DATA ANALYSIS METHODOLOGY 2
Research Proposal: Data Analysis Methodology
Data Analysis
The researcher has hypothesized that enrolling adult patients with chronic health
conditions, presenting to the XXXX emergency department more than 9 times in a rolling 12-
month period in the Bridge program for comprehensive case management, will decrease the
number of unreimbursed Medicare dollars to the organization. Conversely, the null hypothesis to
be rejected is that enrolling these patients in the Bridge program will not decrease the number of
unreimbursed Medicare dollars. Data gathered from the electronic medical record by the HIM
department will be uploaded into the study software. Once the upload is completed, the
researcher will print the material out and carefully cross-reference the data to the original data
from the medical record. This will ensure that the most accurate data will be analyzed (Gray &
Grove, 2020).
This researcher anticipates using the Pearson product-moment correlation coefficient
(also known as the Pearson correlation coefficient) to analyze the data gathered in this study. The
researcher used a decision tree to come to this decision. The researcher plans to study the
relationship between the Bridge program and unreimbursed Medicare dollars to the organization.
The dependent variable of the decreased number of unreimbursed Medicare dollars to the
organization is obtainable as a ratio with a true zero that can be established. Since the researcher
is only studying one group using consecutive methodology from a period before the patient was
enrolled in the Bridge program to a period after they have been participating in the Bridge
program, the decision tree indicates the Pearson correlation coefficient is the most appropriate
analysis technique (Gray & Grove, 2020, p. 648).
DATA ANALYSIS METHODOLOGY 3
The researcher intends to use SPSS statistical data software to aid their research. Since
this study is more exploratory in nature, the analysis will be focused strictly on the sample, and
the population is limited to the XXXXX bridge program. As a result of the exploratory nature of
the study, the sample size may be small (Gray & Grove, 2020). A p-value of .05 will be used to
indicate statistical significance. Using the Pearson correlation coefficient to measure the strength
of the relationship between the continuous variables, the researcher can determine a positive or
negative correlation (Main & Ogaz, 2016).
Anticipated Results
A thorough review of the literature results in mixed results when determining the
effectiveness of case management programs on the outcome of unreimbursed dollars to the
organization (Bilazarian et al., 2021; Chang et al., 2022). In this instance, the researcher
anticipates seeing a decreased number of unreimbursed Medicare dollars. This researcher
believes this to be the case due to the knowledge that the Bridge program is a comprehensive
program that focuses on early screening, multi-disciplinary care coordination, enhanced patient
education, medication management assistance, close telephone follow-up, and 24/7 access to a
nurse call line for support. Available research indicates that a robust, patient-centered case
management program effectively reduces the number of unnecessary emergency department
visits and the number of unreimbursed dollars to the organization (Gonçalves et al., 2022). The
researcher anticipates that as patient participation in the robust Bridge case management program
increases, the organization will see a decrease in unreimbursed Medicare dollars. Given the
available research and the study's limited scope, the researcher anticipates this relationship will
be weak to moderate.
Strengths and Weaknesses
DATA ANALYSIS METHODOLOGY 4
This study has several limitations. First, pregnant women, those with psychiatric
diagnoses, and those with cognitive disabilities are among the participants to be excluded from
the study. Research indicates that these populations could be among the high-need, high-cost
patient population due to their unique healthcare needs and barriers to accessing appropriate care
for those needs (Bilazarian et al., 2022). Excluding this patient population could limit the sample
studied to those more readily assisted with such a program. Second, the study intends to only
review patient data for a 12-month period after they were enrolled in the Bridge program. This
limits the ability to determine the program's long-term effects on the organization's unreimbursed
Medicare dollars and does not aid in determining any other benefiting factor the program may
have on patient quality of life or the value to the organization. Thirdly, this study will not give a
good picture of the program's value to the organization or the community it serves. The study is
limited to Medicare patients and reimbursement dollars and does not evaluate the overall number
of dollars reimbursed to the cost center. The study also does not look at the cost of the Bridge
program to the organization. Finally, this study is limited to the specific case management
program at XXXXX and the Bridge program’s unique design and structure. Therefore, this limits
the application to other organizations nationwide that may not employ the exact program. The
study results will not be generalized to healthcare as a whole.
In contrast, there are several strengths to this study that would benefit the XXXX
organization. The clearly defined objective of assessing the Bridge program's impact on reducing
the organization's costs will only aid in providing the information necessary to increase its
effectiveness in the community it serves. Additionally, the objective outcome measures used to
quantify unreimbursed dollars will aid in assessing the Bridge program’s impact. Advanced
statistical techniques will be utilized to analyze the data and aid in determining the cost-
DATA ANALYSIS METHODOLOGY 5
effectiveness of the Bridge program. It will also aid the organization in providing practical
implications for nursing practice.
