KR102659016B1 - Apparatus and method for providing health care behavior habituation indicators of health programs - Google Patents

Abstract

By calculating the degree of habituation of healthcare program participants' healthcare behavior as an indicator and providing a visualized graphical interface based on the calculated indicators, data that is helpful in analyzing the effectiveness of practical mobile healthcare service projects and developing and operating programs is provided intuitively. It presents a device and method for providing health management behavior habituation indicators that can be easily identified. The presented device includes a device usage rate calculator that calculates the device usage rate based on usage information of devices for health care services collected as the health program progresses; a self-input practice rate calculation unit that calculates a self-input practice rate based on information for each self-input item of the user terminal collected as the health program progresses; an index calculation unit that calculates a health care behavior habituation index based on one or more of the calculated device usage rate and self-input practice rate, and visualizes the calculated health care behavior habituation index in a comparison graph interface; and an indicator transmitter that outputs the visualized health management behavior habituation indicator as an indicator corresponding to the health program.

Description

Apparatus and method for providing health care behavior habituation indicators of health programs}

The present invention relates to an apparatus and method for providing a health management behavior habituation indicator for a health program, and more specifically, to an apparatus and method for providing a health management behavior habituation indicator for a health program for verifying the business effectiveness of mobile healthcare services. will be.

Conventional health management service systems and/or programs use management devices distributed in connection with medical institutions, and the degree of improvement in health after using the program compared to the existing program based on sensor information of the management device or values directly entered into the mobile app, etc. A method of identifying and using it as an indicator is being used.

However, the effects of actual health management services are not calculated in a short period of time, and the indicators are not confirmed solely by the before-and-after changes in the subject's health level, and maintaining health as is is also important, so it is important to check whether the user has actually consistently practiced healthy habits. Although analysis is very important, there is a problem that it is very difficult to identify it as an indicator.

In particular, health care providers who set periodic goals and operate health management programs seek to develop and manage health management programs with the goal of habituating service participants' health management behavior, but the degree of habituation is not measured by before and after changes, but by using specific indicators and quantified data. There is no way to calculate it.

Likewise, since there is no quantified data, there are very few ways to visualize and provide the degree of habituation to health management behavior.

Prior art 1: Republic of Korea Patent No. 10-1439810 (regional and workplace-level health and disease index generation and health management support method and system) Prior art 1: Republic of Korea Patent No. 10-1584623 (Health care service provision system and method)

The present invention was proposed to solve the above-described conventional problems. It calculates the degree of habituation of health care behavior of health care program participants as an index and provides a visualized graphic interface based on the calculated index, thereby providing a practical mobile health care service. The purpose is to provide a device and method for providing indicators for health management behavior habituation of health programs that enable intuitive and easy identification of data helpful for business effect analysis, program development and operation.

In order to achieve the above object, a device for providing a health management behavior habituation indicator for a health program according to a preferred embodiment of the present invention calculates the device usage rate based on the usage information of the health care service device collected as the health program progresses. a device usage rate calculation unit; a self-input practice rate calculation unit that calculates a self-input practice rate based on information for each self-input item of the user terminal collected as the health program progresses; an index calculation unit that calculates a health care behavior habituation index based on one or more of the calculated device usage rate and self-input practice rate, and visualizes the calculated health care behavior habituation index in a comparison graph interface; and an indicator transmitter that outputs the visualized health management behavior habituation indicator as an indicator corresponding to the health program.

The health care service device is a device distributed to health care program participants and may include one or more of a blood sugar meter, a body composition meter, a blood pressure meter, and an activity level meter.

The device usage rate calculation unit counts the number of inputs each time the measurement information of each device is collected, accumulates this as the number of uses of each device, and counts the number of users for each device each time the measurement information of each device is collected. This can be accumulated, and the device usage rate can be calculated based on this.

The device usage rate is the final usage rate for each device generated based on the number of users at least once per device during the last parking of the health care service and the number of users at least once per device during the health care service period; and a total device usage rate, which is the sum of the proportions of people who used the provided device at least once among those who completed health care services.

The final usage rate for each device may be the number of users who used each device at least once during the last parking of the health care program divided by the number of users who used each device at least once during the health care service period.

The total device usage rate may apply the final usage rate for each device as a weight.

