New research from the University of St Andrews has found that women are less like than men with the same medical condition to be offered active management such as surgery, a stent or a strong painkiller.
The findings, published in PLOS One, come from a review that sifted 1112 published studies down to those that directly compared the care given to male and female patients. Of the 38 that analysed patient records, 33 reported a significant difference in the treatment men and women received.
Researchers from the University of St Andrews School of Medicine found that almost none of those studies pointed to any guideline recommending different treatment by sex, leaving open whether this reflects sound clinical judgement or unequal care.
Dr Andrew O’Malley, who co-led the study, said: “For clinicians, the findings are a prompt to check whether treatment is being offered on clinical grounds rather than assumption. For example, one study found that when the teams deciding who receives advanced heart failure therapy functioned poorly, women were less likely to be selected. Other work shows doctors more often attribute women’s symptoms to anxiety and make more diagnostic errors with female patients, even when test results are positive.
Dr Miriam Veenhuizen, Honorary Lecturer in the School of Medicine, said: “While the direction of the findings was not a surprise the consistency was. The same pattern appeared in cardiology, surgery, transplant medicine and emergency care, and it survived statistical adjustment in most studies. It’s not entirely clear why this is happening, but it is likely because women were under-represented in clinical trials until recent decades, so many guidelines rest on data from men.”
Dr Veenhuizen added: “What struck us most was the imbalance in attention. Over the same period, 551 studies examined sex inequality affecting doctors and other health professionals. Only 41 examined what happens to patients.”
The researchers now intend to test whether the same patterns appear in the outputs of generative AI systems, which are trained on this literature and on clinical records, and which could entrench these differences at scale if left unchecked.
Investigation reignites questions about what steps were taken to safeguard public health from any unintended consequences of the vaccination rollout
Photo by Mufid Majnun on Unsplash
US health officials knowingly relied on a compromised algorithm to detect signals of harm from mRNA covid-19 vaccines and silenced efforts to fix it, finds an investigation published by The BMJ.
The findings are based on government emails released under the Freedom of Information Act and in response to US Senate investigators, as well as exclusive interviews with public health officials and other scientists by investigative journalist David Willman.
Before rolling out covid-19 vaccines in December 2020, the US Centers for Disease Control and Prevention (CDC) assured healthcare professionals and the public that its Vaccine Adverse Event Reporting System (VAERS) could quickly spot any potentially harmful reactions following vaccination.
The CDC planned to use two “data mining” techniques: “proportional reporting ratios” (PRRs) and an “empirical bayesian” method provided by the Food and Drug Administration (FDA), which operated VAERS jointly with the CDC. The two agencies planned to share and discuss results.
But according to a letter by CDC Director Rochelle Walensky, the agency did not perform PRR analyses until 2022, and both CDC and FDA “chose to rely” entirely on FDA’s bayesian method.
The BMJ can reveal that the FDA’s algorithm failed to signal a potential relationship between mRNA covid vaccination and myocarditis (inflammation of the heart muscle), pericarditis (inflammation of the fluid-filled sac around the heart), Bell’s palsy, tinnitus, and other reported disorders owing to a flaw in the detection methodology.
The problem arose because over 90% of initial VAERS reports were for the new mRNA covid vaccines made by Pfizer and Moderna. If both vaccines elevated the risk of an adverse event like myocarditis in roughly equal amounts, however, the “observed” frequency and “expected” frequency would be similar, resulting in no automated alert.
Internal records show that FDA officials were aware of this limitation before and during the pandemic. Government documents also show that CDC officials were informed during rollout of the vaccines.
In early 2021, FDA medical officer Dr Ana Szarfman, working with statistician William DuMouchel, who had developed the bayesian algorithm, warned top officials about the flaw and proposed an updated algorithm that flagged signals. But Szarfman was asked to “cease and desist.” Meanwhile, officials continued to cite the lack of system alerts while reassuring clinicians and the public of the vaccines’ safety.
When the CDC finally ran PRR analyses in 2022, CDC director Walensky said results revealed “no additional unexpected safety signals.” Yet the analyses – examined by The BMJ – show hundreds of adverse events that met the agency’s alert criteria, including myocarditis, pericarditis, Bell’s palsy, and tinnitus, which the FDA’s bayesian method had not triggered.
In October 2023, the FDA’s pharmacovigilance chief acknowledged in an email to colleagues that the agency knew – as the vaccines had rolled out more than two years earlier – of the detection deficiency, but did not respond to requests for comment.
Approached by The BMJ, Szarfman insisted that she had not sought to undermine public support for the covid vaccines. Expressing frustration, she noted, “Very few people understand the statistics. That’s the problem.”
DuMouchel said he could not explain officials’ resistance to switch to the updated method, stating, “I think that they were wrong.” He also regretted that FDA officials rejected Szarfman’s proposed fixes for VAERS, adding, “If they had paid attention to Ana, they would have done better.”
Eminent cardiologist involved in treatment guidelines received £50m from drug research contracts Case shows what’s at stake in the debate around transparency of doctor-industry relations
Source: CC0
A British cardiologist and former president of the European Society of Cardiology (ESC) has been judged by the ESC to have committed severe misconduct after a Danish TV documentary reported that he had been involved in drawing up guidelines for the use of the heart drug ivabradine (Corlanor, Procoralan) while profiting from lucrative contracts with the drug’s maker.
An investigation published by The BMJ describes how between 2006 and 2015, Kim Fox, emeritus professor of clinical cardiology at the National Heart and Lung Institute, Imperial College London, who reportedly served as cardiologist to the late Queen Elizabeth II, and his wife Karen Summers, a former drug industry executive, received more than £50m as co-directors of the UK based contract research organisation Heart Research.
This company was involved in running at least three clinical trials of ivabradine, made by French drug company Servier, that were published in the same period, reports freelance journalist, Laura Spinney.
In 2006, when Fox became president of the ESC, he chaired an ESC taskforce that published a guideline recommending ivabradine as an alternative treatment for angina in patients who couldn’t tolerate beta blockers. Authors were asked to disclose conflicts of interests, but the guideline did not publicly identify what Fox had disclosed.
