Adherence to patient-reported symptom monitoring and subsequent clinical interventions for patients with Multiple Myeloma in outpatient care: a longitudinal observational study (Preprint)

crossref(2023)

引用 0|浏览2
暂无评分
摘要
BACKGROUND Use of software to monitor Patient-Reported Outcome Measures (PROMs) can improve outcomes for cancer patients receiving anticancer therapy; however, evidence from applications used in routine clinical practice is lacking. OBJECTIVE We aimed to investigate adherence to, and patient perceptions of a weekly, web-based PROM symptom monitoring in routine clinical practice for patients with Multiple Myeloma. METHODS We conducted a single-center longitudinal observational study to evaluate patient adherence to and perceptions of the PROM monitoring software in routine practice. Patients with Multiple Myeloma remotely completed weekly treatment-specific PROMs to monitor key symptoms via a dedicated web-based platform. Alarming symptoms triggered clinical alerts in the application for the treatment team who could initiate clinical interventions. The primary outcomes were the online assessment completion rate and patients’ perceptions of the monitoring program. The clinical alerts prompted by the system and consequential clinical interventions were analyzed. RESULTS Between July 2021 and June 2022, 55 patients were approached for participation; 39 patients participated (24 male [61%], mean age: 63.2 years, SD 9.2). The median assessment completion rate out of all weekly scheduled assessments was 70.3% (IQR 41.2-89.6). Most patients (77%) felt that the healthcare team was better informed on their health status due to the online assessments. Clinical alerts were triggered for 1758/14639 (12.0%) of reported symptoms. CONCLUSIONS Our study shows that high adherence to regular and tailored PROM monitoring can be achieved in routine clinical care and provides valuable insight into how the PROM monitoring software shaped clinical practice. CLINICALTRIAL NCT05036863 (https://clinicaltrials.gov/)
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要