When the blood sugar meter, body composition monitor, blood pressure monitor, and activity meter are distributed to participants in the health management program, the total device usage rate is calculated using the following equation, total device usage rate = (A/(A+B+C+D))*(activity meter final usage rate of) + (B/(A+B+C+D))*(final usage rate of body composition monitor) + (C/(A+B+C+D))*(final usage rate of blood pressure monitor) + (D /(A+B+C+D))*(Final usage rate of the blood glucose meter) (where A refers to the number of users who used the activity meter, B refers to the number of users who used the body composition monitor, and C refers to the number of users using the body composition monitor) refers to the number of users using a blood pressure monitor, and D refers to the number of users using a blood sugar monitor.).

The information for each self-input item of the user terminal may include information on one or more items among health behavior, meal diary, and exercise diary corresponding to the health program.

The self-input practice rate calculation unit counts and accumulates the number of users who entered the self-input item and the number of times the self-input item was entered each time information about one or more of the plurality of self-input items is collected, and based on this, You can calculate the self-input practice rate.

The self-input practice rate is the final practice rate for each self-input item generated based on the number of practitioners who entered each self-input item at least once in the last week of health care service and the number of practitioners who entered each self-input item at least once during the health care service period; and the total self-input practice rate, which is the sum of the proportion of people who entered at least one self-input item among those who completed health care services.

The final practice rate for each self-input item may be the number of practitioners who entered each self-input item at least once in the last week of the health care service divided by the number of practitioners who entered each self-input item at least once during the health care service period.

The self-input total practice rate may apply the final practice rate for each self-input item as a weight.

When the health behavior, meal diary, and exercise diary are included in the self-input items, the self-input total practice rate is calculated using the formula below, self-input total practice rate = (E/(E+F+G))*(health behavior Final action rate of input) + (F/(E+F+G))*(Final action rate of meal diary entry) + (G/(E+F+G))*(Final action rate of exercise diary entry) (here, The E refers to the number of health behavior entryrs, the F refers to the number of food diary entryrs, and the G refers to the number of exercise diary entryrs.).

The indicator calculation unit may visualize the health management behavior habituation indicators by dividing them by year, gender, and age and displaying them together on one screen or in a scrolling manner.

Meanwhile, the method of providing a health care behavior habituation index according to a preferred embodiment of the present invention is a method of providing a health care behavior habituation index provided by a health care behavior habituation index providing device, and is a health care service device collected according to the progress of a health program. calculating device usage rate based on usage information; Calculating a self-input practice rate based on information for each self-input item of the user terminal collected as the health program progresses; Calculating a health care behavior habituation index based on one or more of the calculated device usage rate and self-input practice rate; Visualizing the calculated health management behavior habituation index using a comparison graph interface; and outputting the visualized health care behavior habituation index as an index corresponding to the health program through an administrator terminal.

According to the present invention with this configuration, it is possible to calculate an indicator indicating the degree of habituation of health behavior based on the device usage rate and self-input practice rate according to specific indicator definitions and calculation methods, and perform health program operation and performance analysis based on this. there is.

In particular, it can provide indicator definitions and calculation methods that can be checked as performance indicators even when health is maintained, and provides a visualization comparison graph interface to enable intuitive and clear identification of indicators by age/gender/year.

In addition, it can be inserted into data from health management organizations and public data areas, and can be used as one of the life log data, and can be used as a major means of verifying the effectiveness of health program projects.

In addition, since it is possible to generate and output screens or images that can intuitively identify health behavior habituation indicators, it has the advantage of improving the convenience of managers and making statistical analysis and status identification easier.

Figure 1 is a configuration diagram of a system for providing a health care behavior habituation indicator to which an embodiment of the present invention is applied.
FIG. 2 is an internal configuration diagram of the server shown in FIG. 1.
Figure 3 is a flow chart for explaining a method of providing a health care behavior habituation index according to an embodiment of the present invention.
Figures 4 to 19 are examples of comparison graph interfaces used to explain a method of providing health care behavior habituation indicators according to an embodiment of the present invention.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail.

However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all changes, equivalents, and substitutes included in the spirit and technical scope of the present invention.

The terms used in this application are only used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that it does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the technical field to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless clearly defined in the present application, should not be interpreted in an idealized or excessively formal sense. No.

