Healthtech Security
Article | August 31, 2023
As medical science has improved rapidly, life expectancy around the world also has risen. Still, as longevity increases, healthcare systems are facing a growing demand for advanced services, increased costs, and a struggling workforce to meet various requirements of patients. Demand is driven by many unstoppable forces: a shift in lifestyle choices, shifting patient expectations, population aging, and the never-ending cycle of innovation are a few among others.
Challenges Faced by the Healthcare Industry
According to Mckinsey, one in four people in North America and Europe will be over the age of 65 by 2050. This shows that, soon, the healthcare industry will have to deal with a larger number of patients with more complex requirements. Catering to these patients is expensive and requires health systems for providing long-term focused and proactive care. To remain sustainable, healthcare systems need major transformational and structural changes.
The industry also needs a larger workforce because according to the World Health Organization (WHO), globally there is a shortfall of approximately 9.9 million nurses, physicians, and midwives. Apart from attracting, training, and retaining these healthcare professionals, you also have to ensure that their time and effort add value to patient care. Utilizing the solutions powered by modern technologies, such as Artificial Intelligence (AI) in the healthcare industry, will add perfection and more value to human efforts.
AI in the healthcare industry has the potential required to transform and revolutionize healthcare by addressing the challenges in the industry mentioned earlier. AI can better the outcomes, improve efficiency, and augment productivity in healthcare delivery. This article takes an in-depth look at the impact of AI in healthcare.
Impact of AI in the Healthcare Industry
In the coming years, AI in the healthcare industry will improve the day-to-day life of healthcare practitioners, augment the patient experience, improve care delivery, and can even facilitate life-saving treatments and revolutionize the industry. Additionally, AI will improve population-health management, operations, and strengthen innovations.
According to Statista, the global AI healthcare market will increase to more than US$28 billion by 2025. Here is a detailed look into the areas where and how AI in the healthcare industry will be impactful.
Chronic Care Management
Chronic diseases, such as cancer, diabetes, kidney diseases, are the leading cause of disability and death in the US and the main drivers of the country’s annual health cost. Effectively managing various chronic diseases is an overarching and long-term process. But with the help of the right tool, healthcare providers can meet the needs of these patients without delay.
Artificial intelligence tools in the healthcare industry can help healthcare providers overcome the complexities of chronic disease management and make it more effective and provide quality treatment. AI in the healthcare industry is increasingly being leveraged by organizations to improve chronic disease management, enhance patient health, and drive down costs, which will also eventually result in data-driven and personalized care. AI in the healthcare industry is expected to move the industry toward proactive care delivery from a reactive one and lead the industry to provide more individualized treatments. This is just one of the ways AI in the medical industry is going to revolutionize chronic care management in hospitals.
Care Delivery
Artificial intelligence in the healthcare industry is changing the way care is delivered; it is expected to make healthcare more efficient, accurate, and accessible. Reducing costs and improving health outcomes are the values health systems and hospitals are trying to deliver to patients every day. Hospitals are increasingly incorporating technologies, which are powered by the use of AI in healthcare to meet the challenge.
According to the American Hospital Association (AHA), AI in the healthcare industry has unlimited potential to solve most of the vexing challenges in the industry. They identify AI use cases in the healthcare industry in four broad areas, which are administrative, operational, financial, and clinical areas.
Administrative Use Cases for AI in the Healthcare Industry
• Admission procedures
• Appointment scheduling
• Customer service responses
• Discharge instructions
• Hiring and orientation protocols
• Licensure verification
• Patient check-in procedure
• Prior authorizations
• Quality measure reporting
Operational Use Cases of AI in the Healthcare Industry
• Inventory management
• Materials management
• Supply chain management
• Facilities management
Financial Use Cases for AI in the Healthcare Industry
• Billing and collections
• Claims management
• Insurance eligibility verification
• Revenue cycle management
Clinical Use Cases of AI in the Healthcare Industry
• Predictive technologies
• Interventional technologies
By incorporating and utilizing these scopes with AI in the healthcare industry, the industry can be transformed into a next-gen level in no time. It also allows healthcare practitioners to focus more on patients, which would eventually help in raising staff morale and improving retention.
