Influence of the COVID-19 Pandemic on Overall Physician Visits and Telemedicine Use Among Patients With Type 1 or Type 2 Diabetes in Japan
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Bibliographic record
Abstract
BACKGROUND: Regular visits with healthcare professionals are important for preventing serious complications in patients with diabetes. The purpose of this retrospective cohort study was to clarify whether there was any suppression of physician visits among patients with diabetes during the spread of the novel coronavirus 2019 (COVID-19) in Japan and to assess whether telemedicine contributed to continued visits. METHODS: We used the JMDC Claims database, which contains the monthly claims reported from July 2018 to May 2020 and included 4,595 (type 1) and 123,686 (type 2) patients with diabetes. Using a difference-in-differences analysis, we estimated the changes in the monthly numbers of physician visits or telemedicine per 100 patients in April and May 2020 compared with the same months in 2019. RESULTS: For patients with type 1 diabetes, the estimates for total overall physician visits were -2.53 (95% confidence interval [CI], -4.63 to 0.44) in April and -8.80 (95% CI, -10.85 to -6.74) in May; those for telemedicine visits were 0.71 (95% CI, 0.47-0.96) in April and 0.54 (95% CI, 0.32-0.76) in May. For patients with type 2 diabetes, the estimates for overall physician visits were -2.50 (95% CI, -2.95 to -2.04) in April and -3.74 (95% CI, -4.16 to -3.32) in May; those for telemedicine visits were 1.13 (95% CI, 1.07-1.20) in April and 0.73 (95% CI, 0.68-0.78) in May. CONCLUSION: The COVID-19 pandemic was associated with suppression of physician visits and a slight increase in the utilization of telemedicine among patients with diabetes during April and May 2020.
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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 | 0.006 |
| 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 | 0.001 |
| 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 it