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the attached drawings. In order to facilitate overall understanding when describing the present invention, the same reference numerals are used for the same components in the drawings, and duplicate descriptions of the same components are omitted.

Figure 1 is a configuration diagram of a system for providing a health care behavior habituation indicator to which an embodiment of the present invention is applied.

The system shown in FIG. 1 may include a user terminal 10, a health care service device 20, an administrator terminal 30, a network 40, and a server 50.

The user terminal 10 may transmit information for each self-input item to the server 50 through the network 40.

In other words, the user terminal 10 is equipped with a predetermined mobile application, and information for each self-input item entered through the mounted mobile application can be transmitted to the server 50 through the network 40.

Here, self-input items may include required items and optional items. Required items include detailed items such as smoking, drinking, physical activity and exercise, nutrition, obesity and weight control. Required items may be displayed on the screen in the form of a health behavior questionnaire, and users (i.e., users who participate in a health management program conducted for a certain period of time) can directly enter information for each detailed item of the required items. Selected items may include meal diary items and exercise diary items. Meal diary entries include detailed items recorded by the user as they eat (e.g., total calories, intake, serving size, calories, caloric nutrients, nutrient evaluation, etc.). For example, a user can enter information about each detailed item of a meal diary entry before/after a meal. Exercise diary items include detailed items (e.g., RPE, exercise duration, calories, etc.) recorded as the user exercises. For example, after exercising, the user can enter information for each detailed item of the exercise diary entry.

In this way, information entered for each self-input item (eg, including one or more of health behavior, meal diary, and exercise diary corresponding to a health program) may be referred to as information for each self-input item.

For example, the user terminal 10 may be implemented as a portable terminal or a portable computer. Here, the portable terminal is a wireless communication device that guarantees portability and mobility, including PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), and PDA (Personal Digital). Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet), Wi-Fi, LTE ( It may include all types of handheld-based wireless communication devices, such as Long Term Evolution (Long Term Evolution) terminals. Portable computers may include notebooks, laptops, etc.

Additionally, the user terminal 10 may be various smart devices such as a smartphone, smart note, tablet PC, or wearable computer.

The health care service device 20 is a device distributed by medical institutions such as public health centers to users (i.e., users who participate in a health care program conducted for a certain period of time), for example, a blood sugar meter, body composition meter, blood pressure meter, activity level meter, etc. This can be.

The health care service device 20 is internally equipped with a sensor (not shown) and a communication module (not shown). Accordingly, the blood sugar meter, body composition meter, blood pressure meter, and activity meter sense various information as the user (i.e., a user who participates in a health management program conducted for a certain period of time) uses the device, and transmit the sensed information to the network (40). ) can be transmitted to the server 50.

For example, the activity meter may transmit information such as number of steps, activity distance, calories burned, heart rate, etc. to the server 50. The body composition monitor can transmit information such as weight, muscle mass, body fat percentage, and BMI to the server 50. The blood pressure monitor can transmit information such as systolic blood pressure, diastolic blood pressure, and pulse to the server 50. The blood sugar meter can transmit blood sugar information to the server 50.

In this way, when a user uses a device, the device operates and transmits certain measurement information (e.g., measurement information such as activity level, body composition, blood pressure, blood sugar, etc.) to the server 50, thereby managing health. Information output from the service device 20 may be referred to as usage information of the health care service device 20.

In FIG. 1, the health care service device 20 is shown as including a blood sugar meter, a body composition meter, a blood pressure meter, and an activity meter, but if necessary, it may additionally include devices other than a blood sugar meter, a body composition meter, a blood pressure meter, and an activity meter. You may.

The administrator terminal 30 is a terminal of a person (i.e., administrator) who plans or manages a health care service program. Preferably, the manager may be a person working in a medical institution such as a public health center.

The manager terminal 30 may receive a health management behavior habituation indicator (eg, in the form of a comparison graph interface) from the server 50 through the network 40 and display it on the screen.

The manager will verify the validity of the health management behavior habituation indicators displayed on the screen on the corresponding terminal 30 and analyze the correlation between the indicators.

