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Design of a clustered observational study to predict emergency admissions in the elderly : statistical reasoning in clinical practice.

Lancaster, Gillian A. and Chellaswamy, Hannah and Taylor, Steve and Lyon, David and Dowrick, Chris (2007) Design of a clustered observational study to predict emergency admissions in the elderly : statistical reasoning in clinical practice. Journal of Evaluation in Clinical Practice, 13 (2). pp. 169-178. ISSN 1356-1294

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Abstract

Objective To describe the statistical design issues and practical considerations that had to be addressed in setting up a clustered observational study of emergency admission to hospital of elderly people. Study design and setting Clustered observational study (sample survey) of elderly people registered with 18 general practices in Halton Primary Care Trust in the north-west of England. Results The statistical design features that warranted particular attention were sample size determination, intra-class correlation, sampling and recruitment, bias and confounding. Pragmatic decisions based on derived scenarios of different design effects are discussed. A pilot study was carried out in one practice. From the remaining practices, a total of 4000 people were sampled, stratified by gender. The average cluster size was 200 and the intra-class correlation coefficient for the emergency admission outcome was 0.00034, 95% confidence interval (0–0.008). Conclusion Studies that involve sampling from clusters of people are common in a wide range of healthcare settings. The clustering adds an extra level of complexity to the study design. This study provides an empirical illustration of the importance of statistical as well as clinical reasoning in study design in clinical practice.

Item Type: Article
Journal or Publication Title: Journal of Evaluation in Clinical Practice
Uncontrolled Keywords: clustered observational study ; intra-class correlation coefficient ; multilevel logistic regression ; sample size
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 26973
Deposited By: Mr Richard Ingham
Deposited On: 20 Aug 2009 14:52
Refereed?: Yes
Published?: Published
Last Modified: 09 Oct 2013 15:17
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/26973

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