Attention Wizard Kim week 7 Discussion & Assignment.

Week 7 Discussion on Optimization in Health Services, 2 pages.

Week 7 Assignment on Optimization Using Health Care Examples

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Name: DDHA_8800_Week7_Assignment_Rubric

 

Excellent Good Fair Not Done
Formulates mechanical heart optimization problem (#36), recommending how to minimize cost Points: Points Range: 11 (18.33%) – 12 (20%) Correctly formulates mechanical heart optimization problem (#36), recommending how to minimize cost Feedback: Points: Points Range: 9 (15%) – 10 (16.67%) Formulates mechanical heart optimization problem (#36), recommending how to minimize cost with some accuracy Feedback: Points: Points Range: 1 (1.67%) – 8 (13.33%) Formulates mechanical heart optimization problem (#36), recommending how to minimize cost with little accuracy Feedback: Points: Points Range: 0 (0%) – 0 (0%) Does not formulate mechanical heart optimization problem (#36), recommending how to minimize cost Feedback:
Uses Solver/Solver table to correctly address part b of mechanical heart problem Points: Points Range: 11 (18.33%) – 12 (20%) Uses Solver/Solver table to correctly address part b of mechanical heart problem Feedback: Points: Points Range: 9 (15%) – 10 (16.67%) Uses Solver/Solver table to address part b of mechanical heart problem with some accuracy Feedback: Points: Points Range: 1 (1.67%) – 8 (13.33%) Uses Solver/Solver table to address part b of mechanical heart problem with little accuracy Feedback: Points: Points Range: 0 (0%) – 0 (0%) Does not use Solver/Solver table to address part b of mechanical heart problem Feedback:
Formulates pharmaceutical problem (#42), recommending how to minimize cost Points: Points Range: 11 (18.33%) – 12 (20%) Correctly formulates pharmaceutical problem (#42), recommending how to minimize cost Feedback: Points: Points Range: 9 (15%) – 10 (16.67%) Formulates pharmaceutical problem (#42), recommending how to minimize cost with some accuracy Feedback: Points: Points Range: 1 (1.67%) – 8 (13.33%) Formulates pharmaceutical problem (#42), recommending how to minimize cost with little accuracy Feedback: Points: Points Range: 0 (0%) – 0 (0%) Does not formulate pharmaceutical problem (#42), recommending how to minimize cost Feedback:
Uses Solver/Solver table to correctly address part b of mechanical heart problem Points: Points Range: 11 (18.33%) – 12 (20%) Uses Solver / Solver table to correctly address part b of mechnical heart problem Feedback: Points: Points Range: 9 (15%) – 10 (16.67%) Uses Solver/Solver table to address part b of mechanical heart problem with some accuracy Feedback: Points: Points Range: 1 (1.67%) – 8 (13.33%) Uses Solver/Solver table to address part b of mechanical heart problem with little accuracy Feedback: Points: Points Range: 0 (0%) – 0 (0%) Does not use Solver/Solver table to address part b of mechanical heart problem Feedback:
Professional Document that is APA Compliant Points: Points Range: 11 (18.33%) – 12 (20%) Writing is organized, concise, and scholarly written with no grammatical errors. Demonstrates consistent use of credible, relevant sources to fully develop ideas. Meets all APA format, citations, and structure requirements. Feedback: Points: Points Range: 9 (15%) – 10 (16.67%) Writing is organized, concise, and scholarly written with minimal to no grammatical errors. Demonstrates consistent use of credible, relevant sources to support ideas. Minimal to no errors in APA format, citations, and structure. Feedback: Points: Points Range: 1 (1.67%) – 8 (13.33%) Writing is unclear or interrupted by grammatical errors. Demonstrates some use of credible and/or relevant sources to support ideas. Moderate errors in APA format, citations, and structure. Feedback: Points: Points Range: 0 (0%) – 0 (0%) Writing lacks clarity, organization and has significant grammatical errors. Demonstrates minimal use of sources to support ideas. Significant errors in APA format, citations, and structure. Or no citing of sources. Feedback:

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Formulates mechanical heart optimization problem (#36), recommending how to minimize cost–

Levels of Achievement: Excellent 11 (18.33%) – 12 (20%) Correctly formulates mechanical heart optimization problem (#36), recommending how to minimize cost Good 9 (15%) – 10 (16.67%) Formulates mechanical heart optimization problem (#36), recommending how to minimize cost with some accuracy Fair 1 (1.67%) – 8 (13.33%) Formulates mechanical heart optimization problem (#36), recommending how to minimize cost with little accuracy Not Done 0 (0%) – 0 (0%) Does not formulate mechanical heart optimization problem (#36), recommending how to minimize cost Feedback:

