ArticleBMC health services research2004
Assessing the impact of heart failure specialist services on patient populations.
Article in BMC health services research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Delayed Improvement of Left Ventricular Function in Newly Diagnosed Heart Failure Depends on Etiology-A PROLONG-II Substudy.Sensors (Basel, Switzerland) · 2022Article
- Population impact of stricter adherence to recommendations for pharmacological and lifestyle interventions over one year in patients with coronary heart disease.Journal of epidemiology and community health · 2005Article
- Factors influencing emergency medical readmission risk in a UK district general hospital: A prospective study.BMC emergency medicine · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe assessment of the impact of healthcare interventions may help commissioners of healthcare services to make optimal decisions. This can be particularly the case if the impact assessment relates to specific patient populations and uses timely local data. We examined the potential impact on readmissions and mortality of specialist heart failure services capable of delivering treatments such as b-blockers and Nurse-Led Educational Intervention (N-LEI).
methodsStatistical modelling of prevented or postponed events among previously hospitalised patients, using estimates of: treatment uptake and contraindications (based on local audit data); treatment effectiveness and intolerance (based on literature); and annual number of hospitalization per patient and annual risk of death (based on routine data).
resultsOptimal treatment uptake among eligible but untreated patients would over one year prevent or postpone 11% of all expected readmissions and 18% of all expected deaths for spironolactone, 13% of all expected readmisisons and 22% of all expected deaths for b-blockers (carvedilol) and 20% of all expected readmissions and an uncertain number of deaths for N-LEI. Optimal combined treatment uptake for all three interventions during one year among all eligible but untreated patients would prevent or postpone 37% of all expected readmissions and a minimum of 36% of all expected deaths.
conclusionIn a population of previously hospitalised patients with low previous uptake of b-blockers and no uptake of N-LEI, optimal combined uptake of interventions through specialist heart failure services can potentially help prevent or postpone approximately four times as many readmissions and a minimum of twice as many deaths compared with simply optimising uptake of spironolactone (not necessarily requiring specialist services). Examination of the impact of different heart failure interventions can inform rational planning of relevant healthcare services.
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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.