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Background Diabetic retinopathy (DR) affects 10–24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in an accurate and timely diagnosis. Purpose The purpose of this meta-analysis was to determine the current state of knowledge regarding deep learning (DL) screening methods for DR in PC. Data sources A systematic literature search was conducted using Medline, Web of Science, and Scopus to identify suitable studies. Study selection Suitable studies were selected by two researchers independently. Studies assessing DL methods and the suitability of these screening systems (diagnostic parameters such as sensitivity and specificity, information on datasets and setting) in PC were selected. Excluded were studies focusing on lesions, applying conventional diagnostic imaging tools, conducted in secondary or tertiary care, and all publication types other than original research studies on human subjects. Data extraction The following data was extracted from included studies: authors, title, year of publication, objectives, participants, setting, type of intervention/method, reference standard, grading scale, outcome measures, dataset, risk of bias, and performance measures. Data synthesis and conclusion The summed sensitivity of all included studies was 87% and specificity was 90%. Given a prevalence of DR of 10% in patients with DM Type 2 in PC, the negative predictive value is 98% while the positive predictive value is 49%. Limitations Selected studies showed a high variation in sample size and quality and quantity of available data.

BackgroundDiabetic retinopathy (DR) affects 10-24% of patients with diabetes mellitus type 1 or 2 in the primary care (PC) sector. As early detection is crucial for treatment, deep learning screening methods in PC setting could potentially aid in an accurate and timely diagnosis.PurposeThe purpose of this meta-analysis was to determine the current state of knowledge regarding deep learning (DL) screening methods for DR in PC.Data sourcesA systematic literature search was conducted using Medline, Web of Science, and Scopus to identify suitable studies.Study selectionSuitable studies were selected by two researchers independently. Studies assessing DL methods and the suitability of these screening systems (diagnostic parameters such as sensitivity and specificity, information on datasets and setting) in PC were selected. Excluded were studies focusing on lesions, applying conventional diagnostic imaging tools, conducted in secondary or tertiary care, and all publication types other than original research studies on human subjects.Data extractionThe following data was extracted from included studies: authors, title, year of publication, objectives, participants, setting, type of intervention/method, reference standard, grading scale, outcome measures, dataset, risk of bias, and performance measures.Data synthesis and conclusionThe summed sensitivity of all included studies was 87% and specificity was 90%. Given a prevalence of DR of 10% in patients with DM Type 2 in PC, the negative predictive value is 98% while the positive predictive value is 49%.LimitationsSelected studies showed a high variation in sample size and quality and quantity of available data.

BACKGROUND:The treatment of upper respiratory tract infections (URTIs) accounts for the majority of antibiotic prescriptions in primary care, although an antibiotic therapy is rarely indicated. Non-clinical factors, such as time pressure and the perceived patient expectations are considered to be reasons for prescribing antibiotics in cases where they are not indicated. The improper use of antibiotics, however, can promote resistance and cause serious side effects. The aim of the study was to clarify whether the antibiotic prescription rate for infections of the upper respiratory tract can be lowered by means of a short (2 x 2.25h) communication training based on the MAAS-Global-D for primary care physicians. METHODS:In total, 1554 primary care physicians were invited to participate in the study. The control group was formed from observational data. To estimate intervention effects we applied a combination of difference-in-difference (DiD) and statistical matching based on entropy balancing. We estimated a corresponding multi-level logistic regression model for the antibiotic prescribing decision of German primary care physicians for URTIs. RESULTS:Univariate estimates detected an 11-percentage-point reduction of prescriptions for the intervention group after the training. For the control group, a reduction of 4.7% was detected. The difference between both groups in the difference between the periods was -6.5% and statistically significant. The estimated effects were nearly identical to the effects estimated for the multi-level logistic regression model with applied matching. Furthermore, for the treatment of young women, the impact of the training on the reduction of antibiotic prescription was significantly stronger. CONCLUSIONS:Our results suggest that communication skills, implemented through a short communication training with the MAAS-Global-D-training, lead to a more prudent prescribing behavior of antibiotics for URTIs. Thereby, the MAAS-Global-D-training could not only avoid unnecessary side effects but could also help reducing the emergence of drug resistant bacteria. As a consequence of our study we suggest that communication training based on the MAAS-Global-D should be applied in the postgraduate training scheme of primary care physicians.

BackgroundIn most western countries a shortage of general practitioners (GP) exists. Newly qualified GPs often prefer to work in teams rather than in single-handed practices. Therefore, new practices offering these kinds of working conditions will be attractive in the future. From a health care point of view, the location planning of new practices will be a crucial aspect. In this work we studied solutions for locating GP practices in a defined administrative district under different objectives.MethodsUsing operations research (OR), a research discipline that originated from logistics, different possible locations of GP practices were identified for the considered district. Models were developed under two main basic requirements: that one practice can be reached by as many inhabitants as possible and to cut down the driving time for every district's inhabitant to the next practice location to less than 15 minutes. Input data included the demand (population), driving times and the current GP locations.ResultsThree different models were analysed ranging from one single practice solution to five different practices. The whole administrative district can reach the central community "A" in at most 23 minutes by car. Considering a maximum driving time of 15 minutes, locations in four different cities in the district would be sufficient.ConclusionOperations research methods can be used to determine locations for (new) GP practices. Depending on the concrete problem different models and approaches lead to varying solutions. These results must be discussed with GPs, mayors and patients to find robust locations regarding future developments.

