Study protocol for two stepped-wedge interventional trials evaluating the effects of holistic information technology-based patient-oriented management in older multimorbid patients with cancer: The GERONTE trials

INTRODUCTION

Current hospital-based care pathways are generally single-disease centred. As a result, coexisting morbidities are often suboptimally evaluated and managed, a deficiency becoming increasingly apparent among older patients who exhibit heterogeneity in health status, functional abilities, frailty, and other geriatric impairments. To address this issue, our study aims to assess a newly developed patient-centred care pathway for older patients with multimorbidity and cancer. The new care pathway was based on currently available evidence and co-designed by end-users including health care professionals, patients, and informal caregivers. Within this care pathway, all healthcare professionals involved in the care of older patients with multimorbidity and cancer will form a Health Professional Consortium (HPC). The role of the HPC will be to centralise oncologic and non-oncologic treatment recommendations in accordance with the patient's priorities. Moreover, an Advanced Practice Nurse will act as case-manager by being the primary point of contact for the patient, thus improving coordination between specialists, and by organising and leading the consortium. Patient monitoring and the HPC collaboration will be facilitated by digital communication tools designed specifically for this purpose, with the added benefit of being customisable for each patient.

MATERIALS AND METHODS

The GERONTE study is a prospective international, multicentric study consisting of two stepped-wedge trials performed at 16 clinical sites across three European countries. Each trial will include 720 patients aged 70 years and over with a new or progressive cancer (breast, lung, colorectal, prostate) and at least one moderate or severe multimorbidity. The patients in the intervention group will receive the new care pathway whereas patients in the control group will receive usual oncologic care.

DISCUSSION

GERONTE will evaluate whether this kind of holistic, patient-oriented healthcare management can improve quality of life (primary outcome) and other valuable endpoints in older patients with multimorbidity and cancer. An ancillary study will assess in depth the socio-economic impact of the intervention and deliver concrete implementation guidelines for the GERONTE intervention care pathway.

TRIAL REGISTRATION

FRONE: NCT05720910 TWOBE: NCT05423808.

Promoting the systematic use of real-world data and real-world evidence for digital health technologies across Europe: a consensus framework

Despite the acceleration in the use of digital health technologies across different aspects of the healthcare system, the full potential of real-world data (RWD) and real-world evidence (RWE) arising from the technologies is not being utilised in decision-making. We examine current national efforts and future opportunities to systematically use RWD and RWE in decision-making in five countries (Estonia, Finland, Germany, Italy and the United Kingdom), and then develop a framework for promotion of the systematic use of RWD and RWE. A review assesses current national efforts, complemented with a three-round consensus-building exercise among an international group of experts (n1 = 44, n2 = 24, n3 = 24) to derive key principles. We find that Estonia and Finland have invested and developed digital health-related policies for several years; Germany and Italy are the more recent arrivals, while the United Kingdom falls somewhere in the middle. Opportunities to promote the systematic use of RWD and RWE were identified for each country. Eight building blocks principles were agreed through consensus, relating to policy scope, institutional role and data collection. Promoting post-market surveillance and digital health technology vigilance ought to rely on clarity in scope and data collection with consensus reached on eight principles to leverage RWD and RWE.

Implementation of Machine Learning Applications in Health Care Organizations: Protocol for a Systematic Review of Empirical Studies

BACKGROUND

An increasing interest in machine learning (ML) has been observed among scholars and health care professionals. However, while ML-based applications have been shown to be effective and have the potential to change the delivery of patient care, their implementation in health care organizations is complex. There are several challenges that currently hamper the uptake of ML in daily practice, and there is currently limited knowledge on how these challenges have been addressed in empirical studies on implemented ML-based applications.

OBJECTIVE

The aim of this systematic literature review is twofold: (1) to map the ML-based applications implemented in health care organizations, with a focus on investigating the organizational dimensions that are relevant in the implementation process; and (2) to analyze the processes and strategies adopted to foster a successful uptake of ML.

METHODS

We developed this protocol following the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. The search was conducted on 3 databases (PubMed, Scopus, and Web of Science), considering a 10-year time frame (2013-2023). The search strategy was built around 4 blocks of keywords (artificial intelligence, implementation, health care, and study type). Based on the detailed inclusion criteria defined, only empirical studies documenting the implementation of ML-based applications used by health care professionals in clinical settings will be considered. The study protocol was registered in PROSPERO (International Prospective Register of Systematic Reviews).

RESULTS

The review is ongoing and is expected to be completed by September 2023. Data analysis is currently underway, and the first results are expected to be submitted for publication in November 2023. The study was funded by the European Union within the Multilayered Urban Sustainability Action (MUSA) project.

CONCLUSIONS

ML-based applications involving clinical decision support and automation of clinical tasks present unique traits that add several layers of complexity compared with earlier health technologies. Our review aims at contributing to the existing literature by investigating the implementation of ML from an organizational perspective and by systematizing a conspicuous amount of information on factors influencing implementation.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47971.

Implementing shared decision-making interventions in breast cancer clinical practice: a scoping review

BACKGROUND

Shared decision-making (SDM) is a collaborative process whereby patients and clinicians jointly deliberate on the best treatment option that takes into account patients' preferences and values. In breast cancer care, different treatment options have become available to patients in the last decade. Various interventions, including patient decision aids (PtDAs), have been designed to promote SDM in this disease area. This study aimed at investigating the factors that influence the successful adoption and implementation of SDM interventions in real-world healthcare delivery settings.