Clinical Decision Support
Recent advancements in AI in the health industry are capable of enhancing the currently used clinical decision support (CDS) tools to have value-based imaging and to improve patient safety. According to the National Institute of Health (NIH), the synergy between CDS systems and AI in the healthcare industry will be able to:
• Reduce friction in radiology workflows
• Identify relevant imaging features easily
• Generate structured data to develop machine learning algorithms
• Enable an evolution toward decision support for a holistic patient perspective
• Suggest imaging examinations in complex clinical scenarios
• Assist in identifying appropriate imaging opportunities
• Suggest appropriate individualized screening
• Aid health practitioners to ensure continuity of care
AI in the healthcare industry is competent in making CDS a next-gen one, enhancing the experiences of radiologists and providers, and improving patient care.
Diagnostics
Slowly but surely, AI is improving almost every aspect of human life with innovations and advancements. The latest is that AI in the healthcare industry is impending a revolution in medical diagnostics by providing accurate risk assessments, accelerating disease detection, and boosting hospital productivity. By automatically prioritizing urgent cases and accelerating reading time, image recognition AI enhances the workflow of radiologists. It even helps in the prevention of diseases by the early detection of diseases.
In medical images such as x-rays, MRIs, and CT scans, AI-driven software can efficiently be used to accurately spot signs of many diseases, especially in detecting many chronic diseases such as cancer. According to the NIH, AI will be widely applied in the healthcare industry especially for various tasks such as patient engagement and adherence, diagnosis, and treatment recommendations. So, there is no doubt that AI in healthcare will revolutionize the diagnostic process in the approaching years by detecting diseases, classifying diseases, and improving the decision-making process. The application of AI in the healthcare industry will make people live longer.
Triage and Diagnosis
AI can be effectively used to automatically triage cases. AI algorithms will analyze the cases and forward cases to pathologists after determining the priority based on the probability of cases according to the criteria set by labs. This makes the workflow of pathologists easier and efficient. Through the process the algorithm will be able to:
• Verify the digital images attached to the case belong to that case
• Validate the tests ordered and match the specimen type
• Identify cases marked as stat
• Determine the cases, which can be positive or are most likely to be negative
Moreover, AI technologies in the healthcare industry also can be effectively used to provide more accurate and faster diagnoses. This speeds up the entire process of triage and diagnosis and is expected to revolutionize the healthcare industry soon.
The Future Outlook for AI in the Healthcare Industry
Over the next few years, AI in the healthcare industry has the best opportunities in hybrid models to support clinicians in diagnosis, identifying risk factors, and in treatment planning. This scope will result in faster adoption of AI technology in healthcare, which will show measurable improvements in operational efficiency and patient outcomes.
With a plethora of issues to overcome, which are driven by documented factors such as growing rates of chronic diseases and the aging population, it is obvious that the healthcare industry needs new innovative solutions. AI-powered solutions in the healthcare industry will achieve a clear impact on the global healthcare industry in a short time.
Frequently Asked Questions
Which is the best application of AI in the healthcare sector?
Cognitive surgical robotics is the best application of AI in the healthcare sector as it helps practitioners collect data from real surgical processes, which would help in improving existing surgical approaches.
Why is artificial intelligence important in healthcare?
Artificial intelligence in healthcare is vital as it can help make decisions, analyze and manage data, and have conversations. So, AI will drastically change the everyday practices and roles of clinicians.
When was AI-first used in healthcare?
The term, Artificial intelligence (AI) was first described in 1950, but the limitations of the term prevented its acceptance. In the 2000s, these limitations were overcome and people started to accept the term.
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Health Technology
Article | September 12, 2023
“Health care is different, the data here is emotional! If you tell me you were buying a fishing rod online and were emotional about it, I’d say you are lying. But I do frequently see people helpless and confused when it comes to receiving health care, managing its costs, making sense of its data.”
