A Remote Evaluation of NAVIFY Oncology Hub Using Clinical Simulation

Oncology

Digital Health, Health tech, Clinical simulation, Healthcare technology

This work seeks to understand current clinical workflow practice and validate use cases for NAVIFY Oncology Hub. The main purpose of NAVIFY Oncology Hub is to enhance clinical and operational effectiveness, from diagnostic workup to treatment planning and management. This might free up providers' time and capacity to provide better and more personalized care to patients. This research protocol builds on previous work that validated clinical simulation methods as a means for clinicians to generate useful insights during the testing and development of digital health tools (Gardner et al. 2020). Accordingly, this study aims to test the ability of NAVIFY Oncology Hub to increase the work efficiency of oncologists and reduce the cognitive burden/mental fatigue associated with patient care and decision-making. The insights generated will be used to guide the development of NAVIFY Oncology Hub and optimise user experience, as well as provide a better understanding of the opportunities for it to have maximal impact in the decision-making process.

NAVIFY Oncology Hub is a platform that aggregates and organizes disparate data into an intuitive, longitudinal view of the patient's cancer care journey. The platform is designed to optimize and support oncology workflows and decision-making by providing quick access to the most relevant data in one place, so that providers can make decisions more efficiently and collaborate more seamlessly. Clinical workflow is critical for the efficient and safe delivery of patient care. In most healthcare settings, clinical workflow is highly complex, and reflects the multidisciplinary collaboration and communication required of most clinical tasks. Studies have demonstrated a positive association between leveraging health information technology workflow tools for care coordination and patient engagement, and improved process quality metrics in preventive screening, diabetes control, as well as maternal and child health (Kruse & Bean 2018; Kranz et al. 2018). Embedded decision support tools have also been proven to improve the performance of risk assessments conducted by providers, as well as enhance patient safety and decrease mortality (Chaudhry et al. 2006; Wells et al. 2008; Jones et al. 2014; Campanella et al. 2015). A set of 10 synthetic breast cancer patient cases will be developed by Prova Health. Cases will include history and examination findings, pathology reports, radiology reports and images (USS, mammogram, CT as applicable) and reports on tumor characteristics. The case details will be representative of a long term patient journey, inclusive of treatment lines such as adjuvant and neoadjuvant therapies. Cases will be selected to span the range of potential case scenarios seen in typical practice. Specifically, cases will be selected to include common invasive breast cancers (eg. IDC, ILC), as well as less common invasive breast cancers (eg. inflammatory). Cases will also represent a range of cancers with different molecular subtypes, such as whether the patient is HER2 positive or negative, hormone receptor (HR) positive or negative or triple negative. Finally, cases will also reflect the presentation of patients at various stages (eg. primary diagnosis, locally and regional advanced breast cancer, recurrent breast cancer, or metastatic advanced breast cancer). Each participant will participate in a 90-minute remote (e.g., online) simulation session. During scheduling, participants will be given a link to use to join the session. This link will take them to a video conference call hosted through Google Meet. At the session, the moderator will facilitate the session and take notes. Participants will use NAVIFY Oncology Hub to review synthetic patient cases. Participants will be tasked with reviewing the cases as if they were preparing to see a patient in a real clinical setting. This task will involve searching for, identifying, reviewing and synthesizing relevant clinical information (demographic information, pathology reports, clinical course, etc.) that supports decision-making. As such, this task is meant to simulate the same activities they would perform in their typical practice before inviting a patient into the clinic room for a consultation, and will permit this study to examine the usage of NAVIFY Oncology Hub on those activities. Ultimately, the aim of the study is to investigate how NAVIFY Oncology Hub improves efficiency and reduces cognitive burden associated with reviewing and synthesizing patient information, and having participants engage with the platform requires them to go through those tasks.

United Kingdom

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