Data Set: Clinical Performance
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Perform data mining activities on two Excel data sets. Prepare a 5 page report of findings, including whether data sets accurately depict performance, the use of data sampling methods in strategic decision making, and conclusions and recommendations about improving patient service and staff performance. Include in the report the analysis of the raw data in Excel data analysis tables.
Data Set 1: Clincial Performance
Data Set 2: Nursing Performance
INSTRUCTIONS
As a Vila Health data analyst, you have been asked to work on a project related to customer satisfaction and nursing staff performance. You will analyze two datasets. One concerns clinic performance, specifically, patient wait times and office visit lengths. The other dataset is on nursing performance.
After analyzing these two datasets, you will compose a report for the clinic’s physicians based on your analysis.
Dataset 1: Clinic Performance
This first dataset contains raw data about clinic performance from a customer-service perspective. First, organize and analyze the raw data in Excel data analysis tables. You will include these tables in your report. Write your report about Dataset 1. Be sure to include these headings and address the bullets following each heading:
- Accurate Depiction of Clinic Performance.
- Explain whether the sample can accurately depict clinic performance, noting variations and patterns.
- Data Sampling Methods and Strategic Decision Making.
- Describe how to use data sampling methods in strategic decision making.
- Conclusions and Recommendations About Clinic Physicians and Customer Service.
- Draw conclusions about clinic physicians and customer service.
- Make two recommendations for improving patient service based on your analysis.
Dataset 2: Nursing Staff Performance
Dataset 2 provides information on nursing staff performance on two tasks. The data show a decrease in nursing staff productivity at one Vila Health clinic in the past few months. Use the Nursing Data Worksheet and the Pivot Table Report, both contained in Dataset 2 Nursing Performance 2016, to perform data mining techniques to determine how nursing staff performed when completing Tasks 1 and 2. Organize and analyze the raw data in Excel data analysis tables. You will include these tables in your report.
Note: Be careful of filters. Be sure to check data from various years.
Write your report, including all of the following:
Data Mining Techniques to Evaluate Nursing Staff Performance on Tasks.
- Explain how each of these data mining techniques can be used to evaluate nursing staff task performance:
- Genetic algorithms.
- Neural networks.
- Predictive modeling.
- Rule induction.
- Decision trees.
- K-Nearest neighbor.
- Include examples of the use of each data mining technique in relation to the nursing data.
Data Mining and Strategic Decision Making.
- Describe the use of data mining in strategic decision making.
Conclusions and Recommendations About Nursing Staff Performance.
- Draw conclusions about nursing performance on tasks.
- Create two recommendations for improving nursing performance.
Conclusion
Summarize the findings of your analysis of the two datasets. Draw conclusions about how the information from the datasets might be connected. For example, how might physician performance impact nursing tasks? Or what is the association between customer satisfaction and nursing task performance?
Resources: Data Collection
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- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
- Chapter 12, “Basic Research Principles,” pages 283–307.
- Chapter 13, “Inferential Statistics in Healthcare,” pages 309–320.
- Cleary, M., Horsfall, J., & Hayter, M. (2014). Data collection and sampling in qualitative research: Does size matter? Journal of Advanced Nursing, 70(3), 473–475.
- Kandola, D., Banner, D., O’Keefe-McCarthy, S., & Jassal, D. (2014). Sampling methods in cardiovascular nursing research: An overview. Canadian Journal of Cardiovascular Nursing, 24(3), 15–18.
- Roberts, P. (2015). Data sampling for the right reasons. Business Intelligence Journal, 20(1), 33–38. Data Set: Clinical Performance
Resources: Data Mining
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- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
- Chapter 14, “Data Analytics,” pages 321–330.
- Lismont, J., Janssens, A., Odnoletkova, I., Vanden Broucke, S., Caron, F., & Vanthienen, J. (2016). A guide for the application of analytics on healthcare processes: A dynamic view on patient pathways. Computers in Biology and Medicine, 77, 125–134.
- Ullah, Z., Fayaz, M., & Iqbal, A. (2016). Critical analysis of data mining techniques on medical data. International Journal of Modern Education and Computer Science, 8(2), 42–48.
- Data Mining | Transcript.
- In under five minutes, this Capella media piece presents some basic assumptions about leading a data mining project.
