ArticleLondon journal of primary care2013
Using routinely gathered data to empower locally led health improvements.
Article in London journal of primary care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Recipes for collaborative practice improvement and community development for health.London journal of primary care · 2013Article
- Recipes for collaborative practice improvement and community development for health.London journal of primary care · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data are routinely used throughout the NHS to report on and monitor performance. For example, detailed information regarding hospital episodes is reported via the Secondary Use Services (SUS) programme. Local commissioners use this data to monitor hospital contracts. In primary care, data such as glycaemic control of diabetes patients is extracted from general practice clinical systems to calculate practice payments for the 'Quality and Outcomes Framework' (QOF). We suggest that this routinely gathered data should also be used to help clusters of practices to learn from locally led innovation and to motivate long-term partnerships for interorganisational health improvement. Following the recent NHS reforms, the number of data sources that could facilitate this is likely to increase in size, variety and complexity. In this paper, we describe some of the existing data sources that could be used to do this; we also describe some of the dangers of using data in this way, and our conclusions about the best way forward.
Indexed as
Identifiers
25949692PMC3960638What 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.