Clinical effectiveness and cost-effectiveness of ambulatory heart failure nurse-led services: an integrated review
Bibliographic record
Abstract
BACKGROUND: Globally the burden of heart failure is rising. Hospitalisation is one of the main contributors to the burden of heart failure and unfortunately, the majority of heart failure patients will experience multiple hospitalisations over their lifetime. Considering the high health care cost associated with heart failure, a review of economic evaluations of post-discharge heart failure services is warranted. AIM: An integrated review of the economic evaluations of post-discharge nurse-led heart failure services for patients hospitalised with acute heart failure. METHODS: Electronic databases were searched using EBSCOHost: CINAHL complete, Medline complete, Embase, Scopus, EconLit, Global Health, and Health source (Consumer and Nursing/Academic) for published articles until 22nd June 2021. The searches focussed on papers that examined the cost-effectiveness of nurse-led clinics or telemonitoring involving nurses to follow-up patients after hospitalisation for acute heart failure. GRADE criteria and CHEERS checklist were used to determine the quality of the evidence and the quality of reporting of the economic evaluation. RESULTS: Out of 453 studies identified, eight studies were included: four in heart failure clinics and four in telemonitoring programs. Five of the articles were cost-effectiveness analyses, one a cost comparison and two studies involved economic modelling The GRADE criteria were rated as high in five studies. In which, four studies examined the cost-effectiveness of telemonitoring programs. Based on the CHEERS checklist for reporting quality of economic evaluations, the majority of economic evaluations were rated between 86 and 96%. All the studies found the intervention to be cost-effective compared to usual care with Incremental Cost Effectiveness Ratios ranging from $18 259 (Canadian dollars)/life year gained to €40,321 per Quality Adjusted Life Years gained. CONCLUSION: Nurse-led heart failure clinics and telemonitoring programs were found to be cost-effective. Certainly, this review has shown that heart failure clinics and telemonitoring programs do represent value for money with their greatest impact and cost savings through reducing rehospitalisations.
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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 | 0.013 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".