Resources: Data Presentation
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- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
- Chapter 11, “Presentation of Data,” pages 245–281.
- Ghazisaeidi, M., Safdari, R., Torabi, M., Mirzaee, M., Farzi, J., & Goodini, A. (2015). Development of performance dashboards in healthcare sector: Key practical issues. Acta Informatica Medica, 23(5), 317–321.
- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
- Horton, L. A. (2017). Calculating and reporting healthcare statistics (5th Rev. ed.). Chicago, IL: AHIMA Press. Available from the bookstore.
Data Set: Clinical Performance
Unformatted Attachment Preview
Happy Health Clinic Data Set Name anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous Date of Visit Tuesday, February 7, 2017 Tuesday, February 7, 2017 Tuesday, February 7, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Friday, February 3, 2017 Friday, February 3, 2017 Friday, February 3, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Thursday, February 2, 2017 Thursday, February 2, 2017 Thursday, February 2, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Friday, February 3, 2017 Friday, February 3, 2017 Friday, February 3, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Saturday, February 4, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Tuesday, February 7, 2017 Tuesday, February 7, 2017 Tuesday, February 7, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Thursday, February 9, 2017 Physician Name Bob Jeffen Bob Jeffen Bob Jeffen Bob Jeffen Bob Jeffen Bob Jeffen Bob Jeffen Jack Jeffen Jack Jeffen Jack Jeffen Jack Jeffen Jack Jeffen Jack Jeffen Jack Jones Jack Jones Jack Jones James Jones James Jones James Jones James Jones James Jones James Jones James Jones James Jones James Jones James Jones James Jones John Cousin John Cousin John Cousin John Jabor John Jabor John Jabor John Jabor John Jabor John Jabor John Jabor John Jabor John Jabor Paul Jabor Paul Jabor Paul Jabor Paul Jabor Paul Jabor Paul Jabor Paul Jabor Paul Jabor Visit Type Well Check Well Check Well Check Short Visit Short Visit Short Visit Long Visit Long Visit Long Visit Long Visit Long Visit Long Visit Long Visit Well Check Well Check Well Check Short Visit Short Visit Short Visit Short Visit Short Visit Short Visit Short Visit Short Visit Short Visit Short Visit Long Visit Short Visit Short Visit Short Visit Discharge Follow Up Discharge Follow Up Discharge Follow Up Short Visit Short Visit Short Visit Discharge Follow Up Discharge Follow Up Discharge Follow Up Well Check Well Check Well Check Well Check Well Check Well Check Well Check Long Visit Price $50 $50 $50 $75 $75 $75 $140 $50 $50 $50 $140 $140 $140 $50 $50 $50 $140 $140 $140 $50 $50 $50 $50 $50 $50 $50 $175 $50 $50 $50 $70 $70 $70 $50 $50 $50 $70 $70 $70 $50 $50 $50 $55 $55 $55 $55 $120 anonymous anonymous anonymous anonymous anonymous anonymous anonymous anonymous Thursday, February 9, 2017 Thursday, February 9, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Monday, February 6, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Wednesday, February 8, 2017 Paul Jabor Paul Jabor Peter Miller Peter Miller Peter Miller Peter Miller Peter Miller Peter Miller This cell left blank intentionally. End of Worksheet Long Visit Long Visit Short Visit Short Visit Short Visit Well Check Well Check Well Check $150 $160 $75 $75 $75 $50 $50 $50 Total Cost of Services $4,075 ic Data Set Amount Paid by Patient $20 $20 $20 $25 $50 $50 $70 $25 $25 $25 $70 $70 $70 $35 $35 $35 $0 $75 $75 $0 $0 $0 $0 $0 $0 $0 $0 $15 $15 $15 $35 $35 $35 $30 $30 $30 $65 $65 $65 $15 $15 $15 $15 $15 $15 $35 $60 Length of Time Waiting Before Being Seen 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 45 mins. 30 mins. 30 mins. 30 mins. 40 mins 40 mins 40 mins 40 mins 40 mins 40 mins 15 min. 15 min. 15 min. