Trial reportBMC health services research2022
Budget impact analysis of a multifaceted nurse-led intervention to reduce indwelling urinary catheter use in New South Wales Hospitals.
Trial report in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed, 1 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn hospitals, catheter acquired urinary tract infection causes significant resource waste and discomfort among admitted patients. An intervention for reducing indwelling catheterisations - No-CAUTI - was trialled across four hospitals in New South Wales, Australia. No-CAUTI includes: train-the-trainer workshops, site champions, compliance audits, and point prevalence surveys. The trial showed reductions on usual care catheterisation rates at 4- and 9-month post-intervention. This result was statistically non-significant; and post-intervention catheterisation rates rebounded between 4 and 9 months. However, No-CAUTI showed statistically significant catheterisation decreases for medical wards, female patients and for short-term catheterisations. This study presents a budget impact analysis of a projected five year No-CAUTI roll out across New South Wales public hospitals, from the cost perspective of the New South Wales Ministry of Health.
methodsBudget forecasts were made for five year roll outs of: i) No-CAUTI; and ii) usual care, among all public hospitals in New South Wales hosting overnight stays (n=180). The roll out design maintains intervention effectiveness with ongoing workshops, quality audits, and hospital surveys. Forecasts of catheterisations, procedures and treatments were modelled on No-CAUTI trial observations. Costs were sourced from trial records, the Medical Benefits Scheme, the Pharmaceutical Benefits Scheme and public wage awards. Cost and parameter uncertainties were considered with sensitivity scenarios.
resultsThe estimated five-year No-CAUTI roll-out cost was $1.5 million. It had an overall budget saving of $640,000 due to reductions of 100,100 catheterisations, 33,300 urine tests and 6,700 antibiotics administrations. Non-Metropolitan hospitals had a net saving of $1.2 million, while Metropolitan hospitals had a net cost of $0.54 million.
conclusionsCompared to usual care, NO-CAUTI is expected to realise overall budget savings and decreases in catheterisations over five years. These findings allow a consideration of the affordability of a wide implementation.
trial registrationRegistered with the Australian New Zealand Clinical Trials Registry ( ACTRN12617000090314 ). First registered 17 January 2017, retrospectively. First enrolment, 15/11/2016.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.