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MHA FPX 5017 Assessment 1 Nursing Home Data Analysis

MHA FPX 5017 Assessment 1 Nursing Home Data Analysis

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Capella university

MHA-FPX 5017 Data Analysis for Health Care Decisions

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Introduction

The administration of a local nursing home is conducting an evaluation of the current department manager and the facility’s performance spanning the last 70 months. The assessment entails a comprehensive review of utilization rates, satisfaction levels, and readmission rates utilizing descriptive statistical tables and histograms. The primary objectives of the nursing administration include achieving higher utilization rates, greater satisfaction among residents, and reducing readmission rates. Additionally, insights gleaned from the data analysis will inform decisions regarding the retention of the current department manager.

Data and Statistics

To facilitate a thorough performance evaluation, three descriptive statistics tables have been devised, delineating utilization, satisfaction, and readmission rates over the past 70 months. These tables highlight measures of central tendency (mean, median, and mode) as well as dispersion (variance, range, and standard deviation). The utilization of descriptive statistics aims to optimize information dissemination while minimizing data loss (Frey, 2018).

In addition to tabular representation, histograms have been constructed to visually depict utilization, satisfaction, and readmission rates within the nursing home. These graphical representations illustrate the frequency distribution of data points on the y-axis against the respective data intervals on the x-axis. The overarching objective of these histograms is to offer insights into the frequency of utilization, the spectrum of patient satisfaction, and the occurrence of patient readmissions throughout the 70-month period.

Results

The subsequent sections delineate the findings from each descriptive statistical table and histogram pertaining to utilization rates, satisfaction levels, and readmission rates.

Utilization Rates

Nursing homes in the United States have evolved from predominantly long-stay facilities to establishments catering to a substantial number of short-stay patients (Applebaum, Mehdizadeh, & Berish, 2020). The current aim is to decrease utilization rates, thereby enhancing reimbursement rates. Analysis indicates an average length of stay per month of 68 days. In comparison, the U.S. average length of stay was considerably higher in 2014 and 2015, at 178 and 180 days, respectively (Statista Research Department, 2016). Notably, the range of length of stay spans 96.05 days, signifying significant variability among patients. Over the 70-month period, the majority of patients had a length of stay ranging from 61 to 80 days, with only a limited duration where stays were 40 days or less. Reducing the length of stay holds implications for nursing home practices and quality monitoring (Applebaum et al., 2020).

Patient Satisfaction Scores

Enhancing the quality of resident care remains a pertinent objective within nursing home administration (Plaku-Alakbarova et al., 2018). Analysis reveals that, on average, 49% of patients expressed satisfaction with their care. However, satisfaction levels were consistently below 40% for 31 months, with only 14 months recording 100% satisfaction. There exists a projected correlation between employee job satisfaction and patient satisfaction, with implications for resident outcomes (Plaku-Alakbarova et al., 2018). Addressing employee satisfaction and re-evaluating policies may yield improvements in patient satisfaction rates.

Readmission Rates

Mitigating preventable readmissions is crucial due to associated adverse events and higher healthcare costs (Mendu et al., 2018). Analysis of readmission rates within 30 days of discharge indicates that 11% of patients were readmitted to the nursing home. The range of readmission rates extends from 1% to 21%, with a significant proportion of readmissions occurring over a 25-month period at 15%.

Recommendation

The primary objectives of the nursing home administration encompass achieving higher utilization rates, enhancing patient satisfaction, and reducing readmission rates.

References

Applebaum, R., Mehdizadeh, S., & Berish, D. (2020). It Is Not Your Parents’ Long-Term Services System: Nursing Homes in a Changing World. Journal of Applied Gerontology, 39(8), 898–901. https://doi.org/10.1177/0733464818818050

MHA FPX 5017 Assessment 1 Nursing Home Data Analysis

Frey, B. (2018). The SAGE encyclopedia of educational research, measurement, and evaluation (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781506326139

Mendu, M. L., Michaelidis, C. I., Chu, M. C., Sahota, J., Hauser, L., Fay, E., Smith, A., Huether, M. A., Dobija, J., Yurkofsky, M., Pu, C. T., & Britton, K. (2018). Implementation of a skilled nursing facility readmission review process. BMJ open quality, 7(3), e000245. https://doi.org/10.1136/bmjoq-2017-000245

Plaku-Alakbarova, B., Punnett, L., Gore, R. J., & Procare Research Team (2018). Nursing Home Employee and Resident Satisfaction and Resident Care Outcomes. Safety and health at work, 9(4), 408–415. https://doi.org/10.1016/j.shaw.2017.12.002

MHA FPX 5017 Assessment 1 Nursing Home Data Analysis

Statista Research Department (2016). Nursing home average length of stay in United States in 2014 and 2015, by ownership. Retrieved from https://www.statista.com/statistics/323219/average-length-of-stay-in-us-nursing-homes-by-ownership/

The post MHA FPX 5017 Assessment 1 Nursing Home Data Analysis appeared first on NURSFPX.com.

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