Overview

Dataset statistics

Number of variables9
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory82.0 B

Variable types

Categorical3
Numeric6

Dataset

Description인천보훈병원에서 개방하는 진료정보 데이터로, 인천보훈병원 만성질환 환자 연령별 현황에 대한 내용이 포함된 공공데이터입니다.
URLhttps://www.data.go.kr/data/15102227/fileData.do

Alerts

상병명 명칭 is highly overall correlated with 상병명 코드High correlation
상병명 코드 is highly overall correlated with 상병명 명칭High correlation
연령별(59이하) is highly overall correlated with 연령별(60-64) and 4 other fieldsHigh correlation
연령별(60-64) is highly overall correlated with 연령별(59이하) and 4 other fieldsHigh correlation
연령별(65-69) is highly overall correlated with 연령별(59이하) and 4 other fieldsHigh correlation
연령별(70-79) is highly overall correlated with 연령별(59이하) and 4 other fieldsHigh correlation
연령별(80-89) is highly overall correlated with 연령별(59이하) and 4 other fieldsHigh correlation
연령별(90이상) is highly overall correlated with 연령별(59이하) and 4 other fieldsHigh correlation
연령별(59이하) has 16 (48.5%) zerosZeros
연령별(60-64) has 17 (51.5%) zerosZeros
연령별(65-69) has 16 (48.5%) zerosZeros
연령별(70-79) has 9 (27.3%) zerosZeros
연령별(80-89) has 11 (33.3%) zerosZeros
연령별(90이상) has 14 (42.4%) zerosZeros

Reproduction

Analysis started2023-12-12 04:25:30.150060
Analysis finished2023-12-12 04:25:35.051173
Duration4.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
입원(실인원)
11 
입원(연인원)
11 
외래
11 

Length

Max length7
Median length7
Mean length5.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입원(실인원)
2nd row입원(실인원)
3rd row입원(실인원)
4th row입원(실인원)
5th row입원(실인원)

Common Values

ValueCountFrequency (%)
입원(실인원) 11
33.3%
입원(연인원) 11
33.3%
외래 11
33.3%

Length

2023-12-12T13:25:35.117223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:35.227376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입원(실인원 11
33.3%
입원(연인원 11
33.3%
외래 11
33.3%

상병명 코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
I10~I13, I15
3 
E10~E14
3 
F00~F99, G40~G41
3 
A15, A16, A19
3 
I05~I09, I20~I27, I30~I52
3 
Other values (6)
18 

Length

Max length25
Median length17
Mean length12.636364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI10~I13, I15
2nd rowE10~E14
3rd rowF00~F99, G40~G41
4th rowA15, A16, A19
5th rowI05~I09, I20~I27, I30~I52

Common Values

ValueCountFrequency (%)
I10~I13, I15 3
9.1%
E10~E14 3
9.1%
F00~F99, G40~G41 3
9.1%
A15, A16, A19 3
9.1%
I05~I09, I20~I27, I30~I52 3
9.1%
I60~I69 3
9.1%
G00~G37, G43~G83 3
9.1%
C00~C97, D00~D09 3
9.1%
E00~E07 3
9.1%
B18, B19, K70~K77 3
9.1%

Length

2023-12-12T13:25:35.336947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
i10~i13 3
 
4.8%
i60~i69 3
 
4.8%
k70~k77 3
 
4.8%
b19 3
 
4.8%
b18 3
 
4.8%
e00~e07 3
 
4.8%
d00~d09 3
 
4.8%
c00~c97 3
 
4.8%
g43~g83 3
 
4.8%
g00~g37 3
 
4.8%
Other values (11) 33
52.4%

상병명 명칭
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
고혈압
3 
당뇨병
3 
정신 및 행동장애
3 
호흡기결핵
3 
심장질환
3 
Other values (6)
18 

Length

Max length9
Median length7
Mean length5.2727273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고혈압
2nd row당뇨병
3rd row정신 및 행동장애
4th row호흡기결핵
5th row심장질환

Common Values

ValueCountFrequency (%)
고혈압 3
9.1%
당뇨병 3
9.1%
정신 및 행동장애 3
9.1%
호흡기결핵 3
9.1%
심장질환 3
9.1%
대뇌혈관질환 3
9.1%
신경계질환 3
9.1%
악성신생물 3
9.1%
갑상선의 장애 3
9.1%
간의 질환 3
9.1%

