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Exploring Transitional Care Models to Enhance Healthcare Outcomes for Elderly Patients

David Alexander Revilla

Florida National University

Nursing Research and Evidence-Based Practice

Professor: Carmen Lazo

December 7, 2024

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Exploring Transitional Care Models to Enhance Healthcare Outcomes for Elderly Patients

Results Overview

The following section describes hypothetical results that the proposed Transitional Care

Model (TCM) intervention might produce in the set of chronic elder patients. Employing a pre-

post intervention design, the results indicate that the TCM is associated with decreased hospital

readmissions, improved patient satisfaction with the hospital experience, and overall enhanced

health stability in the months following discharge. We present a demographic profile of the

sample population, descriptive statistics illustrating the intervention's effects, and discussion of

study limitations.

Demographics and Baseline Characteristics

Eighty participants (intervention: 40, control: 40) were purposively sampled from three

regional hospitals. The age of participants ranged from 60 to 89 years, with 36 participants aged

60–70 years (45%), 32 participants aged 71–80 years (40%) and 12 participants aged 81–89

years (15%). In terms of gender, 55% of the sample (n = 44) was male and 45% (n = 36) was

female. For chronic conditions, 40% (32 of the participants) had diabetes mellitus, 35% (28 of

the participants) had congestive heart failure (CHF), and 25% (20 of the participants) had

chronic obstructive pulmonary disease (COPD). On subjects-education, 65% (52 subjects) had a

high school education or lower, and 35% (28 subjects) had a college education or higher

(Hoogland et al., 2020).

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More specifically, at baseline, 65% (62–68) of participants reported at least one hospital

readmission in the preceding year, with an average of 2.4 readmissions per patient. In addition,

three quarters of the participants reported that adhering to prescribed medication regimens was a

difficult challenge that they had to meet to maintain their health. Just 30% of the cohort felt

confident to manage their condition on their own, representing an important gap in self-

management capabilities. These baseline characteristics highlight the high risk of this population

and the possible effect of exposing an intervention, such as a Transitional Care Model (TCM),

designed to reduce risk factors (Tomlinson et al., 2020).

Statistical Outcomes

1. Decrease in Hospital Readmissions: The intervention group had significantly lower

hospital readmission rates than the control group. Results: A paired t-test showed the

following:

• Mean readmissions (control group): 2.1 ± 0.7

• Mean readmissions (intervention group): 0.8 ± 0.4

• t (39) = -7.35, p < 0.001

2. Improved Patient Satisfaction: Patient satisfaction reported based on a 5-point Likert

scale showed significant improvement in the intervention group. Scores before and after

intervention were:

• Mean satisfaction pre-intervention: 2.8 ± 0.5

• Mean post-intervention satisfaction score: 4.6 ± 0.3

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• t (39) = 12.48, p < 0.001

3. Medication Adherence: The intervention group reported significantly improved

medication adherence. Chi-square analysis revealed:

• Adherence (intervention group): 80%

• Adherence (control group): 45%

• χ²(1, N=80) = 16.82, p < 0.001

4. Improvements in Functional Status: Self-care and mobility index was used to assess

functional status improvements. ANOVA revealed significant differences:

• Mean improvement score of intervention group: 3.2 ± 0.6

• Control group estimated improvement score: 1.1 ± 0.5

• F (1,78) = 24.67, p < 0.001

Research Limitations

There were several limitations to this study that may affect interpretation and

generalizability of results. First, the sample size, while adequate to draw initial conclusions, was

small and consisted of only 80 individuals. A larger and more varied cohort would add to the

generalizability of the findings and give more robust statistical power. Recruiting a more diverse

participant pool in future studies may alleviate this limitation and contribute generalizable

findings (Morkisch et al., 2020).

Second, outcomes were only tracked for 90 days after discharge. Though this period

yielded meaningful short-term insights, it failed to account for the longer-term effects of the

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Transitional Care Model (TCM) intervention on health outcomes. Longer follow-up periods in

future studies would provide further insight into the long-term effectiveness of TCM

interventions (Costa Jacobsohn et al., 2023).

Third, the study's end-point measures were mostly derived from self-reported data on

patient satisfaction and medication adherence. This methodology creates the potential for

response bias if participants overestimate either their adherence or satisfaction. Integrating

objective measures (i.e., electronic monitoring systems to gauge adherence to treatment) not only

reduces this bias but can also enhance data reliability (Tomlinson et al., 2020).

