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week
int64
1
52
month
int64
1
12
service
stringclasses
4 values
available_beds
int64
8
74
patients_request
int64
5
388
patients_admitted
int64
5
74
patients_refused
int64
0
363
patient_satisfaction
int64
60
99
staff_morale
int64
31
99
event
stringclasses
4 values
1
1
emergency
32
76
32
44
67
70
none
1
1
surgery
45
130
45
85
83
78
malaria_peak
1
1
general_medicine
37
201
37
164
97
43
malaria_peak
1
1
ICU
22
31
22
9
84
91
malaria_peak
2
1
emergency
28
169
28
141
75
64
none
2
1
surgery
40
26
26
0
96
56
none
2
1
general_medicine
43
183
43
140
73
93
malaria_peak
2
1
ICU
16
7
7
0
79
85
ngo_donation
3
1
emergency
32
177
32
145
73
58
malaria_peak
3
1
surgery
27
66
27
39
63
72
malaria_peak
3
1
general_medicine
37
58
37
21
95
63
none
3
1
ICU
20
21
20
1
82
89
none
4
1
emergency
32
157
32
125
83
75
none
4
1
surgery
56
57
56
1
74
94
none
4
1
general_medicine
43
152
43
109
67
66
malaria_peak
4
1
ICU
20
21
20
1
64
85
malaria_peak
5
2
emergency
25
388
25
363
93
72
malaria_peak
5
2
surgery
26
70
26
44
81
83
ngo_donation
5
2
general_medicine
40
103
40
63
73
52
none
5
2
ICU
22
13
13
0
73
88
none
6
2
emergency
34
198
34
164
72
76
malaria_peak
6
2
surgery
27
58
27
31
96
81
ngo_donation
6
2
general_medicine
69
90
69
21
72
81
none
6
2
ICU
14
12
12
0
87
51
none
7
2
emergency
33
127
33
94
65
77
none
7
2
surgery
37
46
37
9
89
60
none
7
2
general_medicine
62
80
62
18
84
98
ngo_donation
7
2
ICU
21
47
21
26
72
83
malaria_peak
8
2
emergency
26
240
26
214
96
75
malaria_peak
8
2
surgery
51
20
20
0
91
61
strike
8
2
general_medicine
58
105
58
47
71
88
none
8
2
ICU
12
10
10
0
76
98
none
9
3
emergency
28
113
28
85
82
86
none
9
3
surgery
22
41
22
19
61
93
none
9
3
general_medicine
38
78
38
40
63
60
none
9
3
ICU
11
20
11
9
97
73
none
10
3
emergency
17
130
17
113
81
60
none
10
3
surgery
38
57
38
19
68
55
none
10
3
general_medicine
35
64
35
29
95
68
none
10
3
ICU
13
8
8
0
91
56
none
11
3
emergency
16
97
16
81
98
72
ngo_donation
11
3
surgery
48
48
48
0
82
80
none
11
3
general_medicine
35
50
35
15
75
75
none
11
3
ICU
14
17
14
3
61
50
none
12
3
emergency
28
347
28
319
68
83
malaria_peak
12
3
surgery
38
24
24
0
79
73
none
12
3
general_medicine
33
69
33
36
70
98
none
12
3
ICU
16
13
13
0
79
94
ngo_donation
13
4
emergency
23
142
23
119
77
95
none
13
4
surgery
41
54
41
13
75
90
none
13
4
general_medicine
33
72
33
39
73
70
none
13
4
ICU
17
12
12
0
66
52
none
14
4
emergency
15
97
15
82
71
71
none
14
4
surgery
33
49
33
16
97
87
none
14
4
general_medicine
51
47
47
0
86
76
none
14
4
ICU
10
16
10
6
92
54
none
15
4
emergency
17
53
17
36
94
98
none
15
4
surgery
31
124
31
93
65
76
malaria_peak
15
4
general_medicine
53
179
53
126
90
76
malaria_peak
15
4
ICU
14
11
11
0
92
52
none
16
4
emergency
23
144
23
121
62
89
none
16
4
surgery
37
28
28
0
82
31
strike
16
4
general_medicine
39
41
39
2
85
66
none
16
4
ICU
18
15
15
0
98
78
none
17
5
emergency
21
133
21
112
84
73
none
17
5
surgery
40
23
23
0
95
94
none
17
5
general_medicine
33
76
33
43
75
63
none
17
5
ICU
14
17
14
3
87
83
none
18
5
emergency
18
100
18
82
81
80
ngo_donation
18
5
surgery
43
36
36
0
81
98
none
18
5
general_medicine
31
25
25
0
96
62
strike
18
5
ICU
12
9
9
0
63
55
none
19
5
emergency
16
70
16
54
99
45
strike
19
5
surgery
42
44
42
2
78
66
none
19
5
general_medicine
43
60
43
17
85
86
none
19
5
ICU
14
17
14
3
68
61
none
20
5
emergency
21
45
21
24
93
81
none
20
5
surgery
31
39
31
8
99
94
none
20
5
general_medicine
40
70
40
30
64
71
none
20
5
ICU
10
14
10
4
85
65
none
21
6
emergency
18
95
18
77
88
63
none
21
6
surgery
30
44
30
14
64
67
ngo_donation
21
6
general_medicine
45
70
45
25
95
82
none
21
6
ICU
12
9
9
0
69
54
none
22
6
emergency
16
129
16
113
69
68
none
22
6
surgery
18
21
18
3
63
65
none
22
6
general_medicine
46
36
36
0
87
88
ngo_donation
22
6
ICU
9
6
6
0
92
82
none
23
6
emergency
22
54
22
32
62
50
none
23
6
surgery
26
43
26
17
72
61
none
23
6
general_medicine
27
81
27
54
94
77
ngo_donation
23
6
ICU
17
12
12
0
85
83
none
24
6
emergency
18
105
18
87
70
78
none
24
6
surgery
39
21
21
0
95
39
strike
24
6
general_medicine
47
66
47
19
94
97
none
24
6
ICU
9
9
9
0
91
73
none
25
7
emergency
15
48
15
33
72
72
none
25
7
surgery
22
39
22
17
76
98
none
25
7
general_medicine
36
51
36
15
81
62
none
25
7
ICU
8
6
6
0
71
90
none
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Services Weekly Dataset

