Effects of Discharge Planning Model on Health Outcomes among Older Adults Following Coronary Artery Bypass Graft Surgery

Authors

  • Nipaporn Thaepthap Trang hospital, Trang Province

Keywords:

Discharge planning, Older adults, Coronary artery bypass graft surgery, Health outcomes

Abstract

Background and Objectives Older adults following coronary artery bypass graft (CABG) surgery require effective discharge planning to prepare them for transition. This study aimed to evaluate the effects of a discharge planning model developed by integrating the D-METHOD framework with Meleis’s Transition Theory on health outcomes among older adults following CABG surgery at Trang Hospital.

Methods A two-group pretest–posttest quasi-experimental design was conducted among 56 older adults following CABG surgery at Trang Hospital between May 29, 2025, and April 30, 2026. The sample was selected through purposive sampling according to the established criteria and assigned to study groups based on time periods, with 28 participants in the experimental group and 28 in the control group. The control group received routine nursing care, whereas the experimental group received the newly developed discharge planning model, which encompassed three phases:
1) transition readiness assessment, 2) nursing interventions for transitional care preparation, and 3) role enhancement with continuous follow-up, integrated with family caregiver skill-training. Data were collected regarding knowledge, self-care ability, length of hospital stay, postoperative complications, 28-day hospital readmissions, and 1-month post-discharge quality of life. The research instruments were validated for content accuracy by experts, yielding an overall Index of Item-Objective Congruence (IOC) of 0.96. The reliability of the knowledge questionnaire was 0.84, whereas the Cronbach's alpha coefficients for the self-care ability and quality of life questionnaires were 0.82 and 0.88, respectively. Data were analyzed using descriptive statistics, the Mann-Whitney U test, and Fisher’s exact test, with the statistical significance level set at p < .05

Results Before the intervention, no statistically significant differences were observed between the control and experimental groups regarding baseline knowledge and self-care ability scores (p > .05). Post-intervention, the experimental group demonstrated significantly higher median scores for both knowledge (U = 0.50, p < .001) and self-care ability (U = 2.00, p < .001) compared to the control group. Additionally, the experimental group had a significantly shorter length of hospital stay than the control group (U = 625.00, p < .001). However, overall postoperative complication rates, 28-day hospital readmission rates, and quality of life scores did not differ significantly between the two groups (p > .05)

Conclusions and Recommendations The discharge planning model integrating the D-METHOD framework with Meleis’s Transition Theory effectively improves health outcomes by enhancing knowledge and self-care ability while significantly reducing the length of hospital stay among older adults following CABG surgery. This model can serve as a standardized evidence-based guideline to improve discharge planning in this patient population.

References

Chudgar, N.P., Zhu, R., Gray, K.D., Chiu, R., Delacruz Carrera, A., Lang, S.J., Avgerinos, D.V., & Mack, C. A. (2022). Implementing a high-value care discharge protocol in patients undergoing CABG reduces readmission. The Annals of Thoracic Surgery, 113(4), 1112 –1118. https://doi.org/10.1016/j.athoracsur.2021.07.036

Department of Disease Control (2024). Situation report on noncommunicable diseases (NCDs) and related risk factors. Ministry of Public Health.

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175 – 191. https://doi.org/10.3758/BF03193146

Heart Center, Trang Hospital. (2024). Annual statistics of patients undergoing cardiovascular and thoracic surgery, 2024. Author.

Lima, A. C. P., Maximiano-Barreto, M. A., Martins, T. C. R., & Luchesi, B. M. (2024). Factors associated with poor health literacy in older adults: A systematic review. Geriatric Nursing, 55, 242 – 254. https://doi.org/10.1016/j.gerinurse.2023.11.016

Liu, J., Li, X., Xie, W., Wang, Y., Xu, Z., Bai, Y.X., Zhou, Q., & Wu, Q. (2023). Risk factors and short-term outcomes of postoperative pulmonary complications in elderly patients after cardiopulmonary bypass. Clinical Interventions in Aging, 19, 31 – 39. https://doi.org/10.2147/CIA.S439601

Mahatnirunkul, S., Tantipiwattanaskul, W., Poompaisanchai, W., Wongsuwan, K., & Prommanarungkul, R. (2002). The World Health Organization Quality of Life-BREF, Thai version (WHOQOL-BREF-THAI). Department of Mental Health, Ministry of Public Health.

Meleis, A. I. (2010). Transitions theory: Middle-range and situation-specific theories in nursing research and practice. Springer Publishing Company.

Neumann, F. J., Sousa-Uva, M., Ahlsson, A., Alfonso, F., Banning, A. P., Benedetto, U., Byrne, R. A., Collet, J. P., Falk, V., Head, S. J., Jüni, P., Kastrati, A., Kolh, P., Kristensen, S. D., Niebauer, J., Richter, D.J., Seferovic, P.M., Sibbing, D., Stefanini, G.O., …& Zembala, M.O. (2019). 2018 ESC/EACTS Guidelines on myocardial revascularization. European Heart Journal, 40(2), 87 – 165. https://doi.org/10.1093/eurheartj/ehy394

Persson, S., Dhingra, K., & Grogan, S. (2018). Attributions of victim blame in stranger and acquaintance rape: A quantitative study. Journal of Clinical Nursing, 27, 13 – 14. https://onlinelibrary.wiley.com/doi/10.1111/jocn.15241

Riegel, B., Moser, D. K., Buck, H. G., Dickson, V. V., Dunbar, S. B., Lee, C. S., Lennie, T. A., Lindenfeld, J., Mitchell, J. E., Treat-Jacobson, D. J., & Webber, D. E. (2017). Self-care for the prevention and management of cardiovascular disease and stroke: A scientific statement for healthcare professionals from the American Heart Association. Journal of the American Heart Association, 6(9), e006997. https://doi.org/10.1161/JAHA.117.006997

Thepsuriyanont, S., Sayasathit, J., Tangpanawong, J., Soodasud, T., Prasitpapada, Y., & Konkam, K. (2022). Effects of a transitional care program on knowledge and self-care behavior among patients undergoing cardiac surgery. Thai Journal of Cardio-Thoracic Nursing, 33(1), 167 – 182. https://he02.tci-thaijo.org/index.php/journalthaicvtnurse/article/view/251300

The Society of Thoracic Surgeons of Thailand. (2024). Thailand cardiac surgery statistics 2021–2023. Author. https://thaists.or.th/home

Wang, X., Zhang, Y., Huang, T., Yang, R., Cheng, H., Wang, H., Yin, H., & Lyu, J. (2023). Developing an explainable machine learning model to predict the mechanical ventilation duration of patients with ARDS in intensive care units. Heart & Lung, 58, 74 – 81. https://doi.org/10.1016/j.hrtlng.2022.11.005

World Health Organization. (2024). The top 10 causes of death. Author. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death

Downloads

Published

2026-10-27

How to Cite

Thaepthap, N. (2026). Effects of Discharge Planning Model on Health Outcomes among Older Adults Following Coronary Artery Bypass Graft Surgery. Princess of Naradhiwas University Journal, 18(3), 356–377. Retrieved from https://li01.tci-thaijo.org/index.php/pnujr/article/view/272972