Cardiovascular disease prevention and treatment service quality evaluation system and method based on multi-source data

Abstract

The present application relates to the medical information technology field, and discloses a cardiovascular disease prevention and treatment service quality evaluation system and method based on multi-source data, and the present application relates to the system includes data acquisition module, service identification and classification module, income base evaluation module, service item scoring module, fitting rate calculation module and performance evaluation module.The application collects the electronic medical record and identity information of the patient through the medical information system, constitutes the patient data set, simultaneously obtains the verification data through the independent third party channel, constitutes the external verification data set, determines the service type required by the patient based on the data set, calculates the income base of the service, the total score of the service item and the fitting rate based on the data set collected in the early stage, calculates the total bonus of the performance evaluation of the doctor based on the income base, the total score of the service item and the fitting rate, improves the objectivity and accuracy of the evaluation of the service quality of the doctor, and meanwhile the doctor can dynamically adjust the focus degree of the patient.

Description

Technical Field

[0001] This invention relates to the field of medical information technology, specifically to a cardiovascular disease prevention and treatment service quality assessment system and method based on multi-source data. Background Technology

[0002] Cardiovascular disease is the leading cause of death and disease burden in my country, making the shift of prevention and control focus to primary healthcare institutions a crucial public health strategy. Currently, primary care physicians undertake a significant workload in their daily work, including screening, follow-up, diagnosis, treatment, and referral support related to cardiovascular diseases. However, the quality assessment of primary cardiovascular disease prevention and control services still faces numerous technical challenges.

[0003] Existing primary healthcare information systems mainly record structured data such as diagnoses and medications, lacking systematic quantitative evaluation indicators for the completeness and standardization of service processes. Significant differences exist in the performance of different doctors in providing the same type of service, making objective comparison and quality control difficult. Furthermore, different cardiovascular patients exhibit significant differences in disease risk, disease complexity, and management difficulty, but existing assessment methods often employ a "one-size-fits-all" scoring approach, failing to dynamically adjust service value based on individual patient characteristics (such as age, smoking history, and family history). This results in doctors lacking the motivation to proactively focus on high-risk, high-needs patients. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a cardiovascular disease prevention and treatment service quality assessment system and method based on multi-source data. This system comprises a patient dataset constructed by collecting patients' electronic medical records and identity information, and a verification dataset constructed by collecting verification data. Based on these datasets, the system obtains the revenue base, total service item scores, and consistency rate, and then calculates the total performance evaluation score for primary care physicians. This improves the objectivity and accuracy of physician service quality assessment and solves the aforementioned technical problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a cardiovascular disease prevention and treatment service quality assessment system based on multi-source data, including a data acquisition module, a service identification and classification module, a revenue base assessment module, a service item scoring module, a concordance rate calculation module, and a performance evaluation module;

[0006] The data acquisition module includes a patient information acquisition unit and a verification data acquisition unit. The patient information acquisition unit collects the patient's electronic medical records and identity information through the medical information system to form a patient dataset. The verification data acquisition unit obtains verification data through independent third-party channels to form an external verification dataset.

[0007] The service identification and classification module identifies the type of service the patient currently needs based on the patient's identity information.

[0008] The revenue base assessment module calculates the revenue base based on the patient dataset and service type.

[0009] The service item scoring module calculates the total score for each service item based on the patient dataset.

[0010] The matching rate calculation module calculates the matching rate based on the external verification dataset and service type.

[0011] The performance evaluation module calculates the doctor's total performance evaluation score.

[0012] As a preferred embodiment of the present invention, the expression for the patient dataset is: ,in, , and They represent the first The patient, the first The patient and the first The patient data includes the patient's identity information and electronic medical records. The patient's identity information includes the patient's name, gender, age, ID number, and the service type selected by the patient. The service type includes screening and tracking service, regular follow-up service, disease management service, and referral support service.

[0013] As a preferred embodiment of the present invention, the expression for the external verification dataset is: ,in, , and They represent the first The patient, the first The patient and the first External validation data for one patient, wherein the expression for the external validation data for that patient is: ,in, , and These represent the current patient's number. sequence Second and third Follow-up data corresponding to each service session. The service type is indicated by the follow-up data, which specifically refers to the follow-up verification values ​​corresponding to several key service items obtained by verifying key service items through third-party channels.