Length

2023-12-12T13:25:35.472080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고혈압 3
 
6.7%
당뇨병 3
 
6.7%
정신 3
 
6.7%
및 3
 
6.7%
행동장애 3
 
6.7%
호흡기결핵 3
 
6.7%
심장질환 3
 
6.7%
대뇌혈관질환 3
 
6.7%
신경계질환 3
 
6.7%
악성신생물 3
 
6.7%
Other values (5) 15
33.3%

연령별(59이하)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.818182
Minimum0
Maximum543
Zeros16
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:35.601043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q349
95-th percentile497.6
Maximum543
Range543
Interquartile range (IQR)49

Descriptive statistics

Standard deviation151.25505
Coefficient of variation (CV)2.2303024
Kurtosis5.6504072
Mean67.818182
Median Absolute Deviation (MAD)1
Skewness2.5966462
Sum2238
Variance22878.091
MonotonicityNot monotonic
2023-12-12T13:25:35.735898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 16
48.5%
5 2
 
6.1%
231 1
 
3.0%
58 1
 
3.0%
55 1
 
3.0%
543 1
 
3.0%
108 1
 
3.0%
26 1
 
3.0%
46 1
 
3.0%
480 1
 
3.0%
Other values (7) 7
21.2%
ValueCountFrequency (%)
0 16
48.5%
1 1
 
3.0%
2 1
 
3.0%
3 1
 
3.0%
5 2
 
6.1%
18 1
 
3.0%
26 1
 
3.0%
46 1
 
3.0%
49 1
 
3.0%
55 1
 
3.0%
ValueCountFrequency (%)
543 1
3.0%
524 1
3.0%
480 1
3.0%
231 1
3.0%
108 1
3.0%
84 1
3.0%
58 1
3.0%
55 1
3.0%
49 1
3.0%
46 1
3.0%

연령별(60-64)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.181818
Minimum0
Maximum620
Zeros17
Zeros (%)51.5%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:35.898351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329
95-th percentile211.8
Maximum620
Range620
Interquartile range (IQR)29

Descriptive statistics

Standard deviation123.3074
Coefficient of variation (CV)2.7291377
Kurtosis16.246518
Mean45.181818
Median Absolute Deviation (MAD)0
Skewness3.9277817
Sum1491
Variance15204.716
MonotonicityNot monotonic
2023-12-12T13:25:36.043376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 17
51.5%
1 2
 
6.1%
29 1
 
3.0%
4 1
 
3.0%
82 1
 
3.0%
21 1
 
3.0%
37 1
 
3.0%
87 1
 
3.0%
109 1
 
3.0%
38 1
 
3.0%
Other values (6) 6
 
18.2%
ValueCountFrequency (%)
0 17
51.5%
1 2
 
6.1%
4 1
 
3.0%
5 1
 
3.0%
8 1
 
3.0%
12 1
 
3.0%
21 1
 
3.0%
29 1
 
3.0%
37 1
 
3.0%
38 1
 
3.0%
ValueCountFrequency (%)
620 1
3.0%
366 1
3.0%
109 1
3.0%
87 1
3.0%
82 1
3.0%
71 1
3.0%
38 1
3.0%
37 1
3.0%
29 1
3.0%
21 1
3.0%

연령별(65-69)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.090909
Minimum0
Maximum881
Zeros16
Zeros (%)48.5%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:36.570219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q331
95-th percentile497.6
Maximum881
Range881
Interquartile range (IQR)31

Descriptive statistics

Standard deviation198.34666
Coefficient of variation (CV)2.5078313
Kurtosis9.5428307
Mean79.090909
Median Absolute Deviation (MAD)1
Skewness3.0980027
Sum2610
Variance39341.398
MonotonicityNot monotonic
2023-12-12T13:25:36.715157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 16
48.5%
1 3
 
9.1%
114 1
 
3.0%
86 1
 
3.0%
24 1
 
3.0%
37 1
 
3.0%
402 1
 
3.0%
301 1
 
3.0%
47 1
 
3.0%
641 1
 
3.0%
Other values (6) 6
 
18.2%
ValueCountFrequency (%)
0 16
48.5%
1 3
 
9.1%
4 1
 
3.0%
7 1
 
3.0%
13 1
 
3.0%
19 1
 
3.0%
24 1
 
3.0%
31 1
 
3.0%
37 1
 
3.0%
47 1
 
3.0%
ValueCountFrequency (%)
881 1
3.0%
641 1
3.0%
402 1
3.0%
301 1
3.0%
114 1
3.0%
86 1
3.0%
47 1
3.0%
37 1
3.0%
31 1
3.0%
24 1
3.0%

