Diagnostic errors :

Nowadays, Diagnostic errors are one of the most major issues tormenting the medical care framework. These mistakes are hurting patients and putting doctors and organizations at monetary danger.

The most common reason for these malpractice claims is having a narrow diagnostic focus, a problem that can be alleviated by utilizing diagnostic decision support systems. 

Potential solutions:

Regarding the potential solutions that may help in reducing the diagnostic errors, World Health Organization believes that It is likely a combination of solutions would be most effective some of these solutions are:

1. Focus on building a positive safety culture

Effective leadership and supportive culture are essential for improving safety in primary care.This means creating an environment where professionals feel able to speak up about issues that they are concerned about, without fear of blame or retribution. It means promoting an environment where healthcare providers want to report risks and safety incidents in order to learn from them and reduce their recurrence. Because concern for the healthcare providers and his mental health play an important role in the health system, as he is the one who provides health care to those who need it in all its forms, surgical, medical, psychological, rehabilitation, promotional and preventive forms.

According to studies and research, the healthcare provider suffers psychological crises that come from two sources, the first he is human being so he is not isolated from psychological crises, 

Second, the stress that comes from the health environment in which he works and brings him to what is known as" burnout ", which destroys his physical and psychological health.

Study shows that depression, burnout and suicide occur at higher rates in the medical profession than in many other fields. Nearly one in three doctors is clinically depressed, and approximately 400 physicians take their own lives every year. These numbers are doubled compared to that of the general population. And yet, according to a University of Michigan study, only 6 percent of doctors who are diagnosed with depression report it to their state medical board.

 2. Improving education and skills

Improving the reliability of diagnosis requires better education of primary care providers.Trainees would benefit from explicit training in clinical reasoning, patient safety, human factors, critical thinking, managing uncertainty, cognitive heuristics and biases, test limitations, probability concepts, reliability science and systems thinking.Training focused on the causes and impact of diagnostic error might help providers become more competent in error prevention. Simulations and feedback can be a helpful way to learn.

3. Embedding decision support tools

Many forms of health information technology tools could help to reduce diagnostic errors in countries across the world. Such as Artificial intelligence usage in the health field.

Nowadays, Artificial intelligence is considered  as the key to better decision-making, as it simplifies the lives of patients, doctors and hospital administrators by performing tasks that are typically done by humans, but in less time and at a fraction of the cost.  

For example, an AI model using algorithms and deep learning diagnosed breast cancer at a higher rate than 11 pathologists.

Here are some ways AI is reducing errors and saving lives..

  1. VisualDx 

Working on  improving medical decision-making, medical education, and research. It provides practical tools, methods, and resources to those people and departments passionate about medical imagery.

  1. PATHAI 


How it's using AI in healthcare: PathAI is developing machine learning technology to assist pathologists in making more accurate diagnoses. The company's current goals include reducing error in cancer diagnosis and developing methods for individualized medical treatment.

PathAI has worked with drug developers like Bristol-Myers Squibb and organizations like the Bill & Melinda Gates Foundation to expand its AI technology into other healthcare industries.



How it's using AI in healthcare: Buoy Health is an AI-based symptom and cure checker that uses algorithms to diagnose and treat illness. 



How it’s using AI in healthcare: Enlitic develops deep learning medical tools to streamline radiology diagnoses. The company’s deep learning platform analyzes unstructured medical data (radiology images, blood tests, EKGs, genomics, patient medical history) to give doctors better insight into a patient’s real-time needs.

Lastly. As Virtual Medical Academy is always seeking to develop the healthcare system and search for solutions that contribute to making the right decisions and reducing diagnostic errors as much as possible, a partnership agreement has been signed with one of the largest companies specialized in medical decision support, VisualDx, which has international awards in this field, and has contracted with more than 2,300 health facilities around the world to improve medical decision-making and diagnostics and include its services within the membership package.

VisualDx aims to reduce diagnostic errors by augmenting a clinician’s thinking. It helps establish a logical method of clinical reasoning to avert common diagnostic pitfalls. This leads to evidence-based decision making.

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