For many radiologists, a practice acquisition is an attractive option for realizing the dream of self-employment. However, buying a medical practice also means becoming active as an entrepreneur - with all the obligations, opportunities and risks. Taking the step into self-employment should therefore be carefully planned and systematically implemented. This article provides initial guidance on what to consider when taking over a radiology practice.
The staff shortage in healthcare is pushing many hospitals and medical practices to their limits. Radiology is also affected: In many places, staffing ranks stretch thin, and existing personnel are burned out. This poses a massive threat to patient safety and the quality of medical care. What are the reasons for this and what can HR managers do to close the staffing gaps?
The aim of quality control in mammography is to maximize the benefits of exams while minimizing their potential risks. By law, mammogram screening programs must include quality control measures. In fact, ongoing internal quality controls provide a sound foundation for clinics to pass external reviews, such as audits and certifications, with flying colors. So, how can clinics maintain consistently high standards in mammography, and how can innovative technology such as artificial intelligence (AI) help? In this blog, we’ll provide a helpful overview with six practical tips on how to achieve this.
Despite their best efforts and expert knowledge, it is impossible for radiologists to completely avoid misdiagnoses. However, as radiological findings often determine the course of subsequent treatment, incorrect or delayed diagnoses have the potential to cause great harm. In this article, we outline crucial liability issues and offer five strategies on how to keep the error rate in radiology as low as possible.
In recent decades, breast cancer research has made groundbreaking progress: Breast cancer can now be detected ever earlier, and treated in a much more targeted way. As a result, this cancer has lost much of its former power to threaten – though it is still a serious opponent. Here is an overview of the fascinating history of breast cancer research, ranging from the ancient belief in the four humors, to a modern, tailored oncological approach.
For women in the US and Europe, the absolute risk of developing breast cancer is about 13%. In fact, 1 in 8 women will receive a breast cancer diagnosis in their lifetime. Yet, the individual likelihood of developing breast cancer varies from woman to woman. Research has discovered numerous risk factors – some of which can be influenced, while others can’t. Here’s an overview of the current state of research – and the consequences for early breast cancer detection.
State-organized early detection of breast cancer is evidently a successful project: since the introduction of statutory screening programs, demonstrably fewer women have died of breast cancer. But there is still room for improvement, as standardized screenings are not optimal for every woman. Current studies show how breast cancer screening can be methodologically refined and personalized. More efficient workflows could also reduce the burden on radiology facilities.
It’s a well-known radiology dilemma: Dense breast tissue makes it difficult to detect tumors in X-rays of the female breast. Yet, the risk of carcinoma also rises with breast density. The challenge here is that mammograms become less accurate for women who are more likely to develop breast cancer. So, what are the options for women with dense breast tissue, when it comes to offering them tailored early breast cancer detection? And can these strategies also be implemented for routine screenings?
Wherever people work, there will be mistakes – even in the medical field. If patients are harmed in the process, medical liability applies under certain conditions. Radiology finds itself in a special position here: Although its field of activity is mostly limited to diagnostics, errors can nevertheless have serious medical and legal consequences – for example, if a medically necessary treatment is omitted or delayed due to a diagnostic error. This article clarifies where the main sources of errors in radiology lie, what exactly happens when allegations are made, and how radiology practices can protect themselves from claims for compensation.
Mammograms are a core part of detecting breast cancer early, which can significantly improve a patient’s prognosis. But radiology centers that offer state-organized screening programs often face major challenges: correctly performing a diagnostic mammogram and generating a valid report requires profound specialty knowledge. At the same time, patients feel nervous and unsettled during breast exams, requiring a sensitive and empathetic bedside manner. The key here is to optimize and standardize workflows to ensure the highest quality medical care, and to provide women with a comfortable experience.
Artificial intelligence (AI) in medicine: a subject that’s polarized the public and raises alarm as well as high expectations. However, our lives have already undergone unseen digital transformations in a host of different ways – not just through AI, but also Big Data. We speak to smart speakers and to our smartphones or receive personalized training tips from our fitness trackers. There’s barely a field that has a higher complexity and data-use than medicine – and that makes it a prime area for applying artificial intelligence. There are many myths circulating about the opportunities and risks of using AI in medicine – but these don’t always stand up to a reality check.
ISO 9001 is the best known and most widely used international quality management standard. Originating in the industrial sector, it is increasingly gaining importance in the healthcare sector as well. But does certification according to ISO 9001 have any advantages for radiology practices? What are the requirements and how does the certification process work in practice? This article provides answers to these and other questions.
After confirming a breast cancer diagnosis, doctors face more major challenges: It’s an emotionally stressful situation, and patients need to be treated with sensitivity while being fully informed of what’s to come. As a team, doctors must develop a treatment plan according to medical guidelines. Any mistakes in the diagnosis and treatment of breast cancer can have grave medical – and legal – consequences.
Whether psychiatric diagnoses or lifestyle (drinking and smoking behavior), patient data contains highly sensitive information and is therefore subject to special legal protection. This data is increasingly available in electronic form due to digitalization in the health sector. This has the potential to improve medical care on an individual and societal level, as networked data allows for more efficient therapies and is also a valuable "raw material" for research. At the same time, however, the requirements for data protection and data security are increasing continually to prevent misusage. An overview of what medical practices and clinics should consider when dealing with patient data.
Only about 65 percent of U.S. women over the age of 40 report having participated in mammography screenings in the past two years. Throughout the EU, 49.2 percent of all women between the ages of 50 and 69 participated in mammography screenings in 2016. However, very large country-specific differences can be observed. The highest participation rates of more than 80 percent are found in Denmark, Finland and Slovenia.
The general shortage of healthcare professionals has also brought breast cancer screening to its limits: there are fewer and fewer radiologists and radiology technicians (‘MTRAs’), and increasing patient numbers to work through in less time. This has a negative impact on both the working environment and job satisfaction, but above all, it affects the quality of preventive health services for millions of women. Demographic change will only exacerbate the situation in the future. How can we avoid an impending collapse of the healthcare system?
Artificial Intelligence (AI) in the future of medicine: Science fiction just yesterday, today a beacon of hope
Our healthcare system is creaking under the pressure of multiple strains: lack of personnel, cost pressures, and the aftereffects of a global pandemic. Artificial intelligence (AI) could make the future of medicine more efficient, precise and safe – and at the same time drive the systemic changes that are so urgently needed. What tasks are self-learning systems taking on now, and what could they potentially do in the future? We give an overview of the situation.