[0014] As a preferred technical solution of the present invention, the service identification and classification module obtains the service type currently needed by the patient based on the patient's identity information. Specifically, it retrieves the historical service type sequence currently selected by the patient based on the patient's ID number and takes the latest service type selected by the patient as the service type currently needed by the patient.

[0015] As a preferred embodiment of the present invention, the revenue base assessment module calculates the revenue base based on the patient dataset and service type using the following expression: ; in, Indicates the first The revenue base corresponding to each service type Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; Indicates the first The base revenue for each type of service; Indicates the first of the current service types One risk factor; This represents the set of risk factors related to the current service type; Indicates the current service type number The weighting coefficients corresponding to each risk factor; Indicates the current service type number Risk scores for each risk factor; This indicates a summation operation.

[0016] As a preferred technical solution of the present invention, the service item scoring module calculates the total score of the service item based on the patient dataset, including the following steps: Step A1: Calculate the symptom assessment score and diagnostic assessment score of the patient at each stage of medical treatment. The patient's medical treatment stages include four stages: symptoms and medical history, examination and testing, diagnosis and treatment, and education and consultation. The relevant expressions are as follows: ; ; in, Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment; Indicates the patient was in the first The first stage of medical treatment Symptom assessment scores for each item; Indicates the patient was in the first The first stage of medical treatment Diagnostic assessment scores for each item; and They represent the summation operation; This indicates taking the minimum value;

[0017] Step A2: Calculate the service item scores for each stage of the patient's medical treatment. The relevant expressions are as follows:

[0018] in, Indicates the patient was in the first Scores for service items under each stage of medical treatment; and These are the weighting coefficients; Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment;

[0019] Step A3: Calculate the patient's total score for each service item, as shown in the following expression: ; in, This represents the patient's total score for the service items. Indicates the first The weighting coefficients corresponding to each stage of medical treatment; Indicates the patient was in the first Scores for service items under each stage of medical treatment; This indicates a summation operation.

[0020] As a preferred embodiment of the present invention, the matching rate calculation module calculates the matching rate based on the external verification dataset and service type using the following expression: ; in, Indicates the first The matching rate corresponding to each service type; Indicates the number of services under the current service type. Electronic record values ​​of key service items; Indicates the number of services under the current service type. Follow-up verification values ​​for key service items; Indicates an indicator function, when When, the value is 1, when When the value is 0; This indicates the total number of key service items under the current service type; This indicates a summation operation.

[0021] As a preferred embodiment of the present invention, the performance evaluation module calculates the doctor's total performance evaluation score, including the following steps:

[0022] Step B1: Calculate the performance evaluation score for each service provided by the doctor based on the type of service provided each time; Step B2: Calculate the doctor's total performance evaluation score, the expression of which is as follows:

[0023] in, This indicates the total score in the performance evaluation; This indicates the total number of services provided by the doctor; The doctor's first Bonus points for performance evaluation of the service; This indicates a summation operation.

[0024] As a preferred embodiment of the present invention, the expression for adding points in the performance evaluation in step B1 is as follows: ; in, Indicates the first Performance evaluation bonus points corresponding to different service types Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; No. The revenue base corresponding to each service type; Indicates the first The matching rate corresponding to each service type; This represents the patient's total score for the service items.

[0025] This invention also provides a method for assessing the quality of cardiovascular disease prevention and treatment services based on multi-source data, comprising the following steps:

[0026] S1: Collect patients' electronic medical records and identity information through the medical information system to form a patient dataset;

[0027] S2: Obtain verification data through independent third-party channels to form an external verification dataset;

[0028] S3: Based on the patient's identity information, determine the type of service the patient currently needs;

[0029] S4: Calculate the revenue base based on the S1 patient dataset and the S3 service type. ;

[0030] S5: Calculate the total score for service items based on the S1 patient dataset. ;

[0031] S6: Calculate the matching rate based on the S2 external validation dataset and the S3 service type. ;

[0032] S7: Based on the S4 revenue base S5 service item total score Match rate with S6 The total bonus points for the doctor's performance evaluation were calculated. .

