JP2000163468A - Senior house service management system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To support services and management by predicting changes of the resident of a senior house. SOLUTION: This system is equipped with setting tables 4 and 5 wherein coefficients corresponding to health information are set so as to find a mean resident's final age and the health indexes of residents, resident's final age calculating means 13 and 14 which find the health indexes by referring to the setting tables 4 and 5 according to health information of the respective residents and predicts the final ages of the respective residents according to the mean resident final age, and output means 15 and 16 which finds the transition of the number of the residents from the predicted resident's final ages and outputs service and management information and offeres the service management system of senior houses for the aged person before care is needed. Further, a storage means stores the differences between the predicted resident's final ages and the actual resident's final ages as learning information for the coefficients for finding the health indexes and mean resident's final age.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a senior housing service management system for elderly persons who need to move in before nursing is required.

[0002]

2. Description of the Related Art Apart from conventional nursing homes, senior housing for the elderly has been planned by the Urban Development Corporation. This senior housing will allow you to move in without having to worry about paying monthly rent, and is based on the assumption that you will be able to cover your rent with a lifetime annuity pension. In addition, by making an appointment with a nursing care facility at the time of occupancy, and joining a non-life insurance company with nursing care insurance, it is possible to cope with the need for nursing care.

[0003] In anticipation of an increase in the demand for senior housing as described above toward an aging society, it is very important how to efficiently operate senior housing. Therefore, a system suitable for service and management for senior housing is required, but such a system is not yet established.

[0004]

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and aims at predicting a change in a resident of a senior house and supporting services and management.

[0005] Therefore, the present invention is a senior housing service management system for elderly people who need to move in before nursing, and a coefficient according to health information for obtaining an average occupant final age and a resident's health index. A final setting age calculating means for calculating a health index by referring to the setting table from the health information of each resident to determine a health index for each resident based on the average final occupying age, and And output means for outputting the service / management information by calculating the transition of the number of residents from the estimated final occupancy age.

The health index is set at least for each of the resident's gender, age, living environment, and occupancy conditions, or is obtained by considering resident's health information in terms of gender, age, living environment, and occupancy conditions. It is characterized by the following.
Further, the present invention is characterized in that a storage means is provided for storing the difference between the predicted and calculated final occupancy age and the generated final occupancy age as a coefficient for obtaining the index and learning information of the average final occupancy age.

[0007]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing an embodiment of a senior housing service management system according to the present invention, FIG. 2 is a diagram showing a configuration example of a table, and FIG. 3 is a diagram showing a configuration example of a resident management file. In the figure, 1 is a data processing device, 2
Is an input device, 3 is an output device, 4 is a resident management file,
5 is the average final age table, 6 is the index calculation table, 7
Is a service table by size, 8 is a learning data file,
11 is an input / output processing unit, 12 is a resident management file creation processing unit, 13 is a health index calculation unit, 14 is a resident final age calculation unit, 15 is a occupancy period calculation unit, 16 is a service operation calculation unit, and 17 is learning data. 4 shows an accumulation processing unit.

In FIG. 1, an input device 1 includes a keyboard, a mouse, and other pointing devices for inputting various data relating to services and management of a target senior house, inputting resident data, inputting instructions for arithmetic processing, and the like. is there. The output device 2 is a CR that displays input contents from the input device 1, a menu for input, and processing contents.
T display and other display devices, printers, XY plotters and other printing devices.

The data processing device 1 processes data based on various data and instructions input from the input device 1, and performs input / output processing between the input device 1 and the output device 2. Processing unit 11, resident management file creation processing unit 12, health index calculation unit 13, resident final age calculation unit 1 as various processing units for processing input data
4, a occupancy period calculation unit 15, a service operation calculation unit 16, and a learning data accumulation processing unit 17.

The resident management file 4 includes resident data,
For example, a file as shown in FIG. 3 for storing data of calculation results, result data, and the like. The average final age table 5 is the final age at which the user can enter (the final age) divided by gender as shown in FIG. 2 (A). It is a table for setting an average age for nursing care that disappears. The index calculation table 6 includes, for example, an independent walking shown in FIG.
This is a table for setting coefficients α1, α2, α3,... (≦ 1) in accordance with the resident's health information such as wheelchairs and outpatients. These coefficients are the average occupancy shown in FIG. This is used to predict and calculate the final occupancy age for each resident from the final age. The size-based service table 7 is used to set information on the service structure, cost income, and resident replenishment corresponding to the size of the senior house, the number of occupants, occupancy conditions, and the like. Calculate the balance in the body. The learning data file 8 accumulates the difference between the final occupancy age calculated and predicted for each occupant and the actual occupancy final age.