As outgoing ESC president in 2008, Fox championed the drug publicly though it had failed to meet the primary endpoint in the first of the three trials Heart Research was involved in.
Ivabradine remains approved for angina and heart failure in Europe, and for heart failure in the US, but persistent doubts have been expressed over its efficacy.
It’s rare for alleged conflicts of interest to involve such large sums of money. The case remains unreported in most of Europe and beyond, even though the ESC’s guidelines are influential worldwide.
The Danish documentary, which aired in September 2024, triggered an internal review by the ESC which found that the 2006 guideline recommendations were “appropriate” and reported “no evidence to suggest a bias towards ivabradine.”
But in March 2025, the ESC ethics committee found that Fox “had failed to meet his ethical obligations and considered his behaviour as a severe misconduct.”
Pulmonologist Irène Frachon, described the sums involved in the case as “monstrous” while Rita Redberg, a cardiologist and former editor in chief of JAMA Internal Medicine, said: “It totally goes against the grain of the profession.”
Fox rejected the ethics committee’s findings and resigned his ESC membership, claiming that he had always declared any conflicts of interest and that “he was not prepared to be judged on the basis of rules and regulations described in 2024 retrospectively for activities in 2006 to 2008.”
The ESC admitted to The BMJ that its declarations process was relatively lax in the early 2000s and said that it had been substantially strengthened since. Meanwhile, Servier said that it “strictly complies” with transparency guidelines established by the European Federation of Pharmaceutical Industries and Associations, a trade body.
The Fox story has emerged at a time when some in Europe are pushing for reforms that would end voluntary declaration of conflicts of interest and enshrine greater transparency in law.
For former ESC vice president John Martin, the ESC has not done enough to restore public trust, and the recent revelations risk damaging the doctor-patient relationship while also leaving the volunteers who run the society feeling betrayed. He urged further action. “The ESC board might be seen as tacitly complicit unless there is a thorough public investigation,” he said. “Many questions remain.”
A conversation with Qingyu Chen, PhD, about what medical artificial intelligence learns, what it memorises, and what it takes to use it responsibly.
Qingyu Chen, PhD, and his team set out to study how artificial intelligence language models are adapted for medicine and found that what these models memorise can be both useful and risky. A model may retain valuable medical knowledge, but in a controlled study using real hospital records, the same fine-tuning – the added training that adapts a model to a specific task – that improved diagnostic performance also made it more likely to reproduce material it had seen during training, including sensitive patient information.
The study, published recently in Nature Communications, reflects a question at the center of Chen’s research: How can medical AI become not only more capable but also more reliable and safer? The study was led by its first author, Anran Li, PhD, who conducted the research as a postdoctoral researcher in Yale’s Department of Biomedical Informatics and Data Science.
Chen is an assistant professor of biomedical informatics and data science at Yale School of Medicine, with a secondary appointment in ophthalmology. He leads research on the accuracy and reasoning of medical language models and on multimodal AI-assisted disease diagnosis, which draws on both text and medical images.
The following conversation with Chen discusses what medical AI learns, what it memorises, and what it takes to use it responsibly.
What is your lab’s research focus?
Our lab does two things that are usually treated as separate: We build medical AI, and we study where it fails.
On the building side, we work with two main kinds of information medicine runs on. We develop models that read clinical records and the medical literature, models that analyse medical images to help diagnose disease and predict its course, and systems that combine both, so an AI can weigh a patient’s written history alongside their scans, the way a physician would.
But a model that performs well on a test is not the same as a model you can trust with a patient. So, we also study how these systems fail. They can state falsehoods with complete confidence. They can reach a right answer through faulty reasoning. And, as our recent work shows, they can memorise sensitive information from the data they were trained on.
Our goal is to develop medical AI that is genuinely useful, understand where it breaks down, and produce the evidence needed to know when it can – and cannot – be trusted.
Why work across both text and images?
Because medicine is inherently multimodal. A patient cannot be understood through a single paragraph or a single image. Clinical decisions often require bringing together a patient’s history, laboratory results, medical notes and imaging findings.
Our work spans both sides of that. On the language side, we develop methods to help computers understand clinical records and biomedical literature. On the imaging side, much of our research focuses on medical images and specialties that depend heavily on them—ophthalmology in particular, where we work on diagnosing eye disease and predicting how it will progress. This is also why I hold a secondary appointment in ophthalmology.
Progress here requires more than developing new models. One of the biggest barriers is the limited availability of medical data that is large enough, reliable enough and free for researchers to share.
To help address this, we recently developed MedPMC, a system that has assembled 11 million medical images paired with their accompanying text, drawn from research literature that is openly licensed for reuse—and that is designed to keep growing as new research is published. We’ve made the data, the tools used to assemble it, the tests for measuring performance and the resulting models publicly available so that other institutions can develop, evaluate, reproduce and adapt these systems rather than starting from scratch.
Your team recently published a study in Nature Communications on how AI models ‘memorise’ medical data. What does memorisation mean here?
Memorisation means that a model can recall or reproduce content it encountered during training. If a model has been trained on clinical guidelines, it may reproduce part of a guideline when you give it the opening of that passage. If it has had additional training on a set of medical exam questions, it may produce an answer choice that appeared in that training data – even after we removed that choice from the question.
That is different from simply saying that a model performs well. When a model answers a question correctly, there are several possible explanations. It may have acquired genuine medical knowledge. It may have learned a pattern of reasoning it can apply to problems it hasn’t seen before. Or it may simply recognise the question and reproduce something it previously saw during training. If all we check is whether the final answer is correct, we cannot tell these apart.
So, our goal was to look beyond accuracy and ask a different set of questions: How often does memorisation occur? What types of content get memorised? How much can a model reproduce? Does what it memorised earlier survive further training? And what does all of this mean for using these systems in medicine?
What did you find?
We looked at the main stages a general-purpose model goes through on its way to becoming a medical one.
First, we examined models that had already undergone continued pretraining, in which a general-purpose model is trained further on large collections of medical text, including biomedical literature, clinical guidelines and clinical notes. Second, we evaluated models that had been fine-tuned on the standard question-and-answer datasets that the field uses to test medical models. Third, we conducted a privacy-protected, HIPAA-compliant study using more than 13 000 medical records to fine-tune models for disease diagnosis.
