Quality Improvement of Agricultural Products Supply Chain under Social Preference and CSR by Big Data Analysis

Purpose- The aim of this study is to analyze the effect of corporate social responsibility (CSR) and social preference on quality improvement of the agricultural products supply chain composed of agricultural products producer and processor (A3P) and supermarket by theoretical analysis and empirical evidence. Methodology- This paper sets Stackelberg game model under A3P’s CSR by considering supermarket’s altruistic reciprocity and A3P’s fairness conern, respectively. By comparative analysis, we study the effect of CSR, altruistic reciprocity and fairness conern on the quality improvement of the agricultural products supply chain. Then, we adopt the empirical evidence to analyze the correlation between CSR, altruistic reciprocity (fairness concern) and quality improvement and the mediating effect of altruistic reciprocity (fairness concern) by investigating the agricultural enterprises.

Quality Improvement in Juvenile Idiopathic Arthritis: a Mixed-methods Implementation Pilot of the CAPTURE-JIA Dataset

BackgroundA significant proportion of children and young people with juvenile idiopathic arthritis (JIA) do not achieve inactive disease during the first two years following diagnosis. Refinements to clinical care pathways have the potential to improve clinical outcomes but a lack of consistent and contemporaneous clinical data presently precludes standard setting and implementation of meaningful quality improvement programmes. This study was the first to pilot clinical data collection and analysis using the CAPTURE-JIA dataset, and to explore patient and clinician-reported feasibility and acceptability data.MethodsA multiphase mixed-methods approach enabled prospective collection of quantitative data to examine the feasibility and efficacy of dataset collection and of qualitative data informing the context and processes of implementation. An initial paper pilot informed the design of a bespoke electronic data collection system (the Agileware system), with a subsequent electronic pilot informing the final CAPTURE-JIA data collection tool. ResultsPaper collection of patient data was feasible but time-consuming in the clinical setting. Phase 1 paper pilot data (121 patients) identified three themes: problematic data items (14/62 data items received >40% missing data), formatting of data collection forms and a clinician-highlighted need for digital data collection, informing Phase 2 electronic data collection tool development. Patients and families were universally supportive of the collection and analysis of anonymised patient data to inform clinical care. No apparent preference for paper / electronic data collection was reported by families. Phase 3 electronic pilot data (38 patients) appeared complete and the system reported to be easy to use. Analysis of the study dataset and a dummy longitudinal dataset confirmed that all eleven JIA national audit questions can be answered using the electronic system. ConclusionsMulticentre CAPTURE-JIA data collection is feasible and acceptable, with a bespoke data collection system highlighted as the most satisfactory solution. The study is informing ongoing work towards a streamlined and flexible national paediatric data collection system to drive quality improvement in clinical care.