Change Strategy and Implementation
Scenario
Consider the care settings presented in the Vila Health: Using Evidence to Drive Improvement (SEE BELOW).
For the setting that you choose you will need to have a data set that depicts sub-optimal outcomes related to a clinical issue. This data could be from existing sources in the course (Vila Health: Using Evidence to Drive Improvement).
After you have selected an appropriate data set, use your understanding of the data to create at least one realistic goal (though you may create more) that will be driven by a change strategy appropriate for the environment and goal.
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Order Paper NowPotential topics for this assessment could be:
- Consider ways to help minimize the rate of secondary infections related to the condition, disease, or disorder that you focused on for your Concept Map assessment. As a starting point you could ask yourself, ”What could be changed to facilitate safety and minimize risks of infection?”
- Consider how to help a patient experiencing traumatic stress or anxiety over hospitalization. As a starting point you could ask yourself, ”How could the care environment be changed to enhance coping?”
Once you determine the change you would like to make, consider the following:
- What data will you use to justify the change?
- How can the team achieve this change with a reasonable cost?
- What are the effects on the workplace?
- What other implementation considerations do you need to consider to ensure that the change strategy is successful?
- How does your change strategy address all aspects of the Quadruple Aim, especially the well-being of health care professionals?
- Once the change strategy is implemented, how would you evaluate the efficiency and effectiveness of the care system if the desired outcomes are met?
Instructions
Your assessment submission should include a data table that illustrates the current and desired states of the clinical issue you are attempting to improve through your application of change strategies. Additionally, you will need to explain the rationale for your decisions around your chosen change strategies, as well as how the change strategies will be successfully implemented. The bullet points below correspond to the grading criteria in the scoring guide. Be sure that your change strategy addresses all of them. You may also want to read the Change Strategy and Implementation scoring guide and Guiding Questions: Change Strategy and Implementation to better understand how each grading criterion will be assessed.
- Develop a data table that accurately reflects the current and desired states of one or more clinical outcomes.
- Propose change strategies that will help to achieve the desired state of one or more clinical outcomes.
- Justify the specific change strategies used to achieve desired outcomes.
- Explain how change strategies will lead to quality improvement with regard to safety and equitable care.
- Explain how change strategies will utilize interprofessional considerations to ensure successful implementation.
- Communicate the change plan in a way that makes the data and rationale easily understood and compelling.
Vila Health: Using Evidence to Drive Improvement
To work in health care is to be constantly faced with decisions, both immediate and long–term in nature. In a world of limited resources, continuous improvement is necessary to ensure efficiency and quality patient care. To have any real–world impact, these decisions and the process of improvement must be guided by rigorous analysis of hard data.
In this simulation, you will look at 2 datasets relevant to the operations of St. Anthony Medical Center, a large hospital in Minneapolis, and determine what guidance they offer for improvement initiatives.
RN Turnover
This dataset tracks turnover among RN staff in St. Anthony Medical Center’s various departments over the past year.
Q1Q2Q3Q4Year Total (TABLE DATA)
Behavioral Health
34% Q1
27% Q2
25% Q3
29% Q4
29% TOTAL
Critical Care
12% Q1
16% Q2
15% Q3
20% Q4
16% TOTAL
Emergency
23% Q1
19% Q2
19% Q3
13% Q4
19% TOTAL
Med/Surg
13%
19%
22%
23%
19%
OBGYN
7%
7%
12%
14%
10%
Oncology
21%
24%
15%
22%
21%
Pediatrics
11%
7%
6%
10%
9%
Step Down
15%
13%
22%
19%
17%
Surgical Services
17%
9%
24%
16%
17%
Telemetry
18%
17%
22%
20%
19%
MEDICATION ERRORS
This dataset tracks the types of medication errors made by staff during the past year.
View Data
Q1Q2Q3Q4 (TABLE DATA)
Wrong Drug
Q1 14
Q2 10
Q3 19
Q4 7
Forgot to Discontinue
Q1 0
Q2 3
Q3 2
Q4 0
Contraindications
Q1 0
Q2 1
Q3 4
Q4 1
Wrong Dose (over)
22
17
23
14
Wrong Dose (under)
8
7
8
7
Interactions
37
21
34
19
Forget to Order
23
17
26
21
Transcription Errors
61
66
78
73
Suggested Resources
The resources provided here are optional. You may use other resources of your choice to prepare for this assessment; however, you will need to ensure that they are appropriate, credible, and valid.
Assessment
- Komenan, K., Elidjé, E. J., Ildevert, G. P., Yao, K. I., Kanga, K., Kouamé, K. A., . . . Kanga, J. (2013). Multifocal buruli ulcer associated with secondary infection in HIV positive patient. Case Reports in Medicine, 2013, 1–4. Retrieved from https://www.hindawi.com/journals/crim/2013/348628/
Biopsychosocial
- Scaramuzzo, L. A., Gordils-Perez, J., & Cullen, P. M., (2014). Getting patients active: Using national data to drive practice. Clinical Journal of Oncology Nursing, 18, 41–43.
Change
- Eads, V., & Maruzzella, G. (2016). The clinical nurse as an agent of change. Medsurg Nursing, 25(3), 173–175.
- Heinig, M. J. (2010). Using data to drive and shape change. Journal of Human Lactation, 26(4), 359–361.
- Nundy, S., Mishra, A., Hogan, P., Lee, S. M., Solomon, M. C., & Peek, M. E. (2014). How do mobile phone diabetes programs drive behavior change? Evidence from a mixed methods observational cohort study. The Diabetes Educator, 40(6), 806–819.
Evidence and Goal Setting
- Ahrens, S., & Johnson, C. S. (2013). Finding the way to evidence-based practice. Nursing Management, 44(5), 15–19.
- Taylor, M. V., Priefer, B. A., & Alt-White, A. C. (2016). Evidence-based practice: Embracing integration. Nursing Outlook, 64(6), 575–582.
- View the simulation Vila Health: Using Evidence to Drive Improvement | Transcript.
Pathophysiology
- Li, Y., Lu, Z., Zhang, X., Yu, H., Kirkwood, K. L., Lopes-Virella, M. F., & Huang, Y. (2015). Metabolic syndrome exacerbates inflammation and bone loss in periodontitis. Journal of Dental Research, 94(2), 362–370.
- Mocan Hognogi, L. D., & Simiti, L. V. (2016). The cardiovascular impact of visfatin – An inflammation predictor biomarker in metabolic syndrome. Clujul Medical, 89(3), 322–326.
- pharmacology
- Sharmila, V., & Babu, T. (2015). Oral contraceptive pills induced hemichorea in an adolescent female with polycystic ovarian disease. Indian Journal of Pharmacology, 47(2), 232–233.
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