Postoperative health-related quality of life of patients with gynecological malignancy: a meta-analysis

Patients' preferences, experiences and expectations with wait time until surgery in gynaecological oncology: a mixed-methods study in two gynaecological oncological centres in the Netherlands

OBJECTIVES

Patient-centredness of care during wait time before surgery can be improved. In this study we aimed to assess (1) patients' experiences with and preferences regarding wait time before surgery; (2) the impact of wait time on quality of life (QoL) and (3) which factors influence patients' wait time experience.

DESIGN, SETTING, PARTICIPANTS

We performed an exploratory sequential mixed-methods study among women with gynaecological cancer in two tertiary hospitals. We conducted semistructured interviews and identified aspects of QoL and factors that influenced wait time acceptability through thematic analysis. We developed a questionnaire from this thematic analysis which was completed by 97 women. Descriptive statistics and univariate and multivariate regression analyses were performed.

RESULTS

Average ideal wait time was 3.5 weeks (±1.7 weeks), minimum and maximum acceptable wait times were 2.2 and 5.6 weeks. Many patients scored above the threshold of the Hospital Anxiety and Depression Scale for anxiety (48%) or depression (34%), had sleeping problems (56%) or experienced pain (54%). A number of factors were more common in patients who indicated that their wait time had been too long: low education level (OR 7.4, 95% CI 0.5 to 5.0, p=0.007), time to surgery >4 weeks (OR 7.0, 95% CI 0.8 to 4.4, p=0.002) and experienced sleep disturbance (OR 3.27, 95% CI 0.0 to 3.1, p=0.05). If patients expectation of wait time was >4 weeks (OR 0.20, 95% CI -4.0 to -0.5 p=0008) or if patients experienced pain (OR 0.26, 95% CI -3.6 to -0.3, p=0.03), they less frequently indicated that wait time had been too long.

CONCLUSION

To improve patient-centredness of care, healthcare providers should aim to reduce wait time to 3-4 weeks and ensure that patients are well informed about the length of wait time and are aware of high levels of anxiety, depression and pain during this time. Future studies should evaluate what interventions can improve QoL during wait time.

Construction and evaluation of a cloud follow-up platform for gynecological patients receiving chemotherapy

BACKGROUND

Patient follow-up is an essential component of hospital management. In the current information era, the patient follow-up scheme is expected to be replaced by Internet technology. This study constructed a cloud follow-up platform for gynecological chemotherapy patients and assessed its cost-effectiveness and patients' feedback.

METHODS

A total of 2,538 patients were followed up using a cloud follow-up system between January and October 2021. Prior to this, 690 patients were followed manually via telephone calls. Patients' characteristics, follow-up rate, satisfaction, and session duration were compared between the cloud follow-up and manual follow-up groups. In addition, the read rate of health education materials in the cloud follow-up group was analyzed.

RESULTS

General information, including age, education attainment, cancer stage, and disease category, and follow-up rate (cloud: 6,957/7,614, 91.4%; manual: 1,869/2,070, 90.3%; P = 0.13) did not significantly differ between the two groups. The follow-up satisfaction of the cloud follow-up patients was significantly better than that of the manual follow-up group (cloud: 7,192/7,614, 94.5%; manual: 1,532/2,070, 74.0%; P<0.001). The time spent on the follow-up was approximately 1.2 h for 100 patients in the cloud follow-up group and 10.5 h in the manual follow-up group. Multivariate analysis indicated that the cloud follow-up group had significantly greater follow-up satisfaction (odds ratio: 2.239, 95% CI: 1.237 ~ 5.219). Additionally, the average follow-up duration of the cloud follow-up group decreased by 9.287 h (coefficient: -9.287, 95% CI: -1.439~-0.165). The read rate of health education materials was 72.9% in the cloud follow-up group.

CONCLUSIONS

The follow-up effect of the cloud follow-up group was not inferior to that of the manual follow-up group. The cloud follow-up was more effective for prevention and control requirements in the post-epidemic era. Cloud follow-up can save medical resources, improve cost-effectiveness, provide sufficient health education resources for patients, and improve their satisfaction.

Quality of life in children undergoing tonsillectomy: a cross-sectional survey

BACKGROUND

The quality of life in children undergoing tonsillectomy remains unclear. We aimed to analyze the current status and influencing factors of quality of life in children undergoing tonsillectomy, to provide useful insights to clinical postoperative care for children.

METHODS

Children who underwent tonsillectomy in our hospital from June 1, 2021 to October 31, 2022 were selected. The characteristics of children were collected and Paediatric Quality of Life Inventory Version 4.0 (PedsQL™ 4.0) was used for evaluating the quality of life in children. Pearson correlation, univariate and logistic regression analyses were condcuted to evaluate the influencing factors of quality of life in children undergoing tonsillectomy.

RESULTS

A total of 118 children undergoing tonsillectomy were included. The total score of PedsQL™ 4.0 in children undergoing tonsillectomy was (70.28 ± 13.15). Pearson correlation analyses indicated that age(r = 0.586), courses of tonsillitis(r = 0.595), parental education level(r = 0.612) and monthly family income(r = 0.608) were associated with the PedsQL™ 4.0 total score in children undergoing tonsillectomy (all P < 0.05). Logistic regression analyses indicated that age ≤ 5y (OR = 2.009,95%CI: 1.826 ~ 2.401), courses of tonsillitis ≥ 3years (OR = 2.167,95%CI: 1.688 ~ 2.547), high school of parental education level (OR = 1.807,95%CI: 1.224 ~ 2.181) and monthly family income ≤ 5000 RMB(OR = 2.624,95%CI:2.092 ~ 3.077) were the independent influencing factors of quality of life in children with undergoing tonsillectomy (all P < 0.05).

CONCLUSIONS

The quality of life of children after tonsillectomy is not high, and the quality of life of children is affected by many factors. Medical staff should take early targeted nursing countermeasures tageted on those influencing factors to improve the quality of life of children.