JP2006243922A - Medical work processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To cope with the problem of demands for obtaining accurate predicted values for the trend of numbers of patients from the next month on, an increase or a decrease in medical revenue, and the like. <P>SOLUTION: A medical work computer for calculating medical expenses based upon details of medical practice inputted includes a medical practice information storage means for storing data about the details of medical practice and medical expenses in units of medical practice; an operation day storage means for storing the number of monthly business days or the number of business days; a patient number counting means for calculating the average daily number of patients in that month by referring to the medical practice information storage means; a patient number predictive calculation means for predictively calculating the average daily number of patients in every future month for estimation based upon the calculated average daily number of patients in each previous month by means of a technique of a linear regression analysis; and a total patient number calculating means for calculating the total number of patients in the future month for estimation by multiplying the average daily number of patients in the month by the number of business days in the month. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a medical office processing apparatus, and more particularly, to a method and apparatus for estimating the number of patients coming to the hospital and medical income in a medical institution based on actual data.

In medical institutions, devices called medical office processing devices or receipt computers, which are devices that assist in the processing of insurance claims, have become widespread. Patent Document 1 discloses a system that supports management improvement of a medical institution based on various data recorded in the medical paper processing apparatus. The system collects data related to medical treatment and management indexes of a plurality of medical institutions, compares the actual data with the data of the medical institutions, and provides comparison information. By this, it is possible to know the past and current situation of the medical institution. On the other hand, when the medical institution makes a financial plan, etc., about trends in the number of patients and increase / decrease in medical income from the following month There is also a desire to obtain an accurate prediction value.
JP2001-216379

  In the medical office processing device, a patient's consultation date and medical data thereof, data related to a medical fee calculated based on the data, and data such as a partial burden received from the patient are recorded for each patient. Based on these data, it was possible to aggregate the actual data such as the number of patients per month, the amount of medical income, and the partial burden on the counter, and to output the form and display it.

  However, in order to predict the number of patients and medical income from the following month for which data has not yet been recorded in the medical paper processing device, the difference in the number of operating days of the medical institution, i.e., the number of open days excluding closed days, It is necessary to consider fluctuations. Moreover, since the effect of the amendment of the law amendment that revises the amount of medical fees must be taken into consideration, there has been nothing that can be accurately predicted in the past.

  The present invention relates to a medical office computer that calculates medical expenses based on inputted medical contents, medical information storage means for storing data related to medical contents and medical expenses in a medical unit, and a monthly opening date or opening. Based on the working day storage means for storing the number of days, the patient number counting means for calculating the daily average number of patients with reference to the medical information storage means, and the calculated daily average number of patients for each past month The number of patients predicting and calculating the average number of patients per month for the future trial target month by the method of linear regression analysis, and the average daily number of patients for the future trial target month calculated by the prediction The total number of patients is calculated by multiplying the number of working days to calculate the predicted total number of patients for the month.

According to the medical office computer of the present invention, it is possible to easily obtain predicted values such as the number of patients coming to the hospital in the near future, medical income, and the amount of burden on the counter based on the result data. Moreover, since the actual data uses medical data and accounting data recorded in daily work, it does not take time and effort to input basic data again. In addition, the monthly correction coefficient is automatically calculated based on past performance data and the predicted value is corrected so that it can cope with seasonal fluctuations in the number of patients visiting the hospital, so that a more accurate predicted value can be obtained. it can. In addition, since the revision rate of the medical fee due to the revision of the law, for example, the revision rate published by the Central Social Insurance Medical Council, etc. can be set, it is possible to obtain a predicted value reflecting the effect of the revision.

  FIG. 1 shows the configuration of a medical office processing apparatus according to an embodiment of the present invention. The apparatus 10 is configured by a computer, and the controller 11 performs various functions by introducing and executing various programs from the auxiliary storage unit 12. The control unit 11 also has a basic control function for controlling the display unit 13 configured with a CRT or the like, the input unit configured with a keyboard or the like, and the printing unit 15 such as a laser printer.

  The auxiliary storage unit 12 stores a medical care database and a cashier database. The medical care database is a database that stores information related to medical care contents and medical fees. When the operator inputs the medical treatment contents received by the patient, the control unit 11 calculates the medical fee by adding up the insurance points attached to the individual medical treatments. In addition, treatment costs that cannot be covered by insurance are recorded as non-insurance amounts, and the insurance points and non-insurance amounts are recorded in the database in units of medical care. In this embodiment, the sum of the insurance score and the non-insurance amount is called medical income. In the current law, one insurance point is equivalent to 10 yen.

