Comparing Clinical Outcomes and Health Care Utilization: Telehealth Versus Traditional Care at US Rural Hemodialysis Units
Bibliographic record
Abstract
Objective: To determine whether novel dialysis delivery models, such as telehealth visits combined with face-to-face visits in a hybrid model (telehealth hybrid model), positively influence clinical outcomes and healthcare utilization. Patients and Methods: This retrospective cohort study compares the rates of emergency department visits, hospitalizations, and Medicare established hemodialysis quality metrics before and after implementation of a telehealth hybrid model focused among rural populations in regions served by the Mayo Clinic dialysis system between January 1, 2020, to December 31, 2020, versus face-to-face visits alone before implementation of the program from January 1, 2019, to December 31, 2019. In addition, we used a standardized anonymous survey to examine patient perspectives toward the implementation of telehealth at the dialysis units. Results: =.68) or clinical outcomes (abnormal laboratory measures) between the telehealth and standard care groups were observed. Patient satisfaction with telehealth was high, with 90% reporting successful video visits. Conclusion: Our study provides evidence suggesting that the telehealth hybrid model can deliver nephrology care comparable to traditional care models in in-center dialysis without negatively impacting clinical outcomes, health care utilization, or patient satisfaction. Further research is necessary to confirm these results in other settings and to explore the long-term impacts of such hybrid care models.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".