This was done in an isolated and secure computing environment. These records had already been collected in the course of care; the study did not recruit patients or change anyone’s treatment.
Across those settings, we examined both general-purpose models and models trained on medical data, 10 different datasets containing hundreds of thousands of records and thousands of model responses that we manually reviewed.
The patterns differed depending on the training stage. Continued pretraining was more likely to produce long, word-for-word matches to source documents. Fine-tuning produced less long-form copying in some settings, but more memorisation tied to the specific task the model was trained on. For example, after fine-tuning on medical question-and-answer datasets, models reproduced roughly 14% to 21% of the answer choices that had been removed from the question the model was shown.
We also found that memorisation was persistent. Depending on the setting, as much as 87% of what a model memorised during continued pretraining was still present after it had been fine-tuned on a new medical task. Fine-tuning does not necessarily erase what a model previously memorised. It may preserve that content while adding new memorisation specific to the task it was just trained on.
What did the clinical case study show?
The clinical case study showed both the potential benefit and the risk of adapting these models to real-world medical data. Fine-tuning improved diagnostic performance; for one model, the correct diagnosis came up as its first choice 54.8% of the time, up from 48.6%. In some specialties, the gains were larger than that – more than 10 percentage points in areas such as cardiology and nephrology, which deal with heart and kidney conditions.
At the same time, the study showed a real privacy risk. In a controlled test conducted in a secure research setting, we found that the model could sometimes reproduce sensitive information from the records used to train it. This was not something that would happen during patient care, but it shows that privacy risks should be evaluated before models trained on clinical data are shared or deployed.
Is memorisation always harmful?
No. One of the central findings of our study is that memorisation in medicine is not a single behaviour.
We identified three broad types. The first is beneficial memorisation. A model may accurately retain biomedical concepts, clinical guidelines, the medical literature it has read or specific medical knowledge tied to its task. That kind of memory may support factual accuracy and help the model perform medical tasks more effectively.
The second is uninformative memorisation. Models sometimes reproduce document disclaimers, section headings, formatting instructions or other boilerplate language. This adds little medical value and may indicate that the model is learning surface-level patterns rather than deeper medical understanding.
The third is harmful memorisation. This includes reproducing quirks specific to a particular dataset, word-for-word passages from patient notes, protected health information or other sensitive patient content. This form of memorisation may create privacy risks and may also indicate that the model is leaning too heavily on its training data rather than generalising to new cases.
The important question, then, is not simply whether a model memorises; it is what the model memorises, why it memorises it, and whether that memory supports or undermines the medical use it is intended for.
Did anything about the way memorisation develops surprise you?
One thing that stood out: Memorisation did not only show up late, after a model had been trained too long. It began early.
As we trained the models, we tracked their progress and compared three things: how much they were memorising, how well they were learning by the usual measure, and how accurate their diagnoses were. Memorisation began increasing relatively early, even while the standard measures still showed the model improving, and before its diagnoses had reached their peak accuracy.
That means traditional indicators researchers watch during training – such as whether the model keeps improving on held-out data, or the point at which they would normally stop training – are useful but may not be sufficient on their own. A model can appear to be learning effectively according to standard performance measures while simultaneously increasing its retention of training-specific content.
We also found two other patterns. Larger models and longer inputs were generally associated with more memorisation. By contrast, changing common generation settings such as temperature – which controls how varied the model’s answers are – had relatively limited effects. This suggests that memorisation is fundamentally connected to how a model is trained and what data it is exposed to, rather than being something that can simply be solved by adjusting how the model generates its answers after training.
What do you most want readers to take away from this work?
Adapting an AI model to medicine does not simply make it “more medical.” It changes what the model knows, what it remembers and what it may reproduce.
Some of that memory is valuable. We want models to retain accurate medical knowledge and clinical guidance. But we do not want them to rely on meaningless repetition, echo back the answers to test questions or expose sensitive information from patient records.
Trustworthy medical AI therefore requires more than measuring whether a model gets the answer right. We need to understand how it got there, what it retained from training, and whether it will stay safe and reliable when used in a new setting.
For years, hospitals have relied on the unpaid, unprotected labour of trainee-specialists to fill their rosters, but these doctors are reaching a breaking point.
Across South Africa’s public sector hospitals, a growing number of aspiring specialists are choosing to work for free — sometimes for years at a time — in pursuit of the coveted title.
Nearly every step of the 12 to 15 years of training required to specialise or sub-specialise can only happen in the public sector, but provincial health departments, bruised by more than a decade of austerity and graft, have few paid posts to offer.
As a result, hundreds of local doctors and hopeful specialists are stuck in a nightmarish competition to be the most impressive candidate. There are waiting lists for both paid and unpaid positions.
Once the paid positions are filled, doctors from poorer backgrounds who did not get placed are at a dead end, perpetuating historical injustices and undercutting transformation targets. “A new apartheid,” several doctors call it.
The volunteer specialists Spotlight interviewed knew they were lucky to have the option to specialise, but their stories suggest it’s a dubious privilege.
They endure the financial and emotional stress of specialising without pay for a number of reasons, passion, to take over the family practise, or, most commonly, to secure a ticket out of the public healthcare sector.
But to reach the predictable hours and high income of specialist private practise, they must first navigate a clinical wasteland left behind by years of budget cuts and mismanagement by provincial health departments.
The gruelling unpaid route to specialisation they describe crosses a financial abyss with toll gates guarded by sometimes powerful bullies and dotted with legal and professional traps that could cast a long shadow over the futures they’re working to build.
How to spot a clinical spectre
South Africa’s phantom doctors have many names; they’re called fellows, volunteers or supernumeraries, depending on the facility.
The role was originally created as part of a regional programme that allows foreign doctors to train in South African hospitals. These trainees’ salaries are covered by their home governments and they’re not guaranteed a work visa through the Department of Home Affairs or accreditation from the Health Professions Council of South Africa (HPCSA) once they are qualified. Only 3% of the 5 772 doctors added to the government’s payroll between January and May were not South African citizens.
