- Sterne, Jonathan Ac;
- Hernán, Miguel A;
- Reeves, Barnaby C;
- Savović, Jelena;
- Berkman, Nancy D;
- Viswanathan, Meera;
- Henry, David;
- Altman, Douglas G;
- Ansari, Mohammed T;
- Boutron, Isabelle;
- Carpenter, James R;
- Chan, An-Wen;
- Churchill, Rachel;
- Deeks, Jonathan J;
- Hróbjartsson, Asbjørn;
- Kirkham, Jamie;
- Jüni, Peter;
- Loke, Yoon K;
- Pigott, Theresa D;
- Ramsay, Craig R;
- Regidor, Deborah;
- Rothstein, Hannah R;
- Sandhu, Lakhbir;
- Santaguida, Pasqualina L;
- Schünemann, Holger J;
- Shea, Beverly;
- Shrier, Ian;
- Tugwell, Peter;
- Turner, Lucy;
- Valentine, Jeffrey C;
- Waddington, Hugh;
- Waters, Elizabeth;
- Wells, George A;
- Whiting, Penny F;
- Higgins, Julian Pt
Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.