Strategies for incorporating patient-reported outcomes in the care of people with chronic kidney disease (PRO kidney): a protocol for a realist synthesis
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcomes and experience measures (jointly referred to here as PROs) are internationally recognized as a means for patients to provide information about their quality of life, symptoms, and experiences with care. Although increasingly recognized as key to improving the quality of healthcare at individual (e.g., patients, caregivers, and providers) and aggregate (e.g., government, policy/system-wide decision-making) levels, there are important knowledge gaps in our understanding of how PROs are, and can be, used across different settings, particularly in nephrology to enhance person-centered care. This knowledge is needed for developing strategies to guide optimal use of PROs in nephrology care. Currently, no strategies exist. The purpose of this review is to address this knowledge gap by answering the following realist question: How can PROs be used to enhance person-centered nephrology care, both at individual and aggregate levels? METHODOLOGY: Realist synthesis is an explanatory approach to data synthesis that aims to explain how context and mechanisms influence the outcome of an intervention. An initial program theory will be developed through the systematic search of the published literature in bibliographic databases (Ovid MEDLINE, Ovid Embase, EBSCOhost CINAHL, Web of Science, and Scopus) on existing theories explaining how PROs are used in healthcare settings. This initial program theory will then be tested and refined through the process of realist synthesis, using context-mechanism-outcome configurations. A kidney-specific program theory will then be created to address the utilization of PROs in nephrology across individual and aggregate levels to augment person-centered care. Searching will be iterative and refined as data is extracted and analyzed using a pilot-tested context + mechanism = outcome heuristic. Throughout, we will consult methodological experts, research team practitioners, and the Patient Advisory Committee to help refine the theories. Last, we will develop and disseminate knowledge translation products widely to knowledge user groups. DISCUSSION: The utilization of PROs remains a challenge in nephrology. The findings from this synthesis will provide a framework to guide both policy makers and practitioners on how to enhance person-centered care through successful utilization of PROs across individual and aggregate levels in nephrology. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017056063.
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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 | 0.319 | 0.348 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.010 | 0.018 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.009 | 0.014 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
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".