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blorbortion · 4 months ago

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In a result that will ring familiar for many women, new research has revealed a massive disparity in how pain is treated.

Women being discharged from emergency departments in Israel and the US are far less likely to be given a prescription for pain medication than men, even when being treated for the exact same ailments or when their reported pain scores were exactly the same.

Out of 17,576 patients in one dataset, some 47 percent of men were dispatched with a prescription for an analgesic medicine, compared to just 38 percent of women.

This, according to a team led by psychologists Mika Guzikevits of The Hebrew University of Jerusalem and Tom Gordon-Hecker of Ben-Gurion University of the Negev in Israel, was consistent across all ages and ailments, and the prescribing doctors' genders, revealing an alarming sex bias in how seriously women's complaints are taken.

"We argue that female patients receive less pain treatment than they should, which may adversely impact their health," the researchers write in their paper.

"The findings underscore the critical need to address psychological biases in healthcare settings to ensure fair and efficient treatment for all."

Research in recent years has revealed an alarming bias in the way the world perceives women's pain. Laypeople are more likely to think that women are exaggerating their pain than men, and perceive that grimacing women are experiencing less pain than men with similar facial expressions.

Many studies have shown that women reporting pain are perceived as hysterical, emotional, imagining things, or even lying. And this has the potential to be a big problem when transmuted to a medical setting.

Research has found that women reporting chronic pain are more likely to be diagnosed with a mental health condition. Women wait longer for treatment in emergency rooms. Women are less likely to be prescribed postoperative pain management medication. And multiple studies have found that medical practitioners perceive women to be less, and men more, trustworthy when reporting pain, often based on surveys and virtual patients.

Guzikevits, Gordon-Hecker, and their colleagues wanted to examine real outcomes in clinical settings, so they made a study of anonymized patient data from hospitals in the US and Israel. They looked at factors such as the age and sex of the patient, the level of pain reported and the diagnosed ailment, how often the patient visited the emergency department, and what the patient was prescribed.

Their data included a total of 21,851 patients presenting at the hospital for pain, and the results were striking.

"Across these datasets, a consistent sex disparity emerges," the researchers write.

"Female patients are less likely to be prescribed pain-relief medications compared to males, and this disparity persists even after adjusting for patients' reported pain scores and numerous patient, physician, and emergency department variables."

This disparity in treatment could not be linked to any other variable than the sex of the patient, the researchers found. Given the wealth of studies showing a huge disparity in the way the pain of women and men are perceived, the researchers could only conclude that the reason for this disparity is bias.

In a further test, the team presented 109 healthcare providers with a scenario describing a patient with severe back pain, rated 9 out of 10 by the patient. Only the patient's sex differed, with all other scenario details identical. When the patient was female, participants rated the pain intensity lower on average (72 out of 100) than when the patient was male (80 out of 100).

The researchers also noted that there have been some studies that didn't find a bias. These studies were conducted on patients with a tangible, physical source of pain, such as a broken bone or an infection. For those studies in which a bias is found, the source of the reported pain is less tangible – abdominal pain, or a headache.

The researchers suggest that computerized decision-reporting tools that help prescribe pain relief, and educating health practitioners about gender bias, could help resolve this ongoing issue and ensure better health outcomes for all patients.

"Inadequate pain management is known to lead to unnecessary suffering and deleterious health effects, and also carries preventable costs for public health," the researchers write in their paper.

"The present research provides robust evidence for healthcare providers' sex bias against female patients in pain management. We identify the stereotypical perception of females' pain as one of the potential mechanisms underlying the bias.

"The findings join mounting evidence of discrimination against females in the medical system and in other areas. Undertreatment of females' pain bears immediate implications for the healthcare system and broad implications for society's attitude toward female pain."

The research has been published in the Proceedings of the National Academy of Sciences.

(emphasis mine, article NOT paywalled, more links in the linked article)

#feminism #misogyny #medical misogyny #sexism #radical feminism #radfem #sources

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hellyeahscarleteen · 8 months ago

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"Last month, the UK’s four-year-long review of medical interventions for transgender youth was published. The Cass Review, named after Hilary Cass, a retired pediatrician appointed by the National Health Service to lead the effort, found that “there is not a reliable evidence base” for gender-affirming medicine. As a result, the report concludes, trans minors should generally not be able to access hormone blockers or hormone replacement therapy (HRT) and instead should seek psychotherapy. While the review does not ban trans medical care, it comes concurrently with the NHS heavily restricting puberty blockers for trans youth.

The conclusions of the Cass Review differ from mainstream standards of care in the United States, which recommend medical interventions like blockers and HRT under certain circumstances and are informed by dozens of studies and backed by leading medical associations. The Cass Review won’t have an immediate impact on how gender medicine is practiced in the United States, but both Europe’s “gender critical” movement and the anti-trans movement here in the US cited the report as a win, claiming it is the proof they need to limit medical care for trans youth globally. Notable anti-trans group the Society for Evidence Based Gender Medicine called the report “a historic document the significance of which cannot be overstated,” and argued that “it now appears indisputable that the arc of history has bent in the direction of reversal of gender-affirming care worldwide.”

Most media coverage of the report has been positive. But by and large that coverage has failed to examine extensive critiques from experts in the US and elsewhere. Research and clinical experts I interviewed explained that the Cass Review has several shortcomings that call into question many of its findings, especially around the quality of research on gender medicine. They also question the credibility and bias underpinning the review. I spoke with four clinical and research experts in pediatric medicine for gender-diverse youth to dive into the criticisms.

“I urge readers of the Cass Review to exercise caution,” said Dr. Jack Turban, director of the gender psychiatry program at the University of California, San Francisco and author of the forthcoming book Free to Be: Understanding Kids & Gender Identity."

#cass review #trans #lgbtq #gender #UK politics

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mariacallous · 2 months ago

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Editor's note:This is the first blog in our series that examines how social determinants influence gender biases in public health research, menstrual hygiene product development, and women’s health outcomes.

Worldwide, over 100 million women use tampons every day as they are the most popular form of menstrual products. U.S. women spent approximately $1 billion from 2016 to 2021 on tampons, and 22% to 86% of those who menstruate use them during their cycles, with adolescent girls and young adults preferring them. Tampons and pads are the most practical and common option for those who are working and have limited funds. Yet, a recent pilot study exposed concerning amounts of lead, arsenic, and toxic chemicals in tampons: 30 different tampons from 14 brands were evaluated for 16 different metal(loid)s, and tests indicated that all 16 metal(loid)s were detected in all different samples. This news comes as quite a shock to women who use these products. It raises many concerns and questions for those who do not have other viable options when they menstruate. We explore some of the major questions and concerns regarding the products on the market and their potential to increase the risk of exposure to harmful contaminants. It is clear that beyond this pilot study, further research is required to understand the potential health challenges.

Unpacking the potential risks for those who use menstrual products

Measurable concentrations of lead and arsenic in tampons are deeply concerning given how toxic they are. The World Health Organization (WHO) classifies lead as a major public health concern with no known safe exposure level. Arsenic can lead to several health issues such as cancer, cardiovascular disease, and diabetes. There are three ways in which these metal(loid)s can be introduced into the product: 1) from the raw materials that absorbed the soil and air, like the cotton used in the absorbent core; 2) contamination from water during the manufacturing process; and 3) intentionally being added during the manufacturing process for certain purposes. No matter how these metal(loid)s are introduced into the product, the pilot study stresses that further research must be done to explore the consequences of vaginally absorbed chemicals given the direct line to the circulatory system.

