Using an Electronic Self‐Management Tool to Support Patients with Chronic Kidney Disease (CKD): A CKD Clinic Self‐Care Model
Bibliographic record
Abstract
New healthcare delivery models are needed to enhance the patient experience and improve quality of care for individuals with chronic conditions such as kidney disease. One potential avenue is to implement self-management strategies. There is growing evidence that self-management interventions help optimize various aspects of chronic disease management. With the increasing use of information technology (IT) in health care, chronic disease management programs are incorporating IT solutions to support patient self-management practices. IT solutions have the ability to promote key principles of self-management, namely education, empowerment, and collaboration. Positive clinical outcomes have been demonstrated for a number of chronic conditions when IT solutions were incorporated into self-management programs. There is a paucity of evidence for self-management in chronic kidney disease (CKD) patients. Furthermore, IT strategies have not been tested in this patient population to the same extent as other chronic conditions (e.g., diabetes, hypertension). Therefore, it is currently unknown if IT strategies will promote self-management behaviors and lead to improvements in overall patient care. We designed and developed an IT solution called My KidneyCare Centre to support self-management strategies for patients with CKD. In this review, we discuss the rationale and vision of incorporating an electronic self-management tool to support the care of patients with CKD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".