In recent years, so many South African doctors have accepted such unpaid positions that some provincial health departments advertise such “opportunities” and plan their budgets accordingly.
Spotlight was unable to quantify South Africa’s unpaid trainee specialist workforce. Only two of the eight medical schools surveyed between April and July provided trainee data and requests for the HPCSA’s list of active training codes for specialists and sub-specialists went unanswered. A training code is a non-negotiable prerequisite for sitting specialist exit exams regardless of funding source or employment status of the trainee. When cross-referenced with provincial payroll data, such a list could help estimate the extent to which the health system relies on unpaid expertise.
Anecdotal evidence suggests however that the trend started around 2020 in the Western Cape, where many interviewees say they wouldn’t mind working for the state. These days, Gauteng and KwaZulu-Natal’s cohorts of unpaid citizen specialists appear to be increasing too.
Interviews with numerous local supernumeraries suggest they often endure toxic hierarchies, bullying and administrative neglect, but they prefer to suffer in silence, terrified that seniors will fail them in expensive tests.
Specialist exams are officially set by the Colleges of Medicine (CMSA), but there are usually only a few qualified specialist examiners for each academic circuit. So, in reality, trainees are often being examined by their own department heads or a close colleague.
Pride, debt and resentment
The cutthroat race to build a standout CV starts as soon as medical students graduate. It’s no longer enough to gain experience as a medical officer and then to apply for a job as a registrar a couple of years later, there simply aren’t enough paid positions for either.
Any job posting can draw hundreds of applications from equally qualified candidates.
The resulting competition is harsh, and requirements ever shifting and often unstated.
Naeema Govender*, an aspiring anaesthesiologist in Gauteng, says it took her a couple of failed interviews to figure out how to decode a government job ad.
Experience in intensive care and internal medicine, she says, are now de facto requirements for anyone applying for a job as an anaesthesia registrar (or trainee-specialist) whether the advert says so or not, and “anaesthesia experience” really means a minimum of two years’ experience.
In highly competitive fields such as urology, registrar candidates are now expected to have completed two out of three major specialist exams (usually written during training) before they even apply.
Pulling shifts for free ends up being a good way to get an edge over others.
After a string of unsuccessful interviews for paid jobs, Meera Patel*, another anaesthesiologist-in-training, says she accepted a supernumerary post at Steve Biko Academic Hospital in Tshwane out of sheer desperation.
“I used to tell anyone who would listen that I would never subject myself to it,” she says. The extra experience did help Patel to get a paid registrar job in the Western Cape, but it left her feeling deep resentment for having to compromise her principles and work without pay to crack the system.
In Johannesburg, Govender says she also reluctantly took an unpaid position to beef up her CV. She’s still conflicted about the exploitation she felt forced into.
“I don’t know if I should be proud or ashamed,” she tells Spotlight.
Paranormal planning
The unpaid trainee specialist workforce does little to eventually increase the number of qualified specialists available to the public at government hospitals, so private healthcare appears to be the overall winner.
Once doctors are qualified specialists, they often flee to the private sector or emigrate. This is perhaps illustrated by the fact that 30% of the 22 405 doctors employed by the state are under the age of 35.
The trend has ultimately turned the public sector clinical platform into a subsidised training ground for private healthcare, argues Bernhard Gaede, an associate professor and head of the Department of Family Medicine at the University of KwaZulu-Natal.
There also seems to be an element of privatisation-by stealth unfolding.
Trainees are increasingly being supported by foundations or private hospital groups to fill a growing niche for sub-specialists, says Marthinus Dicks, a member of the South African Medical Association’s (SAMA) subcommittee for registrars.
At the Groote Schuur Hospital unit where Dicks is training to be a clinical haematologist, he says he’s one of only two who are paid a government salary. He also logged unpaid hours before he was offered a paid post.
He worries that the private money is taking pressure off the government to fulfil its training role. At the same time, he knows his already high workload would be much heavier without his three fellowship-supported colleagues. “It’s just not a life I want to imagine,” he says.
Between the free labour, private funding and foreign trainees, there’s little incentive for cash-strapped health provincial health departments to create permanent posts, according to a SAMA submission to the ministerial advisory committee on health staff.
The unpaid trainee specialist workforce isn’t mentioned in the health department’s health staffing reform plan, which lapses in 2030. The document does outline a five-year plan to improve clinical supervision, boost specialist retention and to develop a broader network of clinical support for trainees by 2025.
A progress report was submitted to Health Minister Dr Aaron Motsoaledi in March but critics say the plan is unlikely to have made a difference because the government lacks the high-quality data on public and private sector personnel that would be needed for implementation.
South Africa needs a Workforce Intelligence Authority that collates and cleans workforce data to be used for planning, suggests governance expert Professor Alex van den Heever. In July, he presented a draft policy brief to SAMA which also proposes ring-fencing training funds to protect salaries from provincial mismanagement and extending training subsidies and accreditation to private health facilities.
Without structural changes to address waste and mismanagement, Van Den Heever argues, simply giving provinces more money to counteract austerity will make no difference.
In the meantime, the government now deliberately budgets for clinical gaps to be filled by volunteers, says Sharon Twum-Boafo, head of SAMA’s registrar subcommittee.
“It’s ludicrous,” she says, “without the volunteers, many hospitals would simply not have enough doctors to cover 24-hour rosters.”
A legal void
Unpaid trainee specialists carry a heavy workload with few administrative and legal protections.
Since they lack a payroll number, they’re locked out of the blanket indemnity for healthcare workers employed by the state. Instead, government compels them to buy expensive private malpractice cover just to log hours for free in public hospitals.
Once they’re in the facility, Spotlight is told that it is possible they might be pressured to perform unsupervised, high-risk procedures far beyond their insured scope.
Speaking to Spotlight, several of these phantom physicians described their fear of being held personally liable for costs in potential lawsuits. Some are privately insured for millions of rands, which means that they would make for more lucrative targets than the government, where mediation often leads to lower payouts.
Ruan Vlok, head of SAMA’s employment law unit, agrees that unpaid specialists might become litigation lightning rods.