연령별(70-79)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)69.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean734.0303
Minimum0
Maximum6659
Zeros9
Zeros (%)27.3%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:36.869651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median34
Q3548
95-th percentile4173
Maximum6659
Range6659
Interquartile range (IQR)548

Descriptive statistics

Standard deviation1534.1145
Coefficient of variation (CV)2.0899879
Kurtosis7.2573561
Mean734.0303
Median Absolute Deviation (MAD)34
Skewness2.7020758
Sum24223
Variance2353507.2
MonotonicityNot monotonic
2023-12-12T13:25:37.024082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 9
27.3%
4 2
 
6.1%
24 2
 
6.1%
2 1
 
3.0%
4416 1
 
3.0%
55 1
 
3.0%
482 1
 
3.0%
211 1
 
3.0%
1457 1
 
3.0%
4011 1
 
3.0%
Other values (13) 13
39.4%
ValueCountFrequency (%)
0 9
27.3%
2 1
 
3.0%
4 2
 
6.1%
8 1
 
3.0%
16 1
 
3.0%
24 2
 
6.1%
34 1
 
3.0%
40 1
 
3.0%
42 1
 
3.0%
55 1
 
3.0%
ValueCountFrequency (%)
6659 1
3.0%
4416 1
3.0%
4011 1
3.0%
2664 1
3.0%
1484 1
3.0%
1457 1
3.0%
689 1
3.0%
608 1
3.0%
548 1
3.0%
501 1
3.0%

연령별(80-89)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.24242
Minimum0
Maximum1543
Zeros11
Zeros (%)33.3%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:37.197912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q3224
95-th percentile825.8
Maximum1543
Range1543
Interquartile range (IQR)224

Descriptive statistics

Standard deviation350.30112
Coefficient of variation (CV)1.8910416
Kurtosis6.3591267
Mean185.24242
Median Absolute Deviation (MAD)8
Skewness2.4153496
Sum6113
Variance122710.88
MonotonicityNot monotonic
2023-12-12T13:25:37.374468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 11
33.3%
2 3
 
9.1%
4 2
 
6.1%
706 1
 
3.0%
11 1
 
3.0%
39 1
 
3.0%
42 1
 
3.0%
370 1
 
3.0%
429 1
 
3.0%
825 1
 
3.0%
Other values (10) 10
30.3%
ValueCountFrequency (%)
0 11
33.3%
2 3
 
9.1%
4 2
 
6.1%
8 1
 
3.0%
11 1
 
3.0%
15 1
 
3.0%
26 1
 
3.0%
39 1
 
3.0%
42 1
 
3.0%
53 1
 
3.0%
ValueCountFrequency (%)
1543 1
3.0%
827 1
3.0%
825 1
3.0%
706 1
3.0%
569 1
3.0%
429 1
3.0%
370 1
3.0%
325 1
3.0%
224 1
3.0%
87 1
3.0%

연령별(90이상)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)57.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.424242
Minimum0
Maximum603
Zeros14
Zeros (%)42.4%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T13:25:37.547392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q3101
95-th percentile371.4
Maximum603
Range603
Interquartile range (IQR)101

Descriptive statistics

Standard deviation147.62474
Coefficient of variation (CV)1.9572585
Kurtosis7.1117707
Mean75.424242
Median Absolute Deviation (MAD)2
Skewness2.6515422
Sum2489
Variance21793.064
MonotonicityNot monotonic
2023-12-12T13:25:37.718706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 14
42.4%
1 2
 
6.1%
6 1
 
3.0%
216 1
 
3.0%
4 1
 
3.0%
5 1
 
3.0%
136 1
 
3.0%
92 1
 
3.0%
179 1
 
3.0%
114 1
 
3.0%
Other values (9) 9
27.3%
ValueCountFrequency (%)
0 14
42.4%
1 2
 
6.1%
2 1
 
3.0%
4 1
 
3.0%
5 1
 
3.0%
6 1
 
3.0%
19 1
 
3.0%
20 1
 
3.0%
36 1
 
3.0%
92 1
 
3.0%
ValueCountFrequency (%)
603 1
3.0%
552 1
3.0%
251 1
3.0%
216 1
3.0%
179 1
3.0%
151 1
3.0%
136 1
3.0%
114 1
3.0%
101 1
3.0%
92 1
3.0%