  On the other hand, by referring to the medical database, the control unit 11 knows the number of patients who have been consulted on that day by summing up the records calculated for one point or more than one yen, and summing them for one month You can see how many patients there are. However, since the same patient may visit more than once, what is known here is the total number of patients. In this embodiment, since the purpose is to make a prediction of medical income, it is meaningful here to obtain the total number of patients.

  The accounting database is a database that stores accounting information paid by the patient at the window. The control unit 11 calculates the self-payment determined by each insurance among the calculated medical expenses, the non-insurance expenses for non-insurance treatment and medical materials, the total amount charged, and the amount paid by the patient at the window Etc. are calculated or obtained and recorded as accounting information. That is, the cashier database is a record of cash income of medical institutions. Note that the cash that the patient pays at the window is referred to as the window burden in this embodiment.

  The auxiliary storage unit 12 also stores an operation day file and a correction coefficient file. The working day file is a file that records the working day of each medical institution. In this case, an operator inputs and sets a medical care day and a non-working day every month in a calendar format. By referring to this file, the control unit 11 can calculate the number of working days in the month. The number of working days may be recorded separately for each month.

  The correction coefficient file records a coefficient for correcting the predicted value calculated by the control unit 11. As the correction coefficient, there are a patient number correction rate A for correcting the predicted number of patients and a revision rate B for reflecting the influence of the amendment of laws and regulations that revises medical fees. The patient number correction rate A is for correcting the predicted number of patients after the next month calculated by the control unit 11 based on recent results so as to follow the seasonal variation of the number of visiting patients. The control unit 11 dynamically determines the patient number correction rate A for the target month with reference to the past data, but the operator can also input and set it individually on the trial calculation condition setting screen.

  Here, the procedure for calculating the patient number correction rate A will be described. First, the control unit 11 sums up the total number of patients for all the past months in which the performance data is recorded with reference to the medical care database, and obtains the total. The total average value a1 of the total number of patients is obtained by dividing it by the number of months of all past months in which the record data is recorded. Next, for the month subject to trial calculation, for example, for April, the sum of the total number of patients in April for each year with actual data is calculated and divided by the number of years for which actual data for April is recorded. Find a2. Then, a2 is divided by a1 to obtain the patient number correction rate A for the target month.

  On the other hand, the revision rate B represents how much the medical fee increases or decreases on average after the month when the medical fee score table is revised. The revision rate is announced by the Central Social Insurance Medical Council before the revision date, so medical institutions can roughly grasp the impact of the revisions that the hospital receives. For example, when a new score table is implemented from April 1 and the revision rate is an average increase of 1.5%, the operator sets the revision rate B to “+ 1.5%” and the year of enforcement. Register in advance with the month. The control unit 11 multiplies the predicted value of the medical treatment fee in April calculated by the actual results up to March before the revision by this revision rate B and increases it by 1.5% to reflect the effect of the law revision.

  Next, the operation of this embodiment will be described. Based on the past data recorded in the clinical database and the cash database, this device calculates and presents the predicted number of patients, medical income, and cash income at the counter for the future target month specified by the operator. To do. In this embodiment, it is said that calculating this predicted value is a trial calculation.

  FIG. 4 shows an operation flow of this apparatus. First, the control unit 11 displays a trial calculation condition setting screen on the display means 13 and receives a condition input. The trial calculation condition setting screen is as shown in FIG. 2, and the operator can specify the reference date, trial calculation period, number of patients correction rate, and revision rate.

  The reference year / month refers to the first month of past data used when calculating the predicted value. The control unit 11 calculates future values by the method of linear regression analysis using the actual data after this month.

  The trial calculation period designates how many months of predicted values are calculated from the next month of the latest month having confirmed performance data. For example, when actual data is recorded until March 2005, it is specified that two months from April 2005 are estimated. Such a target month is simply called a trial month.

  The number of patients correction rate A may deviate from previous patient trends, for example, the number of patients suddenly increases in otolaryngology when the hay fever epidemic season begins, and the prediction of the month is accordingly made. It is used to correct the number of patients. Normally, the control unit 11 calculates and determines based on past data, but the operator can also set when there is no past data or when there is not enough. The revision rate B designates how much the medical fee will increase or decrease on average after the enforcement of the law revision.

  When at least the base date and the trial calculation period are specified and the start of the trial calculation is instructed, the control unit 11 acquires the base year and the trial calculation period (step S11), and first obtains actual data necessary for the trial calculation. (S12). That is, for each actual month from the designated reference date to the previous month of the trial calculation period, the total number of patients, medical income, and the contact burden are acquired from the medical database and the cashier database.

