Aug 16, 2017

A CASE STUDY OF SOUTHWEST MEDICAL CENTER MARY IS RESPONSIBLE FOR KEEPING TRACK OF THE NUMBER OF…

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A Case Study of Southwest Medical Center

Mary is responsible for keeping track of the number of billable visits to the Medical Oncology group at Southwest Medical Center. Her anecdotal evidence suggests that the number of visits has been increasing and some parts of the year seem to be busier than others. Some doctors are beginning to complain about the work load and suggest they don’t always have enough time to interact with individual patients.Will additional medical staff be required to handle the apparently increasing demand? If so, how many new doctors should be hired and/or be reassigned from other areas?Need to answer this question after whole report is done in the conclusion.

To provide some insight into the nature of the demand service, Mary opens her EXCEL spreadsheet and examines the total number of billable visit on a monthly basis for the last several fiscal years. The data are listed in Table 1. After examine the data, Mary is not sure which method to use in order to forecast the total number of billable visit from March 2014 through December 2014. Thus, she hired a statistical consultant to analyze the data. Mary asks the consultant to write a report summarizing the data analysis and the implications if needed for additional medical staff to handle the future demand.

Year

Sept

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

2004-2005

725

789

893

823

917

811

1048

970

1082

1028

1098

1062

2005-2006

899

1022

895

828

1011

868

991

970

934

784

1028

956

2006-2007

916

988

921

865

998

963

992

1118

1041

1057

1200

1062

2007-2008

1061

1049

829

1029

1120

1084

1307

1458

1295

1412

1553

1480

2008-2009

1554

1472

1326

1231

1251

1092

1429

1399

1341

1409

1367

1483

2009-2010

1492

1650

1454

1373

1466

1477

1466

1182

1208

1132

1094

1061

2010-2011

1018

1233

1112

1107

1305

1181

1391

1324

1259

1236

1227

1294

2011-2012

1083

1404

1329

1107

1313

1156

1184

1404

1310

1200

1396

1373

2012-2013

1259

1295

1100

1097

1357

1256

1350

1318

1271

1439

1441

1352

2013-2014

1339

1351

1197

1333

1339

1307

Table 1: Total Billable Visits to Medical Oncology, 2004 – 2014

Requirements:

Write a report to present the result and findings of this analysis.A maximum of 1500 words must be written with a word processor.Conduct the analysis required below by using statistical software e.g. Excel, Forecast X, SPSS, etc. Your report should cover the following:

(a) Plot the original time seriesand explain one obvious time-series component that present in the data.

(5 marks)

(b) Choose anyTHREE appropriate methods to forecast the total billable visitsto the Medical Oncologye.g. Naïve method, Moving Average, Decomposition, Exponential Smoothing, etc.Provide detailed descriptions and reasons of the all three forecast methods you have chosen.Give reasons for each method chose…why did you choose it?? Give valid explanations…

(9 marks)

(c) Perform the forecast using the methods you selected in part (b) for the period within September 2004 through February 2014 (only for those periods which are possible). Then,provide graph to compare between observed and forecast values for each method.

(21 marks)

(d) Name two measures of forecast error that should be used in the above situations and provide reasons of the forecast errors chosen. Then,evaluate the statistics of forecast error for each method used in part (b). Identify which forecast method is more appropriate using the measure of forecast error and explain why.

(14 marks)

(e) Use the more appropriate forecast method which determined in part (d) to forecast the total billable visits from March to December in year 2014.

(5 marks)

(f) Conduct the autocorrelation analysis (ACF and PACF) to explore the data pattern for the total billable visitsto the Medical Oncology.Provide detailed descriptions of findings from the autocorrelation analysis.

(16 marks)

(g) Develop a regression model that uses additive dummy variables for the seasonal component if necessary,and forecast the total billable visitsto the Medical Oncology from March to December in year 2014. Find the measure of forecast error using the same forecast error as in part (d). Explain the findings from the regression model.

(23 marks)

(h) Conclusion.

Conclusion should consist of analysis of the results, answer the question that is how many doctors do u suggest?? Why?? Give reasons…

(5 marks)

(i) References and Appendix.


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