- Senior Product Leader inOptum Global Solutions Pvt. Ltd.
Yes, health care is different, and so is product management in it. This piece highlights the top 4 product management trends that are specific to health care and serve beyond being just a list of technologies making their way into health care.
Health care consumerism
Lance broke his ankle in a bicycle accident and is now in hospital waiting for surgery. Which of these words would describe him more aptly— a ‘patient’ or a ‘health care consumer’? The fact that Lance holds a high-deductible health plan, manages an interactive relationship with his primary doctor, keenly monitors his fitness through his smartwatch, and learns about healthier diet plans and recipes online — I can say he isn’t just receiving health care, but making active choices on how to pay for and manage his health. This choice and responsibility that people demand, is ‘health care consumerism’. This trend has been growing since 2015 when value-based care started picking up in the US.
What does this imply for products/PMs?
These are challenging and exciting times to be a product manager (PM) in health tech. This is because people are now demanding an experience equivalent to what they’re used to from other products in their lives, such as e-commerce, streaming platforms, and digital payments, to name a few. Any consumer-facing product (a mobile app, a web-based patient portal, a tech-enabled service) needs to meet high expectations. Flexible employer-sponsored health plans options, health reimbursement arrangements, price transparency products for drugs and medical expenses, remote health care services, and government's push to strengthen data and privacy rights — all point to opportunities for building innovative products with ‘health care consumerism’ as a key product philosophy.
Wellness
COVID-19 has tested health care systems to their limits. In most countries, these systems failed disastrously in providing adequate, timely medical assistance to many infected people. Prevention is of course better than cure, but people were now forced to learn it the hard way when cure became both inaccessible and uncertain. With lockdowns and social isolation, prevention, fitness, diet, and mental wellbeing all took center stage.
Wellness means taking a ‘whole-person approach’ to health care — one where people recognize the need to improve and sustain health, not only when they are unwell, but also when they’re making health care decisions that concern their long-term physical and mental health. A McKinsey study notes that consumers look at wellness from 6 dimensions beyond sick-care— health, fitness, nutrition, appearance, sleep, and mindfulness. Most countries in the study show that wellness has gained priority by at least 35% in the last 2–3 years. And wellness services like nutritionists, care managers, fitness training, psychotherapy consultants contribute 30% of the overall wellness spend.
So, what do health-tech PMs need to remember about wellness?
The first principle is, “Move to care out of the hospital, and into people’s homes”. A patient discharged after knee surgery has high chance of getting readmitted if he/she has high risk of falling in his/her house, or is unable to afford post-discharge at-home care with a physiotherapist. This leads us PMs to build products that recognize every person’s social determinants of health and create support systems that consider care at the hospital and care at home as a continuum.
The second principle is, “Don’t be limited by a narrow view of ‘what business we are in’, as wellness is broad, and as a health tech company, we are in health-care, not sick-care”. Wellness products and services include — fitness and nutrition apps, medical devices, telemedicine, sleep trackers, wellness-oriented apparel, beauty products, and meditation-oriented offerings, to name just a few. Recent regulations in many countries require health care providers to treat behavioural health services at par with treating for physical conditions, and this is just a start.
Equitable AI
Last month, WHO released a report titled “Ethics and Governance of Artificial Intelligence for Health”. The report cautions researchers and health tech companies to never design AI algorithms with a single population in mind. One example I read was, “AI systems that are primarily trained on data collected from patients in high-income settings will not perform as effectively for individuals in low or middle-income communities.” During COVID-19, we came across countless studies that talked about the disproportionate impact on minorities in terms of infections, hospitalizations, and mortality. A student at MIT discovered that a popular out-of-the-box AI algorithm that projects patient mortality for those admitted in hospitals, makes significantly different predictions based on race — and this may have adversely moved hospital resources away from some patients who had higher risks of mortality.
How should I think about health equity as an AI health-tech PM?