  Then, based on the result data, the unit price of medical treatment in the trial calculation period, the average number of patients per day, and the predicted value of the window cash income rate are calculated on a monthly basis (S13).

  The unit price of medical care is the average medical income per treatment, and is the total medical income for the month divided by the total number of patients. Therefore, the control unit 11 obtains the clinical unit price for the actual month, and calculates the clinical unit price for each trial month by linear regression analysis.

The average number of patients per day is the total number of patients for the month divided by the number of working days. Therefore, the control unit 11 obtains the daily average number of patients for the actual month, and calculates the daily average number of patients for each trial month by linear regression analysis.

  In addition, the cash flow rate at the counter is a ratio of the patient's window burden to the average medical revenue per treatment, and is calculated by dividing the total window burden for the month by the total medical revenue. Therefore, the control unit 11 obtains the cash receipt rate for the actual month, and calculates the cash receipt rate for each trial month by linear regression analysis.

  Next, the control unit 11 refers to the working day file, acquires the working days of each month in the trial calculation period, and calculates the predicted number of patients per month by multiplying the daily average number of patients previously calculated. (S14). However, this is a provisional number of patients simply predicted from past data. Therefore, the control unit 11 reads the patient number correction rate A for the trial calculation month from the correction coefficient file, and corrects it by multiplying the provisional predicted number of patients (S15). This is the total predicted number of patients.

  Then, a predicted value of medical income obtained by multiplying the corrected predicted number of patients by the unit price of medical care is calculated every month in the trial calculation period (S16). Usually, the trial calculation of medical income is completed. However, when the revision rate B is set after the enforcement of the legal revision, the monthly medical income is corrected by multiplying the revision rate B. (S18). This is the final predicted value of medical income.

  Next, the control unit 11 multiplies the final predicted value of medical revenue by the counter cash income rate and calculates the predicted value of the counter burden for each month (S19).

  Then, the calculated total number of patients predicted for each month of the trial calculation period, the medical service income final predicted value, and the window burden predicted value are displayed and output on the display means 13 in an easily understandable manner. Alternatively, a form is output from the printing means 15 (S20).

  An example of the form output of the trial calculation results is shown in FIG. The actual data recorded in the database is output from January to March of the designated reference year and month, and the predicted data calculated from April to 2 months of the trial calculation period is output. The subtitles “actual value” and “predicted value” are output on each data so that the user can clearly distinguish them.

It is a block diagram which shows the structure of the medical paperwork apparatus of embodiment. It is a figure which shows the example of a display of the trial calculation condition setting screen of embodiment. It is a figure which shows the example of a form output of embodiment. It is a flowchart which shows the process sequence of embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Medical office processing apparatus 11 Control part 12 Auxiliary memory | storage part 13 Display means 14 Input means 15 Printing means

Claims (15)

