Research Article

Cost Control of Treatment for Cerebrovascular Patients Using a Machine Learning Model in Western China

Table 1

Factor assignment and result of single factor analysis of the factors influencing inpatient medical expenditure (n = 45,575).

VariablesAssignment of influencing factorsSimple sizeExpenditure $ (M + IQR)t/F value

GenderMale = 119,488 (42.76%)1111.82 ± 741.66247.81<0.000
Female = 226,087 (57.24%)1026.12 ± 688.18

AgeAge ≤ 45 = 11,995 (4.37%)808.56 ± 535.69788.16<0.000
Age between 45 and 60 = 29,117 (20.00%)954.13 ± 640.03
Age ≥ 60 = 334,463 (75.62%)1108.76 ± 745.46

Level of hospitalGrade B secondary hospital = 17,609 (16.70%)784.12 ± 431.2623,064<0.000
Grade A secondary hospital = 216,879 (37.04%)932.23 ± 671.61
Grade B tertiary hospital = 39,208 (20.20%)1140.05 ± 825.05
Grade A tertiary hospital = 411,879 (26.06%)1597.27 ± 1160.64

LOS≤9 d = 122,870 (50.18%)779.17 ± 537.8516,838<0.000
9∼13 d = 29,544 (20.94%)1180.41 ± 884.23
≥13 d = 313,161 (28.88%)1708.35 ± 1252.09

SurgeryYes = 12,8201315.17 ± 765.10330.79<0.000
No = 236,9871013.85 ± 684.21
Others = 35,7681212.19 ± 711.22

Discharge statusRecovery = 137,492 (82.26%)1108.33 ± 750.211,413<0.000
Transfers = 2707 (1.55%)933.52 ± 608.18
Death = 3262 (0.57%)1525.31 ± 760.29
Others = 47,954 (15.48%)842.92 ± 570.62
Midway check-out = 560 (0.13%)1112.47 ± 605.51

Comorbidities complicationsThe cerebral arteries lack blood supply = 120,936 (45.94%)1031.86 ± 884.136285.7<0.000
Lacunar infarction = 210,111 (22.19%)1081.60 ± 740.06
Cerebral infarction = 35,246 (11.51%)1477.85 ± 1031.87
Chronic cerebral ischemia = 41,989 (4.36%)1089.20 ± 763.47
Others = 57,293 (16%)1560.89 ± 974.51

Hypertension level threeYes = 19,303 (20.41)1162.96 ± 778.0384.216
No = 036,272 (79.59%)1116.37 ± 699.49