Medical professionals tend to find diagnosing and treating women's health concerns more complicated. Moreover, women have struggled with diagnoses for reasons like lack of research and a lack of understanding of common onset symptoms.
It’s not new that more research needs to be dedicated to solving women’s health problems. But luckily, trends in AI technology and diagnostics may prove to be useful technology to support diagnosis in women’s health.
What’s the Deal With Women’s Health Diagnosis?
A large portion of the population knows that they can turn to a medical practitioner for medical support. They also know that diagnostics and medical care are not perfect. It’s often when a second or third opinion is needed, and a patient is struggling to find the care that they require.
But women face a different kind of diagnosis issue, and this does not have to do with women’s reproductive diagnoses.
According to a large , women seem to be diagnosed years later compared to men when diagnosing many of the same diseases. This study of 6.9 million people found that of the same conditions found in both men and women, men were diagnosed an average of four years earlier in age compared to women.
This study looked at a wide range of diseases, many of which could come from the environment, genetics, or biases in healthcare itself (the causes of which are unknown by researchers). Regardless, across a hundred diseases and 6.9 million Danish folks, the gender of the patient apparently affected the timing of the diagnosis.
When looking at cancer, women received their diagnoses 2.5 years later than men. And for metabolic diseases like diabetes, women received the same diagnosis 4.5 years later.
Understanding the Diagnosis Issue in Healthcare
It’s important to look past the shock of this claim and assess what might be going on. The study pulled data from a lot of records. If women weren’t hospitalized for an issue, this might be an indicator that the issue was not being looked at by doctors at a time when men were hospitalized for the issue. A hospitalization would show up in the data.
If hospitalization is at play, then the diagnosis for men might be more appropriate because the chance of more severe symptoms presenting might be higher. However, we are unsure if this is the case. What this brings up are symptom presentation and gender biases.
For example, women are diagnosed later for heart diseases, and the idea here is that heart disease is a “man’s disease.” In the case of heart disease, men might present symptoms earlier (earlier onset), or a doctor may have minor symptoms on their radar because it’s labeled a man’s disease. Women might not be presenting symptoms, or doctors may not be looking for heart disease-related symptoms as seriously in women.
Diagnostic tests (opens in a new tab) and this comes from years of research that suggested that men were more likely to get the disease than women. This, we know, has more to do with the training and lack of research around women.
AI Can Help Early Diagnostics
The importance of early diagnostics is (opens in a new tab). Catch cancer four years earlier, and you have may a chance at fighting the disease into remission.
Catching a disease early is, in 99% of cases, better than catching it later, even just four years later. If an AI tech is capable of diagnosing an individual earlier, even if they are not presenting symptoms, there are no known negatives (other than the quality of life) that could impact that diagnosis.
We can also look at (opens in a new tab) for women’s health too. Women-specific health issues have long been (opens in a new tab). When it comes to women’s reproductive cycle, things like endometriosis, fertility issues, and cervical cancer plague women and often there is no end in sight. However, luckily, there is an emerging industry of tech (opens in a new tab) that might save this struggling demographic.
An unprecedented wave of innovation is exploring how (opens in a new tab) can transform the women’s health space. Digital birth control, (opens in a new tab), and more are all starting to emerge. We are starting to see greater financial trends as well, with an increase in womens’ health market funding in the last 7 years.
And (opens in a new tab) is looking at the things women need: menstruation care, pregnancy care, fertility solutions, general healthcare, nursing care, menopausal health, cancer care, fertility tracking, sexual health, and more.
How Emerging Diagnostics Tech Can Transform Women’s Care
So what about diagnostics? Luckily, emerging tech is applying their innovative ideas to treat the disease and conditions commonly affecting women, like cancer, reproductive health, pelvic health, menopause and post-menopause, and pregnancy-related conditions.
And this is good news.
In fact, AI has shown promise in the ability to diagnose illnesses (opens in a new tab) do. In a first-of-its-kind systematic review and meta-analysis, researchers looked at AI for diagnostic effectiveness based on a medical image. While more studies are needed, the fact that AI could offer automated and data-rich diagnostics for more patients will alleviate the burden of diagnostics from human doctors.
Think about it—we have so many people and not enough doctors. And doctors are getting tired, so it is natural for doctors to put aside diagnosis until the issue is critical or avoid patient care until it’s necessary. This is not an ideal way of operating, but it’s become a way of survival.
AI diagnostics could alleviate this problem, providing a better diagnostics tool through automation, technology, and genetics, offering nurses and doctors a quick preliminary diagnosis to make care simpler. It can also add to the growing repository of virtual care that physicians will be adding.
With an AI-generated diagnosis at their fingertips, doctors can quickly recommend a treatment or prescription remotely to control the pending problem and eliminate the load on healthcare in the future.
Embracing This New Digital Frontier
The role of AI in healthcare is exciting, to say the least. Not only will it solve many of the problems that plague underrepresented populations, but it will also solve the problem of a lack of personnel in the field.
With the support of data-driven healthcare and remote care, more patients will be able to treat illnesses preventatively before they become a problem!