Background Clinical pathways are associated with improved adherence to clinical guidelines; however, most studies have evaluated pathways for a single intervention at a single institution. The objective of the present study was to develop and evaluate a method of measuring concordance with a population-based clinical pathway map to determine if that method could be feasible for assessing overall health system performance.Methods Patients with stage ii or iii colon cancer diagnosed in 2010 were identified, and clinical data were obtained through linkages to administrative databases. Pathway concordance was defined a priori based on receipt of key elements of the Ontario Health (Cancer Care Ontario) colorectal pathway maps. For stages ii and iii colon cancer alike, concordance was reported as the proportion of patients receiving care that followed the predefined key elements of the pathway map. Regression analysis was used to identify predictors of concordant care.Results Our study identified 816 patients with stage ii and 800 patients with stage iii colon cancer. Of the patients with stage ii disease, 70% (n = 571) received concordant care. Of the patients with stage iii disease, results showed high concordance for all key elements except receipt of chemotherapy, leading to an overall concordance rate of 39% for that cohort.Conclusions Our method of measuring concordance was feasible on a population-based level, but future studies to validate it and to develop more sophisticated methods to measure concordance in larger cohorts and various disease sites are necessary. Measurement of clinical pathway concordance on a population-based level has the potential to be a useful tool for assessing system performance.

Diabetes is a chronic prevalent disease that must be managed to improve the patient's quality of life. However, the limited healthcare management resources compared to the large diabetes mellitus (DM) population are an obstacle that needs modern information technology to improve. Digital twin (DT) is a relatively new approach that has emerged as a viable tool in several sectors of healthcare, and there have been some publications on DT in disease management. The systematic summary of the use of DTs and its potential applications in DM is less reported. In this review, we summarized the key techniques of DTs, proposed the potentials of DTs in DM management from different aspects, and discussed the concerns of this novel technique in DM management.