Impact of Mental Disorders on the Association Between Adherence to Antihypertensive Agents and All‐Cause Healthcare Costs
Bibliographic record
Abstract
Depression and anxiety are factors associated with poor adherence to medications that lead to increased healthcare costs. The authors hypothesize that these conditions will moderate the association between adherence and healthcare costs. The aim was to examine the healthcare costs associated with adherence to antihypertensive agents in the elderly with and without depression and anxiety. The sample included participants with hypertension and used hypertensive agents (N=926). Medication possession ratio was used to calculate medication adherence. Mean total healthcare costs included costs for inpatient stays, emergency department visits, outpatient visits, physician fees, and outpatient medications. Mental disorders were assessed using a questionnaire based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria. The total healthcare costs were significantly greater for nonadherent participants with depression/anxiety than for adherent participants without depression/anxiety (Δ$1841, P<.0001). This study suggests that treating mental disorders in elderly patients with hypertension will decrease total healthcare costs.
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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 | 0.001 | 0.003 |
| 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".