On an institutional level, the public health system has historically been biased toward the male perspective, essentially excluding research related to women’s health. In 1977, the U.S. Food and Drug Administration (FDA) recommended that women of childbearing age should be excluded from clinical research. Because of this gendered bias, many women now experience delayed diagnoses, misdiagnoses, and suffer more adverse drug effects; eight out of 10 of the drugs removed from U.S. markets from 1997 to 2000 were almost exclusively due to the risk to women. In 1989, the National Institutes of Health (NIH) amended its policy to include women and minorities in research studies, but it wasn’t until 1993 that this policy became federal law in the NIH Revitalization Act of 1993. Then, in 2016, the NIH implemented a policy requiring the consideration of sex as a biological variable in research.

Historically, women haven’t been in control of the various industries that support their unique health needs and develop products that allow them to manage their health in safe ways. In spite of this, women-owned businesses have increased over time, with many of them supporting a range of products, services, and health and child care needs. Changes in these industries can lead to a better understanding of how certain products aid or impede women’s health trajectories.

Racialized and gendered bias in health research

The life expectancy of women continues to be higher than men’s. That does not suggest there has been universal nor equitable support for women’s health issues and women’s health care. Black women are three times more likely to die from pregnancy-related issues. They also experience racism and differential treatment in health care and social service settings. This reality becomes starker when stigma and bias influence negative behaviors toward Black women and other women of color, and socioeconomic status limits access to preventative care, follow-up care, and other services and resources.

Toxic menstrual products are just the tip of the iceberg for gender bias in health research. Gendered bias extends into how health care professionals evaluate men and women differently based on the stereotypical ideas of the gender binary. This results in those who are perceived as women receiving fewer diagnoses and treatments than men with similar conditions, as well as doctors interpreting women’s pain as stemming from emotional challenges rather than anything physical. In a study comparing a patient’s pain rating with an observer’s rating, women’s pain was consistently underestimated while men’s pain was overestimated. Women’s pain is often disregarded or minimized by health care professionals, as they often view it as nothing more than an emotional exaggeration or are quick to blame any physical pain on stress. This has led to a pain gap in which women with true medical emergencies are pushed aside. For instance, the Journal of the American Heart Association reported that women with chest pain waited 29% longer to see a doctor in emergency rooms than men.

For people of color, especially Black women, the pain gap, as well as the gap in diagnoses and treatment, is exacerbated due to the intersectionality of gender, race, and the historical contexts of Black women’s health in America. Any analysis must consider the unique systemic levels of sexism and racism they face as being both Black and women. They face a multifaceted front of discrimination, sexism, and racism, in which doctors don’t believe their pain due to implicit biases against Black people—a dynamic that stems from slavery, during which it was common belief that Black people had a higher pain tolerance—and women. A study found that white medical students and residents believed at least one false biological difference between white and Black people and were thus more likely to underestimate a Black patient’s pain level.

Intersectionality, as well as sexism, further explains why medical students that believe in racial differences in pain tolerance are less likely to accurately provide treatment recommendations or pain medications. A Pew study found that 55% of Black people say they’ve had at least one negative experience with doctors, where they felt like they were treated with less respect than others and had to advocate for themselves to get proper care. Comparatively, 52% of younger Black women and 40% of older Black women felt the need to speak up to receive care, while only 29% of younger Black men and 36% of older Black men felt similarly. Particularly among Black women, 34% said their women’s health concerns or symptoms weren’t taken seriously by their health care providers. This even happened to Serena Williams!

Restructuring the health system

On Tuesday, September 11, 2024, the FDA announced they would investigate the toxic chemicals and metals in tampons as a result of the pilot study. This comes after public outcry and Senator Patty Murray’s (D-Wash.) letter to FDA Commissioner Robert M. Califf asking the agency to evaluate next steps to ensure the safety of tampons and menstrual products. In her letter, she specifically asks what the FDA has done so far in their evaluations and what requirements they have for testing these products, ensuring a modicum of accountability within this market. As of July 2024, the FDA classifies tampons as medical devices and does regulate their safety but only to an extent, with no requirements to test menstrual products for chemical contaminants (aside from making sure they do not contain pesticides or dioxin). The pilot study on tampons containing harmful metals was the first of its kind, which sheds light on how long women’s health has been neglected. Regulations requiring manufacturers to test metals in tampons need to be implemented, and future studies on the adverse health impacts of metals entering the bloodstream must be prioritized. The FDA investigation will hopefully be a step in the right direction toward implementing stricter regulations.

For too long, the health field has been saturated with studies by and for men. Women’s health, on the other hand, faces inadequate funding, a lack of consideration for women’s lived experiences, and the need for more women leading research teams investigating women’s health. Women, especially those who face economic and social disparities, have the capacity to break barriers and address real issues that impact millions of women each day but only if they are brought to the table. With structural change, we can address how women’s concerns are undermined and put forth efforts to determine new and effective measures for women’s health.

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darkmaga-returns · 1 month ago

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Originally posted Jan 2023.

The medical community and the media hang their hats on the use of ‘double-blind, placebo-controlled, peer-reviewed studies published in legacy journals such as The New England Journal of Medicine (NEJM) and the Journal of the American Medical Association (JAMA). In a future substack, I will go into detail about the fallacies, and even the scam, of peer review and why it should not be held out as sacrosanct.

For today’s discussion, let’s examine why all vaccine research should be questioned. Yes, ALL of it. If you read enough studies, you’ll see the patterns described below. For this substack, I’ll use this study on the safety of hepatitis B vaccination in children in India as an example. The vaccine used, Revac-B, contained both 0.5mg of aluminum and 0.05 mg of thimerosal, considered to be safe.

1. Vaccine trials can be quite small and include only healthy children.

Every study begins with ‘selection criteria’ that describe including only healthy individuals. This is from the hepatitis B study example:

All 60 subjects included in the study were in good health and had a negative history of hematological, renal, hepatic, or allergic diseases. All were screened and found to have normal blood panels, including normal liver enzymes.

When a vaccine trial has been completed and the vaccine is approved for use by the FDA, the vaccine is recommended for ALL children, regardless of their health condition, family history, or genetics. In fact, the new shot is most ardently pushed on children with underlying health concerns, such as seizure disorders, cardiac anomalies, and conditions such as cystic fibrosis or Down’s syndrome. These children become the next round of experimentation because the vaccines were never tested for safety on these groups and others.

2. Vaccine studies follow side effects for a short period of time.

Most clinical trials monitor for side effects for a paltry 21 days, often less. In some studies, such as in the example we are using, children were monitored for 5 days by study monitors and 5 days by cards given to parents. If no reactions occur, the shot is deemed to be ‘safe.’

However, it can take weeks to months for immune and neurological complications to appear. These arbitrary deadlines, allowed by the FDA, prohibit making the connection between vaccines with chronic health disorders. If an illness emerges later, of course, the doctors will say it has nothing to do with the vaccine.

