Analysis of Influencing Factors of Postoperative Quality of Life in Patients with Renal Cancer under the Continuing Care Model Based on the Omaha System

Abstract

Background: Scientific nursing is of great significance for improving negative emotions, self-management ability and quality of life of patients after cancer surgery. The Omaha system has been widely used in the field of care in many countries and regions, and although it helps to improve the quality of life of cancer patients after surgery, there are still large differences between different patients. This study examines factors affecting postoperative quality of life in renal cancer patients under the continuous care Omaha system, aiming to refine nursing plans.  Methods: We retrospectively analyzed clinical data from 108 renal cancer patients undergoing radical treatment, all of whom received care via the Omaha system. The score for quality of life and the scores for Strategies Used by People to Promote Health (SUPPH), Social Support Rate Scale (SSRS), and Medical Coping Modes Questionnaire (MCMQ) of patients with different baseline data were compared.  Results: Patients with spouses as primary caregivers scored higher across psychological, physical, physiological, and societal dimensions of quality of life than those with children or others as caregivers (p < 0.001). Patients without underlying diseases have higher physiological, societal dimensions, overall satisfaction total score for quality of life (compared to those with underlying diseases, p < 0.001), patients with clinical stage III have lower physiological, societal dimensions, overall satisfaction, and total score for quality of life (compared to stage I/II, p < 0.001). The physiological, societal dimensions, overall satisfaction, and total quality of life score for patients with medical or commercial insurance as the settlement method for medical expenses are higher (compared to self-funded, p < 0.001). In the SUPPH scale, the positive attitude score, stress reduction score, making decisions score, and total score were positively correlated with the total score for quality of life (p < 0.001, p < 0.001, p = 0.008, p < 0.001, respectively). In the SSRS scale, the objective support score, subjective support score, useless support score, and total score were positively correlated with the total score for quality of life (all p < 0.001). In the MCMQ scale, the confrontation score was positively correlated with the total score for quality of life (p < 0.001). The acceptance-resignation and avoidance scores were negatively correlated with the total score for quality of life (p < 0.001).  Conclusion: The quality of life of patients is not only affected by primary caregivers, underlying diseases, clinical staging, and medical expense settlement methods, but also positively correlated with self-efficacy and social support, and negatively correlated with coping styles.