Engaging patients and clinicians in online reporting of adverse effects during chemotherapy for cancer. The eRAPID system (Electronic patient self-Reporting of Adverse-events: Patient Information and aDvice)

Introduction: During cancer treatment the timely detection and management of adverse events (AE) is essential for patient safety and maintaining quality of life. eRAPID was devised to support oncology practice, by allowing patients to self-report symptoms online at home during and beyond cancer treatment. Fundamentally the eRAPID intervention delivers immediate severity-tailored feedback directly to patients to guide self-management strategies or hospital contact. Patient data are available in electronic health records (EHR) for hospital staff to access and review as part of clinical assessments. Methods for interpreting and addressing PRO scores: The eRAPID intervention has 5 main interconnecting components (clinical integration into standard care pathways, patient symptom reports, self-management advice, information technology and staff/patient training). Following guidance for the development of complex interventions and using a mixed methods approach, eRAPID was created through a number of stages and tested in a series of usability settings before undergoing systematic evaluation in an ongoing randomised controlled trial. These developmental stages are described here with a focus on how decisions were made to enhance patient and professional engagement with symptom reports and encourage interpretation and clinical utilisation of the data. Discussion: Clinically embedded PRO interventions involve a number of elements and stakeholders with different requirements. Following extensive developmental work eRAPID was pragmatically designed to fit into current oncology practices for reviewing and managing chemotherapy-related toxicities

Online tool for monitoring adverse events in patients with cancer during treatment (eRAPID): field testing in a clinical setting

Objectives: Electronic patient self-Reporting of Adverse-events: Patient Information and aDvice (eRAPID) is an online system developed to support patient care during cancer treatment by improving the detection and management of treatment-related symptoms. Patients can complete symptom reports from home and receive severity-based self-management advice, including notifications to contact the hospital for severe symptoms. Patient data are available in electronic records for staff to review. Prior to the commencement of a randomised controlled trial (RCT), field testing of the intervention was undertaken to troubleshoot practical issues with intervention integration in clinical practice. Design: Observational clinical field testing. Setting: Medical oncology breast service in a UK cancer centre. Participants: 12 patients receiving chemotherapy for early breast cancer and 10 health professionals (oncologists and specialist nurses). Intervention: Patients were asked to use the eRAPID intervention and complete weekly online symptom reports during four cycles of chemotherapy. Clinical staff were invited to access and use patient data in clinical assessments. Analysis: Descriptive data on the frequency of online symptom report completion and severe symptom notifications were collated. Verbal and written feedback was collected from patients and staff and semistructured interviews were conducted to explore patient experiences. Interviews were transcribed and analysed thematically. Results: The testing ran from January 2014 to March 2014. Feedback from patients and staff was largely positive. Patients described eRAPID as ‘reassuring’ and ‘comforting’ and valued the tailored management advice. Several changes were made to refine eRAPID. In particular, improvement of the clinical notification, patient reminder systems and changes to patient and staff training. Conclusions: The field testing generated valuable results used to guide refinement of eRAPID prior to formal intervention evaluation. Feedback indicated that eRAPID has the potential to improve patients’ self-efficacy, knowledge and confidence with managing symptoms during treatment. A large-scale RCT is underway with data collection due to finish in October 2018

Training clinicians in how to use patient-reported outcome measures in routine clinical practice

Introduction: Patient-reported outcome measures (PROs) were originally developed for comparing groups of people in clinical trials and population studies, and the results were used to support treatment recommendations or inform health policy, but there was not direct benefit for the participants providing PROs data. However, as the experience in using those measures increased, it became obvious the clinical value in using individual patient PROs profiles in daily practice to identify/monitor symptoms, evaluate treatment outcomes and support shared decision-making. A key issue limiting successful implementation is clinicians’ lack of knowledge on how to effectively utilize PROs data in their clinical encounters. Methods: Using a change management theoretical framework, this paper describes the development and implementation of three programs for training clinicians to effectively use PRO data in routine practice. The training programs are in three diverse clinical areas (adult oncology, lung transplant and paediatrics), in three countries with different healthcare systems, thus providing a rare opportunity to pull out common approaches whilst recognizing specific settings. For each program, we describe the clinical and organizational setting, the program planning and development, the content of the training session with supporting material, subsequent monitoring of PROs use and evidence of adoption. The common successful components and practical steps are identified, leading to discussion and future recommendations. Results: The results of the three training programs are described as the implementation. In the oncology program, PRO data have been developed and are currently evaluated; in the lung transplant program, PRO data are used in daily practice and the integration with electronic patient records is under development; and in the paediatric program, PRO data are fully implemented with around 7,600 consultations since the start of the implementation. Conclusion: Adult learning programs teaching clinicians how to use and act on PROs in clinical practice are a key steps in supporting patient engagement and participation in shared decision-making. Researchers and clinicians from different clinical areas should collaborate to share ideas, develop guidelines and promote good practice in patient-centred care