3. Most vaccine safety studies do not use a true placebo.

The gold standard in medical research is the "placebo-controlled" trial. A placebo is an inactive or inert substance, such as a sugar pill or a shot of saline. In the trial, the placebo is given to one group, while the treatment group is given the experimental product. The placebo arm is used to ‘blind’ the study so the investigator doesn’t know if the subject received the Real Thing or the Inert Substance to minimize interpretation bias.

When reading a published vaccine trial, the substance used as the placebo is often not identified; it is simply called ‘placebo.’ For example, in this study for a new hepatitis B vaccine to treat chronic hepatitis B, the word ‘placebo’ is used 22 times, but we don’t know what placebo was used.

And that’s a problem. The substance used as a ‘placebo’ is often not inert; it may even may be another vaccine. For example, I remember reading a study where the meningitis C vaccine was used as a placebo because it was considered to be non-immunogenic and non-reactive. Or, in the instance of the Gardasil (HPV) vaccine, the ‘placebo’ was an injection of aluminum.

All studies for the Gardasil vaccine were said to be placebo-controlled and the total population that received a placebo included 9,701 subjects. The placebo was an aluminum adjuvant in all studies except study 018 (pre-/adolescent safety study), which used a non-aluminum-containing placebo [and we don’t know what that placebo was]

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quilliondollarbaby · 1 year ago

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Can you please explain what patriarchal science is?

Got an interesting ask, I suspect from that squirting/gushing post.

Both medicine and medical research have well-documented structural biases against people with vaginas. (Note: from hereon out I'm going to use "men" and "women" in the very cis way that medical research does, where they don't make a distinction between gender and biological sex. I chose to do that to more accurately reflect the findings of the research, which are incredibly biased toward cis people, but that's another post entirely.)

Medicine has a dark history of being used as a tool for structural sexism. If you want a horrific historical example, read about Female Hysteria for starters. But while these biases are now rarely as overtly abusive, they still exist in the current day. The biases in patient care tend to be far more talked about (I suppose understandably), but part of the reason they exist is because of the deeper structural biases in medical research.

But let's start with patient care. For example, doctors simply believe women less than men. In patient care, one in five women report having had a doctor dismiss or ignore their concerns. A particularly insidious bias against women is called the pain bias: despite women experiencing more chronic pain overall than men, and women's pain is dismissed and undertreated in medicine. Women are less likely to be prescribed painkillers after surgeries, and they're more likely to have their pain complaints ignored or dismissed as being overemotional.

All of this echoes the sentiment that led to so-called "Female Hysteria"--as far as many doctors are concerned, they know womens' bodies better than the women do and all women are too emotional and unreasonable to trust their accounts of their own symptoms.

But all of this is also directly tied to the fact that doctors are not trained how to treat women because medical research strongly privileges men. In the pre-modern era, a tradition going back to the Ancient Greeks said that medicine should only be tested on men, who were obviously stronger and more fit to endure unintended side effects than women.

So, of course, that led to a couple millennia of medical science that had not really considered whether women might experience medicine differently than men. It wasn't even until the 70's that medical research standards changed to to encourage including women at all. The NIH and the FDA didn't force medical researchers to include women in clinical trials until 1993.

But even today, medical research often has far more men than women in their clinical trial groups, fails to record gendered differences or even represent gendered cohorts in their data, and rarely if at all performs studies specifically on groups of women.

I found this paper, which was a survey of recent medical research to examine specifically for gendered medical bias, to be particularly staggering. Just read through the tables and you'll get a strong picture of what I mean.

Part of the reason we get biases in patient care is really just garden variety misogyny in a labcoat. But another part is because even well-meaning professionals don't realize that the information they're using to treat women is entirely incomplete. That's part of what I mean when I say it's a structural bias.

You can read about one particular dearth of knowledge we have in my post about squirting/gushing, but this lack of knowledge also shows up in research about far more life-threatening kinds of medical problems. This bias leads directly to the suffering and death of women every. single. day.

That's what I mean by "patriarchal medicine."

#medicine #science #medical science #patriarchy #feminism #apparently this is a medical science blog now

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medsocionwheels · 11 months ago

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Compliance, per the two main approaches to medical sociology

Sociology in medicine is research that’s of interest to medical professionals, medical educators, medical scientists— things that are important to medicine as an institution.

Sociology of medicine tends to be research of interest to the general scientific field of sociology, not only sociologists who study matters of medicine, health, illness, healthcare, and disability. Importantly, it is not that medicine is simply disinterested in sociology of medicine, the institution of medicine sometimes has a vested interest in silencing or arguing against sociology of medicine. Sociology of medicine may not be useful to medical professionals, but if, for example, sociology of medicine is critiquing medical practice, as is often the case, it might move beyond useless to being perceived as offensive.

To further explore the difference between sociology in versus of medicine, let’s take the issue of compliance.

From the medical perspective, patient compliance is vital for successful medical practice and treatment. if your patient is not listening to you–for example, if they’re not taking their medication, and that medication is supposed to get them better, than you are going to have a much more difficult time treating that patient, and thus, a much harder time doing your job, than if the patient “complied” with your treatment plan. Same thing if your patient won’t have surgery. Well, if operating is the way that you do your job and the patient refuses, you cannot do your job as well. So, sociology in medicine would examine compliance with this medical perspective in mind. Sociology in medicine might investigate the barriers to patient compliance, and they might ask about these barriers in terms of patient behavior, asking something like "why are these patients non-compliant?" with the goal of identifying things that can be addressed to help patients better comply, so that medical professionals can have better chances of success when trying to do their jobs.

Now, moving to sociology of medicine—the greater field of sociology is interested in issues of power and inequality. When examining compliance in terms of power and inequality, we might look at something like physician control over patients, which would contribute to areas of sociology beyond medical sociology, such as the larger sociological literature on deviance and social control.

From this perspective, physicians offer something that patients cannot obtain on their own—prescription medications, surgery, imaging…these are all things that are considered both illegal and dangerous when obtained from non-credentialed entities. This means patients must be compliant to avoid severe consequences, like physical injury, disability, or even death. Healthcare providers hold power to help people feel better when they have few, if any, safe alternatives.

Instead of looking at compliance as inherently positive or necessary, we can critique the concept, and most importantly, the continued endorsement of compliance as “positive” and “necessary” by credentialed actors in medicine. So, sociology of medicine, similarly to sociology in medicine, may examine barriers to compliance, but because it does not assume compliance is necessary or helpful to the patient, it leaves room to explore the patient experience. Sociology of medicine can explore things like mistrust of medical professionals, experiences with bias and discrimination in the clinical encounter, and the patient’s understanding of a potential treatment as helpful versus their belief that the treatment is useless (independent of the science on said treatment’s effectiveness).