Interactions

2023-12-12T13:25:34.245170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:30.635741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.393420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.177235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.844935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.547364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.343908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:30.754727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.495578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.307971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.977795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.663778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.431436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:30.887161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.610908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.416558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.102240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.772987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.517600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:30.985745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.733470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.504993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.207343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.861518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.613454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.096831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.891651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.613329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.322390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.966781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.713446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:31.257225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.027789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:32.729173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:33.435713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:34.121417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:25:37.840256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상병명 코드상병명 명칭연령별(59이하)연령별(60-64)연령별(65-69)연령별(70-79)연령별(80-89)연령별(90이상)
구분1.0000.0000.0000.4150.2370.3960.6460.4200.433
상병명 코드0.0001.0001.0000.0000.0000.1870.0000.0000.000
상병명 명칭0.0001.0001.0000.0000.0000.1870.0000.0000.000
연령별(59이하)0.4150.0000.0001.0000.8000.8020.6730.5870.693
연령별(60-64)0.2370.0000.0000.8001.0000.9720.8680.8320.843
연령별(65-69)0.3960.1870.1870.8020.9721.0000.9830.8840.970
연령별(70-79)0.6460.0000.0000.6730.8680.9831.0000.8440.934
연령별(80-89)0.4200.0000.0000.5870.8320.8840.8441.0000.902
연령별(90이상)0.4330.0000.0000.6930.8430.9700.9340.9021.000
2023-12-12T13:25:37.982566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상병명 명칭구분상병명 코드
상병명 명칭1.0000.0001.000
구분0.0001.0000.000
상병명 코드1.0000.0001.000
2023-12-12T13:25:38.120000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령별(59이하)연령별(60-64)연령별(65-69)연령별(70-79)연령별(80-89)연령별(90이상)구분상병명 코드상병명 명칭
연령별(59이하)1.0000.8640.8830.8490.7740.5630.3290.0000.000
연령별(60-64)0.8641.0000.7770.8320.7800.6870.2150.0000.000
연령별(65-69)0.8830.7771.0000.8390.7460.5690.1540.0000.000
연령별(70-79)0.8490.8320.8391.0000.9180.7150.3130.0000.000
연령별(80-89)0.7740.7800.7460.9181.0000.7600.2810.0000.000
연령별(90이상)0.5630.6870.5690.7150.7601.0000.1750.0000.000
구분0.3290.2150.1540.3130.2810.1751.0000.0000.000
상병명 코드0.0000.0000.0000.0000.0000.0000.0001.0001.000
상병명 명칭0.0000.0000.0000.0000.0000.0000.0001.0001.000

Missing values

2023-12-12T13:25:34.845852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:25:34.998811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

구분상병명 코드상병명 명칭연령별(59이하)연령별(60-64)연령별(65-69)연령별(70-79)연령별(80-89)연령별(90이상)
0입원(실인원)I10~I13, I15고혈압000206
1입원(실인원)E10~E14당뇨병51442152
2입원(실인원)F00~F99, G40~G41정신 및 행동장애000420
3입원(실인원)A15, A16, A19호흡기결핵000000
4입원(실인원)I05~I09, I20~I27, I30~I52심장질환000021
5입원(실인원)I60~I69대뇌혈관질환001841
6입원(실인원)G00~G37, G43~G83신경계질환3011620
7입원(실인원)C00~C97, D00~D09악성신생물250342619
8입원(실인원)E00~E07갑상선의 장애000000
9입원(실인원)B18, B19, K70~K77간의 질환111400
구분상병명 코드상병명 명칭연령별(59이하)연령별(60-64)연령별(65-69)연령별(70-79)연령별(80-89)연령별(90이상)
23외래E10~E14당뇨병4803666414416827216
24외래F00~F99, G40~G41정신 및 행동장애46381141484706251
25외래A15, A16, A19호흡기결핵000000
26외래I05~I09, I20~I27, I30~I52심장질환262947608224114
27외래I60~I69대뇌혈관질환1081093012664825179
28외래G00~G37, G43~G83신경계질환54387402401142992
29외래C00~C97, D00~D09악성신생물5537371457370136
30외래E00~E07갑상선의 장애582124211425
31외래B18, B19, K70~K77간의 질환2318286482394
32외래N18만성신부전증04055110