Primary Care Providers Barriers, Comfort and Awareness in Follow-up Care of Acute Kidney Injury Patients: A Comprehensive Survey on Current Practices
Bibliographic record
Abstract
Background: Patients who experienced acute kidney injury (AKI) may benefit from dedicated care following hospital discharge. Most of these patients will be followed by primary care providers. There is a lack of data on current practices and comfort for these care providers when offering post-AKI care. Objective: We surveyed nurse practitioners and family physicians to assess their awareness, perceptions, practice patterns and comfort regarding post-AKI care. Design/Setting: We distributed a web-based self-administered survey among clinicians from the Province of Quebec. We asked about their awareness and perceptions on how AKI should be disclosed and followed, the barriers encountered regarding the process of care following hospital discharge, and their level of comfort and expertise in offering dedicated post-AKI care. The survey integrated direct and scenario-based questions and was conducted from December 2022 to April 2023. Participants: , respectively. No incentives were provided. Methods: We conducted descriptive analyses and used chi-squared analysis to compare responses between family physicians and nurse practitioners and between hospital-based and cabinet-based practice. Results: The survey was opened by 779 potential participants. Of these, the response rate was 9% (70/779). Most participants were family physicians (79%) and dedicated 70% (±32) of their time in community outpatient clinics. Participants reported that 59% (±20) of all patients seen daily had at least 1 risk factor for AKI, whereas they estimated that 21% (±12) of recently discharged patients suffered from an AKI episode. The lack of awareness by the patient and lack of details on the discharge summary were the barriers most frequently reported impacting the overall process of care at follow-up. Most nurse practitioners (60%) and 33% of family physicians reported at least some levels of discomfort and lack of expertise when offering post-AKI. Limitations: The generalizability of our study is limited by its response rate. However, this is comparable with typical response rates seen in electronic surveys. The distribution was limited to a single province of Canada. Conclusions: We reported significant barriers regarding the hospital-to-community transition of care in patients who experienced AKI and the suboptimal comfort and expertise of primary care providers when offering dedicated post-AKI care. This reflects the need to improve communication, collaboration, and AKI training with primary care providers.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".