The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration

Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users. Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement-a reporting guideline published in 1999-there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA ( Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions. The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and metaanalyses.

Holding eternity in an hour: A practical exploration of the arts in the health care of older people with dementia

This project involved creative artists working with older people with dementia and staff from two Belfast Health and Social Care Trust supported housing centres in a mixed programme of dance, painting, music and drama which culminated in an open workshop with relatives and friends of the tenants. The study steered away from traditional medical models of art/music/dance therapy where the participant is perceived as a ‘patient’ in favour of identifying the participant as a ‘student’ who avails of a life-long learning experience. A key premise was that access to the arts is a human right, especially in the context of advancing age and cognitive impairment. . According to one the tenants of Mullan Mews, the project served to ‘awaken - or reawaken - folk with dementia to the endless vista of possibility already in their lives if they will only look for it’. A phenomenographic analysis of video data generated by the project emphasises the importance of the individual experiences of participants in the programme. The evidence from these storylines gained strength from the development of a documentary-style film text that has proved successful in capturing and translating the live experience of the project participants into a supportive text that goes beyond the written word.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.