Interventions to reduce waiting times for elective procedures

Background Long waiting times for elective healthcare procedures may cause distress among patients, may have adverse health consequences and may be perceived as inappropriate delivery and planning of health care. Objectives To assess the effectiveness of interventions aimed at reducing waiting times for elective care, both diagnostic and therapeutic. Search methods We searched the following electronic databases: Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1946‐), EMBASE (1947‐), the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ABI Inform, the Canadian Research Index, the Science, Social Sciences and Humanities Citation Indexes, a series of databases via Proquest: Dissertations & Theses (including UK & Ireland), EconLit, PAIS (Public Affairs International), Political Science Collection, Nursing Collection, Sociological Abstracts, Social Services Abstracts and Worldwide Political Science Abstracts. We sought related reviews by searching the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effectiveness (DARE). We searched trial registries, as well as grey literature sites and reference lists of relevant articles. Selection criteria We considered randomised controlled trials (RCTs), controlled before‐after studies (CBAs) and interrupted time series (ITS) designs that met EPOC minimum criteria and evaluated the effectiveness of any intervention aimed at reducing waiting times for any type of elective procedure. We considered studies reporting one or more of the following outcomes: number or proportion of participants whose waiting times were above or below a specific time threshold, or participants' mean or median waiting times. Comparators could include any type of active intervention or standard practice. Data collection and analysis Two review authors independently extracted data from, and assessed risk of bias of, each included study, using a standardised form and the EPOC 'Risk of bias' tool. They classified interventions as follows: interventions aimed at (1) rationing and/or prioritising demand, (2) expanding capacity, or (3) restructuring the intake assessment/referral process. For RCTs when available, we reported preintervention and postintervention values of outcome for intervention and control groups, and we calculated the absolute change from baseline or the effect size with 95% confidence interval (CI). We reanalysed ITS studies that had been inappropriately analysed using segmented time‐series regression, and obtained estimates for regression coefficients corresponding to two standardised effect sizes: change in level and change in slope.