[0033] Compared with existing technologies, this invention provides a cardiovascular disease prevention and treatment service quality assessment system and method based on multi-source data, which has the following beneficial effects:

[0034] This invention collects patients' electronic medical records and identity information through a medical information system to form a patient dataset. Simultaneously, it obtains verification data through independent third-party channels to form an external verification dataset. Based on the dataset, it determines the types of services needed by patients. Based on the previously collected dataset, it calculates the service revenue base, total score of service items, and matching rate. Based on the revenue base, total score of service items, and matching rate, it calculates the doctor's total performance evaluation score, thereby improving the objectivity and accuracy of the evaluation of the doctor's service quality. At the same time, doctors can dynamically adjust the level of focus they pay to patients. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0036] Figure 2 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Please see Figure 1 The cardiovascular disease prevention and control service quality assessment system based on multi-source data includes: a data acquisition module, a service identification and classification module, a benefit base assessment module, a service item scoring module, a matching rate calculation module, and a performance evaluation module.

[0039] The data acquisition module includes a patient information acquisition unit and a verification data acquisition unit. The patient information acquisition unit collects patients' electronic medical records and identity information through the medical information system to form a patient dataset. The verification data acquisition unit obtains verification data through independent third-party channels to form an external verification dataset.

[0040] The expression for the patient dataset is: ,in, , and They represent the first The patient, the first The patient and the first Patient data for each patient includes the patient's identity information and electronic medical records. The patient's identity information includes the patient's name, gender, age, ID number, and the type of service selected by the patient. The type of service includes screening and tracking services, regular follow-up services, disease management services, and referral support services.

[0041] The expression for the external validation dataset is: ,in, , and They represent the first The patient, the first The patient and the first External validation data for each patient, the expression for the external validation data for each patient is: ,in, , and These represent the current patient's number. sequence Second and third Follow-up data corresponding to each service session. This indicates the service type. The follow-up data specifically refers to the verification of key service items through third-party channels, such as the follow-up verification values ​​corresponding to several key service items obtained through telephone follow-ups.

[0042] The service identification and classification module identifies the type of service the patient currently needs based on the patient's identity information. Specifically, it retrieves the historical service type sequence selected by the patient based on the patient's ID number and uses the latest service type selected by the patient as the service type the patient currently needs.

[0043] The revenue base assessment module calculates the revenue base based on the patient dataset and service type, and its expression is as follows: ;

[0044] in, Indicates the first The revenue base corresponding to each service type Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; Indicates the first The base revenue for each type of service; Indicates the first of the current service types One risk factor; This represents the set of risk factors related to the current service type; Indicates the current service type number The weighting coefficients corresponding to each risk factor; Indicates the current service type number Risk scores for each risk factor; This represents the summation operation;

[0045] It quantifies the additional risk load of individual patients under the current service type. Multiplying the base value by 1 plus the risk load means that the service value increases proportionally with the increase of patient risk. The higher the risk, the more complex the condition, and the greater the management difficulty, the higher the expected health benefits and the value of the doctor's labor for this service.

[0046] Taking screening and tracking services as an example, the corresponding risk factors include age, weight, smoking, and family history. When a patient's age is ≤30, the age score = 0; when age is 30 < ≤ 40, the age score = 1; when age is 40 < ≤ 50, the age score = 2; when age is 50 < ≤ 60, the age score = 3; and when age is > 60, the age score = 4. When a patient's body mass index (BMI) is normal, the weight score = 0; when BMI is below normal or overweight, the weight score = 1; and when BMI reaches the obesity standard, the weight score = 2. When a patient has never smoked, the smoking score = 0; when a patient has smoked, the smoking score = 1; and when a patient is currently smoking, the smoking score = 2. The patient's family history score = the number of immediate family members who have been diagnosed with cardiovascular disease.

[0047] The service item scoring module calculates the total score for each service item based on the patient dataset, including the following steps: Step A1: Calculate the symptom assessment score and diagnostic assessment score for each stage of the patient's medical treatment. The patient's medical treatment stages include four stages: symptoms and medical history, examination and testing, diagnosis and treatment, and education and consultation. The relevant expressions are as follows: ; ;

[0048] in, Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment; Indicates the patient was in the first The first stage of medical treatment Symptom assessment scores for each item; Indicates the patient was in the first The first stage of medical treatment Diagnostic assessment scores for each item; and They represent the summation operation; This indicates taking the minimum value; This indicates that a score is calculated based on six preset cardiovascular-related symptom items, and the condition is met when four or more of these items are met. A score of 1 is awarded for a perfect score. Related symptom items include dizziness, headache, chest tightness, and chest pain. This indicates that a score is calculated based on 14 preset cardiovascular-related diagnostic items, and the result is achieved when 6 of these items are met. A perfect score of 1 is achieved.

