Circular Business Model for Digital Health Solutions: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: The circular economy reshapes the linear "take, make, and dispose" approach and evolves around minimizing waste and recapturing resources in a closed-loop system. The health sector accounts for 4.6% of global greenhouse gas emissions and has, over the decades, been built to rely on single-use devices and deal with high volumes of medical waste. With the increase in the adoption of digital health solutions in the health care industry, leading the industry into a new paradigm of how we provide health care, a focus must be put on the amount of waste that will follow. Digital health solutions will shape health care through the use of technology and lead to improved patient care, but they will also make medical waste more complex to deal with due to the e-waste component. Therefore, a transformation of the health care industry to a circular economy is a crucial cornerstone in decreasing the impact on the environment. OBJECTIVE: This study aims to address the lack of direction in the current literature on circular business models. It will consider micro, meso, and macro factors that would impact the operational validity of circular models using the digital health solutions ePaper label (medical packaging), smart wearable sensor (health monitoring devices), smart pill box (medication management), and endo-cutter (surgical equipment) as examples. METHODS: The study will systematically perform a scoping review through a database and snowball search. We will analyze and classify the studies from a predetermined set of categories and then summarize them into an evidence map. Based on the review, the study will develop a 2D framework for businesses to follow or for future research to take a standpoint from. RESULTS: Preliminarily, the review has analyzed 26 studies in total. The results are close to equally distributed among the micro (8/26, 31%), meso (10/26, 38%), and macro (8/26, 31%) levels. Circular economy studies emphasize several circular practices such as recycling (17/26, 65%), reusing (18/26, 69%), reducing (15/26, 58%), and remanufacturing (8/26, 31%). The value proposition in the examined business model is mostly dominated by stand-alone products (18/26, 69%) compared to product as a service (7/26, 27%), involving stakeholders such as health care professionals or hospitals (20/26, 77%), manufacturers (11/26, 42%), and consumers (9/26, 35%). All studies encompass societal (12/26, 46%), economic (23/26, 88%), and environmental (24/26, 92%) viewpoints. CONCLUSIONS: The study argues that each digital health solution would have to be accessed individually to find the optimal business model to follow. This is due to their differing life cycles and complexity. The manufacturer will need a layered value proposition, implementing several business models dependent on their respective product portfolios. The need to incorporate several business models implies an ecosystem perspective that is relevant to consider. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47874.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.077 | 0.158 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.034 | 0.036 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.085 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".