K. Nawata, M. Kimura
10.4236/health.2017.98081 1115 Health
[38], and 90% or more diabetes cases are classified as type 2 diabetes [38] [39]
[40].) They found that there were large differences in average LOS (ALOS)
among hospitals. On the other hand, the differences in daily medical expendi-
tures among hospitals were relatively small, and ALOS accounted for the largest
part of total medical expenditures for diabetes. The problem with these studies is
that only diabetic inpatients at Diagnosis Procedure Combination (DPC) hospit-
als were analyzed (for details regarding DPC hospitals, see Nawata
et al
. [41]).
The medical expenditures of outpatients and patients in non-DPC hospitals were
not considered. Analyzing all diabetic patients and comparing these patients
with healthy non-diabetic persons are necessary to evaluate the total cost and
economic burden of diabetes. To prevent diabetes, it is also necessary to deter-
mine what factors affect diabetes. For this purpose, it is necessary to investigate a
dataset including normal and healthy persons and compare them with diabetic
persons. However, it is very difficult and costly to get a large scale individual da-
taset that includes many normal and healthy individuals because they do not go
to hospitals or clinics voluntary by themselves. Moreover, whether a person is
diagnosed diabetes or not is a binary variable, and we cannot use the standard
regression analysis.
In Japan, health insurance societies are formed by private companies and cen-
tral and local governments for their employees. The health insurance societies
pay the medical expenses of their members. Moreover, yearly medical checkups
(hereafter, checkups) are required for most workers age 40 or older in Japan
[42]. This means that the health insurance societies have all of the health and
medical information of their members including normal and healthy persons.
The monthly reports of medical payments, including types of treatments, insti-
tutions used and amounts paid for medical care, that are sent from medical in-
stitutes to health insurance societies are called “receipts” in Japan. Nawata
et al
.
[43] and Nawata and Kimura [44] analyzed blood pressures using a dataset con-
taining 113,979 checkups obtained from 48,022 persons with the cooperation of
one health insurance society. However, information from the receipts was not
used in the analysis.
In this paper, we first analyze the total costs of diabetes using the dataset
combining both checkups and receipts. The dataset contains 113,979 checkups
and 3,671,783 monthly medical, dental, care-giving and pharmacy receipts from
fiscal year 2013 to 2015. Since the outcome (diabetes or not) is a binary variable,
we evaluate factors affecting diabetes by the probit models.
2. Data and Analysis
2.1. Data
In this study, we first made up a dataset combining checkups and receipts with
the cooperation of the health insurance society of one large Japanese corporation.
The dataset was anonymized at the society. The dataset contained information
regarding checkups [43] [44] and all receipts from fiscal year 2013 to fiscal year