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Background: The growth of diabetes prevalence is causing an increasing demand in health care services which affects the clinicians' workload as medical resources do not grow at the same rate as the diabetic population. Decision support tools can help clinicians with the inspection of monitoring data, providing a preliminary analysis to ease their interpretation and reduce the evaluation time per patient. This paper presents Sinedie, a clinical decision support system designed to manage the treatment of patients with gestational diabetes. Sinedie aims to improve access to specialized healthcare assistance, to prevent patients from unnecessary displacements, to reduce the evaluation time per patient and to avoid gestational diabetes adverse outcomes.Methods: A web-based telemedicine platform was designed to remotely evaluate patients allowing them to upload their glycaemia data at home directly from their glucose meter, as well as report other monitoring variables like ketonuria and compliance to dietary treatment. Glycaemia values, not tagged by patients, are automatically labelled with their associated meal by a classifier based on the Expectation Maximization clustering algorithm and a C4.5 decision tree learning algorithm. Two finite automata are combined to determine the patient's metabolic condition, which is analysed by a rule-based knowledge base to generate therapy adjustment recommendations. Diet recommendations are automatically prescribed and notified to the patients, whereas recommendations about insulin requirements are notified also to the physicians, who will decide if insulin needs to be prescribed. The system provides clinicians with a view where patients are prioritized according to their metabolic condition. A randomized controlled clinical trial was designed to evaluate the effectiveness and safety of Sinedie interventions versus standard care and its impact in the professionals' workload in terms of the clinician's time required per patient; number of face-to-face visits; frequency and duration of telematics reviews; patients' compliance to self-monitoring; and patients' satisfaction.Results: Sinedie was clinically evaluated at "Parc Tauli University Hospital" in Spain during 17 months with the participation of 90 patients with gestational diabetes. Sinedie detected all situations that required a therapy adjustment and all the generated recommendations were safe. The time devoted by clinicians to patients' evaluation was reduced by 27.389% and face-to-face visits per patient were reduced by 88.556%. Patients reported to be highly satisfied with the system, considering it useful and trusting in being well controlled. There was no monitoring loss and, in average, patients measured their glycaemia 3.890 times per day and sent their monitoring data every 3.477days.Conclusions: Sinedie generates safe advice about therapy adjustments, reduces the clinicians' workload and helps physicians to identify which patients need a more urgent or more exhaustive examination and those who present good metabolic control. Additionally, Sinedie saves patients unnecessary displacements which contributes to medical centres' waiting list reduction. [ABSTRACT FROM AUTHOR]

Background: Process evaluation studies are recommended to improve our understanding of underlying mechanisms related to clinicians, patients, context and intervention delivery that may impact on trial or program results and on their potential transferability to practice. This paper aims to document the translation of a type-2 diabetes (T2D) prevention program into the routine context of several primary care centers, assessing process indicators related to clinician adoption, patient recruitment, exposure to the intervention components and baseline characteristics.Methods: An observational descriptive process evaluation study was conducted of the 2.5-year implementation of the Prevention of Diabetes in Euskadi cluster randomized trial in 14 primary care centers of the Basque Health Service (Osakidetza). The clinical intervention consisted of three components: (1) risk screening, (2) an educational intervention promoting healthy lifestyles, and (3) remote support (follow-up). A passive dissemination strategy of providing training and materials was used to translate the intervention into practice. All non-diabetic patients aged 45 to 70 years who were identified as being at high risk of developing T2D were eligible for study inclusion. The RE-AIM framework guided the process evaluation.Results: Overall, 31.4 % of family physicians and 57.6 % of nurses participated in the study, while 4170 out of 67,293 (6.2 %) targeted patients who attended the centers during the implementation period were reached through the screening. Around half of the screened patients were identified as being at high risk of developing T2D (FINDRISC score ≥14). The rate of refusal to participate and the proportion of women were higher in the intervention group. Finally, 634 and 454 non-diabetic 45- to 70-year-old patients who were at high risk of T2D were included in the control and intervention group centers (intervention reach = 48 %). Significant variability in most process indicators was observed at center level.Conclusion: The passive dissemination strategy has produced modest process indicators related to the adoption, reach and implementation of the intervention program, and reduced the possibility of its standardized application in heterogeneous contexts. The resulting different procedures and strategies used by the centers were associated with process outcomes. Context-specific variability and possible confounding will require rigorous procedures for analysis of the intervention effects.Trial Registration: The trial was registered in ClinicalTrials.gov (identifier: NCT01365013 ). Registered on June 2011. [ABSTRACT FROM AUTHOR]