Uses Solver/Solver table to correctly address part b of mechanical heart problem–

Levels of Achievement: Excellent 11 (18.33%) – 12 (20%) Uses Solver/Solver table to correctly address part b of mechanical heart problem Good 9 (15%) – 10 (16.67%) Uses Solver/Solver table to address part b of mechanical heart problem with some accuracy Fair 1 (1.67%) – 8 (13.33%) Uses Solver/Solver table to address part b of mechanical heart problem with little accuracy Not Done 0 (0%) – 0 (0%) Does not use Solver/Solver table to address part b of mechanical heart problem Feedback:

Formulates pharmaceutical problem (#42), recommending how to minimize cost–

Levels of Achievement: Excellent 11 (18.33%) – 12 (20%) Correctly formulates pharmaceutical problem (#42), recommending how to minimize cost Good 9 (15%) – 10 (16.67%) Formulates pharmaceutical problem (#42), recommending how to minimize cost with some accuracy Fair 1 (1.67%) – 8 (13.33%) Formulates pharmaceutical problem (#42), recommending how to minimize cost with little accuracy Not Done 0 (0%) – 0 (0%) Does not formulate pharmaceutical problem (#42), recommending how to minimize cost Feedback:

Uses Solver/Solver table to correctly address part b of mechanical heart problem–

Levels of Achievement: Excellent 11 (18.33%) – 12 (20%) Uses Solver / Solver table to correctly address part b of mechnical heart problem Good 9 (15%) – 10 (16.67%) Uses Solver/Solver table to address part b of mechanical heart problem with some accuracy Fair 1 (1.67%) – 8 (13.33%) Uses Solver/Solver table to address part b of mechanical heart problem with little accuracy Not Done 0 (0%) – 0 (0%) Does not use Solver/Solver table to address part b of mechanical heart problem Feedback:

Professional Document that is APA Compliant–

Levels of Achievement: Excellent 11 (18.33%) – 12 (20%) Writing is organized, concise, and scholarly written with no grammatical errors. Demonstrates consistent use of credible, relevant sources to fully develop ideas. Meets all APA format, citations, and structure requirements. Good 9 (15%) – 10 (16.67%) Writing is organized, concise, and scholarly written with minimal to no grammatical errors. Demonstrates consistent use of credible, relevant sources to support ideas. Minimal to no errors in APA format, citations, and structure. Fair 1 (1.67%) – 8 (13.33%) Writing is unclear or interrupted by grammatical errors. Demonstrates some use of credible and/or relevant sources to support ideas. Moderate errors in APA format, citations, and structure. Not Done 0 (0%) – 0 (0%) Writing lacks clarity, organization and has significant grammatical errors. Demonstrates minimal use of sources to support ideas. Significant errors in APA format, citations, and structure. Or no citing of sources. Feedback:

Total Points: 60

Name: DDHA_8800_Week7_Assignment_Rubric

Week 6: Data-Driven decision Making for Health care administrator

 

 

Optimization 1

 

Improving the patient experience is just one initiative that you, as a current or future healthcare administration leader, might be responsible for ensuring in your health services organization. The patient experience is an abstract concept that may capture indices of patient wait times, patient cost, and patient orientation toward healthcare delivery processes in a health services organization.

 

However, how might a healthcare administration leader analyze or determine the best way possible to improve the patient experience, for example, by shortening patient wait time? How might a healthcare administration leader determine how to improve the quality of time patients spend with physicians or clinical staff?

 

These considerations and opportunities can be addressed by the analytic process of optimization. This week, you explore optimization as an analytic technique and consider how you might apply this technique to healthcare administration practice problems. You also conduct an optimization problem solution and reflect on how optimization might be used in your health services organization or one with which you are familiar.

 

Learning Objectives

Students will:

· Analyze problems that may be addressed by optimization in health services organizations

· Conduct an optimization problem solution

· Apply optimization strategies to healthcare administration problems.

 

 

 

 

Learning Resources

Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.

 

Required Readings

Albright, S. C., & Winston, W. L. (2017). Business analytics: Data analysis and decision making (6th ed.). Stamford, CT: Cengage Learning.

 

Chapter 13, “Introduction to Optimization Modeling”

Required Media

Franza, T. [Thomas Franza]. (2012, April 23). How to install Microsoft Excel 2010’s Solver add-in [Video file]. Retrieved from https://www.youtube.com/watch?v=0z2BVsbITAs&feature=youtu.be.