For example, the manager terminal 30 may be implemented as a portable terminal or portable computer. Here, the portable terminal is a wireless communication device that guarantees portability and mobility, including PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), and PDA (Personal Digital). Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet), Wi-Fi, LTE ( It may include all types of handheld-based wireless communication devices, such as Long Term Evolution (Long Term Evolution) terminals. Portable computers may include notebooks, laptops, etc.

Additionally, the manager terminal 30 may be various smart devices such as a smartphone, smart note, tablet PC, or wearable computer.

The network 40 facilitates communication between the user terminal 10 and the server 50, communication between the health care service device 20 and the server 50, and communication between the administrator terminal 30 and the server 50. Let it be lost.

For example, the network 40 may be implemented as a wired network such as a Local Area Network (LAN), a Wide Area Network (WAN), or a Value Added Network (VAN).

In addition, the network 40 includes a mobile radio communication network, a satellite communication network, Bluetooth, Wibro (Wireless Broadband Internet), HSDPA (High Speed Downlink Packet Access), Wi-Fi, and LTE (Long It can be implemented in all types of wireless networks such as Term Evolution).

If necessary, the network 40 may be a mixed wired and wireless network.

The server 50 provides information for each self-input item on the user terminal 10 in which a health program is in progress and usage information of the health care service device 20 (e.g., activity level/body composition/blood pressure according to the user's use of the device). /measurement information such as blood sugar) can be collected, and the device usage rate and self-input practice rate can be calculated based on the collected information.

In addition, the server 50 may calculate an indicator (i.e., referred to as a “health care behavior habituation index”) indicating the degree of health care behavior habituation of health care program participants based on one or more of the calculated device usage rate and self-input practice rate. You can.

The server 50 may visualize the calculated indicators in a comparison graph interface in a graph format and transmit them to the manager terminal 30.

FIG. 2 is an internal configuration diagram of the server shown in FIG. 1.

The server 50 may include an information collection unit 51, a device usage rate calculation unit 52, a self-input practice rate calculation unit 53, an indicator calculation unit 54, an indicator transmission unit 55, and a control unit 56. You can.

The information collection unit 51 provides information for each self-input item in the user terminal 10 in which a health program is in progress and usage information of the health care service device 20 (e.g., activity amount/body composition according to the user's use of the device). /measurement information such as blood pressure/blood sugar, etc.) can be collected.

Here, the information collection unit 51 may periodically collect information for each self-input item of the user terminal 10 and usage information of the health care service device 20.

The device usage rate calculation unit 52 counts the number of inputs each time measurement information for each device (eg, activity meter, body composition monitor, blood pressure monitor, blood sugar meter, etc.) is collected and accumulates this number as the number of uses for each device. In addition, the device usage rate calculation unit 52 can count and accumulate the number of users for each device each time measurement information for each device is collected. As a result, the device usage rate calculation unit 52 can calculate the number of users in the information collection unit 51. The device usage rate can be calculated based on the collected usage information of the health care service device 20.

The above-mentioned device usage rate may include the final usage rate for each device and the total device usage rate.

The total device usage rate refers to the sum of the proportion of people who have used the issued device (e.g., blood glucose meter, body composition monitor, blood pressure monitor, activity monitor) at least once among health care service completers (i.e., participants who completed the health care program). You can. When calculating the total device usage rate, the final usage rate for each device can be applied as a weight. The final usage rate by device is used to eliminate statistical distortions caused by concentrated use of specific devices.

In other words, the total device usage rate can be calculated based on the final usage rate for each device. For example, the final usage rate by device is the last week of health care service (e.g., week 24). The number of users per device more than once is calculated by calculating the number of devices used during the health care service period (i.e., the period during which the health care program is implemented). Divide by the number of users per star more than once.

The total device usage rate can be expressed as a formula as follows.

That is, “device total utilization = (A/(A+B+C+D))*(final utilization of device a) + (B/(A+B+C+D))*(final utilization of device b) + (C/(A+B+C+D))*(final utilization rate of device c) + (D/(A+B+C+D))*(final utilization rate of device d)". The above formula assumes the use of four devices (e.g., activity meter, body composition monitor, blood pressure monitor, and blood sugar meter), where A may refer to the number of users using device a (e.g., activity meter), and B may mean the number of users using device a (e.g., activity meter). may refer to the number of users using device b (e.g., body composition monitor), C may refer to the number of users using device c (e.g., blood pressure monitor), and D may refer to the number of users using device d (e.g., blood sugar monitor). It can mean. Even if the number of devices is 3 or less or 5 or more, it is obvious to those skilled in the art that the total device usage rate can be calculated based on the above formula.

