ArticleBMC health services research2018
Development of a benchmark tool for cancer centers; results from a pilot exercise.
Article in BMC health services research, 2018. 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, 6 citations in OpenAlex.
- Unlocking the Power of Benchmarking: Real-World-Time Data Analysis for Enhanced Sarcoma Patient Outcomes.Cancers · 2023Article
- Implementation and performance of haemovigilance systems in 10 sub-saharan African countries is sub-optimal.BMC health services research · 2021Article
- Quality-assured research environments for translational cancer research.Molecular oncology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 5 countries.
Funding
Abstract
backgroundDifferences in cancer survival exist between countries in Europe. Benchmarking of good practices can assist cancer centers to improve their services aiming for reduced inequalities. The aim of the BENCH-CAN project was to develop a cancer care benchmark tool, identify performance differences and yield good practice examples, contributing to improving the quality of interdisciplinary care. This paper describes the development of this benchmark tool and its validation in cancer centers throughout Europe.
methodsA benchmark tool was developed and executed according to a 13 step benchmarking process. Indicator selection was based on literature, existing accreditation systems, and expert opinions. A final format was tested in eight cancer centers. Center visits by a team of minimally 3 persons, including a patient representative, were performed to verify information, grasp context and check on additional questions (through semi-structured interviews). Based on the visits, the benchmark methodology identified opportunities for improvement.
resultsThe final tool existed of 61 qualitative and 141 quantitative indicators, which were structured in an evaluative framework. Data from all eight participating centers showed inter-organization variability on many indicators, such as bed utilization and provision of survivorship care. Subsequently, improvement suggestions for centers were made; 85% of which were agreed upon.
conclusionA benchmarking tool for cancer centers was successfully developed and tested and is available in an open format. The tool allows comparison of inter-organizational performance. Improvement opportunities were successfully identified for every center involved and the tool was positively evaluated.
Indexed as
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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.