Health equity means that everyone should have a fair chance at being healthy. As a PM, it’s my job to make sure that every AI-assisted feature in my product is crafted to be re-iterative and inclusive, to serve any community or subpopulation, and is validated across many geographies. To prevent any inequitable AI from getting shipped, it is important to ensure that the underlying AI model is transparent and intelligible. This means knowing what data goes into it, how it learns, which features does it weigh over others, and how does the model handles unique features that characterize minorities.
Integrated and interoperable
In every article that I read on topics such as digital platforms, SaaS, or connectivity with EMRs, I always find the words: ‘integrated’ and ‘interoperable’ therein. Most large and conventional health tech companies started by offering point-solutions that were often inextensible, monolithic, and worked with isolated on-prem servers and databases. To give a consistent user experience, leverage economies of scope, and scale products to meet other needs of their customers, started an exodus from fragmented point-solutions to interoperable, integrated solutions. The popularization of service-oriented architectures (SOAs) and cloud vendors like AWS, Azure, and GCP has also helped.
The what and how of integrated-interoperable solutions for PMs:
Integrated solutions (IS), as I see them, are of two kinds — one, in which as a health tech company, we help our customers (health systems, insurance companies, direct to consumers) accomplish not just one, but most/all tasks in a business process. For example, a B2B IS in value-based care contract management would mean that we help our customers and health systems by giving an end-to-end solution that helps them enter into, negotiate, plan for, manage, get payments for their value-based contracts with health plans.
In the second type of IS, we offer products that can be easily customized to different types of customers. For example, a health management app that people can subscribe to for different programs such as obesity, diabetes, hypertension, cholesterol management, as needed. The app works with different datasets for these programs and uses different analyses and clinical repositories in its backend, but still delivers a consistent user experience across programs to a user who enrolled in multiple programs, say diabetes and weight management.
‘Interoperable’ simply means that one product should be able to talk to other products both in and out of the company. For example, if product-A can alert a doctor about any drug-drug interactions or allergies a patient might have, while she is writing prescriptions for the patient in product-B (an EMR), then product-A does talk to product-B, and hence, is interoperable. This trend is picking up further with the growth of IoT devices, and industry-wide participation in adopting common standards for data exchange.
Conclusion
Though the article derives much of its context from US health care, I have tried to keep a global lens while choosing these topics. For developing economies like India, digitization is the number one trend as much of the health system is still moving from manual records to digitally store patient and medical data in EMRs. The good news is that India is booming with health-tech innovation and that is where consumerism, wellness, and equitable AI make sense. Once companies develop enough point-solutions for different health system needs and use-cases, Indian health tech will see a move towards creating integrated, interoperable (IGIO) systems as well.
There are some other trends such as — use of non-AI emerging tech such as Blockchain in health information management, cloud infrastructure for health tech innovation, big data and analytics to improve operational efficiency in areas such as claims management and compliance reporting, Agile product management for co-developing with and continuously delivering to clients etc. — but I see them either as too nascent, or too old to feature in this list.
Finally, as a health tech product manager, you can use the following questions to assess your products against the above trends — (Consumerism) do the products that I manage, empower consumers with choice, information, and actionability? (Wellness) Does my product emphasize keeping them out-of-hospitals and healthy in the first place? (Equitable AI) Am I sure that my product doesn’t discriminate against individuals belonging to underserved populations? (IGIO) And finally, is my product scalable, integrated and interoperable to expand to a platform, in the true sense?
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Health Technology, Digital Healthcare
Article | July 14, 2023
© 2019 American Cranes & Transport Magazine.
Night moves
Moving over-sized, over-dimensional loads during the day is no easy task. Adding darkness and poor visibility to your trip adds numerous hazards that must be thoroughly identified and mitigated.
When planning a specialized transportation project, there are three primary objectives:
Ensure the safety of the transport crew and the general public.
Protect the integrity of the cargo and transport equipment.
Protection of Infrastructure – roads, bridges, traffic control devices, utilities and the like.