Suggestions for Future Research
Recent research indicates that case management programs that segment their patient
population needing increased case management programs have better results in fewer visits or
unreimbursed dollars. Doing this allows for a more patient-centered approach where clinical
specialists with expertise in a specific practice area might be better prepared to work with
patients in a more targeted fashion (Quinton et al., 2021). Future research using this targeted case
management approach would provide a better picture of the effectiveness of the program and its
ability to increase the quality of life for patients.
Additionally, this study limited its research to unreimbursed Medicare dollars. It does not
look at unreimbursed dollars as a whole. Additional research is needed to determine whether an
individualized case management program will affect the bottom line of reimbursed healthcare
costs to the organization. Since current research is conflicted on the cost-benefit analysis of such
a program (Oh et al., 2019), additional research is needed to determine if the Bridge program
would decrease the number of overall dollars lost by XXXX.
Another area to consider is whether the Bridge program effectively reduces the number
of repeat visits to the XXXXXX emergency department. One concern regarding high-need, high-
cost patients is the burden they place on the already burdened resources of the emergency
department (Schoolmeester & Keiser, 2023). Studies indicate that an effective case management
program will aid in decreasing this burden (Piñeiro-Fernández et al., 2021). Of interest to this
researcher is whether or not the uniquely designed Bridge program will benefit the XXXXX
organization in the same way.
DATA ANALYSIS METHODOLOGY 6
References
Bilazarian, A., Hovsepian, V., Kueakomoldej, S., & Poghosyan, L. (2021). A systematic review
of primary care and payment models on emergency department use in patients classified
as high need, high cost. Journal of Emergency Nursing, 47(5), 761–777.e3.
https://doi.org/10.1016/j.jen.2021.01.012
Bilazarian, A., McHugh, J., Schlak, A. E., Liu, J., & Poghosyan, L. (2022). Primary care practice
structural capabilities and emergency department utilization among high-need high-cost
patients. Journal of General Internal Medicine, 38(1), 74–80.
https://doi.org/10.1007/s11606-022-07706-y
Chang, E., Ali, R., Seibert, J., & Berkman, N. D. (2022). Interventions to improve outcomes for
high-need, high-cost patients: A systematic review and meta-analysis. Journal of General
Internal Medicine, 38(1), 185–194. https://doi.org/10.1007/s11606-022-07809-6
Gonçalves, S., von Hafe, F., Martins, F., Menino, C., Guimarães, M., Mesquita, A., Sampaio, S.,
& Londral, A. (2022). Case management intervention of high users of the emergency
department of a Portuguese hospital: A before-after design analysis. BMC Emergency
Medicine, 22(1). https://doi.org/10.1186/s12873-022-00716-3
Gray, J. R., & Grove, S. K. (2020). Burns and Grove's the practice of nursing research:
Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
Main, M. E., & Ogaz, V. L. (2016). Common statistical tests and interpretation in nursing
research. International Journal of Faith Community Nursing, 2(3), Article 2.
https://digitalcommons.wku.edu/ijfcn/vol2/iss3/2/
DATA ANALYSIS METHODOLOGY 7
Oh, E., Kim, J., & Lee, H. (2019). Effects of a safe transition programme for discharged patients
with high unmet needs. Journal of Clinical Nursing, 28(11-12), 2319–2328.
https://doi.org/10.1111/jocn.14831
Piñeiro-Fernández, J., Fernández-Rial, Á., Suárez-Gil, R., Martínez-García, M., García-
Trincado, B., Suárez-Piñera, A., Pértega-Díaz, S., & Casariego-Vales, E. (2021).
Evaluation of a patient-centered integrated care program for individuals with frequent
hospital readmissions and multimorbidity. Internal and Emergency Medicine, 17(3), 789–
797. https://doi.org/10.1007/s11739-021-02876-9
Quinton, J. K., Duru, O., Jackson, N., Vasilyev, A., Ross-Degnan, D., O’Shea, D. L., &
Mangione, C. M. (2021). High-cost high-need patients in Medicaid: Segmenting the
population eligible for a national complex case management program. BMC Health
Services Research, 21(1). https://doi.org/10.1186/s12913-021-07116-6
Schoolmeester, A., & Keiser, M. (2023). Use of care guides to reduce emergency department
visits by high-frequency utilizers. Journal of Emergency Nursing, 49(6), 863–869.
https://doi.org/10.1016/j.jen.2023.07.007
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