 

 

 

Discussion Part

Optimization in Health Services

 

David is a healthcare administration leader who manages the operations of a long-term care facility. Within the past 6 months, long-term care patients and residents have experienced an increased number of hospital readmissions due to ongoing acute infections. In striving to ensure effective healthcare delivery and patient safety, David is seeking to use optimization as an analytic technique to determine how to best implement workflow processes to have clinical staff and physicians dedicate time to routine history and full-body observation to help prevent ongoing acute infections.

 

1. For this Discussion, review the resources for this week, and reflect on how optimization techniques might enhance healthcare delivery. Consider the value of optimization techniques in assisting healthcare administration leaders in providing quality patient care and safety.

 

By Day 3

2. Post a description of some problems that might lend themselves to optimization in your health services organization or one with which you are familiar, and explain why. Then, set up a fictitious optimization problem that would save one of the problems (e.g., Max z = a1x1 + a2x2, subject to constraints). Be specific, and provide examples.

 

By Day 5

Continue the Discussion and respond to your colleagues in one or more of the following ways:

 

· Ask a probing question, substantiated with additional background information, evidence, or research.

· Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.

· Offer and support an alternative perspective, using readings from the classroom or from your own research in the Walden Library.

· Validate an idea with your own experience and additional research.

· Make a suggestion based on additional evidence drawn from readings or after synthesizing multiple postings.

· Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.

 

 

 

Submission and Grading Information

Grading Criteria

To access your rubric:

 

Week 7 Discussion Rubric

 

Post by Day 3 and Respond by Day 5

To participate in this Discussion: Week 7 Discussion

 

 

 

Assignment Part (5 pages) APA format 7th Ed.

 

Optimization Using Health Care Examples

 

In what other ways might optimization be used to maximize healthcare delivery? What types of processes and workflows are best served by optimization in health services organizations?

 

Optimization is a vital prescriptive analytic technique that healthcare administrators can use to help address challenges in effective and efficient healthcare delivery. Health decision makers may seek to find optimal solutions for a particular objective given various constraints. For example, optimization is often used for generating nursing staff schedules to ensure appropriate staff coverage with varying patient inflows.

 

1. For this Assignment, you will be using optimization techniques to evaluate two separate medical problems, one involving mechanical heart valves and another involving a pharmaceutical company. Review the resources for this week, and examine the different optimization techniques that can be used for this Assignment.

 

For Chapter 13, problems 36 and 42, you will need to download the files P13_36.xlsx and P13_42.xlsx from the textbook companion website http://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781305947542. Under “Book Resources”, click on “Student Downloads” to view the downloadable files. Click “Problem Files” and download the zipped file 1305947541_538885.zip. Open the zipped file, and select folder “Problem Files” and then select folder “Chapter 13” to access the files P13_36.xlsx and P13_42.xlsx.

 

The Assignment: (5 pages)

 

Complete Problem 36 on page 657 (mechanical heart valves) and Problem 42 on page 659 (pharmaceutical company) of your course text.

 

Note: You will complete these problems using Excel and Solver.

 

 

Questions

(36) A company manufactures mechanical heart valves from the heart valves of pigs. Different heart operations require valves of different sizes. The company purchases pig valves from three different suppliers. The cost and size mix of the valves purchased from each supplier are given in the file P13_36.xlsx. each month, the company places an order with each supplier. At least 500 large, 300 medium, and 300 small valves must be purchased each month. Because of the limited availability of pig valves, at most 500 valves per month can be purchased from each supplier.

(a) Use Solver to determine how the company can minimize the cost of acquiring the needed valves.

(b) Use Solver Table to investigate the effect on total cost of increasing its minimal purchase requirements each month. Specifically, see how the total cost changes as the purchase requirements of large, medium, and small valves all increase from their original valves by the same percentage. Revise your model so that Solver Table can be used to investigate these changes when the percentage increase varies from 2% to 20% in increments of 2%. Explain intuitively what happens when this percentage is at least 16%.

 

Question 42: A pharmaceutical company manufactures two drugs at Los Angeles and Indianapolis. The cost of manufacturing a pound of each drug depends on the location, as indicated in the file P13_42.xlsx. The machine time (in hours) required to produce a pound of each drug at each city is also shown in this table. The company must produce at least 1000 pounds per week of drug 1 and at least 2000 pounds per week of drug 2. It has 500 hours per week of machine time at Indianapolis and 400 hours per week at Los Angeles.

(a) Determine how the company can minimize the cost of producing the required drugs.

(b) Use Solver Table to determine how much the company would be willing to pay to purchase a combination of A extra hours of machine time at Indianapolis and B extra hours of machine time at Los Angeles, where A and B can be any positive multiples of 10 up to 50.

 

 

 

 

 

By Day 7

Submit your answers and embedded Excel analysis as a Microsoft Word management report.

 

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Click the Week 7 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.

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