INTRODUCTION:For the effective and safe management of complex care needs for patients in community settings, high quality family medicine (FM) training programmes are needed. In less primary care oriented countries, training standards statements for FM postgraduate training are less commonly found. The aim of this study was to review international training standards statements in FM postgraduate training and to catalogue these statements to be used as a best practice standard guide for FM training programs in Germany. MATERIALS AND METHODS:A structured three-tiered search was performed: a systematic literature search in MEDLINE®; a search of international indicator databases; and a search in grey literature, consisting of a survey of international experts and a search in "Google (Scholar)". From all identified documents, training standards statements were extracted, translated and summarized into categories referring to the same quality aspect. RESULTS:The search strategy revealed 25 relevant documents (MEDLINE® n = 15, databases n = 2, experts n = 7, "Google" n = 1), containing 337 training standards statements. These were summarized into 80 statements. They covered structure quality (n = 35); process quality (n = 43); and two training standards statements referred to outcome quality (n = 2). CONCLUSION:A broad range of internationally sourced training standards statements for FM postgraduate training could be identified from countries with well-established primary care systems. Only few statements internationally referred to outcome quality, expressing the difficulty in assessing outcome. The resulting inventory of training standards statements for FM postgraduate training can serve as a resource for institutions seeking to formalise and systematise FM training at regional or national levels.

The STarT Back stratified primary care approach has demonstrated clinical and cost effectiveness in the UK, and is commonly used by General Practitioners (GPs). However, it remains unknown how this approach could be implemented into the German healthcare system. The aim of this study was therefore to explore the views and perceptions of German GPs in respect to using a stratified primary care for low back pain (LBP).A 90-minute think-tank workshop was conducted with 14 male and five female GPs, during which the STarT-Back-Screening-Tool (SBST) and related research evidence was presented. This was followed by two focus groups, based on a semi-structured interview guideline to identify potential implementation barriers and opportunities. Discussions were audiotaped, transcribed and coded using a content analysis approach.For the three deductively developed main themes, 15 subthemes emerged: (1) application of the SBST, with the following subthemes: which health profession should administer it, patients known to the GP practice, the reason for the GP consultation, scoring the tool, the tool format, and the anticipated impact on GP practice; (2) psychologically informed physiotherapy, with subthemes including: provision by a physiotherapist, anticipated impact, the skills of physiotherapists, management of patients with severe psychosocial problems, referral and remuneration; (3) the management of low-risk patients, with subthemes including: concern about the appropriate advising health professional, information and media, length of consultation, and local exercise venues.The attitudes of GPs towards stratified primary care for LBP indicated positive support for pilot-testing in Germany. However, there were mixed reactions to the ability of German physiotherapists to manage high-risk patients and handle their complex clinical needs. GPs also mentioned practical difficulties in providing extended advice to low-risk patients, which nevertheless could be addressed by involvement of specifically trained medical assistants.

When designing interventions and policies to implement evidence based healthcare, tailoring strategies to the targeted individuals and organizations has been recommended. We aimed to gather insights into the ideas of a variety of people for implementing evidence-based practice for patients with chronic diseases, which were generated in five European countries.A qualitative study in five countries (Germany, Netherlands, Norway, Poland, United Kingdom) was done, involving overall 115 individuals. A purposeful sample of four categories of stakeholders (healthcare professionals, quality improvement officers, healthcare purchasers and authorities, and health researchers) was involved in group interviews in each of the countries to generate items for improving healthcare in different chronic conditions per country: chronic obstructive pulmonary disease, cardiovascular disease, depression in elderly people, multi-morbidity, obesity. A disease-specific standardized list of determinants of practice in these conditions provided the starting point for these groups. The content of the suggested items was categorized in a pre-defined framework of 7 domains and specific themes in the items were identified within each domain.The 115 individuals involved in the study generated 812 items, of which 586 addressed determinants of practice. These largely mapped onto three domains: individual health professional factors, patient factors, and professional interactions. Few items addressed guideline factors, incentives and resources, capacity of organizational change, or social, political and legal factors. The relative numbers of items in the different domains were largely similar across stakeholder categories within each of the countries. The analysis identified 29 specific themes in the suggested items across countries.The type of suggestions for improving healthcare practice was largely similar across different stakeholder groups, mainly addressing healthcare professionals, patient factors and professional interactions. As this study is one of the first of its kind, it is important that more research is done on tailored implementation strategies.