BHA FPX4020 Assessment 3 Data Collection and Analysis

BHA FPX4020 Assessment 3 Data Collection and Analysis

BHA FPX4020 Assessment 3 Data Collection and Analysis are critical in healthcare, especially when tackling complicated issues like cancer readmission rates (Wang & Zhu, 2022). Collecting and analyzing data may give healthcare practitioners significant insights into the circumstances causing these readmissions. They can help recognize trends, risk factors, and treatment gaps that may contribute to high readmission rates. This enables hospitals to undertake targeted treatments and create personalized care plans to prevent readmissions. Furthermore, hospitals must report readmission rates for throat cancer to evaluate the quality of treatment they give. It is a critical performance indicator that allows healthcare organizations to assess their efficacy and find development opportunities.

Rational for the Problems Analysis Model

The issue of hospitals experiencing a high rate of readmissions is a noteworthy concern that requires careful examination and scrutiny, particularly in patients suffering from throat cancer (Yang et al., 2022). Patients being readmitted shortly after their initial treatment indicates a failure within the healthcare system to deliver adequate and all-encompassing care. According to research, the 30-day readmission rate for patients after head and neck cancer surgery was reported to be 16% (Chen et al., 2018). Hospitals can endeavor to enhance patient care and alleviate resource burdens by directing their attention toward comprehending and mitigating the factors that contribute to elevated readmission rates.

Analysis Model

The Plan-Do-Study-Act (PDSA) cycle is a widely recognized analysis model that offers a systematic and iterative approach to problem-solving and quality improvement in healthcare. The model provides a systematic method for healthcare professionals to define the problem, develop and implement plausible interventions, evaluate their efficacy, and modify their strategies based on the outcomes (Knudsen et al., 2019). The PDSA cycle is an appropriate framework for analyzing and resolving the complex problem of high hospital readmission rates, as it emphasizes the significance of continuous education and improvement (Knudsen et al., 2019).

Rationale with an Authoritative Source

According to the Agency for Healthcare Research and Quality (AHRQ), reducing hospital readmissions is essential to enhancing patient care and healthcare quality (AHRQ, 2019). The AHRQ stresses the importance of understanding and addressing readmission rates. They emphasize that not only do high readmission rates affect patient outcomes, but also result in increased healthcare costs and resource consumption. In addition, AHRQ encourages the use of quality improvement frameworks, such as the PDSA cycle, to systematically analyze and enhance care processes (AHRQ, 2021).

Analysis of Data Relative to Internal and External Benchmarks

Benchmarks are crucial tools within healthcare organizations. They are utilized for evaluating performance and facilitating enhancements in the provision of patient care. Healthcare performance metrics assist in measuring the effectiveness of healthcare providers and pinpointing their strengths and weaknesses. Ensuring patient readmission rates are minimized is particularly crucial in the context of cancer care, as these rates serve as a significant metric for assessing the caliber of healthcare provided.

Internal and External Benchmarks

In healthcare, two distinct categories of benchmarks are utilized: internal and external (Willmington et al., 2022). Examples of an internal benchmarking approach involve the evaluation of patient satisfaction ratings across distinct locations within a given healthcare facility. Similarly, other examples can include length of stay, readmission rates, and patient outcomes across different departments or units within the same healthcare facility. This can provide information on matters that require attention and facilitate the enhancement of procedures or methodologies within departments (Reponen et al., 2021).

BHA FPX4020 Assessment 3 Data Collection and Analysis

One potential example of an external benchmark involves the evaluation of metrics, such as wait times, compared to those of other hospitals or clinics situated in the same or distinct geographical regions. Similarly, another example can be the 30-day unplanned readmissions for cancer patients. These practices can facilitate knowledge sharing among healthcare organizations, improving processes.

Rationale for Benchmark

The Centers for Medicare and Medicaid Services in the United States has put forth the 30-Day Unplanned Readmissions for Cancer Patients Measure (PCH-36) as a metric for public display to evaluate hospital performance (CMS, 2023). Healthcare facilities can evaluate their operational effectiveness by benchmarking their performance against national standards, pinpointing specific domains requiring enhancement. This performance metric not only establishes a system of responsibility for hospitals regarding the quality of healthcare they dispense but also encourages the implementation of different strategies and measures to reduce the frequency of patients requiring readmission (CMS, 2023).

Evidence-Based Recommendations

By implementing evidence-based recommendations, healthcare organizations can improve patient satisfaction rates and reduce the chances of readmission.

Enhancing Patient Education and Engagement

Hospital staff can ensure that patients receive comprehensive and easy-to-understand instructions upon discharge. Clear guidance on medication management, follow-up appointments, and self-care activities can empower patients to take responsibility for their health and reduce the likelihood of readmissions (Centers for Medicare and Medicaid Services, 2022)

Strengthening Care Transitions

Seamless transitions between healthcare settings are crucial for preventing readmissions. Implementing care coordination programs, such as regular follow-up calls, interdisciplinary meetings, and electronic health record sharing, can enhance communication among healthcare providers and ensure continuity of care (AHRQ, 2019).

