This thesis details the adaptation and evaluation of an e-health software platform known as TrueColours (originally developed by the Oxford Department of Psychiatry for treating bipolar disorder) for use in ulcerative colitis (UC). The resulting web-based programme, TrueColours UC, is capable of recording symptoms, quality of life (QoL), biomarkers, blood, endoscopic and histopathological results as well as internationally agreed patient-reported outcome measures (PROMs). The approach involved a pilot followed by qualitative analysis of system usability and quantative analysis of symptom patterns and decision-making to develop a predictive index. TrueColours UC was piloted for 6 months in 66 patients. Feasibility testing revealed adherence rates to daily and fortnightly questionnaires of 76% and 95% respectively. The retention rate at 6 months was 86%. Mixed methods analysis on system usability identified minor areas for improvement. Qualitative interviews revealed that by using TrueColours UC, patients felt empowered, expressed by an increased awareness, control over decision-making, reassurance and communication. Logistic regression models for predicting escalation of therapy at an outpatient appointment were developed. These models revealed that remotely collected symptom information can largely predict whether escalation of therapy will occur. External validation is necessary, but this model has the potential to improve resource utilisation. Analysis of longitudinal repeated measurements allowed novel exploration of validated indices for symptoms and QoL. A simulation model estimated the information loss that occurs when intervals between data entry are increased. A new method for phenotyping disease pattern was identified. Cut-off levels for faecal calprotectin in remission and active disease are proposed. Involving patients in collecting PROMs has the potential to change disease management pathways, identify patients for trials and provide insight into the biology of the disease.