Next, each processing unit in the data processing device 1 will be described. Resident management file creation processing unit 12
Creates a resident management file 4 shown in FIG. 3, for example. The resident management file 4 shown in FIG. 3 includes information input from the input device 2 such as a resident number (name), gender, age, health information, and conditions before and after occupancy, a health index, a final occupancy age, It consists of items of information that are predicted and calculated by each calculation unit such as a period. Health information, Figure 2
(B) are independent walking, wheelchair, outpatient, etc. The conditions before and after entering the house are, for example, before entering the house, the family structure, the area of residence (local, that is, near or far from a senior house, distant), dating Relationships such as the living environment before the tenants move in and the conditions leading up to the move, etc.
For example, whether a person is moving in or alone. The health index is the coefficient of the resident obtained from the health information, the final occupancy is the predicted final calculated age of the resident, and the period is the predicted calculated occupancy period up to the final occupancy age.

The health index calculator 13 calculates a coefficient α1, a coefficient α1 from the index calculation table 6 shown in FIG. 2B based on gender, age, health information, and conditions before and after the occupancy input from the input device 1.
The health index of each resident is obtained by extracting α2, α3,.... Therefore, in the index calculation table 6 shown in FIG. 2 (B), the index is set at least for each gender and age, and a coefficient is set for each condition before and after moving in. As with the life expectancy, the final occupancy age of each occupant varies depending on whether it is male or female (gender), and the age of the occupant is different. There is a difference depending on whether the tenant is moving in, living alone, or having a very little relationship. Therefore, the health index is to predict and calculate the final occupancy age at which there is a difference between these tenants from the average final occupancy age.

The final occupancy calculation unit 14 calculates the final occupancy of each occupant based on the average occupancy final age of the average final ages table 5 shown in FIG. 2A and a health index corresponding to the health information of the occupants. Is calculated, and the health index calculating unit 13 is added to the average occupancy final age of the average final age table 5.
Multiply by the health index obtained in step 2 and use this as the final age of occupancy.
The occupancy period calculation unit 15 calculates the difference between the occupancy final age for each occupant obtained by the occupancy final age calculation unit 14 and the age at the time of occupancy. You will be asked how many years to move up to the age of the time.

The service operation calculation unit 16 calculates the transition of the number of occupants in each year from the occupancy period of each occupant obtained by the occupancy period calculation unit 15 and predicts the change of the occupants. It refers to information on personnel, procurement of daily necessities and equipment, supply of food and drinks, other services, cost income, replenishment of residents, and the like.

The learning data accumulation processing section 17 calculates the final occupancy age when the last occupancy of the deceased is input as resident data as a record when a departed person is actually operated when the senior house is actually operated. The difference from the final occupancy age calculated by the unit 14, that is, the difference from the calculated value, is obtained, and this is used as learning data for correcting the coefficient according to the average occupancy final age and the health information obtained by performing the prediction calculation. , Stored in the learning data file 8.

FIG. 4 is a diagram for explaining an example of a process for predicting occupant fluctuation, FIG. 5 is a diagram for explaining an example of a process for learning a health index based on actual results, and FIG. FIG. 4 is a diagram illustrating a configuration example of a table for storing information used for learning.

As shown in FIG. 4, the process of predicting the change of the resident in each year based on the resident data is as follows. First, the name, gender, age, health information, living environment, and conditions before and after the occupancy of each occupant Enter resident data such as (Step S
11) The health index of each resident is obtained from the resident data by referring to the index calculation table 6 (step S12). Next, for each occupant, the occupant's final occupancy is predicted and calculated from the health index and the average occupancy final age (mean age required for nursing care) (step S13), and the difference between the occupancy final age and the age at the time of occupancy is entered. Forecast calculation as a period (Step S1
4). Then, the transition of the number of residents is predicted and calculated for each year (step S15). By predicting and calculating the transition of the number of occupants based on the occupant data in this manner, it is possible to predict the vacancy of each year in the future, and to add the predicted number of occupants of each year according to the vacancy prediction. Accordingly, it is possible to calculate the fluctuation of the resident when the senior housing is continuously operated, and to calculate the income and expenditure in the business entity that services and manages the resident.

In addition, if each of the occupants who predicted and calculated the final occupancy by actually performing the above-mentioned processing and operated actually leaves, there will be an error from the predicted and calculated final occupancy age. This error is considered to be based on the setting accuracy of the health index, or the setting accuracy or fluctuation of the average occupancy final age. Therefore, as shown in FIG. 5, a coefficient α1 corresponding to health information for obtaining a health index,
α2, α3,..., accumulate learning data for correcting the setting of the average occupancy final age. First, it is checked whether or not there is a departed person (step S21). If a departed person is found, the difference between the age of the departed person and the estimated final arrival age is calculated (step S22), and the difference is calculated. It is added to the item corresponding to the health information of the resident data corresponding to the departed person (step S23), and 1 is added to the occurrence frequency (step S24). FIG. 6 shows a configuration example of the table.