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 30 mins. 15 min. 15 min. 15 min. 30 mins. 30 mins. 30 mins. 15 mins 15 mins 15 mins 35 mins. 35 mins. 35 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 25 mins. 45 mins. Length of Visit 30 mins. 30 mins. 30 mins. 15 mins. 15 mins. 15 mins. 30 mins. 40 mins. 35 mins. 30 mins. 50 mins. 50 mins. 50 mins. 30 mins. 20 mins. 20 mins. 35 mins. 20 mins. 25 mins. 15 mins. 15 mins. 15 mins. 20 mins. 20 mins. 20 mins. 20 mins. 40 mins. 20 mins. 20 mins. 20 mins. 30 mins. 30 mins. 30 mins. 15 mins. 15 mins. 15 mins. 30 mins. 30 mins. 30 mins. 30 mins. 30 mins. 30 mins. 25 mins. 25 mins. 25 mins. 25 mins. 30 mins. Insurance Coverage no no no no no no no yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes no no no no no yes yes yes no no no yes yes yes yes yes yes no no no no no no no no $64 $80 $92 $92 $92 $15 $25 $25 Total Amount Paid by Patients $1,900 45 mins. 45 mins. 15 min. 15 min. 15 min. 30 mins. 30 mins. 30 mins. 30 mins. 30 mins. 20 mins. 20 mins. 20 mins. 25 mins. 25 mins. 25 mins. no no no no no no no no This cell left blank intentionally. [Company name] Nursing data worksheet [Date] Blank Account Number X000001 X000002 X000003 X000004 X000005 X000006 X000007 X000008 X000009 X000010 X000011 X000012 X000013 X000014 X000015 X000016 X000017 X000018 X000019 X000020 X000021 X000022 X000023 X000024 X000025 X000026 X000027 X000028 X000029 X000030 Blank Blank Blank Blank Admit Date Nurse, Last Name Nurse, First Name Title 10/4/2016 10/9/2016 10/14/2016 10/19/2016 10/24/2016 10/29/2016 11/3/2016 11/8/2016 11/13/2016 11/18/2016 11/23/2016 11/28/2016 12/3/2016 12/8/2016 12/13/2016 12/18/2016 12/23/2016 12/28/2016 1/2/2017 1/7/2017 1/12/2017 1/17/2017 1/22/2017 1/27/2017 2/1/2017 2/6/2017 2/11/2017 2/16/2017 2/21/2017 2/26/2017 Sacksteder Jaffe Daniels Naik Salavaria Waldal Jaffe Naik Sacksteder Daniels Waldal Salavaria Jaffe Daniels Naik Waldal Salavaria Sacksteder Naik Jaffe Salavaria Sacksteder Waldal Daniels Salavaria Naik Waldal Sacksteder Waldal Jaffe Lane David David Mandar Sharon Deb David Mandar Lane David Deb Sharon David David Mandar Deb Sharon Lane Mandar David Sharon Lane Deb David Sharon Mandar Deb Lane Deb David RN RN RN RN LPN LPN RN RN RN RN LPN LPN RN RN RN LPN LPN RN RN RN LPN RN LPN RN LPN RN LPN RN LPN RN [Company name] CONFIDENTIAL Blank Blank Blank Blank [Task 1] [Task 2] Unit Complete? Complete? MONTH YEAR QUARTER COUNT Med/Surg ICU PreOp Ortho Med/Surg Ortho ICU Ortho Med/Surg PreOp Ortho Med/Surg ICU PreOp Ortho Ortho Med/Surg Med/Surg Ortho ICU Med/Surg Med/Surg Ortho PreOp Med/Surg Ortho Ortho Med/Surg Ortho ICU Yes No Yes No Yes Yes No Yes No Yes Yes Yes Yes No No Yes Yes No Yes Yes Yes Yes No Yes Yes Yes No Yes Yes Yes Yes No Yes No Yes No No Yes No Yes Yes Yes No No No Yes Yes No Yes Yes Yes No No Yes Yes Yes No Yes Yes Yes Oct Oct Oct Oct Oct Oct Nov Nov Nov Nov Nov Nov Dec Dec Dec Dec Dec Dec Jan Jan Jan Jan Jan Jan Feb Feb Feb Feb Feb Feb 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2016 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [Company name] Nursing data worksheet [Date] Blank Blank Blank Account Number Admit Date Nurse, Last Name X000031 X000032 X000033 X000034 X000035 X000036 X000037 X000038 X000039 X000040 X000041 X000042 X000043 X000044 X000045 X000046 X000047 X000048 X000049 X000050 X000051 X000052 X000053 X000054 X000055 X000056 X000057 X000058 3/3/2017 3/8/2017 3/13/2017 3/18/2017 3/23/2017 3/28/2017 4/2/2017 4/7/2017 4/12/2017 4/17/2017 4/22/2017 4/27/2017 5/2/2017 5/7/2017 