“It could become an easy making money machine for attorneys,” he says.
There are long term risks too.
Private insurance premiums are tied to clinical outcomes, so a pattern of bad events could drive up a doctor’s insurance premiums, or even render them uninsurable, the ultimate career-ending risk for a specialist.
Unfinished business
Some unpaid trainees face another tough reality.
They are often summoned to fill critical service gaps left by paid, full-time consultants who have vanished to moonlight in the private sector.
Dual practise is allowed within certain parameters, but enforcement of the rules is patchy across provinces and facilities. Money is one of the factors driving moonlighting among the state’s contracted specialists, whose salaries have not kept pace with inflation. A SAMA report estimates that in 2022, doctors were earning about as much as they were in 2013.
In order to save money, provincial health departments have limited the number of paid overtime hours that consultants can log. In this case, says Vlok, doctors are fully within their rights to refuse to work for free.
Ironically, this is when those who choose to work for free become extra useful in hospitals.
Yet should the phantom doctors themselves attempt to pull a paid shift to survive, they could be threatened with disciplinary action, heavy fines, or the immediate deactivation of their training numbers.
Under HPCSA and university rules, trainee registrars are legally barred from doing private paid work. Worse still, when a crisis occurs, these supernumeraries find themselves locked in dual contracts with universities and hospitals, with little protection from either.
An uneasy peace
The rights of the health system’s unpaid workforce have never been challenged in court, Vlok says, in part because doctors fear that any litigation would lead to them being targeted or failed in their exit exams.
Because supernumeraries aren’t officially employees, they’re also excluded from recourse through the country’s labour dispute resolution body, the Commission for Conciliation, Mediation and Arbitration and the Bargaining Council, leaving them with no mechanism for redress.
Local supernumeraries technically sign away they rights by agreeing to work without pay, but Vlok argues the state is taking advantage of a vulnerable group because the public sector is the only route to specialisation.
The regulations that allow foreign trainees to work in South Africa do not cater to or even make provision for South African citizens, Vlok says. In his view, the Labour Relations Act and the Basic Conditions of Employment Act should take legal precedence, under which he believes unpaid trainees clearly meet the criteria of an employee.
“I don’t use this word lightly,” he says, “this is abuse.”
It’s unclear how much longer the strained peace will hold.
One exhausted trainee specialist told Spotlight: “We have to fix the medical system, it’s broken. Who is going to look after us when we’re old?”
*Spotlight granted the doctors quoted in this article anonymity because of the risk of reprisals from provincial health departments and the hospitals where they are working.
Hazel Moagi proudly shows off awards for her work as a specialist forensic nurse, which represent her commitment to the field. (Photo: Elna Schütz/Spotlight)
By Elna Schütz for Spotlight
In a country like South Africa which grapples with a high prevalence of gender-based violence, forensic nursing unfortunately remains a largely overlooked specialisation, with little incentive for remuneration. One nurse tells Spotlight every flicker of hope a patient carries home is a reminder of why she chose this path.
Sister Hazel Moagi has won quite a few accolades as a forensic specialist nurse. These certificates and trophies are displayed on a table in one corner of her office at the Bertha Gxowa Care Centre in Germiston on the East Rand of Gauteng.
To Moagi, this small table carries tremendous weight. It motivates her to keep pushing in a career that is much needed but often soft-pedalled in both recognition and remuneration. “I call it my place of safety,” she says. “Whenever I feel down or that I’m not okay, I look at the achievements, and I say, you need to stand up, pick up the pieces, and try to do more for the community because they need me to.”
She lets out a giggle as she shares that colleagues would fondly call her ‘Nurse Hero’ after she scooped a 2023 Nurse Hero award. “It’s so fulfilling, more than monetary remuneration,” she says, adding that it also brings a sense of pride to those who know her “because you know small things make people happy.”
Those who know her well enough may notice an absence of yellow merchandise among the trophies in her office. As a long-time supporter of the Kaizer Chiefs football club, it wouldn’t be amiss in the forensic nurse’s office. She says she makes sure to catch every game in person or on television to decompress, given the heavy and sensitive nature of her work.
As operational manager of the Care Centre, Moagi runs a forensic medical service that she says many do not know is available when they need it. The Centre, on the grounds of the Bertha Gxowa Hospital, provides inclusive and comprehensive patient management of people who experience gender-based violence, including vulnerable populations such as children and people with disabilities as well as cases linked to trauma and driving under the influence of alcohol.
Both suspected perpetrators and victims of crimes are helped in the building, but the sections are separate, with the entrances out of sight of each other. Inside, there are rooms for various parts of the investigative and medical process. There’s a swing set, playroom, and colourful doctor’s room meant to make children feel more comfortable.
From victim to survivor
“We are turning victims into survivors,” Moagi says. It is particularly important to her that all her clients are treated with dignity and respect, for instance, by offering them bathing facilities, fresh clothes, and food. Safe lodging, such as access to shelters is arranged if needed.
Moagi says that a lot of patients arrive scared, traumatised, and often in the same clothes they were wearing during the crime. But after testing, treatment and brief recovery, the physical and emotional change is so different that she says even police staff fetching patients are regularly surprised that this is the same person they dropped off earlier.
Moagi says she finds cases involving children, especially those abused by a family member, especially difficult to handle.
“It’s so painful to see … abuse that happened within a space where it’s supposed to be a safe environment, and somebody you trusted with your child.”
The specialised unit’s work includes collecting forensic samples and offering support in cases of gender-based violence. She explains that it usually starts with the gathering of DNA and other samples into a Sexual Assault Evidence Collection Kit if a person reports sexual assault within 72 hours.
“Then the history that the patient gives us also guides us in terms of where to collect,” Moagi says. She explains that carefully asking patients to detail what happened will help her know where on the body it’s best to swab. The whole process may take over three hours, and the DNA is particularly important in forensic cases where the perpetrator was unknown to the victim.
Sometimes Moagi says she and her team notices commonalities between patients, which she then relays to her supervisor and the police. For instance, there may be multiple people who have been raped describing similar perpetrators and circumstances in the same geographical area, even if they have gone to different police stations or places for help. “If there’s a specific trend that is currently happening, then we escalate to say we have noted that this and this is happening around the specific area,” she says.
