Thomas Lung1,2, Lei Si1,3, Richard Hooper4, Gian Luca Di Tanna5. 1. The George Institute for Global Health, University of New South Wales, Sydney, NSW, 2042, Australia. 2. Faculty of Medicine and Health, School of Public Health, Edward Ford Building A27, University of Sydney, Sydney, NSW, 2006, Australia. 3. School of Health Policy & Management, Nanjing Medical University, Nanjing, China. 4. Institute of Population Health Sciences, Queen Mary University of London, London, UK. 5. The George Institute for Global Health, University of New South Wales, Sydney, NSW, 2042, Australia. GDiTanna@georgeinstitute.org.au.
Abstract
BACKGROUND: Recently, there has been an increase in use of the stepped wedge trial (SWT) design in the context of health services research, due to its pragmatic and methodological advantages over the parallel group design. OBJECTIVE: Our objective was to summarise the statistical methods used when conducting economic evaluations alongside SWTs. METHODS: A systematic literature search extending to February 2020 was conducted in the PubMed, Scopus, Cochrane and National Health Service Economic Evaluation Database (NHS-EED) databases to find and evaluate studies where there was an intention to conduct an economic evaluation alongside an SWT. Studies were assessed for their eligibility, findings, reporting of statistical methods and quality of reporting. RESULTS: Of the 586 studies retrieved from the literature search, 69 studies were identified and included in this systematic review. A total of 54 studies were published protocols, with eight economic evaluations and seven studies reporting full trial results. Included studies varied in terms of their reporting of statistical methods, in both detail and methodology. There were 34 studies that did not report any statistical methods for the economic evaluation, and only 16 studies reported appropriate methods, mainly using some form of mixed/multilevel model, and two used seemingly unrelated regression. Twelve studies reported the use of generic bootstrap methods and other modelling techniques, whilst the remaining studies failed to appropriately account for clustering, correlation or adjustment for time. CONCLUSIONS: The use of appropriate statistical methods that account for time, clustering and correlation between costs and outcomes is an important part of SWT health economics analysis, one that will benefit from an effort to communicate the methods available and their performance.
BACKGROUND: Recently, there has been an increase in use of the stepped wedge trial (SWT) design in the context of health services research, due to its pragmatic and methodological advantages over the parallel group design. OBJECTIVE: Our objective was to summarise the statistical methods used when conducting economic evaluations alongside SWTs. METHODS: A systematic literature search extending to February 2020 was conducted in the PubMed, Scopus, Cochrane and National Health Service Economic Evaluation Database (NHS-EED) databases to find and evaluate studies where there was an intention to conduct an economic evaluation alongside an SWT. Studies were assessed for their eligibility, findings, reporting of statistical methods and quality of reporting. RESULTS: Of the 586 studies retrieved from the literature search, 69 studies were identified and included in this systematic review. A total of 54 studies were published protocols, with eight economic evaluations and seven studies reporting full trial results. Included studies varied in terms of their reporting of statistical methods, in both detail and methodology. There were 34 studies that did not report any statistical methods for the economic evaluation, and only 16 studies reported appropriate methods, mainly using some form of mixed/multilevel model, and two used seemingly unrelated regression. Twelve studies reported the use of generic bootstrap methods and other modelling techniques, whilst the remaining studies failed to appropriately account for clustering, correlation or adjustment for time. CONCLUSIONS: The use of appropriate statistical methods that account for time, clustering and correlation between costs and outcomes is an important part of SWT health economics analysis, one that will benefit from an effort to communicate the methods available and their performance.
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