The device usage rate calculation unit 52 may calculate the device usage rate for each cycle of each health care program implemented by medical institutions such as public health centers.

The self-input practice rate calculation unit 53 counts the number of users who entered the self-input item each time information on one or more of the plurality of self-input items (e.g., health behavior, meal diary, exercise diary) is collected. It can be accumulated. In addition, the self-input practice rate calculation unit 53 counts and accumulates the number of times the self-input item has been entered each time information on one or more of the plurality of self-input items (e.g., health behavior, meal diary, exercise diary) is collected. You can do it. Accordingly, the self-input practice rate calculation unit 53 can calculate the self-input practice rate based on the information for each self-input item of the user terminal 10 collected by the information collection unit 51.

The self-input practice rate described above may include the final practice rate for each self-input item and the total self-input practice rate.

The total self-input practice rate may mean the sum of the proportion of people who entered at least one self-input item among those who completed health care services (i.e., participants who completed a health care program). When calculating the total self-input practice rate, the final practice rate for each self-input item can be applied as a weight. The final implementation rate for each self-input item is used to eliminate statistical distortion caused by focusing on specific self-input items.

In other words, the total self-input practice rate can be calculated based on the final practice rate for each self-input item. For example, the final practice rate for each self-entered item is the last week of health care service (for example, it could be week 24). The number of practitioners who entered each self-entered item more than once is calculated by the health care service period (i.e., the number of people who implemented the health care program). Self-input at least once during the period) can be divided by the number of people who entered each item.

The total self-input practice rate can be expressed as a formula as follows.

In other words, "Total practice rate of self-input = (E/(E+F+G))*(final practice rate of health behavior entry) + (F/(E+F+G))*(final practice rate of food diary entry) + It can be equal to “(G/(E+F+G))*(final practice rate of exercise diary entry)”. In the above formula, E may mean the number of people who entered health behavior, F may mean the number of people who entered a meal diary, and G may mean the number of people who entered an exercise diary. The formula for the total self-input rate is assumed to be set to 3 self-input items (health behavior, food diary, exercise diary). Even if the number of self-input items is 4 or more, those skilled in the art will It is clear that the total self-input practice rate can be calculated based on the formula.

The self-input practice rate calculation unit 53 can calculate the self-input practice rate for each cycle of each health care program implemented by medical institutions such as public health centers.

The indicator calculation unit 54 includes the device usage rate calculated by the device usage rate calculation unit 52 (e.g., including the final usage rate for each device and the total device usage rate) and the self-input practice rate calculated by the self-input practice rate calculation unit 53 ( For example, based on the final practice rate for each self-entered item and the total self-entered practice rate), an indicator indicating the degree of health management behavior habituation of health care program participants (i.e., referred to as “health care behavior habituation index”) can be calculated. You can. For example, the indicator calculation unit 54 may use the calculated device usage rate or self-input practice rate as an indicator of health care behavior habits of health care program participants. As another example, the indicator calculation unit 54 may calculate an indicator of health care behavior habituation of health care program participants by adding the device usage rate and self-input practice rate. As another example, the indicator calculation unit 54 may calculate a combination of the device usage rate and the self-input practice rate to calculate the health management behavior habituation index of health care program participants.

In addition, the index calculation unit 54 can visualize the health care behavior habituation index in a comparative graph interface in a graph format divided by year, gender, and age. This is to enable managers to understand indicators intuitively and clearly. To this end, the index calculation unit 54 can be understood as having a built-in visualization processing module (not shown).

For example, the indicator calculation unit 54 can visualize indicators based on device usage rate and self-input practice rate by dividing them by year, gender, and age and displaying them together on one screen or in a scrolling manner.

Additionally, if necessary, the index calculation unit 54 may visualize the index based on the device usage rate by dividing it by year, gender, and age and displaying them together on one screen or in a scrolling manner.

