methods and systems for providing diagnosis or prognosis of parkinson's disease using body-fixed sensors |
| CN105205601A (en) * | 2015-09-23 | 2015-12-30 | 复旦大学附属中山医院 | System for improving chronic disease long-term follow-up management/compliance through mobile phone terminals |
| CN105912847A (en) * | 2016-04-08 | 2016-08-31 | 北京阳光欣晴健康管理有限责任公司 | System for implementing coronary heart disease post-diagnosis management |
| CN107229814A (en) * | 2016-03-24 | 2017-10-03 | 深圳中迈数字医疗技术有限公司 | The method and system intervened according to chronic's information |
| CN108766573A (en) * | 2018-06-01 | 2018-11-06 | 南华大学 | A kind of doctors and patients' Symptoms Assessment system |
| CN109691983A (en) * | 2018-11-13 | 2019-04-30 | 深圳市和缘科技有限公司 | A kind of intelligence disturbances in patients with Parkinson disease monitor system |
-
2020
- 2020-05-19 CN CN202010424830.2A patent/CN111739660A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2938629A1 (en) * | 2014-02-04 | 2015-08-13 | The Medical Research, Infrastructure and Health Services Fund of the Tel Aviv Medical Center | Methods and systems for providing diagnosis or prognosis of parkinson's disease using body-fixed sensors |
| CN105205601A (en) * | 2015-09-23 | 2015-12-30 | 复旦大学附属中山医院 | System for improving chronic disease long-term follow-up management/compliance through mobile phone terminals |
| CN107229814A (en) * | 2016-03-24 | 2017-10-03 | 深圳中迈数字医疗技术有限公司 | The method and system intervened according to chronic's information |
| CN105912847A (en) * | 2016-04-08 | 2016-08-31 | 北京阳光欣晴健康管理有限责任公司 | System for implementing coronary heart disease post-diagnosis management |
| CN108766573A (en) * | 2018-06-01 | 2018-11-06 | 南华大学 | A kind of doctors and patients' Symptoms Assessment system |
| CN109691983A (en) * | 2018-11-13 | 2019-04-30 | 深圳市和缘科技有限公司 | A kind of intelligence disturbances in patients with Parkinson disease monitor system |
Non-Patent Citations (2)
| Title |
|---|
| 医脉通神经科: "帕金森病诊断只能等运动症状？这篇文章教你提前几年做诊断", 《微信》 * |
| 帕友AI助手: "帕友AI助手小程序功能介绍一（自我评测及用药记录）", 《微信》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112687378A (en) * | 2020-12-31 | 2021-04-20 | 中国科学院合肥物质科学研究院 | Parkinson's disease dyskinesia symptom monitoring platform and application thereof |
| CN112687378B (en) * | 2020-12-31 | 2024-06-21 | 中国科学院合肥物质科学研究院 | Parkinson disease dyskinesia symptom monitoring platform and application thereof |
| CN115148330A (en) * | 2022-05-24 | 2022-10-04 | 中国医学科学院北京协和医院 | POP treatment scheme forming method and system |
| CN115148330B (en) * | 2022-05-24 | 2023-07-25 | 中国医学科学院北京协和医院 | POP treatment scheme forming method and system |
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