For the most part, specialized carriers perform night transports to reduce the impact on day-time commuter traffic. Route challenges – construction, road closures, lane crossovers, bridges and other obstacles – are often better solved at night. Police and utility support are often more readily available at night.
Night transport hazards include employee fatigue, slowed reaction time and poor visibility for both the transport crew and motorists. Decreased visibility increases potential for trips, falls, runovers, back overs and equipment strikes.
It can’t be emphasized enough how critically important it is to ensure that all transport crew members have had adequate rest for these projects. Workers need complete rest before the transport takes place. A fatigued worker is a danger to himself as well as his fellow crew members. And while impaired drivers can be out on the streets during the day, there is often an increased number of these drivers on roadways at night.
Limited visibility is a given when it comes to night-time transports. Limited visibility increases the chance of going off route and striking objects, and the transport driver’s maneuverability and reaction time maybe be reduced. Road conditions can abruptly change during a night-time transport. Therefore, it is critically important to know the route and to have drivers run it in advance. Statistically speaking, accident frequency increases when the transporter goes off route and attempts to correct itself. While providing the necessary lighting to make night transport is important, artificial lighting can pose visibility hazards, especially to the drivers. Other hazards may include bright work lighting that produces glare.
OSHA has identified the “Focus Four” accident events that make up the most serious injuries and fatalities in the construction business. They are also known as the “Fatal Four.” Many carriers have had employees injured in the past as a result of one of these four incidents.
Caught-in-between hazards are injuries resulting from a person being squeezed, caught, crushed, pinched or compressed between two or more objects or between parts of an object. This is also referred to as “pinch points or entrapment.” As the transporter navigates its designated route the landscape is continuously changing. It is imperative that all ground crew members maintain situational awareness and not place themselves between the moving transporter and fixed objects such as guardrails, parked vehicles, buildings, etc.
Struck-by hazards are injuries produced by forcible contact or impact between the injured person and an object or piece of equipment. There are many potential struck-by hazards. Guide wires that must be raised can snap and strike workers on the ground. Tag lines should be used to control loads. The primary purpose of using tag lines is to control the load but more importantly give the worker a safe buffer distance away from suspended and the uncontrolled movement of these loads.
Fall hazards are anything that could cause an unintended loss of balance or bodily support and result in a fall. To prevent fall hazards all workers should have either fall prevention or a means of fall protection in place. As a rule, 100 percent tie off is required when using a fall arrest system (FAS). FAS’s should be thoroughly inspected before each use.
Electrocution hazards result when a person is exposed to a lethal amount of electrical energy. Maintaining minimum approach distances (MAD) is a critical safety practice. As everyone knows, equipment does not have to physically make contact with energized equipment or lines to cause serious injuries and even death. Electrical energy can “jump” from lines into equipment that has encroached the Minimum Approach Distance based on its voltage.
As noted above, it is critically important to ensure that crew members have had adequate rest and are not fatigued. Night transports are difficult enough, and the last thing you want to introduce are tired and fatigued workers. Being fatigued creates a risk for anyone who undertakes an activity that requires concentration and a quick response.
All companies should have an “Hours Worked Policy” that clearly spells out the number of hours allowed to work before a mandatory rest period. This policy should ensure that the transport crew has had adequate rest during day, that a fatigue assessment is conducted on all team members, that crews are never allowed to work double shifts and that employees are prohibited from driving long distances to return home.
Dealing with darkness
Visibility and slowed reaction times should be a part of the project planning. A limited amount of ambient light that only projects upward and outward impedes vision and increases blind spots for drivers. Lights cast shadows, increasing the potential for slips, trips and falls.
All transport moves should establish pre-planned Emergency Action Plans. When an emergency occurs, time is of the essence and can mean the difference between life and death. If it is a long-distance move the emergency numbers and first responder information can change. Crews should know when it’s time to seek emergency “safe harbor.”
When approaching overhead obstructions such as guide wires, electrical lines, communication lines and overpasses, travel speed is of utmost importance. Again, pre-route surveys provide advance knowledge of obstructions. At night, visual identification of roadway obstructions is reduced and delayed and last second reactions to oncoming hazards can lead to accidents. Support personnel in bucket trucks also have the challenge of reduced visibility.