When forensic samples are collected properly and each case is understood in its wider context, it can make the difference in helping police identify a serial rapist and build a case. Moagi says she has testified in court in several such cases.
While being mindful of sharing confidential details, she does remember one case in particular. “He’s currently serving more than 200 years,” she says. “It makes you feel good that at least we have saved more women from becoming his victims.”
Memory of a neat white dress
Moagi says her passion for nursing comes from her early childhood in a small village near Bushbuckridge.
“There was a nurse that I used to see wearing her uniform, going to work, and coming back, and that’s when I said I also want to be a nurse,” she recalls. She smiles at the memory of the neat white dress the nurse wore, and how competent she seemed whenever Moagi saw her. She says she held on tight to that vision throughout her school years.
Indeed, she studied nursing and a few years later the dream was fulfilled. She started working as a general nurse.
A few years later she attended a three-day workshop on forensic medicine organised by several government departments. It was there, listening to forensic nurses speak about their work, that something new clicked for her. She says during the break, she felt compelled to speak to them and learn more about the work they did. “Since that day, I started to fall in love with managing gender-based violence cases,” she says. Around a year later, she started studying forensic nursing at the University of the Free State.
Passion over money
In specialising in forensic nursing, Moagi chose her passion over the potentially higher salary she could potentially get with other nursing specialisations. This is because, unlike nephrology or orthopaedics, forensic nursing is not recognised by the South African Nursing Council (SANC) as a professional specialisation. The SANC’s website does list forensic nursing as a nursing competency, but it does not include it in the list of specialised nursing competencies, which would make someone an Advanced Practice Nurse, with greater recognition and higher renumeration.
A June 2026 parliamentary reply to a question to the Minister of Health alludes to the fact that this is due to the educational programmes used in the past, including the one Moagi studied, not being recognised in regulations. It notes that future qualified forensic nurses would likely be recognised. However, no current educational programmes appear to be approved for this yet.
The parliamentary answer indicates that even if newer qualification lists are recognised in the future, Moagi’s previous diploma will continue not to be recognised.
Moagi says she knew about this from the start and admits that it can be difficult with the current cost of living to see other nursing fields being paid more. She says she may see job posts with salaries posted for other specialties and feel a tinge of jealousy.
She says she knows of nurses who were eager to specialise in forensic nursing but have been unable to because the additional recognition and remuneration do not reflect the demands of the role. “I think as soon as the nursing council recognises it, then more nurses will join,” she says.
Doing this work for years to come
It has now been a decade since Moagi moved to Germiston and started managing the 24-hour clinical forensic medical care facility located on the corner of Hospital and Cross Streets. She says she loves working with her team and the various stakeholders, such as the police and the Department of Social Development.
If it is up to her, she will keep doing this work for many more years to come. She says that every patient who walks away with a little more hope after facing some of their darkest moments is a reminder of why she chose this path.
“It’s seeing victims of gender-based violence walking out with hope that there is still life, and they can still pick up the pieces and try to move on with their lives,” she says.
Meanwhile, another shiny trophy has been added to that table in the corner of her office. The Gauteng Department of Health’s Ekurhuleni Health District Services recently named her best female gender-based violence activist at their Annual Gender-Based Violence Awards.
The awards are nice, but speaking to Moagi it is clear that they, like the higher salaries she may have had with another specialisation, are secondary. What drives her is a deep passion to help and serve others.
“There are those days where you feel like no matter how bad the situation was, I did my best to make sure that the patient is managed,” Moagi says. “And by the time you go home, you know you have done something good for the patients.”
*Thisarticleis part of Spotlight’s 2026 Women in Health series, featuring the remarkable contributions of women to healthcare and science. Sign up to the Spotlight newsletter.
Navigating patient confidentiality, social media and professional boundaries
Photo by National Cancer Institute on Unsplash
Date: Thursday 13th August 2026
Time: 18:00 – 19:45
Earn 2 ethics CPD points
During this webinar, the HPCSA Booklet 5: Confidentiality – Protecting and Providing Information and HPCSA Booklet 16: Ethical Guidelines on social media will be explored from a South African legal and ethical practice perspective. The webinar will offer insights into the complexities of digital communication, including WhatsApp and social media use, consent, online reviews and cybersecurity, while focusing on protecting patient confidentiality and public trust across all forms of communication.
The audience will have an opportunity to listen and engage with clinical, legal and medicolegal subject matter experts. During the webinar, a range of learning opportunities will be offered including short lectures, interactive case studies, audience polling and Q&A.
This webinar will focus on healthcare practitioners engaging in digital communication with patients and colleagues. Administrative staff working in these practices are welcome to join the discussion.
Joining us as panellists will be Emma Sadleir, South Africa’s leading expert on social media law, and Dr Isabel do Vale, a practising medical practitioner and President-elect of APRASSA. Attendance will qualify for 2 Ethics CPD points and EthiQal Recognition Programme points.
Human kidneys sell for up to £150 000 on the black market, but donors receive as little as £1000. Dr Saradamoyee Chatterjee exposes the criminal syndicates exploiting the desperate on both sides of the illegal organ trade, and asks how we can stop them.
Slums are a goldmine for organ traders. The brokers exploit people who are trapped in poverty and debt, and lure them into selling their kidneys.
Dr Saradamoyee Chatterjee
How much does a human kidney cost on the black market? It depends on who you are in the transaction.
Buyers can pay between £60 000 and £150 000. But donors only receive between £1000 and £7500, if they are lucky.
Where does the rest of the money go? The lion’s share goes to the organ brokers: criminal organisations who act as middlemen between donors and buyers.
These syndicates are sophisticated, exploitative, and international.
“One racket, operating from Israel, brought together Brazilian donors with American buyers, with the transplant taking place in South Africa.” So says Dr Saradamoyee Chatterjee, Bye-Fellow and Director of Studies in Land Economy at Lucy Cavendish College.