Lastly, there may have been geographic and cultural restrictions since participants were

limited to one geographic region. This narrow focus limits the generalizability of findings to

other settings with different cultural, socioeconomic or healthcare delivery systems. Future

studies need to try to encompass participants from more diverse regions and cultures to enhance

the generalizability of the findings. Highlighting these limitations will support further research to

strengthen the evidence base for TCM interventions and programmatic applicability in a variety

of healthcare settings.

Suggestions for Future Research

To solidify the evidence for the Transitional Care Model (TCM) and diversify the patient

population in this body of literature we recommend following as future directions of research:

• Stretch out Sample Size and Diverseness: Future research should try to recruit a larger

sample size so that the results can carry statistical power and generalizability. The

participants need to be recruited from diverse ethnic, cultural, and socioeconomic

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backgrounds to determine the effectiveness of the intervention for different populations

and to notice any disparities between different groups in the outcomes (Leithaus et al.,

2022).

• Extend Follow-Up Duration: The research should extend the follow-up period used in

this study beyond 90 days. Extended follow-up periods will shed light on the long-term

consequences of TCM interventions on health outcomes, such as readmission prevalence,

medication compliance, and functional steadiness longitudinally (Costa Jacobsohn et al.,

2023).

• Use Objective Measures: Incorporating objective measures can strengthen data. Future

studies should implement the use of electronic medication monitoring systems to validate

self-reported data around medication adherence and patient behaviors. These initiatives

will mitigate response bias and provide more accurate evaluations of intervention impacts

(Leithaus et al., 2022).

• Examine Cost-Effectiveness: Understanding the cost-effectiveness of TCM interventions

is essential for assessing their economic viability and potential for broader

implementation. Future studies should evaluate if hospital readmissions are reduced, and

patient outcomes are improved such that the cost of implementation of TCM strategies is

justified.

Conclusion

Hypothetical study results suggest the TCM may significantly improve outcomes for

elderly patients with chronic conditions. Key findings are a significant decrease in hospital

readmissions, greater patient satisfaction, improved adherence to medications, and enhanced

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functional status in participants receiving the intervention. These results highlight the importance

of applying TCM interventions to common discordant transitions of care experiences,

particularly in vulnerable populations.

Although the results highlight the potential of TCM to enhance health outcomes and

decrease healthcare expenses, several limitations must be resolved to corroborate and optimize

these discoveries in larger, real-world settings. Increasing sample sizes, extending follow-up

times, using objective data collection methods and broadening geographic and cultural diversity

are vital next steps for future research. These initiatives will secure greater evidence behind

TCM interventions, making them more adaptable and applicable across varied healthcare

settings. Long-term outcomes in elderly patients are improved through patient-centered,

evidence-based practices demonstrated in transitional care, and this study highlights the

significance of those practices to achieve improved patient-centered outcomes.

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References

Costa Jacobsohn, G., Maru, A. P., Green, R. K., Gifford, A. N., Lukasik, M. D., Bandara, T.,

Caprio, T. V., Cochran, A. L., Cushman, J. T., Jones, C. M. C., Kind, A. J. H., Lohmeier,

M., & Shah, M. N. (2023). Multimethod Process Evaluation of a Community Paramedic

Delivered Care Transitions Intervention for Older Emergency Department

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https://doi.org/10.1080/10903127.2022.2094514

Hoogland, A. I., Mansfield, J., Lafranchise, E. A., Bulls, H. W., Johnstone, P. A., & Jim, H. S.

(2020). eHealth literacy in older adults with cancer. Journal of geriatric oncology, 11(6),

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Leithaus, M., Beaulen, A., de Vries, E., Goderis, G., Flamaing, J., Verbeek, H., & Deschodt, M.

(2022). Integrated Care Components in Transitional Care Models from Hospital to Home

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care, 22(2), 28. https://doi.org/10.5334/ijic.6447

Morkisch, N., Upegui-Arango, L. D., Cardona, M. I., van den Heuvel, D., Rimmele, M., Sieber,

C. C., & Freiberger, E. (2020). Components of the transitional care model (TCM) to

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Tomlinson, J., Cheong, V. L., Fylan, B., Silcock, J., Smith, H., Karban, K., & Blenkinsopp, A.

(2020). Successful care transitions for older people: a systematic review and meta-

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