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Improving the X-Ray Process at County Hospital, Case Study Example

Pages: 2

Words: 555

Case Study

Opportunities

Management at County Hospital has a number of underlying opportunities amid the x-ray improvement process.

Data Analytics

County hospital has been collecting a lot of useful information pertaining to the arrival process of patients. While this information has not been analyzed, technical and statistical analysis of this information can reveal important trends regarding the arrival and departure of patients. Such information can be used to understand influences behind these patient trends. Furthermore, analysis of this information can be used to help management plan and strategize service delivery so as to realize maximum patient service and as such result in the sustainability and eventual profitability of the x-ray department.

An example is the analysis of the arrival times of patients. One could notice patterns within the arrival times of patients. Most of the patients arrive at the waiting room after 3 hours of opening and the first patient arriving. After the third hour of operation, the x-ray department receives the most number of patients per hour for three hours. Between the third and fourth hour of operation, the department receives 12 patients. During the following hour, the department receives the same number of patients and 10 patients within the final hour of operations.

Time of arrival Difference between each patient Difference with the first patient  
6.3 Patients within the first half-hour

8

10.13 3.83 3.83
17.07 6.94 10.77
17.09 0.02 10.79
23.94 6.85 17.64
26.06 2.12 19.76
27.65 1.59 21.35
29.21 1.56 22.91
41.65 12.44 35.35 Patients within the first hour

3

44.69 3.04 38.39
60.07 15.38 53.77
70.34 10.27 64.04 Patients within 2 hours

9

70.73 0.39 64.43
74.32 3.59 68.02
84.59 10.27 78.29
91.77 7.18 85.47
95.78 4.01 89.48
98.2 2.42 91.9
117.24 19.04 110.94
122.85 5.61 116.55
130.58 7.73 124.28 Patients within 3 hours

8

137.46 6.88 131.16
139.76 2.3 133.46
142.52 2.76 136.22
150.7 8.18 144.4
151.95 1.25 145.65
154.74 2.79 148.44
157.48 2.74 151.18
193.25 35.77 186.95 Patients within 4 hours

12

195.46 2.21 189.16
197.89 2.43 191.59
205.5 7.61 199.2
215.42 9.92 209.12
219.95 4.53 213.65
223.5 3.55 217.2
233.33 9.83 227.03
234.89 1.56 228.59
239.2 4.31 232.9
244.29 5.09 237.99
247.29 3 240.99
249.9 2.61 243.6 Patients within 5 hours

12

250.25 0.35 243.95
256.34 6.09 250.04
257.9 1.56 251.6
268.97 11.07 262.67
276.82 7.85 270.52
280.43 3.61 274.13
281.94 1.51 275.64
293.23 11.29 286.93
299.79 6.56 293.49
303.75 3.96 297.45
306.58 2.83 300.28
308.13 1.55 301.83 Patients within 6 hours

10

314.06 5.93 307.76
322.82 8.76 316.52
326.51 3.69 320.21
338.21 11.7 331.91
339.91 1.7 333.61
353.65 13.74 347.35
359.79 6.14 353.49
353.65 -6.14 347.35
359.79 6.14 353.49

Health Informatics

The Community Hospital has already depicted the ability to effectively collect data. However, the application of this data has never been put into consideration. As a result, there is an underlying opportunity regarding the application of health informatics. This process has been applied on a single process within the 9-step x-ray process design. Health informatics can be applied on all 9 steps within the current process design. Application of health informatics on all steps would significantly increase information that can be used to analyze performance of each task. This is critical in identifying redundancies within the x-ray process and improving each part of the process to realize optimal output.

References

Dollinger, M. J. (2008). Entrepreneurship : strategies and resources. Lombard: Marsh Publications.

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