Integrative review of remote patient monitoring in gynecologic and urologic surgical oncology

Electronic Patient Reported Outcome Measures for Optimal Remote Symptom Management in Advanced Breast Cancer: Embracing Digital Health Technology

OBJECTIVE

To review the use of electronic patient outcome measures (ePROMs) in advanced breast cancer (ABC) and its effectiveness in supporting remote symptom monitoring.

DATA SOURCES

An overview of published randomized controlled trials using electronic patient-reported outcome measures (ePROMs) in ABC care.

CONCLUSION

The use of ePROMs in ABC care combined with oncology clinical nurse specialist (CNS) interventions has shown that patient-centered care through remote monitoring of disease and treatment symptoms can improve ABC patient outcomes and experience.

IMPLICATIONS FOR NURSING PRACTICE

Oncology clinical nurse specialists (CNSs) have an important role in the effective implementation of ePROMs in ABC care. CNSs are considered most appropriate to lead on and respond to ePROMs, addressing complex symptom issues and maximizing the quality of life (QoL) for the ABC patient. CNSs are a crucial link between the patient, primary and secondary level care health professionals, and the ePROM portal for ABC care.

Systematic Review of the Literature on Multiple Co-occurring Symptoms in Patients Receiving Treatment for Gynecologic Cancers

OBJECTIVE

Patients with gynecologic cancers experience a very high symptom burden that has a negative impact on their quality of life. This systematic review aims to identify the common co-occurring symptoms, the prevalence of common symptoms, common instruments used to measure symptoms, associated risk factors, and the symptom burden in patients with gynecologic cancers.

DATA SOURCES

A search of four databases (ie, PubMed, Embase, Web of Science, and CINAHL) was done from January 1, 2012, through September 5, 2022. A qualitative synthesis of the extant literature was performed using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA 2020).

CONCLUSION

A total of 118 studies met the prespecified inclusion criteria. Ninety-six symptoms were assessed across these studies. The top six symptoms and their grand mean prevalence rates were lack of energy (64.4%), fatigue (62.1%), abdominal pain (53.3%), depression (52.6%), concentration dysfunction (52.0%), and drowsiness (51.9%). Numerous methodologic challenges were evident across studies. Future research needs to develop a disease-specific symptom assessment measure, evaluate for risk factors associated with a higher symptom burden, and determine the impact of multiple symptoms on patient outcomes.

IMPLICATION FOR NURSING PRACTICE

The results are relevant for oncology clinicians to assess patients with gynecologic cancers for the presence of common symptoms and risk factors for higher symptom burden in the patients and to offer effective management interventions.

Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise

Over the last 75 years, artificial intelligence has evolved from a theoretical concept and novel paradigm describing the role that computers might play in our society to a tool with which we daily engage. In this review, we describe AI in terms of its constituent elements, the synthesis of which we refer to as the AI Silecosystem. Herein, we provide an historical perspective of the evolution of the AI Silecosystem, conceptualized and summarized as a Kuhnian paradigm. This manuscript focuses on the role that the AI Silecosystem plays in oncology and its emerging importance in the care of the community oncology patient. We observe that this important role arises out of a unique alliance between the academic oncology enterprise and community oncology practices. We provide evidence of this alliance by illustrating the practical establishment of the AI Silecosystem at the City of Hope Comprehensive Cancer Center and its team utilization by community oncology providers.