Chatterjee unpicks the illegal trade of human organs. She gives voice to the desperate players trapped inside its transactions, and suggests ways to stamp it out.
The organ bazaars
Beginning in the 1950s, science radically improved the success rate of human organ transplantation. Researchers found ways to suppress the immune response of the recipient, so that new organs are not rejected. Transplants now have a high degree of success between strangers, provided that donors and recipients match in blood and tissue type.
Kidneys are by far the most commonly transplanted organ, but transplants of heart, lungs, liver lobes and corneas are also possible.
In countries like India, Pakistan and the Philippines, these advancements initially led to completely unregulated human organ markets. Whichever country had the fewest regulations attracted international patients.
“In the 1980s, these countries were like an organ bazaar,” Chatterjee says. “Patients from the Middle East, UK and USA flocked to get their transplants done.”
Currently, only Iran has a legalised system for paying donors for their organs. Everywhere else relies on legal means, like organ donor lists, or illegal ones, which are still rampant in some countries. The persistence of organ trafficking reflects the desperation on all sides of the transaction.
The need for healthy organs is ever-increasing. Modern ‘lifestyle’ diseases such as diabetes and hypertension lead to kidney failure. Among the 2 current treatments – dialysis and organ transplantation – the latter significantly enhances the quality of life. Many people wait decades on donor lists and will do anything for a healthy organ.
Among slum-dwellers and asylum seekers, there is both a supply of valuable organs and the desperation required to part with them.
Here is where the middlemen come in, servicing an unsavoury gap in the market.
The sellers
Chatterjee travelled to Mumbai, Delhi, Chennai and Kolkata to seek out people with first-hand knowledge of the organ trade. In these cities she found a network of medical professionals, transplant coordinators, buyers and donors willing to share their views.
“Slums are a goldmine for organ traders,” Chatterjee says. “The brokers exploit people who are trapped in poverty and debt, and lure them into selling their kidneys.”
Many people are in need of a lump sum to escape dire circumstances – the organ traders supposedly offer that.
Once a broker gets a kidney, the sellers seldom receive the promised compensation and the vital post-operative care. Even the nominal fee would not provide any relief from poverty.
“One woman I spoke to was a cleaner for weddings,” recalls Chatterjee. “She sold her kidney to save the life of her husband. He’d fallen into debt after buying a tuktuk via a money lender, and couldn’t afford the interest payments. In the end, she only received half the offered price for her kidney.
“She was left weakened, deeply disappointed, and regretful of the whole organ-selling experience.”
In matching sellers with buyers, the syndicates respond to pleas for organ transplants on social media.
To dodge India’s prohibitions, the syndicates exploit loopholes in the law, including the forging of fake backstories. They generate false documents and testimonies to convince doctors and clinicians that 2 strangers know each other.
The transplant can then take place as if it were happening legally – as an agreement between friends or family, without money changing hands. These tactics make it difficult for doctors to detect potential exploitation.
The buyers
Organ trades are a bad deal for buyers too. Both the buying patients Chatterjee interviewed died shortly after their operations.
“In one case, the broker took payment before providing a mis-matched donor,” Chatterjee says. “In the second case, a female doctor saw that her new husband’s kidneys were failing. She placed an advertisement in the local newspaper, and a broker responded. But on the day of the planned transplant, the donor ran away.”
Operating with no regulation, the middlemen don’t uphold medical standards. They often don’t screen donors for existing conditions, exposing recipients to blood diseases like HIV or hepatitis.
The proliferation of lifestyle diseases in massive populations means that the organ trade isn’t only for the super rich: buyers only need to be rich relative to the poverty-stricken sellers.
Both of the buyers Chatterjee spoke to came from the middle class. They were compelled to borrow money from their relatives to pay the broker.
How can we make things better?
Meaningfully reducing the illegal trade of human organs requires action on many fronts.
Reducing the gap in supply means encouraging more legal donations. Other countries have focused on deceased donations, where people donate their organs after death. In Spain, everyone is an organ donor by default, meaning they have the world’s highest deceased donors rate (49 per million people; by comparison, India has only 0.77).
India claims to be tackling the black market with increased regulations and harsher sentences for perpetrators. Information campaigns targeting potential sellers should warn people about the dangerous middlemen. Further exposure of the black market by researchers like Chatterjee and Dr Sean Columb may also prevent people from being dragged into it.
On the demand side, societies need to properly fund their citizens’ healthcare. More successful countries focus on the prevention of lifestyle diseases that are leading causes of renal failure.
Encouraging people into healthier lifestyles – with fewer carbohydrates and more exercise – would decrease the prevalence of conditions like diabetes. Better screening programmes would also encourage patients to adjust before their condition deteriorates, reducing the demand for new organs.
“Organ traffickers exploit the vulnerabilities of both the donors and buyers,” says Chatterjee. To wipe out the middlemen, we need to make people on all sides of organ transplantation less vulnerable and more resilient.
The surge in demand for GLP-1 and GIP medicines—particularly those containing semaglutide and tirzepatide—has created significant commercial opportunity. It has also exposed a growing problem: the manufacture and sale of unregistered and potentially unlawful alternatives.
Recent enforcement action by the South African Health Products Regulatory Authority (SAHPRA) highlights the scale of the issue, particularly in relation to products marketed for weight loss (see SAHPRA and the SAPC Crack Down on Unlawful Manufacturing of Unregistered GLP-1/ GIP Medicines). While this is often viewed as a regulatory concern, it raises equally important questions for trade mark law.
Trade marks are traditionally seen as tools for distinguishing one trader’s goods from another’s. In the pharmaceutical sector, however, they do far more. They signal quality, safety, efficacy and regulatory legitimacy.
When those signals are misused, the consequences extend beyond commercial harm—they can directly affect public health.
More Than Molecules: Reputation as the Real Asset
The success of products such as OZEMPIC®, Wegovy® and MOUNJARO® is not driven by their active ingredients alone.
Through years of clinical research, regulatory scrutiny and market presence, these brands have accumulated significant reputational capital. Consumers are not simply looking for semaglutide or tirzepatide—they are looking for certainty.
Consumers want products backed by known standards of safety, tested efficacy and regulatory oversight.
