NURS 3110 Week 3 Comparing Organizations Using Benchmark Data

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In order to ensure the delivery of high-quality care, it is crucial to assess the quality of care provided. Clinical quality measures (CQMs) serve this purpose by tracking various aspects of care, including structure, process, and outcomes, using data from electronic health record systems (EHRs) (Cholan et al., 2019). These measures help identify gaps in care and provide evidence-based guidelines for improvement. Meeting benchmarks within CQMs often influences reimbursement for healthcare facilities (Cholan et al., 2019). This paper aims to explore the impact of CQMs by comparing the benchmarks of two organizations, while also examining factors contributing to any differences.

Description of Two Organizations

The organizations selected for comparison are Asante Three Rivers Medical Center (TRMC), where I work, and Asante Rogue Regional Medical Center (RRMC), another hospital within the same healthcare system located approximately 35 miles south. Although not direct financial competitors, there is a sense of competition among employees, as both hospitals publicly post outcomes from CQM benchmarks and satisfaction surveys, motivating staff to improve their scores (Asante, n.d.).

TRMC is a 125-bed acute-care hospital and level three trauma center situated in Grants Pass, Oregon. It has been recognized as a ‘Pathway to Excellence’ hospital by the American Nurses Credentialing Center (ANCC) multiple times, demonstrating its commitment to excellence in nursing care. TRMC is also the first hospital in Oregon to be designated as ‘Baby Friendly’ by the World Health Organization and UNICEF (Asante, n.d.).

NURS 3110 Week 3 Comparing Organizations Using Benchmark Data

RRMC, located in Medford, Oregon, is an urban medical center with 378 beds. It serves as a regional referral center and level 2 trauma center, with specialized units such as a neonatal intensive care unit and hospital-based sleep center. RRMC has consistently been recognized as one of Watson Health’s 15 Top Health Systems in the nation, along with the Mayo Clinic (Asante, n.d.).

Comparison of Two Organizations

The first benchmark I will compare relates to timely emergency department care, specifically the percentage of patients who leave the emergency department before being seen. Nationally and in Oregon, the average for this benchmark is 2%. RRMC performs below these averages, with a rate of 1%, indicating efficient care. In contrast, TRMC’s rate is significantly higher at 5%, suggesting a potential lack of resources or staff to provide timely care in their emergency department (Medicare, n.d.).

The second benchmark I will examine pertains to unplanned hospital visits, focusing on the rate of readmission after hip/knee replacement. The national average for this measure is 4%. TRMC performs better than the national rate, while RRMC aligns with the national average. Both facilities meet or exceed the goal, suggesting effective prevention of complications, particularly by TRMC (Medicare, n.d.).

Analysis of Factors Contributing to Performance Measures

One possible contributing factor to TRMC’s lower percentage in timely emergency care is nurse staffing. Adequate nurse staffing is crucial for delivering quality care, as it enables efficient assessments and interventions to prevent adverse events and promote positive patient outcomes (Clarke & Donaldson, n.d.). Waiting time, which affects the percentage of patients leaving before treatment, has been found to correlate with RN and physician staffing levels (Anderson, 2016).

Another contributing factor to the difference in the rate of readmission after hip/knee replacement could be the quality of discharge instruction provided by nurses. Nurses play a critical role in developing and delivering discharge plans to patients, and unmet discharge needs have been associated with higher readmission rates and poorer outcomes (Pieper, 2006).

Data Standardization to Improve Quality Comparison Measures

Standardization of data is crucial for quality improvement, as emphasized by the Centers for Medicare & Medicaid Services (CMS) (CMS, n.d.). By eliminating randomness and uncertainty in free-text data entry and adopting a systematic approach to recording data, more structured analysis and effective processes can be achieved. Standardized data reduces errors and enhances positive outcomes, ultimately improving quality measures (CMS, n.d.).

NURS 3110 Week 3 Comparing Organizations Using Benchmark Data Conclusion

Utilizing tools like the Hospital Compare website can be instrumental in identifying and comparing areas of concern and gaps in care through the use of CQMs. CQMs and data standardization are vital in accurately recording, analyzing, identifying, and improving issues in patient care. Nurses play a significant role in each of these steps, influencing measure outcomes and the overall quality of care.


Anderson, D., Pimentel, L., Golden, B., Wasil, E., & Hirshon, J. M. (2016). Drivers of ED efficiency: a statistical and cluster analysis of volume, staffing, and operations. American Journal of Emergency Medicine, 34(2), 155–161.

Asante. (n.d). Retrieved from

Center for Medicare & Medicaid Services (CMS). (n.d.) Quality Measure and Quality Improvement. Retrieved from:

Cholan, R. A., Weiskopf, N. G., Rhoton, D. L., Colin, N. V., Ross, R. L., Marzullo, M. N., … Dorr, D. A. (2018). Specifications of Clinical Quality Measures and Value Set Vocabularies Shift Over Time: A Study of Change through Implementation Differences. AMIA Annual Symposium proceedings. AMIA Symposium, 2017, 575–584. Retrieved from

Clarke S., Donaldson N. (n.d.). Nurse Staffing and Patient Care Quality and Safety. In: Hughes RG, editor. Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Apr. Chapter 25. Available from:

Medicare. (n.d). Hospital Compare. Retrieved from

Pieper, B., Sieggreen, M., Freeland, B., Kulwicki, P., Frattaroli, M., Sidor, D., … Garretson, B. (2006). Discharge information needs of patients after surgery. Journal of Wound Ostomy and Continence Nursing, 33(3), 281–289. Retrieved from