Patients' confidence in treatment decisions for early stage non-small cell lung cancer (NSCLC).

BACKGROUND: In early-stage Non-Small Cell Lung Cancer (NSCLC) patients, little is known about how to measure patient participation in Shared-Decision Making (SDM). We examined the psychometric properties and clinical acceptability of the Decision Self-Efficacy scale (DSE) in a cohort of patients undergoing to Stereotactic Ablative Radiotherapy (SABR) or Video-assisted Thoracoscopic Surgery (VATS) to capture patient involvement in treatment decisions. METHODS: In the context of a prospective longitudinal study (Life after Lung Cancer-LiLAC) involving 244 patients with early-stage NSCLC, 158 (64.7%) patients completed the DSE either on paper or electronically online prior to treatment with SABR or VATS pulmonary resection. DSE psychometric properties were examined using: principal components analysis of item properties and internal structure, and internal construct validity; we also performed a sensitivity analysis according to Eastern Cooperative Oncology Group Performance Status (ECOG PS), gender, age and treatment received (VATS or SABR) difference. RESULTS: Exploratory factor analysis using polychoric correlations substantiated that the 11 item DSE is one scale accounting for 81% of the variance. We calculated a value of 0.96 for Cronbach's alpha for the total DSE score. DSE scores did not differ by gender (p = 0.37), between the two treatment groups (p = 0.09) and between younger and older patients (p = 0.4). However, patients with an ECOG PS > 1 have a DSE mean of 73.8 (SD 26) compared to patients with a PS 0-1 who have a DSE mean of 85.8 (SD 20.3 p = 0.002). CONCLUSION: Findings provide preliminary evidence for the reliability and validity of the DSE questionnaire in this population. However, future studies are warranted to identify the most appropriate SDM tool for clinical practice in the lung cancer treatment field

The effect of Liver Transplantation on the quality of life of the recipient's main caregiver - a systematic review

Introduction: Liver transplantation (LT) is a transformative, life-saving procedure with life-long sequale for patients and their caregivers. The impact of LT on the patient's main caregiver can be underestimated. We carried out a systematic review of the impact of LT on the Health Related Quality of Life (HRQL) of LT patients’ main caregivers. Methods: We searched 13 medical databases from 1996 to 2015. We included studies with HRQL data on caregivers of patients following LT then quality assessed and narratively synthesized the findings from these studies. Results: Of 7076 initial hits, only five studies fell within the scope of this study. In general, they showed caregiver burden persisted in the early period following LT. One study showed improvements, however the other four showed caregiver's levels of stress, anxiety and depression, remained similar or got worse post-LT and remained above that of the normal population. It was suggested that HRQL of the patient impacted on the caregiver and vice versa and may be linked to patient outcomes. No data was available investigating which groups were at particular risk of low HRQL following LT or if any interventions could improve this. Conclusion: The current information about LT caregivers’ needs and factors that impact on their HRQL are not adequately defined. Large studies are needed to examine the effects of LT on the patients’ family and caregivers in order to understand the importance of caregiver support to maximise outcomes of LT for the patient and their caregivers

Quality of life support in advanced cancer – Web and technological interventions: systematic review and narrative synthesis