[0049] Step A2: Calculate the service item scores for each stage of the patient's medical treatment. The relevant expressions are as follows:

[0050] in, Indicates the patient was in the first Scores for service items under each stage of medical treatment; and These are the weighting coefficients; Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment;

[0051] Step A3: Calculate the patient's total score for each service item, as shown in the following expression: ; in, This represents the patient's total score for the service items. Indicates the first The weighting coefficients corresponding to each stage of medical treatment; Indicates the patient was in the first Scores for service items under each stage of medical treatment; This represents the summation operation;

[0052] The matching rate calculation module calculates the matching rate based on the external validation dataset and service type, and its expression is as follows: ; in, Indicates the first The matching rate corresponding to each service type; Indicates the number of services under the current service type. Electronic record values ​​of key service items; Indicates the number of services under the current service type. Follow-up verification values ​​for key service items; Indicates an indicator function, when When, the value is 1, when When the value is 0; This indicates the total number of key service items under the current service type; This formula represents a summation operation; it quantifies the authenticity and accuracy of the service records submitted by primary care physicians by comparing key service items in electronic medical records with the follow-up verification results from telephone follow-ups item by item.

[0053] The performance evaluation module calculates the doctor's total performance evaluation score, including the following steps:

[0054] Step B1: Calculate the performance evaluation score for each service based on the type of service provided by the doctor each time. The expression is as follows: ; in, Indicates the first Performance evaluation bonus points corresponding to different service types Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; No. The revenue base corresponding to each service type; Indicates the first The matching rate corresponding to each service type; This represents the patient's total score for each service item; Step B2: Calculate the doctor's total performance evaluation score, expressed as follows: ; in, This indicates the total score in the performance evaluation; This indicates the total number of services provided by the doctor; The doctor's first Bonus points for performance evaluation of the service; This indicates a summation operation.

[0055] Please see Figure 2 The present invention also provides a method for evaluating the quality of cardiovascular disease prevention and treatment services based on multi-source data, comprising the following steps:

[0056] S1: Collect patients' electronic medical records and identity information through the medical information system to form a patient dataset;

[0057] S2: Obtain verification data through independent third-party channels to form an external verification dataset;

[0058] S3: Based on the patient's identity information, determine the type of service the patient currently needs;

[0059] S4: Calculate the revenue base based on the S1 patient dataset and the S3 service type. ;

[0060] S5: Calculate the total score for service items based on the S1 patient dataset. ;

[0061] S6: Calculate the matching rate based on the S2 external validation dataset and the S3 service type. ;

[0062] S7: Based on the S4 revenue base S5 service item total score Match rate with S6 The total bonus points for doctors' performance evaluations were calculated. .

[0063] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cardiovascular disease prevention and treatment service quality assessment system based on multi-source data, characterized in that: It includes a data acquisition module, a service identification and classification module, a revenue base assessment module, a service item scoring module, a matching rate calculation module, and a performance evaluation module; The data acquisition module includes a patient information acquisition unit and a verification data acquisition unit. The patient information acquisition unit collects the patient's electronic medical records and identity information through the medical information system to form a patient dataset. The verification data acquisition unit obtains verification data through independent third-party channels to form an external verification dataset. The service identification and classification module identifies the type of service the patient currently needs based on the patient's identity information. The revenue base assessment module calculates the revenue base based on the patient dataset and service type. The service item scoring module calculates the total score for each service item based on the patient dataset. The matching rate calculation module calculates the matching rate based on the external verification dataset and service type. The performance evaluation module calculates the doctor's total performance evaluation score.

2. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 1, characterized in that: The expression for the patient dataset is: ,in, , and They represent the first The patient, the first The patient and the first The patient data includes the patient's identity information and electronic medical records. The patient's identity information includes the patient's name, gender, age, ID number, and the service type selected by the patient. The service type includes screening and tracking service, regular follow-up service, disease management service, and referral support service.

3. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 2, characterized in that: The expression for the external validation dataset is: ,in, , and They represent the first The patient, the first The patient and the first External validation data for one patient, wherein the expression for the external validation data for that patient is: ,in, , and These represent the current patient's number. sequence Second and third Follow-up data corresponding to each service session. The service type is indicated by the follow-up data, which specifically refers to the follow-up verification values ​​corresponding to several key service items obtained by verifying key service items through third-party channels.

4. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 3, characterized in that: The service identification and classification module identifies the type of service the patient currently needs based on the patient's identity information. Specifically, it retrieves the historical service type sequence selected by the patient based on the patient's ID number and uses the latest service type selected by the patient as the service type the patient currently needs.

5. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 4, characterized in that: The revenue base assessment module calculates the revenue base based on the patient dataset and service type using the following expression: ； in, Indicates the first The revenue base corresponding to each service type Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; Indicates the first The base revenue for each type of service; Indicates the first of the current service types One risk factor; This represents the set of risk factors related to the current service type; Indicates the current service type number The weighting coefficients corresponding to each risk factor; Indicates the current service type number Risk scores for each risk factor; This indicates a summation operation.

6. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 5, characterized in that: The service item scoring module calculates the total score for each service item based on the patient dataset. The calculation process includes the following steps: Step A1: Calculate the symptom assessment score and diagnostic assessment score for each stage of the patient's medical treatment. The patient's medical treatment stages include four phases: symptoms and medical history, examination and testing, diagnosis and treatment, and education and consultation. The relevant expressions are as follows: ； ； in, Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment; Indicates the patient was in the first The first stage of medical treatment Symptom assessment scores for each item; Indicates the patient was in the first The first stage of medical treatment Diagnostic assessment scores for each item; and They represent the summation operation; This indicates taking the minimum value; Step A2: Calculate the service item scores for each stage of the patient's medical treatment. The relevant expressions are as follows: ; in, Indicates the patient was in the first Scores for service items under each stage of medical treatment; and These are the weighting coefficients; Indicates the patient was in the first Symptom assessment scores at each stage of medical treatment; Indicates the patient was in the first Diagnostic assessment scores at each stage of medical treatment; Step A3: Calculate the patient's total score for each service item, as shown in the following expression: ; in, This represents the patient's total score for the service items. Indicates the first The weighting coefficients corresponding to each stage of medical treatment; Indicates the patient was in the first Scores for service items under each stage of medical treatment; This indicates a summation operation.

7. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 6, characterized in that: The matching rate calculation module calculates the matching rate based on the external validation dataset and service type, and the expression for the matching rate is as follows: ； in, Indicates the first The matching rate corresponding to each service type; Indicates the number of services under the current service type. Electronic record values ​​of key service items; Indicates the number of services under the current service type. Follow-up verification values ​​for key service items; Indicates an indicator function, when When, the value is 1, when When the value is 0; This indicates the total number of key service items under the current service type; This indicates a summation operation.

8. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 1, characterized in that: The performance evaluation module calculates the doctor's total performance evaluation score, including the following steps: Step B1: Calculate the performance evaluation score for each service provided by the doctor based on the type of service provided each time; Step B2: Calculate the doctor's total performance evaluation score, the expression of which is as follows: ; in, This indicates the total score in the performance evaluation; This indicates the total number of services provided by the doctor; The doctor's first Bonus points for performance evaluation of the service; This indicates a summation operation.

9. The cardiovascular disease prevention and treatment service quality assessment system based on multi-source data according to claim 8, characterized in that: The expression for adding points in the performance evaluation in step B1 is as follows: ； in, Indicates the first Performance evaluation bonus points corresponding to different service types Indicates screening and tracking services, This indicates regular follow-up services. Indicates disease treatment services. Indicates referral support services; No. The revenue base corresponding to each service type; Indicates the first The matching rate corresponding to each service type; This represents the patient's total score for the service items.

10. A method for assessing the quality of cardiovascular disease prevention and control services based on multi-source data, and based on the cardiovascular disease prevention and control service quality assessment system based on multi-source data as described in any one of claims 1-9, characterized in that: Includes the following steps: S1: Collect patients' electronic medical records and identity information through the medical information system to form a patient dataset; S2: Obtain verification data through independent third-party channels to form an external verification dataset; S3: Based on the patient's identity information, determine the type of service the patient currently needs; S4: Calculate the revenue base based on the S1 patient dataset and the S3 service type. ; S5: Calculate the total score for service items based on the S1 patient dataset. ; S6: Calculate the matching rate based on the S2 external validation dataset and the S3 service type. ; S7: Based on the S4 revenue base S5 service item total score Match rate with S6 The total bonus points for doctors' performance evaluations were calculated. .

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