In addition, if necessary, the indicator calculation unit 54 can visualize the indicators based on the self-input practice rate by dividing them by year, gender, and age and displaying them together on one screen or in a scrolling manner.

The indicator transmitter 55 may transmit the health management behavior habituation indicator visualized in the indicator calculation unit 54 to the manager terminal 30.

The control unit 56 controls the overall operation of the server 50, including an information collection unit 51, a device usage rate calculation unit 52, a self-input practice rate calculation unit 53, an indicator calculation unit 54, and an indicator transmission unit. (55) The control flow or data flow between can be managed.

In the above, it has been explained that the indicator calculation unit 54 visualizes the health management behavior habituation indicator in a graph format comparison graph interface divided by year, gender, and age. However, if necessary, the indicator transmitter 55 may be processed in a graph format. It may be visualized using the comparison graph interface.

The server 50 as described above may be an example of a device for providing a health management behavior habituation indicator as described in the claims of the present invention.

Figure 3 is a flow chart for explaining a method of providing a health care behavior habituation index according to an embodiment of the present invention.

First, the server 50 receives information for each self-input item from the user terminal 10 in which a health program is in progress and usage information from the health management service device 20 (e.g., the amount of activity/activity due to the user using the device). Measurement information (body composition/blood pressure/blood sugar, etc.) is collected (S10).

Then, the server 50 determines the device usage rate (i.e., including the final usage rate for each device and the total device usage rate) and the self-input action rate (i.e., the final action rate for each self-input item and the total self-input action rate) based on the collected information. (including) is calculated (S20). In other words, the server 50 can calculate the device usage rate based on the collected usage information of the health care service device 20, and calculate the self-input practice rate based on the collected information for each self-input item of the user terminal 10. It can be calculated.

Thereafter, the server 50 calculates an index (i.e., health care behavior habituation index) indicating the degree of health care behavior habituation of health care program participants based on one or more of the calculated device usage rate and self-input practice rate (S30). For example, the server 50 may use the calculated device usage rate or self-input practice rate as an indicator of health care behavior habits of health care program participants. As another example, the server 50 may calculate the health management behavior habituation index of health care program participants by adding the device usage rate and self-input practice rate. As another example, the server 50 may calculate the health management behavior habituation index of health care program participants by combining the device usage rate and self-input practice rate.

The server 50 visualizes the calculated indicators in a comparison graph interface in a graph format (S40).

Then, the server 50 transmits the visualized comparison graph interface to the manager terminal 30 (S50).

Figures 4 to 19 are examples of comparison graph interfaces used to explain a method of providing health care behavior habituation indicators according to an embodiment of the present invention.

The server 50 visualizes the indicators calculated based on the final usage rate for each device and provides a comparison graph interface in the form of a graph divided by year, gender, and age to the manager terminal 30 as shown in FIGS. 4 to 6. It can be sent to . Accordingly, in the manager terminal 30, the comparison graph interface in the graph format of FIGS. 4 to 6 may be displayed together on one screen or may be displayed in a scrolling manner.

In addition, the server 50 visualizes the indicators calculated based on the total device usage rate and provides a comparison graph interface in the form of a graph divided by year, gender, and age to the manager terminal 30 as shown in FIGS. 7 to 9. It can be sent to . Accordingly, in the manager terminal 30, the comparison graph interface in the graph format of FIGS. 7 to 9 may be displayed together on one screen or displayed in a scrolling manner.

In addition, the server 50 visualizes the indicators calculated based on the final practice rate for each self-input item and displays a comparative graph interface in the form of a graph divided by year, gender, and age as shown in FIGS. 10 to 12 at the administrator terminal ( 30) can be sent to. Accordingly, in the manager terminal 30, the comparison graph interface in the graph format of FIGS. 10 to 12 may be displayed together on one screen or may be displayed in a scrolling manner.

In addition, the server 50 visualizes the indicators calculated based on the self-input total practice rate and provides a comparative graph interface in the form of a graph divided by year, gender, and age as shown in FIGS. 13 to 15 through the administrator terminal 30. It can be sent to . Accordingly, in the administrator terminal 30, the comparison graph interface in the graph format of FIGS. 13 to 15 may be displayed together on one screen or may be displayed in a scrolling manner.

