Assessing the quality of cardiac rehabilitation programs by measuring adherence to the Australian quality indicators.
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Australian National Health and Medical Research Council (NHMRC) Background Cardiac rehabilitation (CR) prevents recurrent cardiac events and supports patients’ return to an active and fulfilling lifestyle. Evidence on the efficacy of CR programs is well established, but variability of quality across programs may compromise patient outcomes. Core components, quality indicators (QIs) and accreditation of programs have been introduced internationally to increase program standardisation, quality and outcomes. (1) The Australian Cardiovascular Health and Rehabilitation Association (ACRA) and National Heart Foundation (NHF) recently published 10 QIs for CR, comprising process and outcome indicators that can guide delivery of evidence-based service content (Figure 1). (2) Purpose The aim was to assess the performance of CR programs in Australia through their adherence to the measurement of the Australian QIs. Methods A cross-sectional survey design with face validity testing was used to formulate questions to evaluate CR program performance based on adherence to 9 of the 10 Australian QIs. Between October 2020- December 2021, all 23 CR programs across country and metropolitan areas of South Australia (SA) participated. In addition, each QI was weighted by an expert group of clinician researchers and a service performance score was calculated out of 16. According to the score quartiles, programs could be categorised across 4 performance levels: Poor (0-4.5), Low (5-8.5), Medium (9-12.5) or High (13-16). Results Among the 23 participating CR programs, median wait time from discharge to enrolment (QI-2) was 27 days, (interquartile range 19.0-46.0) and completions of enrolled were 66% (n=1316 /1972). All QIs were measured, but not by all programs. Pre-program QI adherence was higher than post program for depression, medication adherence, health-related quality of life and comprehensive re-assessment (Figure 1). Health-related quality of life (HRQOL) was poorly measured pre and post program (21.7% versus 17.3%). For functional exercise capacity assessment, the six-minute walk test was used by 69.5% of programs. Mean performance score was 11.4 /16 (SD ±0.79). Most (74%) programs were ranked at a medium level of performance, whereas 13% were ranked at low and high levels and none as poor. Conclusions A survey of 23 CR programs showed gaps in adherence to measurement of the ACRA/NHF Quality indicators in SA, including re-assessment (QI9), HRQOL (QI-8), medication adherence (QI-6) and exercise capacity (QI-7). Service performance scores were lower than an Australian national audit for each category, with United Kingdom data showing more services in the high and less in the medium category than SA. These data give us a baseline from which to improve CR service quality and outcomes.
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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 | 0.034 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".