ArticleFrontiers in clinical diabetes and healthcare2022
Proposing a Practical, Simplified Framework for Implementing Integrated Diabetes Data and Technology Solutions.
Article in Frontiers in clinical diabetes and healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Diabetes Technology Meeting 2023.Journal of diabetes science and technology · 2024Article
- A study of the impact of digital technology on industrial ecologisation in the Yellow River Basin of China.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Diabetes is a uniquely quantifiable disease, and as technology and data have proliferated over the past two decades, so have the tools to manage diabetes. Patients and providers have at their disposal devices, applications, and data platforms that generate immense amounts of data, provide critical insights into a patient's disease, and allow for personalization of treatment plans. However, the proliferation of options also comes with new burdens for providers: selecting the right tool, getting buy-in from leadership, defining the business case, implementation, and maintenance of the new technology. The complexity of these steps can be overwhelming and sometimes lead to inaction, depriving providers and patients of the advantages of technology-assisted diabetes care. Conceptually, the adoption of digital health solutions can be thought of as occurring in five interconnected phases: Needs Assessment, Solution Identification, Integration, Implementation, and Evaluation. There are a number of existing frameworks to help guide much of this process, but relatively little attention has been focused on integration. Integration is a critical phase for a number of contractual, compliance, financial, and technical processes. Missing a step or doing them out of order can lead to significant delays and potentially wasted resources. To address this gap, we have developed a practical, simplified framework for integrating diabetes data and technology solutions that can guide clinicians and clinical leaders on the critical steps in adopting and implementing a new technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.