Implementing Post-Discharge Support

By establishing robust transitional care programs that provide individualized support for patients after discharge. These programs may include home visits, telemonitoring, and caregiver education to address potential gaps in post-hospital care and facilitate early intervention if necessary (Yang et al., 2022). BHA FPX4020 Assessment 3 Data Collection and Analysis

Cost Benefit Analysis

Cost-benefit analysis can be a crucial factor in enhancing outcomes and optimizing healthcare delivery for cancer, which is one of the primary causes of mortality worldwide, as shown in the graphic illustration below. Cost-benefit analysis enables decision-makers to make informed choices regarding resource allocation, intervention prioritization, and the overall value of implementing evidence-based practices by evaluating the costs and benefits associated with a particular intervention (Ananthapavan et al., 2021).

BHA FPX4020 Assessment 3 Data Collection and Analysis

During the fiscal year of 2022, Medicare directed a comprehensive evaluation of readmission rates in a total of 3,046 hospitals. Of the hospitals under consideration, it was found that around 74.6% (2,273 hospitals) were subject to penalties because of their readmission rates exceeded the 30-day risk-standardized threshold (Statista, 2023). As a result, these healthcare facilities encountered consequences due to their readmission rates exceeding the anticipated levels. In contrast, a notable proportion of hospitals, precisely 25.4% (773 hospitals), avoided incurring penalties, which suggests that their readmission rates were within the acceptable range (Statista, 2023).

Developing patient education and engagement, strengthening care transitions, and implementing post-discharge support interventions can potentially improve cancer care while generating cost benefits (Chan et al., 2021). Get BHA FPX4020 Assessment 3 Data Collection and Analysis

The table below presents a cost-benefit analysis for these interventions regarding implementation costs, ongoing costs, and potential cost savings for readmission of patients with throat cancer.


Implementation Costs

Ongoing Costs per Year

Potential Cost Savings

Enhancing Patient Education and Engagement




Strengthening Care Transitions




Implementing Post-Discharge Support






The acquisition and examination of data is essential in tackling the issue of elevated rates of readmission in healthcare, specifically within the realm of cancer treatment. Through the process of data collection and analysis, healthcare professionals can discern patterns, potential hazards, and areas of treatment deficiency that may lead to instances of readmission. This data facilitates the implementation of focused interventions and customized care strategies by hospitals to avert readmissions.


AHRQ. (2021). Primary care practice facilitator training series job aid: Model for improvement and PDSA cycles using the model for improvement. www.AHRQ.giv.

AHRQ. (2019, September 7). Readmissions and adverse events after discharge.

Ananthapavan, J., Moodie, M., Milat, A., Veerman, L., Whittaker, E., & Carter, R. (2021). A cost–benefit analysis framework for preventive health interventions to aid decision-making in Australian governments. Health Research Policy and Systems, 19(1).

Centers for Medicare and Medicaid Services. (2022). Hospital readmissions reduction program (HRRP).

Chan, R. J., Crawford-Williams, F., Crichton, M., Joseph, R., Hart, N. H., Milley, K., Druce, P., Zhang, J., Jefford, M., Lisy, K., Emery, J., & Nekhlyudov, L. (2021). Effectiveness and implementation of models of cancer survivorship care: An overview of systematic reviews. Journal of Cancer Survivorship.

Chen, M. M., Orosco, R. K., Harris, J. P., Porter, J. B., Rosenthal, E. L., Hara, W., & Divi, V. (2018). Predictors of readmissions after head and neck cancer surgery: A national perspective. Oral Oncology, 71, 106–112.

CMS. (2023). FY 2023 Hospital Inpatient Prospective Payment System (IPPS) and Long-Term Care Hospital Prospective Payment System (LTCH PPS) Final Rule — CMS-1771-FCMS.

Reponen, E., Rundall, T. G., Shortell, S. M., Blodgett, J. C., Juarez, A., Jokela, R., Mäkijärvi, M., & Torkki, P. (2021). Benchmarking outcomes on multiple contextual levels in lean healthcare: A systematic review, development of a conceptual framework, and a research agenda. BMC Health Services Research, 21(1).

Statista. (2023). Hospitals punished for high readmissions U.S. FY2023. Statista.

Wang, S., & Zhu, X. (2022). Nationwide hospital admission data statistics and disease-specific 30-day readmission prediction. Health Information Science and Systems, 10(1).

Willmington, C., Belardi, P., Murante, A. M., & Vainieri, M. (2022). The contribution of benchmarking to quality improvement in healthcare. A systematic literature review. BMC Health Services Research, 22(1).

Yang, S., Adams, W., & Bier‐Laning, C. (2022). Head and neck cancer readmission reduction (HANCARRE) project: Reducing 30‐day readmissions. World Journal of Otorhinolaryngology-Head and Neck Surgery.


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