5/12/2017 5/17/2017 5/22/2017 5/27/2017 6/1/2017 6/6/2017 6/11/2017 6/16/2017 6/21/2017 6/26/2017 7/1/2017 7/6/2017 7/11/2017 7/16/2017 Waldal Daniels Salavaria Jaffe Sacksteder Naik Waldal Daniels Naik Jaffe Salavaria Sacksteder Salavaria Daniels Naik Sacksteder Waldal Salavaria Daniels Jaffe Sacksteder Naik Waldal Salavaria Jaffe Sacksteder Daniels Waldal Blank Blank Nurse, First Name Title Deb David Sharon David Lane Mandar Deb David Mandar David Sharon Lane Sharon David Mandar Lane Deb Sharon David David Lane Mandar Deb Sharon David Lane David Deb LPN RN LPN RN RN RN LPN RN RN RN LPN RN LPN RN RN RN LPN LPN RN RN RN RN LPN LPN RN RN RN LPN [Company name] CONFIDENTIAL Blank Blank Blank Blank [Task 1] [Task 2] Unit Complete? Complete? MONTH YEAR QUARTER COUNT Ortho PreOp Med/Surg ICU Med/Surg Ortho Ortho PreOp Ortho ICU Med/Surg Med/Surg Med/Surg PreOp Ortho Med/Surg Ortho Med/Surg PreOp ICU Med/Surg Ortho Ortho Med/Surg ICU Med/Surg PreOp Ortho Yes Yes Yes No Yes No Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No Yes No Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes Mar Mar Mar Mar Mar Mar Apr Apr Apr Apr Apr Apr May May May May May May Jun Jun Jun Jun Jun Jun Jul Jul Jul Jul 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 2017 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [Company name] Nursing data worksheet [Date] Blank Blank Blank Account Number Admit Date Nurse, Last Name X000059 X000060 7/21/2017 7/26/2017 Naik Salavaria End of Worksheet Blank Blank Nurse, First Name Title Mandar Sharon RN LPN [Company name] CONFIDENTIAL Blank Blank Blank Blank [Task 1] [Task 2] Unit Complete? Complete? MONTH YEAR QUARTER COUNT Ortho Med/Surg Yes No Yes No Jul Jul 2017 2017 3 3 1 1 [Company name] Blank Nursing data worksheet:PivotTable report [Date] Blank Blank YEAR QUARTER MONTH Blank Sum of COUNT Title LPN RN Grand Total 2016 (All) (All) Blank [Task 1] Complete? No Blank Blank Blank Blank End of Worksheet Blank Blank Blank Blank Blank Blank [Company name] CONFIDENTIAL Yes 3 3 6 Grand Total 13 23 36 16 26 42 CRITERION 1 Organize raw data. Organizes raw data and explains organization choices from a statistical analysis perspective. CRITERION 2 Perform data mining activities. Data Set: Clinical Performance
Performs data mining activities. Describes data mining techniques and provides rationale for using particular techniques. CRITERION 3 Analyze data samples. Analyzes data samples. Analysis includes multiple examples, specifics, and references to current, scholarly and/or authoritative sources. CRITERION 4 Explain how to use data sampling methods and data mining to inform strategic decision making. Explains how to use data sampling methods and data mining to inform strategic decision making. Explanation includes multiple specifics, examples, and references to current scholarly and/or authoritative sources. CRITERION 5 Recommend quality of care improvements based on statistical analysis. Recommends quality of care improvements based on statistical analysis. Recommendations include multiple examples, specifics, and references to current scholarly and/or authoritative sources. CRITERION 6 Create a clear, well-organized, professional document that is generally free of errors in grammar, spelling, and punctuation. Creates a clear, well-organized, error-free professional document. Document includes multiple examples, specifics, and references to current scholarly and/or authoritative sources. CRITERION 7 Follow APA style and formatting guidelines for citations and references. Follows APA style and formatting guidelines for citations and references without errors. … Data Set: Clinical Performance
Data Set: Clinical Performance