BackgroundNumerous studies emphasize the importance of context in implementation. Successful implementation across the health care system depends on conditions and requirements that are often presented to health professionals through text-based materials and might present contradictory expectations to the work of health professionals. In this study, we operationalize institutional context as the text-based material, which from the perspective of health professionals, influence health care work. Via the case of a readmission prevention program for elderly patients, we examine the experiences of health professionals that work with implementation, concerning the contradictions that arise between the demands imposed by program implementation and their everyday work routines, and the role of text-based materials in these contradictions.MethodWe conducted five focus group interviews among health professionals working at different locations in a single administrative region of Denmark. The 24 health professionals in our study included hospital physicians, hospital nurses, medical secretaries, municipal care managers, registered municipal nurses, and general practitioners. All focus group interviews were transcribed verbatim. Inspired by institutional ethnography, we look into text-based materials, such as written guidelines, if health professionals indicate they are important.ResultsThe health professionals experience that specific demands of the readmission prevention program come into conflict with the existing demands and daily work routines. Professional resistance to control and the existing digital communication tools create tensions with a program requirement for standardized enrollment of patients to the program. In addition, the striving for autonomy among health professionals and the high level of mono-professional working routines create tension with the program requirements for an additional amount of interdisciplinary work. The different demands are widely mediated by text-based materials such as the existing digital communication tools and the instructions on how to use them, and the official agreement of the role and assignment for Danish GPs.ConclusionSuccessful implementation of the prevention program is affected by various tensions between the program demands and the existing health care work. Text-based materials mediate the different demands of the institutional context in to health care work and influence the process of implementation.Electronic supplementary materialThe online version of this article (10.1186/s13012-018-0730-0) contains supplementary material, which is available to authorized users.

BackgroundReadmission rate is one way to measure quality of care for older patients. Knowledge is sparse on how different social factors can contribute to predict readmission. We aimed to develop and internally validate a comprehensive model for prediction of acute 30-day readmission among older medical patients using various social factors along with demographic, organisational and health-related factors.MethodsWe performed an observational prospective study based on a group of 770 medical patients aged 65 years or older, who were consecutively screened for readmission risk factors at an acute care university hospital during the period from February to September 2012. Data on outcome and candidate predictors were obtained from clinical screening and administrative registers. We used multiple logistic regression analyses with backward selection of predictors. Measures of model performance and performed internal validation were calculated.ResultsTwenty percent of patients were readmitted within 30 days from index discharge. The final model showed that low educational level, along with male gender, contact with emergency doctor, specific diagnosis, higher Charlson Comorbidity Index score, longer hospital stay, cognitive problems, and medical treatment for thyroid disease, acid-related disorders, and glaucoma, predicted acute 30-day readmission. Area under the receiver operating characteristic curve (0.70) indicated acceptable discriminative ability of the model. Calibration slope was 0.98 and calibration intercept was 0.01. In internal validation analysis, both discrimination and calibration measures were stable.ConclusionsWe developed a model for prediction of readmission among older medical patients. The model showed that social factors in the form of educational level along with demographic, organisational and health-related factors contributed to prediction of acute 30-day readmissions among older medical patients.