The Kidney Score Platform for Patient and Clinician Awareness, Communication, and Management of Kidney Disease: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Patient awareness, clinician detection, and management of chronic kidney disease remain suboptimal, despite clinical practice guidelines and diverse education programs. OBJECTIVE: This protocol describes a study to develop and investigate the impact of the National Kidney Foundation Kidney Score Platform on chronic kidney disease awareness, communication, and management, by leveraging the Behavior Change Wheel, an implementation science framework that helps identify behavioral intervention targets and functions that address barriers to behavior change. METHODS: We interviewed 20 patients with chronic kidney disease and 11 clinicians to identify patient and clinician behaviors suitable for intervention and barriers to behavior change (eg, limited awareness of chronic kidney disease clinical practice guidelines within primary care settings, limited data analytics to highlight chronic kidney disease care gaps, asymptomatic nature of chronic kidney disease in conjunction with patient reliance on primary care clinicians to determine risk and order kidney testing). Leveraging the Behavior Change Wheel, the Kidney Score Platform was developed with a patient-facing online Risk Calculator and a clinician-facing Clinical Practice Toolkit. The Risk Calculator utilizes risk predictive analytics to provide interactive health information tailored to an individual's chronic kidney disease risk and health status. The Clinical Practice Toolkit assists clinicians in discussing chronic kidney disease with individuals at risk for and with kidney disease and in managing their patient population with chronic kidney disease. The Kidney Score Platform will be tested in 2 Veterans Affairs primary health care settings using a pre-post study design. Outcomes will include changes in patient self-efficacy for chronic kidney disease management (primary outcome), quality of communication with clinicians about chronic kidney disease, and practitioners' knowledge of chronic kidney disease guidelines. Process outcomes will identify usability and adoption of different elements of the Kidney Score Platform using qualitative and quantitative methods. RESULTS: As of September 2020, usability studies are underway with veterans and clinicians to refine the patient-facing components of the Kidney Score Platform before study initiation. Results and subsequent changes to the Kidney Score Platform will be published at a later date. The study is expected to be completed by December 2021. CONCLUSIONS: Results of this study will be used to inform integration of the Kidney Score Platform within primary care settings so that it can serve as a central component of the National Kidney Foundation public awareness campaign to educate, engage, and empower individuals at risk for and living with chronic kidney disease. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/22024.
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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 | 0.061 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.086 | 0.016 |
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".