In darkness, overhead hazards often require more utility support for height clearances, which means the need for raising energized lines, lifting traffic control devices, trimming tree limbs, releasing tension on guide wires, removing highway signs, repositioning street lights and raising railroad crossing arms.
Traffic control can also create hazards. The general public may ignore pilot car lights at night, so it’s often advisable to also use police escorts. All support vehicles and trucks should be properly marked and equipped with strobe lights.
The configuration of the transport system can also be a hazard. Navigating sharp turns or crossovers is greatly reduced based on the length of transporter. Snake-like maneuvers of trailers pose an increased risk.
It’s important to never allow personnel to take shortcuts by walking through or under transporter while it’s in motion. Stop or have the worker go around.
Situational awareness
The transport crew must always maintain “situational awareness” to prevent being in line of fire or entrapped between moving and fixed objects.
All the equipment used in the transport must be deemed safe. You should have procedures to conduct thorough assessment of all new equipment.
Ensure machine guard devices are in place especially around moving components.
Provide secured areas using catwalks/railing system.
All steps should be designed with slip resistant material.
Ensure that all deck openings are properly protected and covered.
Components that hydraulically extend and retract should be clearly posted with DANGER signs.
Roadway conditions are always a bigger concern at night. Assess weather conditions prior to start of the project and don’t take chances. A “Go – No Go” criteria should be developed for each project. Once the decision is made to transport the load there is no turning back. Changing weather can cause the transporter to lose traction. Underpasses that are shaded during the day will likely freeze up more quickly. If the temperatures drop significantly during the move, equipment performance may be affected – especially those with hydraulics.
Because the reaction time of the transport crew is reduced, speeds are often reduced, causing potential for curfew violations. Boarding and deboarding the transporter increases risk for slips and falls. Other potential road condition hazards include grade of road, width of road, shoulder surfaces, railroad crossing clearances and bottoming out, overpasses, tight and narrow turning lanes, parked vehicles and frequent grade changes.
Crew prep is essential and should be a part of the job plan and job training. The team should be briefed each day to identify the responsibilities of all crew members. The crew should know it is empowered; everyone has the authority to stop the transport if something looks unsafe or when someone is unsure. In the event of a complication, crews should be informed of how to regroup and formulata mitigation plan. There should be an established means of communication that is limited only to transport issues. Most importantly, crew should embrace these words: When in doubt, call time out!
A Task Hazard Analysis (THA) should address all scope of work activities, identify hazards and have a mitigation plan for each, clear channels of communication, the traffic control plan and an “Emergency Preparedness Plan.” And finally: Know the route; ride the route and expect the unexpected.
Edwards-Moving_Faktor-5 (2).jpg
Edwards Moving performs a night move using it’s Goldhofer Faktor-5 transport system.
Keys to a successful night transport
Early planning and attention to detail. Anticipate roadway hazards such as guardrails, poles & hydrants that pose obstruction with travel path or turning radius.
Preparing a detailed traffic control plan.
Thorough due diligence throughout scope of work.
Established contingency plan for equipment.
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AI
Article | December 21, 2021
Global efforts to tackle gender inequality have grown in recent years. But there is still so much to be done. Figures from the United Nations show that outcomes for women and girls continue to lag across a range of issues, including poverty, education, work and health. And according to the World Economic Forum, at the current rate, it will take 108 years to close the gender gap.
Although healthcare is founded in objectivity and science, gender bias is still remarkably common. We wanted to understand more about female perceptions of healthcare, so we undertook consumer research that delved into the experiences of women compared to men. The results pointed to a clear disparity, finding that women are less likely to visit the doctor when they have symptoms of ill health and, in some cases, are taken less seriously when they do seek medical advice.