So, while sociology in medicine and sociology of medicine might both be interested in the question of “why do patients become noncompliant,” sociology in medicine might approach that question with the intent of identifying something that will lead to increased compliance, whereas sociology of medicine may approach the question in terms of medical harm, so not taking the assumption that compliance is positive, instead, taking the more skeptical view that compliance might be an exercise of power on the part of the healthcare provider over the patient and focusing on issues like the potential for patterns of exploitation and/or harm of certain groups of patients with shared characteristics. Sociology of medicine might ask whether healthcare providers, because they are powerful, are inherently good or right. Sociology in medicine would probably not ask this question at all, instead assuming the answer to be "yes"

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#sociology #studyblr #phdblr #social science #medblr #health science #research #paradigm #medical sociology #sociology of medicine #sociology in medicine #compliance #power #inequality #deviance #social control #medical sociology 101 #Youtube

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religion-is-a-mental-illness · 1 year ago

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By: Leor Sapir

Published: Nov 13, 2023

Few figures in the medical world generate more controversy than psychiatrist Jack Turban. An assistant professor of child and adolescent psychiatry at the University of California, San Francisco, Turban is one of the leading figures promoting “gender-affirming care” in the United States. He is also regularly criticized for producing deeply flawed research and denying the significant rollback of youth gender transition in Europe.

The American Civil Liberties Union recently retained Turban as an expert witness—paying him $400 per hour—in its legal challenge to Idaho’s Vulnerable Child Protection Act, which restricts access to “gender-affirming” drugs and surgeries to adults only. On October 16, Turban submitted to a seven-hour deposition at the hands of John Ramer, an attorney with the law firm Cooper & Kirk, who is assisting Idaho in the litigation. In the course of the deposition, Turban revealed that, aside from churning out subpar research and misleading the public about scientific findings, he also appears not to grasp basic principles of evidence-based medicine.

Evidence-based medicine (EBM) refers to “the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients. . . . The practice of evidence-based medicine means integrating individual clinical expertise with the best available external clinical evidence from systematic research.” Because the expert opinion of doctors, even when guided by clinical experience, is vulnerable to bias, EBM “de-emphasizes intuition, unsystematic clinical experience, and pathophysiologic rationale as sufficient grounds for clinical decision making and stresses the examination of evidence from clinical research.” EBM thus represents an effort to make the practice of medicine more scientific, with the expectation that this will lead to better patient outcomes.

Systematic reviews and meta-analyses sit at the top of the hierarchy of evidence in EBM. A key difference between the U.S. and European approaches to pediatric gender medicine is that European countries have changed their clinical guidelines in response to findings from systematic reviews. In the U.S., medical groups have either claimed that a systematic review “is not possible” (the World Professional Association for Transgender Health), relied on systematic reviews but only for narrowly defined health risks and not for benefits (the Endocrine Society), or used less scientifically rigorous “narrative reviews” (the American Academy of Pediatrics). One of the world’s leading experts on EBM has called U.S. medical groups’ treatment recommendations “untrustworthy.”

In the deposition, Ramer asked Turban to explain what systematic reviews are. “[A]ll a systematic review means,” Turban responded, “is that the authors of the reports pre-defined the search terms they used when conducting literature reviews in various databases.” The “primary advantage” of a systematic review, he emphasized, is to function as a sort of reading list for experts in a clinician field. “Generally, if you are in a specific field where you know most of the research papers, the thing that’s most interesting about systematic review is if it identifies a paper that you didn’t already know about.” Ramer showed Turban the EBM pyramid of evidence, which appears in the Cass Review (page 62) of the U.K.’s Gender Identity Development Service. He asked Turban why systematic reviews sit at the top of the pyramid. Turban responded: “Because you’re looking at all of the studies instead of looking at just one.”

Turban’s characterization represents a fundamental misunderstanding of what EBM is and why systematic reviews are the bedrock of trustworthy medical guidelines.

First, even if the only thing that makes a review systematic is that it “pre-defines the search terms,” Turban failed to explain the relevance of this. A major reason systematic reviews rank higher than narrative reviews in EBM’s information hierarchy is that systematic reviews follow a transparent, reproducible methodology. Anyone who applies the same methodology and search criteria to the same body of research should arrive at the same set of conclusions. Narrative reviews don’t use transparent, reproducible methodologies. Their conclusions are consequently more likely to be shaped by the personal biases of their authors, who may, for instance, cherry-pick studies.

To achieve transparency and reproducibility, systematic reviews define in advance the populations, interventions, comparisons, and outcomes of interest (PICO). They search for and filter the available literature with Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Authors register their methodology and search criteria in advance in databases such as PROSPERO. These steps are meant to minimize the risk that authors will change their methodology midway through the process in response to inconvenient findings.

Turban acknowledged that pre-defining the search terms “makes it a little bit easier for another researcher to repeat their search.” However, he did not seem to grasp that the additional steps introduced by systematic reviews are designed to reduce bias and improve accuracy. Turban, one should note, endorses the American Academy of Pediatrics’ 2018 narrative review—a document that, with its severe flaws, perfectly illustrates why EBM prefers systematic to narrative reviews.

Second, Turban is incorrect that the “primary advantage” of the systematic review is to generate a comprehensive reading list for (in this case) gender clinicians. Systematic reviews also assess the quality of evidence from existing studies. In other words, they avoid taking the reported findings of individual studies at face value. This is especially important in gender medicine because so much of the research in this field comes from authors who are professionally, financially, and intellectually invested in the continuation of gender medicine—in other words, who have conflicts of interest. Financial conflicts of interest are typically reported, but professional and intellectual conflicts rarely so. Conflicted researchers frequently exaggerate positive findings, underreport negative findings, use causal language where the data don’t support it, and refrain altogether from studying harms. In short, assessing the quality of evidence is especially important in a field known for its lack of equipoise and scientific rigor.

In EBM, quality of evidence is a technical term that refers to the degree of certainty in the estimate of the effects of a given intervention. The higher the quality, the more confident we can be that a particular intervention is what causes an observed effect. It was only in response to Ramer’s prodding that Turban addressed “the risk of bias associated with primary studies”—namely, one of the key considerations for assessing quality of evidence.

During the deposition, Ramer read Turban excerpts from Users’ Guides to the Medical Literature, a highly regarded textbook of EBM published by the American Medical Association. Ramer asked Turban to explain what the Users’ Guides means when it says that narrative reviews, unlike systematic reviews, “do not include systematic assessments of the risk of bias associated with primary studies and do not provide quantitative best estimates or rate the confidence in these estimates.” Turban responded that systematic reviews do sometimes assess the quality of evidence, but that this is not a necessary condition for a review to be called systematic.

I asked Gordon Guyatt, professor of health research methods, evidence, and impact at McMaster University, what he thought of Turban’s answer. Guyatt is widely regarded as a founder of the field of EBM and is the primary author of Users’ Guides. “The primary advantage of a systematic review,” Guyatt assured me, “is not only not missing studies, but also assessing quality of the evidence. Anybody who doesn’t recognize that a crucial part of a systematic review is judging the quality or certainty of the evidence does not understand what it’s all about.”

Ramer asked Turban to explain the GRADE method (Grading of Recommendations Assessment, Development and Evaluations), a standardized EBM framework for evaluating quality. “GRADE generally involves looking at the research literature,” Turban explained. “And then there’s some subjectivity to it, but they provide you with general guidelines about how you would—like, great level of confidence in the research itself. Then there’s a—and then each of those get GRADE scores. I think it’s something like low, very low, high, very high. I could be wrong about the exact names of the categories.” Turban is indeed wrong: the categories are high, moderate, low, and very low. It’s surprising that someone involved in the debate over gender-medicine research for several years, and who understands that questions of GRADE and of quality are central, doesn’t know this by heart.

