The BMJ has published a study indicating that medical errors result in between 200,000 and 400,000 deaths annually across the United States. The BMJ estimate took into account diagnostic errors, communications breakdowns, systems failures, inadequate skill and poor judgment. The focus of the study was fatalities that occur secondary to a medical error, and many occurred in New York.
New York patients may be interested in the results of a study that found that men and women encounter different safety issues in medical situations. For example, women are more likely to have adverse reactions to drugs that they have been administered, ranging from rashes to low blood pressure to changes in their mental state. Men are more likely to get abrasions and cuts.
Women throughout the country are urged by their health care providers to get annual screenings in order to detect possibly deadly diseases and illnesses, such as cancer, before they reach their advanced stages. In addition, women are also encouraged to talk to their doctor about any symptoms they are experiencing that could indicate a serious health problem.
While New Yorkers likely have trusting relationships with their doctors, there are certain times when they should seek second opinions to make certain that the diagnosis or treatment regimen that has been proposed is appropriate. Health care practitioners sometimes make diagnostic or treatment mistakes, which can cause serious repercussions for patients.
Medical errors can cover a wide variety of situations. The wrong medication dose could be given to a patient, or a nick from a scalpel during surgery could cause internal bleeding or neurological injury. Surprisingly, the majority of errors take place in connection with visits to a physician’s office rather than in the context of hospital stays. However, the number of such errors annually makes this the third leading cause of death in the nation. New York healthcare professionals may need to consider some important issues related to medical errors in order to turn the statistical tide.
