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Primary care is a vital element of the healthcare system as it is often patients’ first point of contact. It addresses the main health problems in the community and encompasses different curative and preventive services, such as diagnosis and treatment of chronic and acute conditions, and patient education concerning the major health problems (1). As populations continue to age, the burden of chronic conditions continues to increase, making the importance of primary care more evident (2) . The fundamental platform for service delivery in primary care is the physician-patient consultation. Consultations can be made more congruent through several mechanisms e.g. competition amongst healthcare professionals and measurement and feedback of patients’ satisfaction (3). Philips et al found that an increasing number of patients in many European countries are using emergency rooms for less urgent problems in out-of hour’s situations (4). In order for policy makers to address these problems and reorganize resources more efficiently, patient preferences need to be known. If policy makers attempt to address these problems and to reorganize out-of-hours care more efficiently, patients’ preferences need to be known. The design and evaluation of healthcare programs require an understanding of the preferences of various stakeholders. Clinical, licensing, reimbursement, and policy decisions that incorporate the valuation of these interventions may improve the effectiveness of healthcare interventions by aligning better with the preferences of stakeholders, especially patients (5). Discrete choice experiments (DCE) are a survey-based method to elicit preferences by measuring the strength of preferences between service attributes (6). The discrete choice experiment is based on random utility theory (RUT) (7) and is consistent with Lancaster’s theory of characteristics and neoclassical economics whereby the utility of goods or services are determined by different attributes that characterize the good or service (8). They identify the turning point where preferences differ. This is especially useful with complex interventions involving target user groups. Kleij et al conducted a systematic review of DCEs between 2006 and 2015 on patients’ preferences for primary health care (9). Three databases (PubMed, Scopus, and PsycINFO) were searched and a total of 18 studies were included. However, Kleij et al only categorized and presented the attributes that the DCEs have examined, without details on how the DCEs were designed, analysed and presented which would provide a comprehensive picture on the DCEs have been used to inform policy decisions in primary care (9). In the last 5 years, interest in DCEs has grown tremendously and more studies have been conducted. As such, this review seeks to provide a more comprehensive understanding of DCE studies in primary care, in terms of the design, analysis and presentation of findings by including more databases with more recent studies and using more exhaustive search terms.

The International Diabetes Federation estimated that 425 million of the people worldwide have diabetes in year 2017 with a disproportionate distribution of 79% in low- and middle-income countries (LMICs). The cost of illness of diabetes will pressurize the health system in LMICs as primary health care (PHC) systems are traditionally organized for acute care and the main sources of health care financing are through general taxation and out-of-pocket payment. With reference to Declaration of Alma-Ata, PHC includes both community and primary facility-based care, ranging from promotive, preventive, curative and rehabilitative services. Targeting PHC is a sustainable and relatively inexpensive approach in addressing the issues that contributes to the loses in care. There were systematic reviews on effectiveness of different interventions on diabetes care carried out at the facility level. Systematic reviews that included studies from developed countries showed that multicomponent intervention improved T2D care. Outcomes measured by most of the systematic reviews are intermediate clinical outcomes (e.g. glycaemic control) and process of care. Despite a large body of literature on different interventions on diabetes management, little evidence is known for LMICs with different priorities, workforce and financial arrangement. There is also a lack of evidence on the effectiveness of complex intervention in this setting. Hence, we would like to conduct a systematic review and meta-analysis to synthesize evidence on complex interventions for type 2 diabetes in primary health care setting of LMICs.

Additional file 1: Appendix 1. PRISMA checklist. Appendix 2. Search strategies. Appendix 3. List of inclusion and exclusion criteria. Appendix 4. Detailed characteristics of included studies (include quality rating for each paper). Appendix 5. Methodological quality ratings of included studies, based on ISPOR Task Force for Conjoint Analysis checklist. Appendix 6. Number of studies that examined attributes within various levels, dimensions, and features of primary care according to the types of visits. Appendix 7. Full list of attributes according to evidence levels, overall and by types of visits (main analyses). Appendix 8. Full list of factors affecting preference heterogeneity according to evidence levels, overall and by types of visits (main analyses).

Supplemental material, Appendix_12_Funnel_plots_v2 for Risk of malignancies in patients with spondyloarthritis treated with biologics compared with those treated with non-biologics: a systematic review and meta-analysis by Yu Heng Kwan, Ka Keat Lim, Warren Fong, Hendra Goh, Linkai Ng, Benjamin Haaland, Jie Kie Phang, Lian Leng Low, Joo Guan Yeo, Feng Huang, Ying Ying Leung, Julian Thumboo and Truls Østbye in Therapeutic Advances in Musculoskeletal Disease

Supplemental material, PRISMA_Checklist_for_Submission_TAMD_v2 for Risk of malignancies in patients with spondyloarthritis treated with biologics compared with those treated with non-biologics: a systematic review and meta-analysis by Yu Heng Kwan, Ka Keat Lim, Warren Fong, Hendra Goh, Linkai Ng, Benjamin Haaland, Jie Kie Phang, Lian Leng Low, Joo Guan Yeo, Feng Huang, Ying Ying Leung, Julian Thumboo and Truls Østbye in Therapeutic Advances in Musculoskeletal Disease