Ramer asked Turban what method, if any, he uses to assess quality in gender-medicine research. Turban explained that he reads the studies individually and does his own assessment of bias. GRADE is “subjective,” and this subjectivity, Turban said, is one reason that the U.K. systematic reviews rated studies that he commonly cites as “very low” quality. Turban’s thinking seems to be that, because GRADE is “subjective,” it is no better than a gender clinician sitting down with individual studies and deciding whether they are reliable.

I asked Guyatt to comment on Turban’s understanding of systematic reviews and GRADE. “Assessment of quality of evidence,” he told me, “is fundamental to a systematic review. In fact, we have more than once published that it is fundamental to EBM, and is clearly crucial to deciding the treatment recommendation, which is going to differ based on quality of evidence.” Guyatt said that “GRADE’s assessment of quality of the evidence is crucial to anybody’s assessment of quality of evidence. It provides a structured framework. To say that the subjective assessment of a clinician using no formal system is equivalent to the assessment of an expert clinical epidemiologist using a standardized system endorsed by over 110 organizations worldwide shows no respect for, or understanding of, science.”

At one point, Ramer pressed Turban to explain his views on psychotherapy as an alternative to drugs and surgeries. Systematic reviews have rated the studies Turban relies on for his support of puberty blockers and cross-sex hormones “very low” quality in part because these studies are confounded by psychotherapy. Because the kids who were given drugs and improved were also given psychotherapy and the studies lack a proper control group, it is not possible to know which of these interventions caused the improvement.

Turban seemed not to grasp the significance of this fact. If hormonal treatments can be said to cause improvement despite confounding psychotherapy, why can’t psychotherapy be said to cause improvement despite confounding drugs?

The exchange about confounding factors came up in the context of Ramer asking Turban about an article he wrote for Psychology Today. The article, aimed at a popular audience, purports to give an overview of the research that confirms the necessity of “gender-affirming care.” Last year, I published a detailed fact-check of the article, showing how Turban ignores confounding factors, among other problems. Four days later, Psychology Today made a series of corrections to Turban’s article. Some of these corrections were acknowledged in a note; others were done without any acknowledgement. In the deposition, Ramer asked Turban about my critique, to which Turban replied that he “left Psychology Today to do whatever edits they needed to do,” and that, when he later read the edits, he found them “generally reasonable.”

In sum, though Turban says that “there are no evidence-based psychotherapy protocols that effectively treat gender dysphoria itself,” the same studies he cites furnish just as much evidence for psychotherapy as they do for puberty blockers or cross-sex hormones—which is to say “very low” quality evidence.

Other remarkable moments occur in the Turban deposition. For instance, when asked whether he had read the Florida umbrella review (a systematic review of systematic reviews) conducted by EBM experts at McMaster University and published over a year ago, Turban said that he hadn’t because he “didn’t have time.” When I mentioned this confession to Guyatt, he seemed taken aback. How could a clinician who claims expertise in a contested area of medicine not be curious about a systematic review of systematic reviews? “If all systematic reviews come to the same conclusion,” Guyatt told me, “it clearly increases our confidence in that conclusion.” (My conversation with Guyatt dealt exclusively with Turban’s claims and how they stack up against EBM. I did not ask Guyatt about, and he did not opine on, the wisdom of state laws restricting access to “gender-affirming care.”)

I believe that Turban is being honest when he says he didn’t read the Florida umbrella review. He doesn’t seem interested in literature that might call his beliefs into question. He has staked his personal and professional reputation on a risky and invasive protocol before the appearance of any credible evidence of its superiority to less risky alternatives. Turban regularly maligns as bigoted and unscientific anyone who disagrees with him. Some gender clinicians in Europe now admit that the evidence is weak, the risks serious, and the protocol still experimental. Turban, however, would seemingly rather go down with the sinking ship than admit that he was too hasty in promoting “gender-affirming care.”

Put another way, Turban has intellectual, professional, and financial conflicts of interest that prejudice his judgment on how best to treat youth experiencing issues with their bodies or sex. European health authorities are aware of this problem; that’s why they chose to commission their evidence reviews from clinicians and researchers not directly involved in gender medicine. For instance, England’s National Health Service appointed physician Hilary Cass to chair the Policy Working Group that would lead the investigation of its Gender Identity Development Service and its systematic reviews. The NHS explained that there was “evident polarization among clinical professionals,” and Cass was “asked to chair the group as a senior clinician with no prior involvement or fixed views in this area.”

Unfortunately, in the U.S., personal investment in gender medicine is often seen as a benefit rather than a liability. James Cantor, a psychologist who testifies in lawsuits over state age restrictions, emphasizes the difference between the expertise of clinicians and that of scientists. The clinician’s expertise “regards applying general principles to the care of an individual patient and the unique features of that case.” The scientist’s expertise “is the reverse, accumulating information about many individual cases and identifying the generalizable principles that may be applied to all cases.” Cantor writes:

In legal matters, the most familiar situation pertains to whether a given clinician correctly employed relevant clinical standards. Often, it is other clinicians who practice in that field who will be best equipped to speak to that question. When it is the clinical standards that are themselves in question, however, it is the experts in the assessment of scientific studies who are the relevant experts.

The point is not that clinicians are never able to exercise scientific judgment. It’s that conflicts of interest for involved clinicians need to be acknowledged and taken seriously when “the clinical standards . . . are themselves in question.” Unfortunately, the American propensity for setting policy through the courts makes that task difficult. Judges intuitively believe that gender clinicians are the experts in gender medicine research. The result is a No True Scotsman argument wherein the more personally invested a clinician is (and the more conflict of interest he has as a result), the more credible he appears.

Last year, a federal judge in Alabama dismissed Cantor’s expert analysis of the research, citing, among other things, the fact that Cantor “had never treated a child or adolescent for gender dysphoria” and “had no personal experience monitoring patients receiving transitioning medications.” Turban’s deposition illustrates why this thinking is misguided. It is precisely gender clinicians who often seem to be least familiar, or at any rate least concerned, with subjecting their “expert” views to rigorous scientific scrutiny. It is precisely these clinicians who are most likely to be swimming in confirmation bias, least interested in the scientific method, and, conveniently, least concerned with evidence-based medicine.

Jack Turban is frequently a star "expert" in so-called "gender affirming care" enquiries. Aside from being a pathological liar, we can now also conclude he's dangerously unqualified.

#Leor Sapir #Jack Turban #Gordon Guyatt #evidence based medicine #gender affirming care #gender affirmation #gender affirming healthcare #dangerously unqualified #gender ideology #queer theory #conflict of interest #confirmation bias #medical scandal #medical malpractice #ideological corruption #gender activism #religion is a mental illness

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radiologycenter · 1 month ago

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Impact of AI on Radiology Practices

The integration of AI in radiology practices has far-reaching implications for healthcare delivery and patient care. Some of the notable impacts include:

Streamlining Workflow and Reducing Turnaround Time

AI-powered tools can automate repetitive tasks, such as image analysis and report generation, leading to a more efficient workflow and reduced turnaround time for radiological examinations. This can contribute to faster diagnosis and treatment planning for patients.

Facilitating Personalized Treatment Plans for Patients

AI technologies can analyze large volumes of patient data, including imaging studies, genetic information, and clinical records, to support the development of personalized treatment plans. By leveraging predictive analytics and decision support systems, radiologists can tailor interventions to individual patient needs.