A medical office calculator that calculates medical expenses based on the contents of medical treatment entered,
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Working day storage means for storing the opening date or the number of opening days per month;
Patient number counting means for calculating the average number of patients per day with reference to the medical information storage means,
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating a predicted total number of patients for the month by multiplying the average number of patients in the predicted target month calculated in the future by the number of working days of the month;
Medical office calculator equipped with. A medical office calculator that calculates medical expenses based on the contents of medical treatment entered,
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Working day storage means for storing the opening date or the number of opening days per month;
Patient number counting means for calculating the total number of patients per month and the average number of patients per day with reference to medical information storage means and working day storage means;
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating a predicted total number of patients for the month by multiplying the average number of patients in the predicted target month calculated in the future by the number of working days of the month;
A unit price calculation unit for calculating a unit price per month in the past based on the information related to the medical cost stored in the medical information storage unit and the total number of patients;
A unit price prediction calculation means for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month;
Medical revenue calculation means for calculating the monthly medical revenue by multiplying the total number of patients and the unit price of medical treatment for the future target month calculated by the prediction;
Medical office calculator equipped with. A medical office calculator that calculates medical expenses based on the contents of medical treatment entered,
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Accounting information storage means for storing data relating to the patient's window burden in a medical unit;
Working day storage means for storing the opening date or the number of opening days per month;
Patient number counting means for calculating the total number of patients per month and the average number of patients per day with reference to medical information storage means and working day storage means;
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating a predicted total number of patients for the month by multiplying the average number of patients in the predicted target month calculated in the future by the number of working days of the month;
A unit price calculation unit for calculating a unit price per month in the past based on the information related to the medical cost stored in the medical information storage unit and the total number of patients;
A unit price prediction calculation means for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month;
A medical revenue calculating means for calculating a predicted medical revenue for each month by multiplying the predicted unit price of the future trial calculation target month and the predicted total number of patients;
Cash income rate calculating means for calculating a monthly cash receipt cash rate from the information on the medical expenses stored in the cashier information storage means and the medical expenses stored in the medical information storage means;
A cash income rate prediction calculating means for predicting and calculating a cash income rate for each month in the future calculation target month by a method of linear regression analysis based on the calculated monthly cash income rate for the past month;
A burden calculation means for calculating a predicted window burden for each month by multiplying the cash income rate of the future calculation target month calculated by the prediction and the medical income of the future calculation target month;
Means for displaying and outputting the predicted total number of patients, the predicted medical income, and the predicted contact burden for the calculated future trial target month;
Medical office calculator equipped with. In the medical office computer according to any one of claims 1 to 3,
A correction rate calculating means for calculating a correction rate for correcting the total number of patients in the trial calculation target month based on past performance data;
The total number of patients calculation means corrects the calculated predicted total number of patients by multiplying the correction ratio of the month calculated by the correction ratio calculation means,
A medical office computer characterized by that. In the medical office computer according to any one of claims 1 to 4,
A storage means for storing the revision rate of medical fees due to the revision of the law and at least the date of enforcement of the revision is further provided.
The medical revenue calculation means corrects the calculated predicted medical revenue by multiplying the revised rate when the trial calculation target month is after the revision is implemented,
A medical office computer characterized by that. In a medical office computer that calculates medical expenses based on the contents of medical treatment entered,
A medical information storage step for storing data relating to medical contents and medical costs in a medical information storage means in a medical unit;
A working day storage step for storing the opening date or the number of opening days per month in the working day storage means;
A patient number counting step of calculating the average number of patients per day with reference to the medical information storage means;
A number-of-patients prediction calculation step for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by the method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total patient number calculating step of calculating the predicted total number of patients for the month by multiplying the daily average number of patients in the predicted target month calculated in advance by the number of working days in the month;
A method for estimating the number of patients, etc. In a medical office computer that calculates medical expenses based on the contents of medical treatment entered,
A medical information storage step for storing data relating to medical contents and medical costs in a medical information storage means in a medical unit;
A working day storage step for storing the opening date or the number of opening days per month in the working day storage means;
A patient number counting step of calculating the total number of patients and the average number of patients per day with reference to the medical information storage means and the working day storage means;
A number-of-patients prediction calculation step for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by the method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total patient number calculating step of calculating the predicted total number of patients for the month by multiplying the daily average number of patients in the predicted target month calculated in advance by the number of working days in the month;
A unit price calculation step for calculating a unit price per month for each past person based on information on the medical cost stored in the medical information storage means and the total number of patients,
A unit price prediction calculation step for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month,
A medical income calculation step of calculating a monthly medical income by multiplying the estimated number of patients for the future trial calculation month and the unit price of medical treatment,
A method for estimating the number of patients, etc. In a medical office computer that calculates medical expenses based on the contents of medical treatment entered,
A medical information storage step for storing data relating to medical contents and medical costs in a medical information storage means in a medical unit;
A cashier information storage step for storing data relating to the patient's window burden in the cashier information storage means in the medical care unit;
A working day storage step for storing the opening date or the number of opening days per month in the working day storage means;
A patient number counting step of calculating the total number of patients and the average number of patients per day with reference to the medical information storage means and the working day storage means;