Dataset Description

This collection tracks weekly performance metrics across four hospital services (emergency, surgery, ICU, general_medicine) for a full year. Metrics include bed availability, patient requests/admissions, satisfaction scores, staff morale, and special events. The data enables analysis of resource allocation, service capacity, seasonal patterns, and the impact of external events on hospital operations.

Dataset Structure

Data Instances

[
  {
    "week":1,
    "month":1,
    "service":"emergency",
    "available_beds":32,
    "patients_request":76,
    "patients_admitted":32,
    "patients_refused":44,
    "patient_satisfaction":67,
    "staff_morale":70,
    "event":"none"
  },
  {
    "week":1,
    "month":1,
    "service":"surgery",
    "available_beds":45,
    "patients_request":130,
    "patients_admitted":45,
    "patients_refused":85,
    "patient_satisfaction":83,
    "staff_morale":78,
    "event":"malaria_peak"
  },
  {
    "week":1,
    "month":1,
    "service":"general_medicine",
    "available_beds":37,
    "patients_request":201,
    "patients_admitted":37,
    "patients_refused":164,
    "patient_satisfaction":97,
    "staff_morale":43,
    "event":"malaria_peak"
  }
]

Data Fields

  • week (int64): Week number of the year
  • month (int64): Month number
  • service (object): Hospital service (emergency, surgery, ICU, general_medicine)
  • available_beds (int64): Number of beds available in the service
  • patients_request (int64): Number of patients requesting admission
  • patients_admitted (int64): Number of patients actually admitted
  • patients_refused (int64): Number of patients refused due to capacity
  • patient_satisfaction (int64): Average patient satisfaction for the week
  • staff_morale (int64): Average staff morale score for the week
  • event (object): Special event during the week (malaria_peak, ngo_donation, strike, none)

Data Splits

  • Total records: 208

Dataset Creation

Source Data

This dataset was synthetically generated to simulate real-world hospital operations for a medium-sized Nigerian hospital.

Localization

  • Names: All patient and staff names use authentic Nigerian names from Yoruba, Igbo, and Hausa ethnic groups
  • Events: Localized to Nigerian context (e.g., malaria peaks, NGO donations)
  • Context: Simulates a typical medium-sized hospital in Nigeria

Additional Information

Dataset Curators

Generated for healthcare operations analysis and research.

Licensing Information

This synthetic dataset is provided for research and educational purposes.

Citation Information

@dataset{nigerian_hospital_services_weekly_dataset,
  title={Nigerian Hospital Services Weekly Dataset},
  year={2025}
}
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