Generic Patient-Reported Outcomes and Outcome Measures: A Systematic Review Study Protocol

BackgroundPatient-reported outcomes (PROs) are an essential part of health outcome measurement and vital to patient-centricity and valued-based care. Several international consortia have developed core outcome sets and many of them include PROs. PROs are measured by patient-reported outcome measures (PROMs). PROs and PROMs can be generic or specific to certain diseases or conditions. While the characteristics of generic PROs and PROMs are well recognised as widely relevant and applicable across different domains, diseases and conditions, there is a lack of knowledge on the types of PROs measured by generic PROMs. We also do not know in which disease areas generic PROs and PROMs are commonly used. To date, there has been no systematic review solely focusing on generic PROMs, what they measure and their areas of application. ObjectivesThis systematic review will identify core PROs measured by generic PROMs used in adult populations and the areas in which they are applied. MethodsWe will conduct a systematic review of reviews. The screening process and the reporting will comply with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 Statement. We will use four databases, Medline [PubMed], CINHAL [Ebsco], Cochrane [Cochrane Library], and PsycINFO [Ovid], and reports from international consortia. Inclusion criteria are systematic reviews, meta-analysis or patient-reported outcome sets developed by international consortia reporting on generic PROMs in adult populations. Articles primarily focusing on patient-reported experience measures (PREMs), children or adolescents, or those not written in English will be excluded. Risk of bias will be assessed by checking if the included articles comply with established guidelines for systematic reviews such as the PRISMA statement. We will extract generic PROMs and PROs measured by these PROMs, and the areas applied from the selected articles and reports. Extracted data and information will be quantitatively and qualitatively synthesised without statistical interference. The quality of the synthesised evidences will be assessed by clarifying the strengths, limitations and possible biases in our review.