Determining the Association Between Continuity of Primary Care and Acute Care Use in Chronic Kidney Disease: A Retrospective Cohort Study
Bibliographic record
Abstract
PURPOSE: Acute care use is high among individuals with chronic kidney disease (CKD). It is unclear how relational continuity of primary care influences downstream acute care use. We aimed to determine if poor continuity of care is associated with greater rates of acute care use and decreased prescriptions for guideline-recommended drugs. METHODS: We conducted a population-based retrospective cohort study of adults with stage 3-4 CKD and ≥3 visits to a primary care clinician during the period April 1, 2011 to March 31, 2014 in Alberta, Canada. Continuity was calculated using the Usual Provider Continuity index. Descriptive statistics were used to summarize patient and acute care encounter characteristics. Adjusted rates and incidence rate ratios for all-cause and CKD-related ambulatory care-sensitive condition (ACSC) hospitalizations and emergency department (ED) visits were estimated using negative binomial regression. Adjusted odds ratios for prescription use were estimated by multivariable logistic regression. RESULTS: Among 86,475 patients with CKD, 51.3%, 30.0%, and 18.7% had high, moderate, and poor continuity of care, respectively. There were 77,988 all-cause hospitalizations, 6,489 ACSC-related hospitalizations, 204,615 all-cause ED visits, and 8,461 ACSC-related ED visits during a median follow-up of 2.3 years. Rates of all-cause and ACSC hospitalization and ED use increased with poorer continuity of care in a stepwise fashion across CKD stages. Patients with poor continuity were less likely to be prescribed a statin. CONCLUSIONS: Poor continuity of care is associated with increased acute care use among patients with CKD. Targeted strategies that strengthen patient-physician relationships and guide physicians regarding guideline-recommended prescribing are needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".