The Drug Burden Index and Level of Frailty as Determinants of Healthcare Costs in a Cohort of Older Frail Adults in New Zealand
Bibliographic record
Abstract
OBJECTIVES: Frailty is common in older people and is associated with increased use of healthcare services and ongoing use of multiple medications. This study provides insights into the healthcare cost structure of a frail group of older adults in Aotearoa, New Zealand. Furthermore, we investigated the relationship between participants' anticholinergic and sedative medication burden and their total healthcare costs to explore the viability of deprescribing interventions within this cohort. METHODS: Healthcare cost analysis was conducted using data collected during a randomized controlled trial within a frail, older cohort. The collected information included participant demographics, medications used, frailty, cost of service use of aged residential care and outpatient hospital services, hospital admissions, and dispensed medications. RESULTS: Data from 338 study participants recruited between 25 September 2018 and 30 October 2020 with a mean age of 80 years were analyzed. The total cost of healthcare per participant ranged from New Zealand $15 (US dollar $10) to New Zealand $270 681 (US dollar $175 943) over 6 months postrecruitment into the study. Four individuals accounted for 26% of this cohort's total healthcare cost. We found frailty to be associated with increased healthcare costs, whereas the drug burden was only associated with increased pharmaceutical costs, not overall healthcare costs. CONCLUSIONS: With no relationship found between a patient's anticholinergic and sedative medication burden and their total healthcare costs, more research is required to understand how and where to unlock healthcare cost savings within frail, older populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".