METHODS

A scoping review of scientific and grey literature was conducted for the period 2006-2021 to analyse the support for SDM interventions and their adoption in breast cancer clinical practice. The interpretation of findings was based on the Practical, Robust Implementation and Sustainability Model (PRISM) for integrating research findings into practice.

RESULTS

Overall, 19 studies were included for data synthesis, with more than 70% published since 2017. The availability of SDM tools does not automatically translate into their actual use in clinical settings. Factors related to users' co-creation, the clinical team's attitude and knowledge, organisational support and regulatory provisions facilitate the adoption of SDM interventions. However, overlooking aspects such as the re-organisation of care pathways, patient characteristics, and assigning of resources (human, financial, and facilities) can hinder implementation efforts.

CONCLUSIONS

Compared to the mounting evidence on the efficacy of SDM interventions, knowledge to support their sustained implementation in daily care is still limited, albeit results show an increasing interest in strategies that facilitate their uptake in breast cancer care over time. These findings highlight different strategies that can be used to embed SDM interventions in clinical practice. Future work should investigate which approaches are more effective in light of organisational conditions and external factors, including an evaluation of costs and healthcare system settings.

Impella Versus VA-ECMO for Patients with Cardiogenic Shock: Comprehensive Systematic Literature Review and Meta-Analyses

Impella and VA-ECMO are two possible therapeutic courses for the treatment of patients with cardiogenic shock (CS). The study aims to perform a systematic literature review and meta-analyses of a comprehensive set of clinical and socio-economic outcomes observed when using Impella or VA-ECMO with patients under CS. A systematic literature review was performed in Medline, and Web of Science databases on 21 February 2022. Nonoverlapping studies with adult patients supported for CS with Impella or VA-ECMO were searched. Study designs including RCTs, observational studies, and economic evaluations were considered. Data on patient characteristics, type of support, and outcomes were extracted. Additionally, meta-analyses were performed on the most relevant and recurring outcomes, and results shown using forest plots. A total of 102 studies were included, 57% on Impella, 43% on VA-ECMO. The most common outcomes investigated were mortality/survival, duration of support, and bleeding. Ischemic stroke was lower in patients treated with Impella compared to the VA-ECMO population, with statistically significant difference. Socio-economic outcomes including quality of life or resource use were not reported in any study. The study highlighted areas where further data collection is needed to clarify the value of complex, new technologies in the treatment of CS that will enable comparative assessments focusing both on the health impact on patient outcomes and on the financial burden for government budgets. Future studies need to fill the gap to comply with recent regulatory updates at the European and national levels.

Evaluating barriers and facilitators to the uptake of mHealth apps in cancer care using the Consolidated Framework for Implementation Research (CFIR): A scoping literature review (Preprint)

BACKGROUND

Mobile health (mHealth) solutions have proven to be effective in a wide range of patient outcomes and have proliferated over time. However, a persistent challenge of digital health technologies, including mHealth, is that they are characterized by early dropouts in clinical practice and struggle to be used outside experimental settings or on larger scales.

OBJECTIVE

This study aimed to explore barriers and enablers to the uptake of mHealth solutions used by patients with cancer undergoing treatment, using a theory-guided implementation science model, that is, the Consolidated Framework for Implementation Research (CFIR).

METHODS

A scoping literature review was conducted using PubMed (MEDLINE), Web of Science, and ScienceDirect databases in March 2022. We selected studies that analyzed the development, evaluation, and implementation of mHealth solutions for patients with cancer that were used in addition to the standard of care. Only empirical designs (eg, randomized controlled trials, observational studies, and qualitative studies) were considered. First, information on the study characteristics, patient population, app functionalities, and study outcomes was extracted. Then, the CFIR model was used as a practical tool to guide data collection and interpretation of evidence on mHealth uptake.

RESULTS

Overall, 91 papers were included in the data synthesis. The selected records were mostly randomized controlled trials (26/91, 29%) and single-arm, noncomparative studies (52/91, 57%). Most of the apps (42/73, 58%) were designed for both patients and clinicians and could be used to support any type of cancer (29/73, 40%) and a range of oncological treatments. Following the CFIR scheme (intervention, outer setting, inner setting, individuals, process), multistakeholder co-design, codevelopment, and testing of mHealth interventions were identified as key enablers for later uptake. A variety of external drivers emerged, although the most relevant outer incentive fostering mHealth use was addressing patient needs. Among organizational factors likely to influence technology uptake, interoperability was the most prominent, whereas other providers' dimensions such as managerial attitudes or organizational culture were not systematically discussed. Technology-related impediments that could hamper the use of mHealth at the individual level were considered least often.

CONCLUSIONS

The hype surrounding mHealth in cancer care is hindered by several factors that can affect its use in real world and nonexperimental settings. Compared with the growing evidence on mHealth efficacy, knowledge to inform the uptake of mHealth solutions in clinical cancer care is still scarce. Although some of our findings are supported by previous implementation research, our analysis elaborates on the distinguishing features of mHealth apps and provides an integrated perspective on the factors that should be accounted for implementation efforts. Future syntheses should liaise these dimensions with strategies observed in successful implementation initiatives.