Women being left behind
According to our research, a significant proportion of British women feel disappointed in the healthcare they receive, with one in five reporting they weren’t taken seriously when presenting symptoms to a healthcare provider. What’s more, a staggering one in four said they are reluctant to seek medical advice at all for fear of wasting a GP’s time. These statistics suggest that, not only are female experiences of healthcare damaging their relationship with clinicians, but they could be eroding confidence in recognising and acting on warning signs and symptoms too.
This sentiment is particularly evident when focusing on cardiac care. One in eight women (13%) feel ignored when presenting symptoms of heart disease to healthcare professionals, compared to just 4% of men. And of UK adults who have received a coronary heart disease (CHD) diagnosis, women experiencing symptoms were 55% more likely than men to visit the doctor multiple times before receiving a referral for further investigation. On top of this, women are five times more likely to receive a false finding from the cardiac stress tests that are traditionally used to assess heart health.
“There does appear to be a gender bias in onward referral to secondary care and for diagnostics in the local area, which is influenced by the attending healthcare professionals’ risk assessment. Traditional teaching has led to gender bias, as we are programmed to attribute a lower level of pre-test probability and risk to females. This may have contributed to a general lack of awareness around cardiovascular health in women. For example, in a survey I carried out among more than 600 female employees working within North West Anglia NHS Foundation Trust, 82% said they didn’t feel informed about their cardiovascular health. Considering participants included some of the most medically informed women in the UK, the results speak volumes about how we view cardiac health among women.”
- Dr Rebecca Schofield, consultant cardiologist at North West Anglia NHS Foundation Trust
These widespread misconceptions around heart disease and heart attacks are often exacerbated by what we see in the media – think of the countless TV stereotypes of male characters clutching their chests and falling to the floor.
But given that CHD is responsible for one in 13 female deaths, it appears that public health efforts have failed to make people aware of the risks for women. It is, perhaps, not surprising then that 42% of women with CHD did not immediately recognise their symptoms as signs of heart disease. In short, women are missing out on time-critical diagnoses and treatment due to a lack of awareness and education among both healthcare providers and the public.
Technologies making a difference
Thankfully, progress is being made to improve healthcare outcomes for women. Innovative technologies are increasingly providing diagnostic solutions that can reduce incidences of human bias and give clinicians greater clarity on the presence or severity of different conditions in their female patients.
For example, AI is already being used to detect diseases such as cancer more accurately. Its adoption is facilitating reviews and translations of mammograms 30 times faster, with 99% accuracy, reducing the need for unnecessary biopsies.
There’s extraordinary potential for AI and healthcare, and it’s something the NHS continues to recognise, most recently with the launch of its Artificial Intelligence Laboratory (AI Lab) and NHS England’s (NHSE) MedTech Funding Mandate. The latter aims to accelerate the uptake of selected innovative medical devices, diagnostics, and digital products to patients.
As part of the NHS efforts, NHSE has mandated the HeartFlow Analysis for use in hospitals across England for patients, male or female, who might otherwise be sent for a cardiac stress test. The HeartFlow Analysis is a gender-neutral technology that takes data from a coronary CT scan of the heart and leverages deep learning (a form of AI) and highly trained analysts to create a personalised, digital 3D model of each patient’s coronary arteries. This then helps clinicians to quickly diagnose CHD and decide the appropriate treatment for patients of any gender. Time spent in hospital is minimised for patients and often layered testing and unnecessary invasive diagnostic procedures can be avoided.
Final thoughts
While AI is helping us tackle gender bias in certain areas such as oncologic and cardiac testing, healthcare professionals are not absolved of responsibility when it comes to confronting this problem. It remains incumbent upon clinicians to recognise unconscious bias that would deter them from referring women or minority patients for much-needed testing.
Outside of the hospital, public health education efforts must expand so that far more of us can recognise shortness of breath, nausea, vomiting, back or jaw pain, and other symptoms beyond chest pain to be indicators of a heart attack in a woman. Knowing what to look for and overcoming personal bias that might lead to these signs being disregarded, may allow us to help one of the more than 100 women who will experience a heart attack in the UK today.
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