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Regardless of political affiliation, every citizen has a stake in

 

Agenda Comparison Grids

Regardless of political affiliation, every citizen has a stake in healthcare policy decisions. Hence, it is little wonder why healthcare items become such high-profile components of presidential agendas. It is also little wonder why they become such hotly debated agenda items.

In Part 1 of this module’s Assignment, you were asked to begin work on an Agenda Comparison Grid to compare the impact of the current/sitting U.S. president and the two previous presidents’ agendas on the healthcare item you selected for study. In this Discussion, you will share your first draft with your colleagues to receive feedback to be applied to your final version.

To Prepare:

  • Review the Resources and reflect on the importance of agenda setting.
  • Consider how federal agendas promote healthcare issues and how these healthcare issues become agenda priorities.
  • Review Part 1 of the Module 1 Assignment and complete the requirements for this Discussion.
BY DAY 3 OF WEEK 1

Post a draft of the Agenda Comparison Grid you completed for Part 1 of the Agenda Comparison Grid and Fact Sheets or Talking Points Brief Assignment.

BY DAY 6 OF WEEK 1

Respond to at least two of your colleagues on two different days and provide a critique on their comparison grids. Suggest at least one feature of your colleagues’ comparison grids that you would revise and explain why. Be specific and provide examples.

Click on the Reply button below to reveal the textbox for entering your message. Then click on the Submit button to post your message.

Respond to at least two of your colleagues* on two different days and provide a critique on their comparison grids. Suggest at least one feature of your colleagues’ comparison grids that you would revise and explain why. Be specific and provide examples.

*Note: Throughout this program, your fellow students are referred to as colleagues.

I also have a textbook that goes with this assig nment. It is on Bookshelf (the website). The  

I’m going to send you my classmate’s post so you can respond base in what he is saying. doesn’t have to be too long. I’ll need three references also. Thank You in advance!!

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Robert Majors

RE: Discussion – Week 1

COLLAPSE

In the healthcare industry, a prominent concern for all healthcare organizations is to limit or decrease the rate of patients being readmitted to the hospital within a short-term timeframe, who is experiencing identical signs and symptoms of a medical condition from the previous inpatient admission. However, this term in a psychiatric setting is defined as the revolving door syndrome. The revolving door consists of persistently ill mental health patients with a diagnosis of schizophrenia or bipolar or a personality disorder with an underlining mood ailment (depression, mood swings, etc.). The recurrent hospitalizations for chronically mental health patients have significantly increased over the last five decades. A study by Jeppesen, Christensen, and Vestergaard (2016), showed a 20% increased readmission rate and a substantial decrease of 76% annual days spent by chronic mentally ill schizophrenia patients in acute hospitalization from the year 1970 to 2012. For my scenario, what interventions would momentously diminish the number of psychiatric readmissions to improve the reimbursement proportions for healthcare organizations.

To begin, my investigation will take place at a single local hospital with a mental health ward to search for readmission rates. In the United States, the 30-day time period is the criteria for a patient to be considered to be readmission from an initial discharge with an unchanged diagnosis, and the readmission rate average is approximately 18 percent to 25 percent for all healthcare organizations. (Becker, Boaz, Andel, & Hafner, 2016). To collect the readmission data, the majority of hospitals have transferred from paper to electronic health records (EHRs). An electronic health record is a database filled with personal health information (patients), which provides researchers with easier access to expedite essential data (Milstead & Short, 2018). This database permits me to search for patient’s length of stay (LOS), psychiatric diagnoses, treatment interventions, and planning, prescribed medications, and discharge summary (patient released to the community or transferred to another acute setting for additional treatment). Overall, EHRs allows researcher to process the data to determine the ultimate causes for the increased readmissions. The results of my research will bring an enlightened awareness of evidence demonstrating that multiple factors trigger the increase higher readmission rate.

In eyesight, the clinical experience of a nursing leader will utilize the collection of data into the development of knowledge. In my scenario, there are two separate measures that likely cause for the increased readmission rates; decisions made in the clinical setting and the failure of the client to mentally prosper into society after discharge. In the clinical setting, the results of earlier than expected discharge, lack of family teaching, decline to attend schedule therapies, patients do not have enough money to buy and retrieve medical prescription after discharge. (Jewell, 2018). On the other end of the spectrum, patients disregard to use effective coping skills to reduce immediate stressors, noncompliant with medication regiment, and failure to follow-up with outpatient mental health appointments (Jewell, 2018). To conclude, the understanding of exercising knowledge and experience with the collecting of research data will implement interventions to likely change the individual outcomes in a psychiatric setting to reduce the number of readmissions.

References

Becker, M. A., Boaz, T. L., Andel, R., & Hafner, S. (2016). Risk of early rehospitalization for non-behavioral health conditions among adult Medicaid beneficiaries with severe mental illness or substance use disorders. The Journal of Behavioral Health Services & Research, 44(1), 113-121. http://dx.doi.org/10.1007/s11414-016-9516-9.

Jeppesen, R. M., Christensen, T., & Vestergaard, C. H. (2016). Changes in the utilization of psychiatric hospital facilities in Denmark by patients diagnosed with schizophrenia from 1970 through 2012. Acta Psychiatrica Scandinavica, 133, 419-425. http://dx.doi.org/10.1111/acps.12549

Jewell, K. E. (2017). Strategies for reducing readmissions to the inpatient psychiatric setting. Retrieved November 25, 2019, from https://www.lsqin.org/wp-content/uploads/2017/04/Q…

Milstead, J. A., & Short, N. M. (2019). Health policy and politics: A nurse’s guide (6th ed.). Burlington, MA: Jones & Bartlett Learning

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