This newly developed tool can be used to monitor quality performance of nurse practitioners and to plan quality improvement actions in nurse practitioners' performance in primary care settings.

Introduction Family history (FH) is an important part of the patients’ medical history during preventive management at model family medicine practices (MFMP). It currently includes a one (or two) generational inquiry, predominately in terms of cardiovascular diseases, arterial hypertension, and diabetes, but not of other diseases with a probable genetic aetiology. Beside family history, no application-based algorithm is available to determine the risk level for specific chronic diseases in Slovenia. Methods A web application-based algorithm aimed at determining the risk level for selected monogenic and polygenic diseases will be developed. The data will be collected in MFMP; approximately 40 overall with a sample including healthy preventive examination attendees (approximately 1,000). Demographic data, a three-generational FH, a medical history of acquired and congenital risk factors for the selected diseases, and other important clinical factors will be documented. Results The results will be validated by a clinical genetic approach based on family pedigrees and the next-generation genetic sequencing method. After the risk of genetic diseases in the Slovenian population has been determined, clinical pathways for acting according to the assessed risk level will be prepared. Conclusion By means of a public health tool providing an assessment of family predisposition, a contribution to the effective identification of people at increased risk of the selected monogenic and polygenic diseases is expected, lessening a significant public health burden.

ObjectivesIn Slovenia, the role of family physicians in primary care and preventive procedures is very important. Influenza vaccination rates in Slovenia are low. The reasons for low vaccination rates in Slovenia were not clear. We suppose that patient’s beliefs and attitudes are important factors. We assessed patients’ opinions regarding the acceptance of flu vaccination by their family physicians and their beliefs and attitudes about flu and vaccination. The aim was to check out factors that influence the decision to take the vaccine in family physician offices.MethodsThis was a cross-sectional, multicenter, observational study in the Styria region in Slovenia. We included patients from seven family physicians during regular office visits. They filled in a questionnaire about their general demographic data and attitudes regarding influenza and vaccination. The main outcome was the decision to be vaccinated.ResultsThe logistic regression model identified five predictors for influenza vaccination, namely: heart disease, previous vaccination, an agreement with the beliefs ‘the vaccination is an efficient measure to prevent influenza’, ‘after the vaccination there are usually no important side effects’ and ‘the vaccination is also recommended for a healthy adult person’. The belief that vaccinations harm the immune system is negatively associated with vaccination.ConclusionsPatients’ beliefs are an important factor to decide for vaccination or not. Family physician teams should discuss with patients their beliefs and concerns about vaccination.

It is possible to use the questionnaire developed by EGPRW on a national scale and to obtain representative valid national data. The home visiting rate in Slovenia is low compared with rates in other countries. Rural location of practice, GP's age, trainee status and the number of older patients on the list are the most important predictors of the home visiting rate.

Asymptomatic peripheral arterial disease (PAD) can be easily identified using the ankle-brachial index (ABI). This study was designed to investigate the benefits of performing ABI in patients aged 50 - 70 years. A random sample of 107 patients was chosen and data on gender, age, risk factors and laboratory tests were collected and the ABI measured. Twenty (19%) patients were found to have PAD. Smoking, high total cholesterol, high triglycerides and diabetes mellitus were shown to be associated with a low ABI and the presence of PAD. Age, diabetes and smoking were identified as the strongest predictors of PAD. Having more risk factors for PAD also predicted a lower ABI. These results suggest that measuring ABI is not necessary in patients aged 50 - 70 years if they only have one risk factor, with the exception of patients with diabetes and those who smoke. In contrast, measuring ABI seems to be useful for patients with multiple risk factors for PAD, although additional studies are required.