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Charles Christian Adarkwah,1–3 Nikita Jegan,1 Monika Heinzel-Gutenbrunner,4 Felicitas Kühne,5,6 Uwe Siebert,5–7 Uwe Popert,8 Norbert Donner-Banzhoff,1 Sarah Kürwitz1,9 1Department of General Practice and Family Medicine, University of Marburg, Marburg, Germany; 2Department of Health Services Research and General Practice, Faculty of Life Sciences, University of Siegen, Siegen, Germany; 3Department of Health Services Research, Maastricht University, Maastricht, The Netherlands; 4MH Statistik Beratung, Marburg, Germany; 5Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, University for Health Sciences, Medical Informatics and Technology, Innsbruck, Austria; 6Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL – Center for Personalized Cancer Medicine, Innsbruck, Austria; 7Center for Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, Boston, MA, USA; 8Department of General Practice, University of Göttingen, Göttingen, Germany; 9Department of Public Health, University of Bielefeld, Germany Background: Shared decision-making is a well-established approach to increasing patient participation in medical decisions. Increasingly, using lifetime-risk or time-to-event (TTE) formats has been suggested, as these might have advantages in comparison with a 10-year risk prognosis, particularly for younger patients, whose lifetime risk for some events may be considerably greater than their 10-year risk. In this study, a randomized trial, the most popular 10-year risk illustration in the decision-aid software Arriba (emoticons), is compared with a newly developed TTE illustration, which is based on a Markov model. The study compares the effect of these two methods of presenting cardiovascular risk to patients on their subsequent adherence to intervention.Methods: A total of 294 patients were interviewed 3 months after they had had a consultation with their GP on cardiovascular risk prevention. Adherence to behavioral change or medication intervention was measured as the primary outcome. The latter was expressed as a generated score. Furthermore, different secondary outcomes were measured, ie, patient perception of risk and self-rated importance of avoiding a cardiovascular event, as well as patient numeracy, which was used as a proxy for patient health literacy.Results: Overall, no significant difference in patient adherence was found depending on risk representation. In the emoticon group, the number of interventions had a significant impact on the adherence score (P=0.025). Perception of risk was significantly higher in patients counseled with the TTE risk display, whereas the importance of avoiding a cardiovascular event was rated equally highly in both groups and actually increased over time.Conclusion: The TTE format is an appropriate means for counseling patients. Adherence is a very complex construct, which cannot be fully explained by our findings. The study results support our call for considering TTE illustrations as a valuable alternative to current decision-support tools covering cardiovascular prevention. Nevertheless, further research is needed to shed light on patient motivation and adherence with regard to cardiovascular risk prevention.Trial registration: The study was registered at the German Clinical Trials Register and at the WHO International Clinical Trials Register Platform (ICTRP, ID DRKS00004933); registered February 2, 2016 (retrospectively registered). Keywords: randomized trial, Arriba, decision aid, adherence, risk perception, shared decision-making 10-year prognosis, risk assessment, lifetime risk, time to event, cardiovascular disease

Primary care physicians in Germany don't benefit from coding diagnoses-they are coding for the needs of others. For coding, they mostly are using either the thesaurus of the German Institute of Medical Documentation and Information (DIMDI) or self-made cheat-sheets. Coding quality is low but seems to be sufficient for the main use case of the resulting data, which is the morbidity adjusted risk compensation scheme that distributes financial resources between the many German health insurance companies.Neither the International Classification of Diseases and Health Related Problems (ICD-10) nor the German thesaurus as an interface terminology are adequate for coding in primary care. The ICD-11 itself will not recognizably be a step forward from the perspective of primary care. At least the browser database format will be advantageous. An implementation into the 182 different electronic health records (EHR) on the German market would probably standardize the coding process and make code finding easier. This method of coding would still be more cumbersome than the current coding with self-made cheat-sheets.The first steps towards a useful official cheat-sheet for primary care have been taken, awaiting implementation and evaluation. The International Classification of Primary Care (ICPC-2) already provides an adequate classification standard for primary care that can also be used in combination with ICD-10. A new version of ICPC (ICPC-3) is under development. As the ICPC-2 has already been integrated into the foundation layer of ICD-11 it might easily become the future standard for coding in primary care. Improving communication between the different EHR would make taking over codes from other healthcare providers possible. Another opportunity to improve the coding quality might be creating use cases for the resulting data for the primary care physicians themselves.