Predictors of Provider-Patient Visit Frequency during Hemodialysis
Bibliographic record
Abstract
BACKGROUND/AIMS: In 2004, the Centers for Medicare and Medicaid Services tied reimbursement for outpatient hemodialysis services to the number of times per month providers see their dialysis patients, resulting in increased provider-patient visit frequency. Greater provider-patient visit frequency is associated with lower hospitalization risk for hemodialysis patients, and determinants of visit frequency are uncertain. We aimed to identify patient, provider, and dialysis facility characteristics associated with provider visit frequency. METHODS: This retrospective cohort study used United States Renal Data System (USRDS) data for point-prevalent patients receiving in-center hemodialysis on January 1, 2006 (n = 144,860). Patient characteristics were defined from January 1 to June 30, 2006, and provider-patient visit frequency (<4 vs. ≥4 visits/month) from July 1 to December 31, 2006. Patient characteristics were obtained from the USRDS. Provider data were obtained from the American Medical Association Physician Master File. We determined longitudinal associations between patient, provider, and facility characteristics and provider-patient visit frequency using logistic regression. RESULTS: Patient characteristics independently associated with greater provider-patient visit frequency included older age, African-American race, longer dialysis duration, higher comorbidity score, Medicaid eligibility, urban residence, better compliance with dialysis, and more hospital days during run-in. Provider characteristics associated with greater provider-patient visit frequency included more years in practice, graduation from a foreign medical school, shorter distance between provider office and dialysis unit, and caring for more dialysis patients; facility characteristics included free-standing, independent status. CONCLUSION: After the Medicare reimbursement policy change, several patient, provider, and facility characteristics were independently associated with greater dialysis provider-patient visit frequency.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".