A number-of-patients prediction calculation step for predicting and calculating the number of daily average patients in a future trial target month on a monthly basis by the method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total patient number calculating step of calculating the predicted total number of patients for the month by multiplying the daily average number of patients in the predicted target month calculated in advance by the number of working days in the month;
A unit price calculation step for calculating a unit price per month for each past person based on information on the medical cost stored in the medical information storage means and the total number of patients,
A unit price prediction calculation step for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month,
A medical revenue calculation step for calculating a predicted medical revenue for each month by multiplying the predicted unit price of the future trial calculation target month and the predicted total number of patients,
A cash income rate calculating step for calculating a monthly cash cash rate from the information on the medical expenses stored in the cashier information storage means and the medical expenses stored in the medical information storage means;
A cash income rate prediction calculation step for predicting and calculating monthly the cash income rate of the target month for the trial calculation based on the calculated monthly cash income rate of the past month;
A burden calculation step of calculating a predicted window burden for each month by multiplying the cash income rate of the future calculation target month calculated by the prediction and the medical income of the future calculation target month;
A step of displaying and outputting the predicted total number of patients, the predicted medical income, and the predicted contact burden for the calculated future trial target month;
A method for estimating the number of patients, etc. In the trial calculation method such as the number of patients in the medical office computer according to any one of claims 6 to 8,
A correction rate calculating step for calculating a correction rate for correcting the total number of patients in the trial calculation target month based on past performance data;
The total number of patients calculating step corrects the calculated predicted total number of patients by multiplying by the correction rate of the month calculated in the correction rate calculating step.
A trial calculation method such as the number of patients in a medical office computer. In the trial calculation method such as the number of patients in the medical office computer according to any one of claims 6 to 9,
A step of storing the revision rate of medical treatment fees and at least the date of enforcement of the revision in the storage means according to the law revision;
In the medical revenue calculation step, when the calculation target month is after the revision is implemented, the calculated predicted medical revenue is multiplied by the stored revision rate, and corrected.
A trial calculation method such as the number of patients in a medical office computer. Computer
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Working day storage means for storing the opening date or the number of opening days per month,
Patient number counting means for calculating the daily average number of patients for the month with reference to the medical information storage means,
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month for each month by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating the predicted total number of patients for the month by multiplying the average number of patients for the trial calculation target month calculated in the future by the number of working days of the month;
Program to function as. Computer
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Working day storage means for storing the opening date or the number of opening days per month,
Patient number counting means for calculating the total number of patients and the average number of patients per day with reference to the medical information storage means and the working day storage means,
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month for each month by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating the predicted total number of patients for the month by multiplying the average number of patients for the trial calculation target month calculated in the future by the number of working days of the month;
A unit price calculation unit for calculating a unit price per month for each past person based on information on the medical cost stored in the medical information storage unit and the total number of patients,
A unit price prediction calculation means for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month,
Medical revenue calculating means for calculating the monthly medical revenue by multiplying the total number of patients and the unit price of the trial calculation target month calculated in the prediction,
Program to function as. Computer
Medical information storage means for storing data relating to medical treatment contents and medical expenses in a medical unit;
Accounting information storage means for storing data relating to the patient's window burden in the medical unit;
Working day storage means for storing the opening date or the number of opening days per month,
Patient number counting means for calculating the total number of patients and the average number of patients per day with reference to the medical information storage means and the working day storage means,
A number-of-patients prediction calculation means for predicting and calculating the number of daily average patients in a future trial target month for each month by a method of linear regression analysis based on the calculated average number of patients per day in the past month;
A total number of patients calculating means for calculating the predicted total number of patients for the month by multiplying the average number of patients for the trial calculation target month calculated in the future by the number of working days of the month;
A unit price calculation unit for calculating a unit price per month for each past person based on information on the medical cost stored in the medical information storage unit and the total number of patients,
A unit price prediction calculation means for predicting and calculating a unit price for a future trial calculation month by a linear regression analysis based on the calculated unit price for each past month,
A medical revenue calculating means for calculating a predicted medical revenue for each month by multiplying the predicted unit price of the future trial calculation month calculated by the prediction and the predicted total number of patients;
Cash income rate calculating means for calculating a monthly cash receipt cash rate from the information on the medical expenses stored in the cashier information storage means and the medical expenses stored in the medical information storage means,
A cash income rate prediction calculating means for predicting and calculating monthly the cash income rate of the target month for the trial calculation based on the calculated monthly cash income rate of the past month by the method of linear regression analysis;
A burden calculating means for calculating a predicted window burden for each month by multiplying the cash income rate of the future target month calculated by the prediction and the medical income of the future target month,
Means for displaying and outputting the predicted total number of patients, the predicted medical income, and the predicted contact burden for the calculated future trial month,
Program to function as. In any of claims 11 to 13,
Furthermore, the computer is caused to function as a correction rate calculation means for calculating a correction rate for correcting the total number of patients for the trial calculation target month based on past performance data,
Means for correcting the total number of patients calculating means by multiplying the calculated predicted total number of patients by the correction rate for the month calculated by the correction rate calculating means;
Program to function as. In any of claims 11 to 14,
In addition, the computer functions as a storage means for storing the revision rate of medical fees due to legal revisions and at least the date of enforcement of the revisions,
Means for correcting the medical income calculation means by multiplying the calculated predicted medical income by the revision rate stored in the storage means when the trial calculation target month is after the revision is implemented;
Program to function as.

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