Case #1
You are the manager of a family practice clinic. You have been collecting patient satisfaction surveys for the past 6 months and discovered the one item that is consistently the number 1 complaint is the wait time. Your staff nurse tells you that the wait times do not seem very long. However, the employee who schedules the appointments tells you the patients seem bothered by the amount of time they have to wait to see a physician. The wait time data is included in the data table below.
Day of the month
|
Avg. Wait time (min)
|
Day of month
|
Avg. wait time (min)
|
1
|
30
|
16
|
34
|
2
|
50
|
17
|
34
|
3
|
28
|
20 (Mon.)
|
75
|
6 (Mon.)
|
85
|
21
|
60
|
7
|
70
|
22
|
28
|
8
|
20
|
23
|
45
|
9
|
35
|
24
|
50
|
10
|
40
|
27 (Mon.)
|
80
|
13 (Mon.)
|
75
|
28
|
25
|
14
|
62
|
29
|
18
|
15
|
38
|
30
|
40
|
What is the best graph to use to display this data and why?
- Complete this graph using Excel. Graph is to be in presentation ready style. Legend must be included with graph.
- What analysis can you make after seeing the data displayed?
Case #2
You have submitted a request to the CEO of your hospital for new linens. Before your request will be approved you are asked to the submit reasons for linen discards. Below is the data you collected over the past month:
Discard Reason
|
Number discarded
|
Large tear
|
15
|
Small holes
|
9
|
Permanently soiled
|
16
|
Discolored
|
10
|
Threadbare
|
25
|
- Graph this date in the most appropriate graph. Same data must be included as stipulated above
(Title,etc.)
- Complete the corresponding percentages for the number of linens discarded. Graph accordingly.
- What analysis can you make from this data?
Case #3
From the data provided in the tables below, pick one set of data and create an appropriate graph to represent that data which is (Pareto graph).
Profile of Hospital Patients, Lakewood Regional Medical Center, California
|
Discharges
|
% of patients
|
Length of stay in days
|
Race/Ethnicity
|
|
|
|
White
|
5235
|
63.5
|
4.8
|
Black
|
772
|
9.4
|
4.3
|
Hispanic
|
1597
|
19.4
|
3.1
|
Native American
|
96
|
1.2
|
3.8
|
Asian
|
482
|
5.9
|
5.0
|
Other/unknown
|
55
|
0.7
|
3.3
|
Admission Source
|
|
|
|
Routine
|
3,585
|
43.5
|
4.2
|
Emergency Room
|
3299
|
40.0
|
5.2
|
Home Health
|
1
|
0.0
|
3.0
|
SNF/ICF
|
167
|
2.0
|
8.4
|
Other facility
|
38
|
0.5
|
4.7
|
Newborn
|
1032
|
12.5
|
1.6
|
|
Adjusted Total Charges
Age
|
Total $
|
$/Day
|
$/stay
|
Average stay in days
|
<29 days
|
781,716
|
476
|
746
|
1.6
|
29-364
|
29,432
|
1402
|
2676
|
1.9
|
1-4 yrs.
|
74,596
|
1622
|
3108
|
1.9
|
5-14 yrs.
|
280,570
|
1990
|
4600
|
2.3
|
15-18 yrs.
|
641,857
|
2077
|
4427
|
2.1
|
19-44
|
17,251,826
|
2528
|
7540
|
3.0
|
45-64
|
24,390,763
|
3064
|
14936
|
4.9
|
65-69
|
12,545,685
|
3159
|
18235
|
5.8
|
70-74
|
15,700,837
|
3078
|
19194
|
6.2
|
75-84
|
21,994,942
|
2998
|
19691
|
6.4
|
85+
|
6,490,931
|
2499
|
15988
|
6.4
|
Total
|
100,183,155
|
2787
|
12160
|
4.4
|
What analysis can you make after graphing your data?