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Failure Modes Effects Analysis Project -Final Wk10

Failure Modes Effects Analysis Project -Final Wk10

Failure Modes Effects Analysis Project -Final Wk10

Assignment: Textbook Problems: Failure Modes Effects Analysis Project
How are risk priority numbers (RPN) useful for health care administration leaders?
As you continue your examination of the use of and purposes for FMEA,  you will begin to critically evaluate the numbers associated with your  analyses. That is, the rates with which certain processes may be failing  in your health services organization will allow you to strategically  assess and implement efforts aimed to reduce errors and to promote  quality health care delivery.

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For this Assignment, review the resources for this week regarding  chi-square, ANOVA, ANOM, and regression. Pay particular attention to the  examples shown in the textbook. Consider how these tools may contribute  to the value-chain perspective.
The Assignment: (3- pages)
·  Using SPSS and Microsoft Word, complete problems 1 through 4 on pages 405–406 in the Ross textbook. Show all work. Submit both your SPSS and Word files for grading.

http://asq.org/learn-about-quality/process-analysis-tools/overview/fmea.html

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    Summary

    PROBLEMS

    1. An FMEA will be performed on postoperative infections. Data is available by surgery type on the frequency, severity, and detectability of these infections. The director of quality improvement wants you to prepare a priority list giving the order in which the various sur- geries should be examined, to produce the greatest potential benefit for the organization. Severity is ranked from most severe (4) to least severe (1), and detectability is ranked from difficult to detect (4) to easy to detect (1). Calculate a frequency ranking from very high (5) to very low (1) based on the number of infections and cases shown in the following and the RPNs for each type of surgery. Which surgery should be examined first? Which surgery should be examined last? What is the maximum possible risk score for this analysis?

    Surgery Types

    Number of Infections

    Number of Cases

    Frequency

    Severity of Infections

    Detectability

    Risk Priority Number

    Thoracic 5

    Neuro 1

    Orthopedic 50

    Plastic 32

    Oral 25

    General 100

    200 3 3

    100 4 3

    2,000 2 2

    800 1 2

    500 1 1

    5,000 2 1

    2. Instead of the ordinal ranking of frequency, 1 to 5, used in problem 10.1, the director of quality improvement has collected data on the number of cases for each type of surgery and the num- ber of patients that contracted a postoperative infection. The director wants you to recalculate the RPN using the actual incidence rates of infection. Infection severity and detectability are ranked the same as in problem 10.1. Compare your new RPNs with those calculated in 10.1. How does the use of the incidence rate change the improvement work list? Which surgery should be examined last? What is the maximum possible risk score for this analysis?

    Surgery Types

    Number of Cases

    Number of Infections

    Rate of Infection

    Severity of Infections

    Detectability

    Risk Priority Number

    Thoracic 200

    Neuro 100

    Orthopedic 2,000

    Plastic 800

    Oral 500

    General 5,000

    5 3 3

    1 4 3

    50 2 2

    32 1 2

    25 1 1

    100 2 1

    Chapter : Failure Mode and Effects Analysis

    3. Assume that in problem 10.2 strict adherence to antibiotic administration one hour prior to thoracic surgery has reduced the rate of infection to 1.0% and severity to 2.0. How did this improvement affect the priority list? Which surgery should be the primary target for improvement?

    4. A hospital is setting its quality improvement agenda for the upcoming year and will per- form an FMEA in one area. The hospital has rated sentinel events for severity, probability, and detectability on the following scale: very high, high, moderate, low, very low. Calculate the risk priority number for each type of event. Which sentinel event should be the focus of the hospital’s FMEA effort?

    Event

    Severity

    Probability

    Detectability

    Hospital-acquired High Moderate Infection

    Medication Error Moderate High

    Patient Fall Low High

    Pressure Ulcer Low High

    Treatment Delay Low High

    High

    Moderate

    Very high

    Very high

    High

    References

    Apkon M, Leonard J, Probst L, DeLizio L, and Vitale R, 2004, Design of a Safer Approach to Intravenous Drug Infusions: Failure Mode Effects Analysis, Quality and Safety in Health Care 13 (4): 265–271.

    Camp RC and DeToro IJ, 1999, Benchmarking, in Juran’s Quality Handbook, 5th ed., edited by JM Juran and AB Godfrey, McGraw-Hill, New York, NY, 12.1–12.20.

    Cleary P and Edgman-Levitan S, 1997, Health Care Quality: Incorporating Consumer Perspectives, JAMA 278 (19): 1608–1612.

    Cohen H, 2007, Protecting Patients from Harm: Reduce the Risk of High-Alert Drugs, Nursing (September 2007): 49–54.

    Coronary Drug Project Research Group, 1980, Influence of Adherence to Treatment and Response of Cholesterol on Mortality in the Coronary Drug Project, New England Journal of Medicine 303 (18): 1038–1041.

    Curran TA and Ladd A, 2000, SAP R/3 Business Blueprint, Prentice Hall PTR, Upper Saddle River, NJ.

    DeToro IJ, 1995, Business Process Benchmarking Workshop, The Quality Network Inc., Rochester, NY.

    Duwe B, Fuchs B, and Hansen-Flaschen, J, 2005, Failure Mode and Effects Analysis Application to Critical Care Medicine, Critical Care Clinics 21 (1): 21–30.

    406

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