Assuming that a person who leaves the health information independently and has a value of the coefficient α1 has occurred, for example, the following data is stored in the table of FIG. First, a difference between the age of the departed person and the predicted final occupancy age is calculated, and an error value is added or subtracted according to ± of the difference, and 1 is added to the frequency. On the + side, when the age of the departed person is greater than the predicted final age of entry, the difference is added and 1 is added to the frequency.
On the negative side, when the age of the departed person is smaller than the predicted final arrival age, the difference is added and 1 is added to the frequency. By accumulating data for each piece of health information using such a table, it is possible to obtain information on average errors and variations in errors, and use the information as information for correcting the set value of the health index. Data on the average occupancy final age can be similarly stored and used as information for correcting the set value.

It should be noted that the present invention is not limited to the above embodiment, and various modifications are possible. For example, in the above-described embodiment, the service and management of the resident are performed with the age required for nursing care as the final age of occupation. Of course. In addition, according to the present invention, the service and management of the resident are performed by predicting the change in the number of resident based on the resident data. The present invention may be applied to perform operation simulation, may be applied to management in daily operation, or may be applied to any occasion. Therefore, it goes without saying that the items of the health information and the contents of the service work are selected not only according to the above-described embodiment but also according to each situation.

[0021]

As is apparent from the above description, according to the present invention, there is provided a senior housing service management system for the elderly who are not required for nursing care, and which is based on the average final occupancy age and health information. A setting table that sets a health index to correct the average occupancy final age for each occupant and a occupancy that predicts the occupancy final age for each occupant by referring to the setting table based on the health information of each occupant Since there is provided a final age calculating means and an output means for outputting the service / management information by calculating the transition of the number of occupants from the estimated final occupancy, the fluctuation of the number of occupants is predicted based on the occupant data, The service menu can be provided according to the change in the number of residents, and other services and management can be performed. In addition, as a health index, at least the gender of the resident,
Precise occupancy according to various conditions of each resident by setting by age, living environment, occupancy condition, or by setting gender, age, living environment, occupancy condition in resident's health information The final age can be predicted. Furthermore, by providing a storage means for storing a difference between the predicted calculated final occupancy age and the generated final occupancy age as a coefficient for obtaining a health index, as learning information of the average final occupancy age,
By accumulating results, it is possible to improve forecast accuracy, provide useful support tools for business planning and planning of senior housing, and improve service and management efficiency.

[Brief description of the drawings]

FIG. 1 is a diagram showing an embodiment of a senior housing service management system according to the present invention.

FIG. 2 is a diagram illustrating a configuration example of a table.

FIG. 3 is a diagram illustrating a configuration example of a resident management file.

FIG. 4 is a diagram for explaining an example of a process for performing resident change prediction.

FIG. 5 is a diagram for explaining an example of processing for learning a health index based on actual results.

FIG. 6 is a diagram illustrating a configuration example of a table for storing information used for learning a health index.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Data processing device, 2 ... Input device, 3 ... Output device, 4
... tenant management file, 5 ... average final age table, 6
… Index calculation table, 7… Service table by size, 8
... learning data file, 11 ... input / output processing unit, 12 ... resident management file creation processing unit, 13 ... health index calculation unit,
14: moving-in final age calculation unit, 15: moving-in period calculation unit, 1
6 ... Service operation calculation unit, 17 ... Learning data storage processing unit

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Takeshi Naruse 1-3-2 Shibaura, Minato-ku, Tokyo Shimizu Construction Co., Ltd. (72) Inventor Hikaru Harato 1-2-3 Shibaura, Minato-ku Tokyo Co., Ltd. F-term (reference) 5B049 BB41 BB51 CC11 EE31 EE41

Claims (4)

[Claims] 1. A senior housing service management system for elderly people who need to move in before nursing is required, wherein a setting is made to set a coefficient in accordance with health information for obtaining an average occupant final age and a resident's health index. A table, a final occupancy age calculating means for predicting and calculating a final occupancy age for each occupant based on the average occupancy final age by obtaining a health index by referring to the setting table from the health information of each occupant,
Output means for obtaining service / management information by calculating a change in the number of residents from the predicted final occupancy final age. 2. The senior housing service management system according to claim 1, wherein the health index is obtained at least for each of the resident's sex, age, living environment, and occupancy conditions. 3. The senior housing service management system according to claim 1, wherein the health index is obtained in consideration of gender, age, living environment, and occupancy conditions of the resident's health information. 4. A senior housing service management system for the elderly who is required to move in before nursing is required, wherein the average final moving age is corrected for each occupant according to the average final moving age and health information. A setting table for setting the index, a final occupancy age calculating means for predicting and calculating the final occupancy for each resident by referring to the setting table, and obtaining the transition of the number of occupants from the predicted and calculated final occupancy. Output means for outputting service / management information;
A senior housing service management system, comprising: a coefficient for obtaining the index, which is a difference between the predicted calculated final occupancy age and the generated final occupancy age, and accumulating means for accumulating learning information on the average final occupancy age. .