You can learn more about DICOM Anonymisation Software

Redefining the Role of Radiologists in the Healthcare Ecosystem

AI integration in radiology is reshaping the role of radiologists from image interpreters to strategic decision-makers. Radiologists are increasingly becoming collaborators in multidisciplinary care teams, leveraging AI insights to provide comprehensive patient management and treatment strategies.

You can learn more about PACS System Radiology

Challenges and Limitations of AI in Radiology

While the potential benefits of AI in radiology are substantial, there are also challenges and limitations that need to be addressed for successful integration. Some of the key concerns include:

Data Privacy and Security Concerns

The use of AI in radiology relies on access to vast amounts of sensitive patient data, raising concerns about data privacy, security, and compliance with regulatory standards such as HIPAA. Safeguarding patient information and ensuring secure data transmission and storage are critical considerations in AI integration.

Integration with Existing Healthcare Systems and Processes

Integrating AI technologies into existing radiology workflows and healthcare systems can present technical and logistical challenges. Compatibility with electronic health record (EHR) systems, interoperability with imaging devices, and seamless integration into clinical practice are essential for the successful adoption of AI in radiology.

Addressing the Potential for Algorithmic Bias and Errors

AI algorithms are susceptible to biases and errors, particularly when trained on imbalanced or incomplete datasets. Ensuring the fairness and reliability of AI-driven diagnostic tools is crucial to mitigate the risk of misdiagnosis or inaccurate clinical recommendations.

You can learn more about Radiology Teaching Files

#Radiology

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cloudastra1 · 1 month ago

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The Transformative Impact of AI in Healthcare: A Case Study in Lymphoma Treatment

AI in Healthcare: Revolutionizing Patient Care and Medical Research

Artificial Intelligence (AI) is transforming the healthcare industry by enhancing the accuracy of diagnoses, personalizing patient care, accelerating medical research, and optimizing operational efficiency. From predictive analytics to robotic surgery, AI is redefining the landscape of modern medicine. This blog explores the various applications of AI in healthcare, the benefits it offers, the challenges it faces, and the future prospects of this groundbreaking technology.

1. Enhancing Diagnostic Accuracy

AI-powered diagnostic tools are proving to be invaluable in detecting diseases early and accurately.

a. Medical Imaging: AI algorithms can analyze medical images such as X-rays, MRIs, and CT scans with remarkable precision. By identifying patterns and anomalies that may be missed by the human eye, AI helps radiologists diagnose conditions like tumors, fractures, and infections more accurately and at an earlier stage.

b. Pathology: In pathology, AI systems are used to examine tissue samples and detect abnormalities such as cancer cells. These systems can process large volumes of data quickly, providing pathologists with insights that improve the accuracy and speed of diagnoses.

2. Personalizing Patient Care

AI is enabling more personalized approaches to patient care, improving outcomes and patient satisfaction.

a. Predictive Analytics: AI-driven predictive analytics can forecast disease progression and patient outcomes based on historical data and current health status. This allows healthcare providers to tailor treatment plans to individual patients, improving effectiveness and reducing adverse effects.

b. Virtual Health Assistants: AI-powered virtual health assistants provide patients with 24/7 access to medical information, appointment scheduling, medication reminders, and symptom checking. These tools enhance patient engagement and adherence to treatment plans.

3. Accelerating Medical Research

AI is revolutionizing medical research by accelerating the discovery of new treatments and improving clinical trial processes.

a. Drug Discovery: AI algorithms can analyze vast datasets to identify potential drug candidates, predict their efficacy, and optimize their chemical structures. This significantly speeds up the drug discovery process and reduces costs.

b. Clinical Trials: AI helps design and manage clinical trials more efficiently by identifying suitable participants, predicting patient responses, and monitoring compliance. This leads to faster and more reliable trial outcomes.

4. Optimizing Operational Efficiency

AI applications in healthcare operations are improving efficiency and reducing costs.

a. Administrative Automation: AI systems can automate administrative tasks such as patient scheduling, billing, and claims processing. This reduces the administrative burden on healthcare staff and minimizes errors.

b. Supply Chain Management: AI-driven supply chain management solutions optimize inventory levels, predict demand, and manage logistics. This ensures that healthcare facilities have the necessary supplies and medications without overstocking or shortages.

5. Addressing Challenges in AI Integration

While AI offers numerous benefits, its integration into healthcare also presents several challenges.

a. Data Privacy and Security: Protecting patient data is paramount in healthcare. Ensuring that AI systems comply with data privacy regulations and safeguard sensitive information is crucial.

b. Ethical and Bias Concerns: AI systems can inadvertently perpetuate biases present in training data, leading to disparities in care. Developing fair and unbiased AI algorithms is essential to ensure equitable healthcare.

c. Interoperability: Integrating AI solutions with existing healthcare systems and ensuring interoperability between different platforms is a significant challenge. Standardizing data formats and communication protocols can help overcome this hurdle.

d. Regulatory Compliance: AI technologies must meet stringent regulatory requirements to be approved for clinical use. Navigating the regulatory landscape can be complex and time-consuming.

6. Future Prospects

The future of AI in healthcare is promising, with ongoing advancements and new applications emerging.

a. Genomics and Precision Medicine: AI will play a crucial role in genomics and precision medicine by analyzing genetic data to develop personalized treatment plans based on an individual’s genetic makeup.

b. Remote Monitoring and Telehealth: AI-powered remote monitoring devices and telehealth platforms will continue to expand, providing patients with convenient access to healthcare services and enabling continuous health monitoring.

c. AI in Mental Health: AI applications in mental health are developing rapidly, with tools that can analyze speech and behavior patterns to detect mental health issues and provide early interventions.

d. Collaborative AI: AI systems will increasingly collaborate with healthcare professionals, augmenting their capabilities and allowing them to focus on complex and high-value tasks.

Conclusion

AI is revolutionizing healthcare by improving diagnostic accuracy, personalizing patient care, accelerating medical research, and optimizing operations. Despite the challenges, the potential benefits of AI in healthcare are immense. As technology continues to advance, AI will play an increasingly central role in delivering high-quality, efficient, and personalized healthcare, ultimately improving patient outcomes and transforming the medical landscape. The integration of AI into healthcare is not just a technological evolution; it represents a paradigm shift that holds the promise of a healthier future for all.

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digitalxonixblogs · 2 months ago

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AI in Healthcare Research: the Next Wave of Innovation

The field of research in healthcare is experiencing a radical change driven by advances of Artificial Intelligence (AI). While healthcare is continuing to develop with the advancement of AI, the fusion of AI technology opens up new possibilities for innovation, improving the quality of care as well as streamlining the process. Photon Insights is at the forefront of this transformation offering the most cutting-edge AI solutions that enable healthcare professionals and researchers to discover new opportunities for medical science research.

The Importance of Photon Insights in Healthcare Research

Healthcare research plays a crucial part in improving patient care and developing new treatments and enhancing the health system. But, traditional research methods frequently face difficulties such as excessive data collection, long time frames and resource limitations. AI can provide innovative solutions that solve these issues by allowing researchers to study huge quantities of data fast and precisely.

