Feasibility and implementation of an eHealth dashboard for the remote monitoring of Dutch CML patients: Multi Methods approach
ABSTRACT
Background:
Healthcare resource utilization and costs are increasing due to the aging population and rising numbers of long-living patients with chronic diseases, including cancers. Innovative approaches, such as eHealth, could enable the delivery of sustainable, affordable, and patient-centered care. The Dutch CMyLife digital care platform aims to inform and empower patients and provide them with tools to manage their disease. The CML-dashboard for healthcare professionals is the first step to enable remote monitoring of Dutch CML-care.
Objective:
The aim of this study is to explore the use of this CML-dashboard to remotely monitor the care of CML patients, and the barriers and facilitators for implementation in regular care.
Methods:
A mixed method approach was used. Quantitative data was retrieved from the CML-dashboard during 2.5 years and descriptive statistics were used for analysis. In a qualitative approach barriers and facilitators for implementation were explored, using semi-structured interviews with healthcare professionals of CML patients. Transcripts were analyzed using framework analysis.
Results:
Quantitative data showed information about the population using the CML-dashboard, their TKI treatment, BCR::ABL1 values, and guideline-driven monitoring appointments. Data of 177/199 patients was included for analysis. First used TKI was registered by 146 of 177 patients (82%). Mean first registered BCR::ABL1 value was 19.66 (% IS) and 57.1% of CML patients started with using imatinib. Usefulness of data was suboptimal due to manual input of data by patients. Although many facilitators of the CML-dashboard were identified by end users, barriers were also mentioned, as for example lack of compatibility with other information systems.
Conclusions:
This is the first attempt showing that remote monitoring of CML patients is feasible. However, future data infrastructure should enable automation of data input from electronic medical records, ensuring complete and reliable data which can be useful for remote monitoring and real-world data driven guideline adjustments. This step needs to be taken before CML care can be moved towards the home environment.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.