Background As treatments continue to progress, patients with advanced cancer are living longer. However, ongoing physical side-effects and psychosocial concerns can compromise quality of life (QoL). Patients and physicians increasingly look to the internet and other technologies to address diverse supportive needs encountered across this evolving cancer trajectory. Objectives 1. To examine the features and delivery of web and technological interventions supporting patients with advanced cancer. 2. To explore their efficacy relating to QoL and psychosocial well-being. Methods Relevant studies were identified through electronic database searches (MEDLINE, PsychINFO, Embase, CINAHL, CENTRAL, Web of Science and ProQuest) and handsearching. Findings were collated and explored through narrative synthesis. Results Of 5274 identified records, 37 articles were included. Interventions were evaluated within studies targeting advanced cancer (13) or encompassing all stages (24). Five subtypes emerged: Interactive Health Communication Applications (n=12), virtual programmes of support (n=11), symptom monitoring tools (n=8), communication conduits (n=3) and information websites (n=3). Modes of delivery ranged from self-management to clinically integrated. Support largely targeted psychosocial well-being, alongside symptom management and healthy living. Most studies (78%) evidenced varying degrees of efficacy through QoL and psychosocial measures. Intervention complexity made it challenging to distinguish the most effective components. Incomplete reporting limited risk of bias assessment. Conclusion While complex and varied in their content, features and delivery, most interventions led to improvements in QoL or psychosocial well-being across the cancer trajectory. Ongoing development and evaluation of such innovations should specifically target patients requiring longer-term support for later-stage cancer

Using Machine Learning to Predict Unplanned Hospital Utilisation and Chemotherapy Management from Patient-Reported Outcome Measures

Purpose Adverse effects of chemotherapy often require hospital admissions or treatment management. Identifying factors contributing to unplanned hospital utilization may improve health care quality and patients' well-being. This study aimed to assess if patient-reported outcome measures (PROMs) improve performance of machine learning (ML) models predicting hospital admissions, triage events (contacting helpline or attending hospital), and changes to chemotherapy. Materials and Methods Clinical trial data were used and contained responses to three PROMs (European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire [QLQ-C30], EuroQol Five-Dimensional Visual Analogue Scale [EQ-5D], and Functional Assessment of Cancer Therapy-General [FACT-G]) and clinical information on 508 participants undergoing chemotherapy. Six feature sets (with following variables: [1] all available; [2] clinical; [3] PROMs; [4] clinical and QLQ-C30; [5] clinical and EQ-5D; [6] clinical and FACT-G) were applied in six ML models (logistic regression [LR], decision tree, adaptive boosting, random forest [RF], support vector machines [SVMs], and neural network) to predict admissions, triage events, and chemotherapy changes. Results The comprehensive analysis of predictive performances of the six ML models for each feature set in three different methods for handling class imbalance indicated that PROMs improved predictions of all outcomes. RF and SVMs had the highest performance for predicting admissions and changes to chemotherapy in balanced data sets, and LR in imbalanced data set. Balancing data led to the best performance compared with imbalanced data set or data set with balanced train set only. Conclusion These results endorsed the view that ML can be applied on PROM data to predict hospital utilization and chemotherapy management. If further explored, this study may contribute to health care planning and treatment personalization. Rigorous comparison of model performance affected by different imbalanced data handling methods shows best practice in ML research

Asking the right questions to get the right answers: Using cognitive interviews to review the acceptability, comprehension and clinical meaningfulness of patient self-report adverse event items in oncology patients

Background: Standardized reporting of treatment-related adverse events (AE) is essential in clinical trials, usually achieved by using the National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) reported by clinicians. Patient-reported adverse events (PRAE) may add value to clinician assessments, providing patient perspective on subjective toxicity. We developed an online patient symptom report and self-management system for real-time reporting and managing AE during cancer treatment integrated with electronic patient records (eRAPID). As part of this program we developed a patient version of the CTCAE (version 4.0), rephrasing terminology into a self-report format. We explored patient understanding of these items via cognitive interviews. Material and method: Sixty patients (33 female, 27 male) undergoing treatment were purposively sampled by age, gender and tumor group (median age 61.5, range 35–84, 12 breast, 12 gynecological, 13 colorectal, 12 lung and 11 renal). Twenty-one PRAE items were completed on a touch-screen computer. Subsequent audio-recorded cognitive interviews and thematic analysis explored patients’ comprehension of items via verbal probing techniques during three interview rounds (n = 20 patients/round). Results: In total 33 item amendments were made; 29% related to question comprehension, 73% response option and 3% order effects. These amendments to phrasing and language improved patient understanding but maintained CTCAE grading and key medical information. Changes were endorsed by members of a patient advisory group (N = 11). Conclusion: Item adaptations resulted in a bank of consistently interpreted self-report AE items for use in future research program. In-depth analysis of items through cognitive interviews is an important step towards developing an internationally valid system for PRAE, thus improving patient safety and experiences during cancer treatment