Key Benefits of AI in Healthcare Research

1. “Enhanced Analysis of Data AI algorithms are adept at processing huge amounts of data and gaining information that will help aid in making clinical decisions as well as research direction. This ability lets researchers identify the patterns and trends in their data that could be missed by conventional methods.

2. Accelerated Drug Discovery: AI-driven models could significantly cut down on the time and expense associated in the process of developing drugs. By anticipating how various chemicals are likely to interact with biochemical systems AI could speed up the process of drug discovery which results in faster and more efficient treatment options.

3. “Personalized Medicine”: AI assists in the study of genome-related data and patient histories, which can lead to the creation of customized treatment plans. This method increases the efficacy of treatments and improves the patient’s outcomes by tailoring treatments to the individual’s needs.

4. “Predictive Analytics: AI can forecast disease outbreaks, patient admissions and treatment response using previous data. This capability can help healthcare professionals allocate resources more efficiently and prepare for the possibility of challenges.

5. Improved Clinical Trials AI improves the planning and execution for clinical research by discovering appropriate candidates, enhancing protocols, and monitoring results in real-time. This results in better-performing trials and faster access to the latest therapies.

Challenges in Implementing AI

Although it has many benefits however, the implementation of AI in research on healthcare isn’t without its difficulties. Concerns like data security concerns and privacy, requirement for standardized data formats and the possibility of bias in algorithms must be taken care of in order to fully utilize what is possible with AI technology.

1. Data Security and Privacy: Protecting the privacy of patient data is essential. Researchers must be sure to comply with the rules like HIPAA when employing AI tools to examine sensitive information.

2. Standardization of Data Inconsistent formats for data within healthcare systems could hinder the efficient use of AI. Establishing standard protocols for sharing and collecting data is essential to ensure seamless integration.

3. Algorithmic Bias AI systems are as effective as the data they’re taught on. If the data is flawed or insufficient the algorithms that result may result in skewed outcomes, increasing health disparities.

Photon Insights: Leading the Charge In Healthcare Research

Photon Insights is revolutionizing healthcare research with cutting-edge AI solutions to address these challenges head on. The platform was designed to provide clinicians, researchers, and healthcare institutions with the tools needed to use AI efficiently.

Key Features of Photon Insights

1. Superior Data Integration: Photon Insights combines data from a variety of sources, such as medical records on the internet, trials in clinical research as well as genomic database. This approach is comprehensive and lets researchers do more thorough analysis, which improves the quality of their results.

2. “User-Friendly Interface”: Its easy-to-use design enables researchers from all backgrounds in technology to access complex data easily. This ease of use encourages collaboration among multidisciplinary teams, enabling innovations in research.

3. Advanced Analytics Tools Photon Insights offers state-of-the-art machine learning algorithms that are able to analyze and interpret massive datasets quickly. Researchers can gain actionable insights from data, enabling informed decisions.

4. Ethical AI Practices Photon Insights puts a high priority on ethical considerations when it comes to AI development. The platform implements strategies to minimize bias and to ensure the transparency of its processes, which helps build trust between both the user and other parties.

5. Real-time monitoring and reporting This platform allows researchers to keep track of ongoing research and clinical trials in real-time, offering timely data that inform immediate actions. This feature improves the flexibility of research strategies and enhances results.

Real-World Applications of AI in Healthcare Research

AI technologies are currently used in a variety of research areas in the field of healthcare, showing their ability to create improvements in patient care:

1. Diagnosis of Disease : AI techniques are designed to analyze medical images including X-rays, and MRIs with astonishing precision. These tools aid radiologists in identifying illnesses earlier, resulting in timely treatments.

2. “Chronic disease Management AI-driven analytics are able to track the patient’s data over time, which can help healthcare professionals manage chronic illnesses like hypertension and diabetes more efficiently. Predictive models are able to alert healthcare professionals to the possibility of complications prior to they occur.

3. “Genomic research: AI plays a pivotal role in the field of genomics, processing large quantities of genetic information. Researchers are able to identify the genetic markers that cause illnesses, opening the way for targeted treatments and preventive actions.

4. “Healthcare Operations”: AI enhances operations in hospitals by anticipating admissions of patients as well as scheduling staff, and enhancing supply chain management. This improves utilization of resources and better patient experience.

The Future of AI in Healthcare Research

What lies ahead for AI in the field of healthcare research is expected to transform healthcare research. As technology improves, a variety of tendencies are likely to influence the future of AI in healthcare research:

1. Increased Collaboration Integrating AI will lead to more collaboration among researchers, clinicians and tech developers. Multidisciplinary partnerships will fuel forward the pace of innovation and result in advancements in the treatment and care field.

2. Enhanced Frameworks for Regulation as AI is becoming more commonplace in healthcare, regulators are developing guidelines to ensure appropriate and ethical usage of these technology. This will improve trust and encourage ethical AI methods.

3. Greater focus on health Equity The future will see greater emphasis on the use of AI to tackle health disparities. Researchers will use AI to identify populations at risk and design interventions that meet their particular needs.

4. Continuous Learning and Adaptation: AI systems will continue to develop, taking in new information and experiences. This ability to adapt will increase the accuracy of predictions as well as the efficiency of interventions in the long run.

Conclusion

AI is opening a brand new era in research into healthcare that will open up opportunities for innovation previously impossible to imagine. Through enhancing data analysis, speeding up the discovery of drugs, and providing personalization of medical treatment, AI is transforming the ways that researchers tackle healthcare issues. Photon Insights is leading this revolution, offering the most powerful AI tools to help medical professionals to make educated decisions and create positive change.

While the use of AI is evolving the potential for AI to improve the patient experience and streamline processes in healthcare will only grow. By taking advantage of these developments in healthcare, the industry will be sure that it is in the forefront of technological advancement which will ultimately benefit the patients as well as society as a as a whole. The future of research in the field of healthcare is bright and AI is a major influencer in its development.

#AI academic research #AI #AI in healthcare research #AI in thesis writing #photon insights #photon live #AI risk analysis #documents insights #free AI tool #AI tool for students #AI Research Assistant

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davidtech · 2 months ago

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AI in Healthcare Research: the Next Wave of Innovation

The Importance of Photon Insights in Healthcare Research

Key Benefits of AI in Healthcare Research

1. Enhanced Analysis of Data AI algorithms are adept at processing huge amounts of data and gaining information that will help aid in making clinical decisions as well as research direction. This ability lets researchers identify the patterns and trends in their data that could be missed by conventional methods.

4. Predictive Analytics: AI can forecast disease outbreaks, patient admissions and treatment response using previous data. This capability can help healthcare professionals allocate resources more efficiently and prepare for the possibility of challenges.