Accordingly, the manager can intuitively understand each device usage rate, self-input practice rate, etc. by checking the comparison graph interface in the graph format of FIGS. 4 to 15 displayed on the corresponding terminal 30.

Meanwhile, the server 50 visualizes the device usage rate and self-input practice rate and provides the manager terminal 30 with a comparison graph interface in the form of a graph divided by year, gender, and age as shown in FIG. 16 for health behavior improvers. It can be sent to .

On the other hand, the server 50 visualizes the device usage rate and self-input practice rate and provides a comparison graph interface in the form of a graph divided by year, gender, and age as shown in FIG. 17 for those who have not improved their health behavior to the manager terminal 30. It can be sent to .

On the other hand, the server 50 visualizes the device usage rate and self-input practice rate and displays a comparative graph interface in the form of a graph divided by year, gender, and age as shown in FIG. 18 for those with reduced health risk factors on the administrator terminal (30). ) can be sent to.

On the other hand, the server 50 visualizes the device usage rate and self-input practice rate and displays a comparative graph interface in the form of a graph divided by year, gender, and age as shown in FIG. 19 for those who have not reduced health risk factors on the administrator terminal (30). ) can be sent to.

Accordingly, as the manager checks the comparison graph interface in the graph format of FIGS. 16 to 19 displayed on the corresponding terminal 30, the higher the degree of actual health behavior habituation (i.e., the higher the device usage rate or self-input practice rate), the higher the ) You can intuitively confirm that health indicators are maintained or improved. In other words, if managers use devices a lot and are good at self-input, it can be understood that there is an effect of improving/maintaining health behavior and a small effect of reducing risk factors.

The embodiment of the present invention as described above can be used as an indicator output method for business verification services of health care institutions such as companies and public institutions, and can be used to index and display the user practice level of a health care program, and can be used to display health care programs. It can be used to output the monitoring screen of the project's follow-up management process.

In addition, the method of providing a health care behavior habituation index of the present invention described above can be implemented as computer-readable code on a computer-readable recording medium. Computer-readable recording media include all types of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices. Additionally, the computer-readable recording medium can be distributed in a computer system connected to a network, so that the computer-readable code can be stored and executed in a distributed manner. And, functional programs, codes, and code segments for implementing the method can be easily deduced by programmers in the technical field to which the present invention pertains.

As described above, the optimal embodiment has been disclosed in the drawings and specifications. Although specific terms are used here, they are used only for the purpose of describing the present invention and are not used to limit the meaning or scope of the present invention described in the claims. Therefore, those skilled in the art will understand that various modifications and other equivalent embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the attached claims.

10: User terminal 20: Device for health care services
30: Administrator terminal 40: Network
50: Server 51: Information collection unit
52: Device usage rate calculation unit 53: Self-input practice rate calculation unit
54: indicator calculation unit 55: indicator transmitter
56: control unit

Claims (15)

