Student Name
Capella University
NURS-FPX 6414 Advancing Health Care Through Data Mining
Prof. Name:
Date
Greetings, everyone. My name is _______, and today’s presentation will address patient satisfaction levels as a quality outcome indicator in the Emergency Department (ED) of Providence Medical Center. Throughout the presentation, we will cover objectives as follows:
Patient satisfaction levels are described as the degree to which a patient is comfortable and satisfied with the healthcare services provided in a healthcare setting (Manzoor et al., 2019). Measuring these levels is essential to gain valuable insights into the quality of care and the overall patient experiences. A high percentage of these levels indicates that the care delivered is effective and compassionate, leading to positive patient health and quality-of-life outcomes. Low ranges of such levels provide the organization with insights about areas of improvement so that the care can be optimized according to patients’ needs and satisfaction levels, ensuring the well-being of the patients.
There are several ways to measure patient satisfaction levels in an organization. Surveys and questionnaires are the most commonly used methods, which allow patients to rate their experiences and mention the feedback for future improvements. Other methods include online portals, social media reviews, and telephonic feedback. Indirect methods of analyzing patient satisfaction are adherence to appointments and patient retention, which indicates patients’ experiences and levels of contentment with healthcare services (Friedel et al., 2023).
Several benchmarks are associated with patient satisfaction levels in a hospital’s ED, which can help stakeholders understand the organizational performance against the standards. Regularly monitoring the organizational data against these standards is essential to make necessary improvements and enhance healthcare quality. Quantitative benchmarks include;
The categories that would be used to create a spreadsheet examining baseline data and the data trends related to patient satisfaction include;
Time Period (2023) | Patient Satisfaction (%) | Waiting Times & Length of Stay | Infection Rate (%) | FTE Nurses | Revenue | QI Initiatives |
Jan-Mar (Baseline) | 80% | 20 mins & 3 hours | 0.5% | 35 | $130,000 | 2 |
Apr-June | 77% | 22 mins & 4 hours 30 minutes | 0.5% | 40 | $128,000 | 3 |
July-Sep | 81% | 21mins & 3 hours 20 minutes | 0.3% | 42 | $130,000 | 2 |
Oct-Dec | To be calculated at the end of the year | To be calculated at the end of the year | To be calculated at the end of the year | To be calculated at the end of the year | To be calculated at the end of the year | To be calculated at the end of the year |
In the context of the spreadsheet presented earlier, I collected the data from the ED of Providence Medical Center to assess the ongoing development and quality of care in the emergency department. Patient satisfaction data was collected through a standardized ED CAHPS survey. This standardized survey has provided insights into the quality of care and patients’ experiences within the emergency department. Since it is a standard form developed by CMS, it is comprehensive and has components essential to be analyzed. The hospital’s information system automatically collects operation metrics of waiting times, LOS, and clinical outcomes about infection rates, providing real-time and authentic data.
For collecting data about FTE nursing staff, I collaborate with the nursing director of the medical center. She provided a record of nurses hired, retained, and left the organization in 2023. The finance department was integrated to collect data specific about the revenues generated mainly by the ED in the organization. Involving field-specific experts in the data collection provides authentic data and helps the researcher understand and interpret the collected information. The hospital quality management team reported successful QI initiatives and their outcomes for improving patient care. They also provided information about prospective projects.
Coming to the end of the presentation, it is essential to interpret the data and data trends and evaluate them based on benchmarks to effectively utilize the data for improving outcomes in the emergency department at Providence Medical Center. The categories chosen to determine patient satisfaction levels in the ED are based on the qualitative and quantitative indicators within the healthcare settings. Clinical outcomes defining patient’s health conditions, operational indicators showing the workflows and functions of the department, and staffing are considered essential indicators to analyze patients’ experiences with healthcare services, enabling organizations to plan future actions (Wang et al., 2023). Similarly, financial outputs and quality improvement are other parameters indicating the necessary need for organizational improvement. Thus, they are considered essential and have been chosen for this evaluation.