Challenges in Implementing AI

Photon Insights: Leading the Charge In Healthcare Research

Key Features of Photon Insights

Real-World Applications of AI in Healthcare Research

AI technologies are currently used in a variety of research areas in the field of healthcare, showing their ability to create improvements in patient care:

The Future of AI in Healthcare Research

Conclusion

#AI academic research #AI data analysis #AI in healthcare research #AI in finance #photon insights #photon live #AI risk analysis #documents insights #free AI tool #AI tool for students #AI Research Assistant

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jamespotter7860 · 2 months ago

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AI in Healthcare Research: the Next Wave of Innovation

The Importance of Photon Insights in Healthcare Research

Key Benefits of AI in Healthcare Research

Challenges in Implementing AI

Photon Insights: Leading the Charge In Healthcare Research

Key Features of Photon Insights

Real-World Applications of AI in Healthcare Research

AI technologies are currently used in a variety of research areas in the field of healthcare, showing their ability to create improvements in patient care:

The Future of AI in Healthcare Research

Conclusion

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zealandimmigration1 · 2 months ago

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How to Obtain a New Zealand Nursing Qualification

How the New Zealand OSCE Programme Helps Doctors Secure Licensure

For international medical graduates (IMGs) looking to practice in New Zealand, the New Zealand OSCE Programme is a crucial step toward securing licensure. This structured assessment evaluates the clinical skills and competencies of doctors, ensuring they meet New Zealand’s healthcare standards. With the right qualifications and preparation, IMGs can navigate the OSCE successfully and obtain the necessary Visa for doctors in New Zealand to begin their medical careers.

Understanding the New Zealand OSCE Programme

The New Zealand OSCE Programme (Objective Structured Clinical Examination) is designed to assess the practical skills of medical graduates. The OSCE is a widely recognized examination format that tests various competencies through multiple stations, each focusing on different clinical scenarios. This approach helps ensure that doctors are well-equipped to provide high-quality care to patients in New Zealand.

Key Features of the New Zealand OSCE Programme:

Objective Assessment: The OSCE uses standardized patients and clear assessment criteria to evaluate performance, minimizing bias.

Multiple Stations: Candidates rotate through various clinical stations, allowing them to demonstrate different skills in real-world scenarios.

Practical Focus: Emphasizing hands-on skills, the OSCE assesses essential areas such as communication, clinical examination, diagnosis, and management.

Successfully completing the New Zealand OSCE Programme is essential for IMGs seeking medical registration and practice in New Zealand.

The Path to Licensure: Steps Involved

For international doctors, the path to obtaining licensure in New Zealand involves several steps, including completing the New Zealand OSCE Programme. Here’s an overview of the process:

Verify Your Medical Qualifications: Before you can apply for the OSCE, you must have your medical qualifications assessed by the Medical Council of New Zealand (MCNZ). This step ensures that your qualifications are equivalent to New Zealand standards.

Apply for the New Zealand OSCE Programme: Once your qualifications are verified, you can apply for the New Zealand OSCE Programme. Ensure you meet all prerequisites and understand the application timeline, as spots may be limited.

Prepare for the OSCE: Preparation is crucial for success in the New Zealand OSCE Programme. Familiarize yourself with the exam format, practice clinical scenarios, and consider joining study groups or preparation courses.

Complete the OSCE: Take the exam, demonstrating your clinical skills across various stations. You’ll need to show competence in communication, patient examination, and clinical decision-making.

Receive Your Results: After completing the New Zealand OSCE Programme, you will receive your results. A passing score is necessary for medical registration.

Apply for Medical Registration: With a successful OSCE outcome, you can apply for medical registration with the MCNZ, which allows you to practice medicine in New Zealand.

Obtain Your Visa for Doctors in New Zealand: After securing registration, you can apply for a Visa for doctors in New Zealand to legally work in the country.

Importance of the New Zealand OSCE Programme

The New Zealand OSCE Programme serves several critical functions for IMGs seeking licensure:

1. Ensures Competence

The OSCE rigorously evaluates the clinical skills of doctors, ensuring they meet New Zealand’s healthcare standards. This assessment process helps protect patient safety and maintains the quality of care in the healthcare system.

2. Enhances Confidence

Preparing for the New Zealand OSCE Programme allows doctors to enhance their clinical skills and gain confidence in their abilities. This preparation is vital for building a successful career in a new healthcare environment.

3. Fosters Integration

Completing the OSCE helps IMGs integrate into the New Zealand healthcare system. Understanding local practices, cultural aspects, and communication styles is essential for effective patient care and collaboration with colleagues.

4. Provides a Clear Pathway

The New Zealand OSCE Programme outlines a clear pathway for IMGs to achieve licensure. By following the established steps, doctors can systematically navigate the process and secure the necessary qualifications to practice in New Zealand.

Preparing for the New Zealand OSCE Programme

Preparation is key to succeeding in the New Zealand OSCE Programme. Here are several tips to assist you in your preparation:

1. Understand the Format

Familiarize yourself with the OSCE format, including the number of stations, types of scenarios, and assessment criteria. This knowledge will help you feel more comfortable on exam day.

2. Practice Clinical Skills

Regular practice is essential. Engage in mock OSCEs with peers or mentors to simulate exam conditions. This practice will help you refine your skills and improve your performance.

3. Study Clinical Guidelines

Review relevant clinical guidelines and protocols that are commonly used in New Zealand. Familiarizing yourself with local practices will give you an advantage during the OSCE.

4. Seek Support

Consider joining study groups or seeking mentorship from those who have successfully completed the OSCE. Their insights and experiences can provide valuable guidance during your preparation.

The Role of Visa for Doctors in New Zealand

Securing a Visa for doctors in New Zealand is an essential part of the process for IMGs. After completing the New Zealand OSCE Programme and obtaining medical registration, you must apply for the appropriate visa to work legally in the country.

Types of Visas Available:

Resident Visa: If you have secured a job offer from a New Zealand employer, you may be eligible for a resident visa. This visa permits you to reside and work in New Zealand on a permanent basis

Work Visa: If you have not yet secured a job but wish to explore opportunities, a work visa may be suitable. This visa allows you to work for a specified employer for a limited time.

Visa Application Process:

Gather Required Documents: This may include your medical registration, proof of qualifications, and job offer letter.

Submit Your Application: Complete the visa application form and submit it along with the required documents to Immigration New Zealand.

Wait for Processing: The processing time may vary, so ensure you apply well in advance of your intended start date.

Conclusion

The New Zealand OSCE Programme plays a vital role in helping international medical graduates secure licensure and successfully practice medicine in New Zealand. By ensuring competence and fostering integration into the healthcare system, the OSCE serves as a crucial stepping stone for IMGs.

With thorough preparation and a clear understanding of the steps involved, doctors can confidently approach the New Zealand OSCE Programme and navigate the visa application process. Achieving medical registration and obtaining a Visa for doctors in New Zealand allows IMGs to embark on a fulfilling career in a country known for its high-quality healthcare and supportive environment.

By following this guide, you’ll be well-equipped to take on the challenges ahead and thrive in your medical career in New Zealand.

#zealandimmigration #Visa for Doctors in New Zealand #Medical Registration in New Zealand #International Medical Graduates

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photon-insights · 2 months ago

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AI in Healthcare Research: the Next Wave of Innovation

The Importance of Photon Insights in Healthcare Research

Key Benefits of AI in Healthcare Research

Challenges in Implementing AI

Photon Insights: Leading the Charge In Healthcare Research

Key Features of Photon Insights

Real-World Applications of AI in Healthcare Research

AI technologies are currently used in a variety of research areas in the field of healthcare, showing their ability to create improvements in patient care:

The Future of AI in Healthcare Research

Conclusion

#Health Care Research #Ai Innovation #Ai Practices #Photon Insights #Ai For Healthcare

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