a device usage rate calculation unit that calculates a device usage rate based on usage information of devices for health care services collected as the health program progresses;
a self-input practice rate calculation unit that calculates a self-input practice rate based on information for each self-input item of the user terminal collected as the health program progresses;
an index calculation unit that calculates a health care behavior habituation index based on one or more of the calculated device usage rate and self-input practice rate, and visualizes the calculated health care behavior habituation index in a comparison graph interface; and
It includes an indicator transmitter that outputs the visualized health management behavior habituation indicator as an indicator corresponding to the health program,
The health care service device is a device distributed to health care program participants,
The device usage rate calculation unit,
Each time measurement information for each device is collected, the number of inputs is counted and accumulated as the number of uses for each device, and each time measurement information for each device is collected, the number of users for each device is counted and accumulated.
The device usage rate is,
A final usage rate for each device, which is calculated by dividing the number of users of the health program at least once for each device during the last parking period by the number of users for each device at least once during the health care service period; and
It includes a total device usage rate calculated by applying the final usage rate for each device as a weight to the sum of the proportions of people who used the device provided at least once among those who completed health care services,
The self-input practice rate calculation unit,
Whenever information on one or more of the self-input items is collected, the number of users who entered the self-input item and the number of times the self-input item was entered are counted and accumulated.
The self-input practice rate is,
The final practice rate for each self-input item, which is calculated by dividing the number of practitioners who entered each self-input item at least once in the last week of the health program by the number of practitioners who entered each self-input item at least once during the health care service period; and
Includes a total self-input practice rate that applies the final practice rate for each self-input item as a weight to the sum of the proportion of people who entered at least one self-input item among those who completed health care services,
The indicator calculation unit calculates the health management behavior habituation indicator by combining the device usage rate and the self-input practice rate.
A device that provides indicators for health management behavior habituation in health programs. According to clause 1,
The device for health care services is,
Containing one or more of a blood sugar meter, a body composition meter, a blood pressure meter, and an activity meter,
A device that provides indicators for health management behavior habituation in health programs. delete delete delete delete According to clause 2,
When the blood sugar monitor, body composition monitor, blood pressure monitor, and activity monitor are distributed to participants in the health care program, the total device usage rate is calculated by the following equation,
Total device usage rate = (A/(A+B+C+D))*(Final usage rate of activity tracker) + (B/(A+B+C+D))*(Final usage rate of body composition monitor) + (C /(A+B+C+D))*(Final usage rate of blood pressure monitor) + (D/(A+B+C+D))*(Final usage rate of blood glucose meter)
(Here, A refers to the number of users using an activity meter, B refers to the number of users using a body composition monitor, C refers to the number of users using a blood pressure monitor, and D refers to the number of users using a blood sugar monitor. Meaning.)
Saved by,
A device that provides indicators for health management behavior habituation in health programs. According to clause 1,
The information for each self-input item of the user terminal is,
Containing information on one or more items among health behavior, meal diary, and exercise diary corresponding to the health program,
A device that provides indicators for health management behavior habituation. delete delete delete delete According to clause 8,
If the health behavior, meal diary, and exercise diary are included in the self-input items, the total self-input practice rate is calculated by the following equation,
Total practice rate of self-input = (E/(E+F+G))*(final practice rate of health behavior entry) + (F/(E+F+G))*(final practice rate of food diary entry) + (G/ (E+F+G))*(Final implementation rate of exercise diary entries)
(Here, E refers to the number of health behavior entryrs, F refers to the number of food diary entries, and G refers to the number of exercise diary entries.)
Saved by,
A device that provides indicators for health management behavior habituation in health programs. According to clause 1,
The indicator calculation unit,
The health care behavior habituation indicators are categorized by year, gender, and age and visualized so that they are displayed together on one screen or displayed in a scrolling manner.
A device that provides indicators for health management behavior habituation in health programs. As a method of providing a health care behavior habituation index provided by a health care behavior habituation index providing device,
Calculating a device usage rate based on usage information of a healthcare service device collected as the health program progresses;
Calculating a self-input practice rate based on information for each self-input item of the user terminal collected as the health program progresses;
Calculating a health care behavior habituation index based on one or more of the calculated device usage rate and self-input practice rate;
Visualizing the calculated health management behavior habituation index using a comparison graph interface; and
A step of outputting the visualized health care behavior habituation index as an index corresponding to the health program through an administrator terminal,
The health care service device is a device distributed to health care program participants,
The step of calculating the device usage rate is,
Each time measurement information for each device is collected, the number of inputs is counted and accumulated as the number of uses for each device, and each time measurement information for each device is collected, the number of users for each device is counted and accumulated.
The device usage rate is,
A final usage rate for each device, which is calculated by dividing the number of users of the health program at least once for each device during the last parking period by the number of users for each device at least once during the health care service period; and
It includes a total device usage rate calculated by applying the final usage rate for each device as a weight to the sum of the proportions of people who used the device provided at least once among those who completed health care services,
The step of calculating the self-input practice rate is,
Whenever information on one or more of the self-input items is collected, the number of users who entered the self-input item and the number of times the self-input item was entered are counted and accumulated.
The self-input practice rate is,
The final practice rate for each self-input item, which is calculated by dividing the number of practitioners who entered each self-input item at least once in the last week of the health program by the number of practitioners who entered each self-input item at least once during the health care service period; and
Includes a total self-input practice rate that applies the final practice rate for each self-input item as a weight to the sum of the proportion of people who entered at least one self-input item among those who completed health care services,
Calculate the health care behavior habituation index by combining the device usage rate and the self-input practice rate.
How to provide indicators for habituation of health care behavior.

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