The data is divided into periods of three months, considering the first three months as the baseline for other months of the year. Initially, patient satisfaction was 80%, indicating a relatively higher rate. In operational terms, waiting time and LOS was 20 mins and 3 hours, respectively. This data slightly differs from the benchmark, where the arrival-to-triage time is 10-15 minutes; however, LOS follows the benchmark. Thus advocating a need to fulfill the benchmark for wait time. Other indicators show baseline data. The patient satisfaction level decreased in the next period, and the waiting time and LOS increased.
They are again indicating the variation from the benchmarks. However, the organization has increased its number of nurses to ensure quality care is provided without delays and has initiated three QI projects. The revenue is slightly lower than the baseline, demonstrating low levels of patient satisfaction and patient retention. The other half of the year has started, and the service line has received a higher patient satisfaction score concerning both the baseline and the previous period. This can be interpreted as several improvements that would have been made.
Nonetheless, improvement need is identified in operational outcomes. As per the clinical outcomes, the infection rate has also reduced by 0.3%, and the organization is back at the baseline revenue of $130,000. The last quarter is yet to be calculated, which will be an evaluation for the organization to sustain or improve practices in the upcoming year. The data can be utilized to improve outcomes by the following measures:
These actions would improve patient satisfaction levels and impact the organization’s financial viability, reducing the economic burden on the Providence Medical Center.
In conclusion, patient satisfaction levels, especially in the emergency department (ED), are crucial to improving outcomes, quality of care, and financial viability of the organization. Thus, we interpreted data from Providence Medical Center, highlighting some variations from the benchmarks. To address these differences and improve outcomes, I presented recommendations to improve satisfaction, optimize operations, reduce infection rates, and enhance workflow stability. Thank you for your patience while listening to my presentation.
CMS. (2023). Emergency Department CAHPS (ED CAHPS). Centers for Medicare & Medicaid Services.https://www.cms.gov/data-research/research/consumer-assessment-healthcare-providers-systems/emergency-department-cahps
Friedel, A. L., Siegel, S., Kirstein, C. F., Gerigk, M., Bingel, U., Diehl, A., Steidle, O., Haupeltshofer, S., Andermahr, B., Chmielewski, W., & Kreitschmann-Andermahr, I. (2023). Measuring patient experience and patient satisfaction—how are we doing it and why does it matter? A comparison of European and U.S American approaches. Healthcare, 11(6), 797. https://doi.org/10.3390/healthcare11060797
Kulińska, J., Rypicz, Ł., & Zatońska, K. (2022). The impact of effective communication on perceptions of patient safety—A prospective study in selected Polish hospitals. International Journal of Environmental Research and Public Health, 19(15), 9174. https://doi.org/10.3390/ijerph19159174
Manzoor, F., Wei, L., Hussain, A., Asif, M., & Shah, S. I. A. (2019). Patient satisfaction with health care services; an application of physician’s behavior as a moderator. International Journal of Environmental Research and Public Health, 16(18), 3318. https://doi.org/10.3390/ijerph16183318
Otto, R., Blaschke, S., Schirrmeister, W., Drynda, S., Walcher, F., & Greiner, F. (2022). Length of stay as a quality indicator in emergency departments: Analysis of determinants in the German Emergency Department Data Registry (AKTIN registry). Internal and Emergency Medicine, 17(4), 1199–1209. https://doi.org/10.1007/s11739-021-02919-1
Wang, Y., Liu, C., & Wang, P. (2023). Patient satisfaction impact indicators from a psychosocial perspective. Frontiers in Public Health, 11. https://www.frontiersin.org/articles/10.3389/fpubh.2023.1103819
Yancey, C. C., & O’Rourke, M. C. (2022). Emergency department triage. In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih.gov/books/NBK557583/
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