In this context, the goodwill attached to a pharmaceutical trade mark reflects far more than brand recognition. It represents confidence in the entire lifecycle of the product—from development and approval to manufacture and distribution.
Reputation Laundering: Trading on Trust Without Earning It
In the current GLP-1 market, misuse of reputation does not always take the form of direct counterfeiting or even traditional trade mark infringement.
More often, products are marketed as alternatives, equivalents or substitutes for well-known medicines. Advertising often references established brands to attract consumer attention and to confer an aura of legitimacy on products that may not have undergone the same level of regulatory scrutiny.
This is where a more subtle form of exploitation emerges.
Even without reproducing a trade mark, these practices appropriate the trust associated with it. The result is what can aptly be described as reputation laundering, being the transfer of credibility from a trusted product to one that has not independently earned it.
From a trade mark perspective, the damage goes far beyond lost sales. It weakens the link between the brand and the qualities consumers expect from it.
The Consequences for Consumer Trust
The risks become most apparent when products fail to meet expectations- or worse, raise safety concerns.
If a consumer experiences harm after using a product marketed with reference to a well-known brand, the reputational fallout rarely remains confined to the seller. It can spill over to the genuine product.
This is what makes pharmaceutical trade marks unique. The goodwill they embody is inseparable from consumer trust in the safety and reliability of medicines.
Once that trust is compromised, the consequences extend beyond individual brand owners. They can influence patient behaviour, clinical decision and confidence in an entire class of treatments.
The Growing Union Between Regulatory Enforcement and Trade Mark Protection
Historically, regulatory compliance and trade mark enforcement have been treated as distinct legal disciplines. Increasingly, however, the two are becoming interconnected.
Regulatory authorities seek to protect consumers from unsafe or unapproved products. Trade mark owners seek to protect the reputation and goodwill associated with their brands. In many cases, these objectives are aligned.
SAHPRA’s recent focus on unregistered GLP-1 products illustrates this convergence. Both regulators and trade mark proprietors share an interest in ensuring that consumers are not misled regarding the nature, origin or reliability of pharmaceutical products.
As pharmaceutical brands continue to acquire substantial reputational capital, the distinction between consumer protection and brand protection becomes increasingly difficult to draw.
It is clear that pharmaceutical trade marks are no longer simply badges of origin. They have become proxies for trust. As the current GLP-1 market demonstrates, protecting that trust is not only a commercial imperative- it is increasingly a matter of public health.
Fake and substandard medicines, along with bogus healthcare practitioners, pose a growing threat to patient safety in South Africa.
The sale of fake and substandard medicines is a significant threat to patient safety around the world. In South Africa, the main affected products are painkillers, antibiotics, weight-loss and sexual enhancement products, skin-lightening products, and some chronic medicines.
In pealing back the different layers of this problem, it is essential to get the definitions right.
Substandard products are those that do not meet quality standards and specifications.
Falsified products deliberately misrepresent their identity, composition or source.
Neither of these should be confused with generic medicines, which have the medicines regulator’s green light for being safe, effective, and of good quality.
People are often duped into purchasing substandard and falsified products, especially when the real thing is not available or too expensive. But, as Elna Schütz this week reports for Spotlight, there are also people who buy these medicines fully aware of the risks.
These unregulated medicines are mostly distributed through informal channels, unregulated outlets, online platforms, and cross-border smuggling networks. It is also possible that some substandard and falsified medicines have been infiltrated into otherwise reputable medicines distribution channels.
Data on the scale of the problem is scant, but there is agreement that the problem is substantial. The WHO estimates that around 1 in 10 medicines in low- and middle-income countries are substandard or falsified.
The South African Health Products Regulatory Authority (SAHPRA) is the main body responsible for regulating substandard and falsified medicines. It does this through post-market surveillance and inspections, a whistleblower reporting system, product recalls, and monitoring illegal advertising and online sales. A new National Action Plan and comments from the Minister of Health suggests there is some intent to step up these efforts.
The good news is that we can generally trust that the medicines we buy at pharmacies contain what they are supposed to and that they were manufactured according to good quality standards. As regulatory entities go in South Africa, SAHPRA is generally one of the better-functioning ones.
But, outdated legislation means that SAHPRA doesn’t have all the tools it needs to stamp out the sale of unauthorised medicines. For instance, it has limited powers in relation to advertising and marketing, cannot block a web site, and cannot issue infringement notices, or impose sanctions on entities or individuals whose actions potentially place the public at risk of harm.
The misrepresentation may include using fraudulent certificates, using another practitioner’s registration, or still offering healthcare services while being suspended or erased from the register.
From early 2024 through late 2025, 66 bogus practitioners were caught and arrested, with the majority operating in the economic hubs of the Western Cape, Gauteng, and KwaZulu-Natal.
You can help curb these problems. Suspicious practitioners can be reported to the HPCSA, and suspicious products or sellers can be reported to SAHPRA. People are also advised to buy only from licensed and authorised pharmacies and checking if healthcare providers are registered.
And then there is fake news
In some areas, as with bogus health professionals and falsified medicines, the solution to misrepresentation is clearly to have legally empowered regulators with enough muscle to consistently enforce the law.
But when it comes to misinformation and disinformation – call it fake news if you will – the way forward is much less obvious. In recent years, we’ve seen a toxic mix of political polarisation, conspiracy theories, disinformation campaigns, and twisted social media algorithms – often fuelling a rejection of science and evidence-based policy-making. Beyond just our screens, these trends have unfortunately started to distort the real world, as we’ve seen at various critical health institutions in the United States.
In our view, regulators should have a role in preventing misinformation and disinformation about medicines. But how exactly to make such regulation work in an age of largely unaccountable social media networks is not at all clear.
What we think is clear, is that much of the solution to the problem of health misinformation and disinformation, is simply to keep creating its opposite, high-quality, rigorous, and evidence-based journalism.
This is the core of what we try to do at Spotlight. It is also why we have made our journalism subject to the South African Press Code, work hard to stick to our Editorial Policy and Style Guide, and why we urge you to hold us accountable when we get things wrong, as we will inevitably do from time to time.
