Health Technology, AI
Article | July 18, 2023
Rural, community, and independent hospitals are constantly facing mounting challenges in the form of staff shortages, accessibility to patient care and a multitude of cost concerns. Getting even one of these areas under control can help hospitals drastically boost their outcomes.
Here are three areas of IT investment that hospitals must control to go beyond staying functional and create an excellent patient experience.
Telehealth for Staff Shortage
Healthcare currently face massive staff shortage with a projected gap of up to 48,000 primary care physicians and up to 77,100 specialty physicians till 2034.
The effects of this shortage could be lessened by using virtual care, which would allow hospitals to care for patients through remote staffing.
Digitalizing Patient Care with Asynchronous Telehealth
Async telehealth of patients sending photos and videos to fast-track diagnosis. Async telehealth makes it easier for doctors to connect with more patients. This shortens the time it takes to see specialists and get important care services.
Remote Patient Monitoring
According to a CDC report, 90% of all healthcare spending goes into treating chronic conditions. Considering that U.S. nonmetropolitan areas have a high number of patients diagnosed with chronic conditions, accessibility is one of the contributing factors.
Remote patient monitoring enhances patient care for people with chronic conditions. Wearable medical devices are already driving the move towards remote patient monitoring. Whether it’s through wearable weight scales, heart monitors, blood pressure bands, or pulse oximeters, clinicians can generate regular updates about a patient’s health readings and ensure a timely response in order to avert complications.
Conclusion
There is much to be achieved on the healthcare front when it comes to digitalizing care. The above technologies are enabling healthcare providers take delivery of medical care further than ever and ensure they generate more traction from their IT investments in these areas of medtech.
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Health Technology, Digital Healthcare
Article | September 7, 2023
Over the last couple of years, the healthcare industry has witnessed significant technological advancements transforming numerous procedures and treatments, ranging from magnetic resonance imaging scanners and radiotherapy to antibiotics and anesthetics.
In addition, the introduction of novel technologies (new pharmaceuticals and treatments, new equipment, new social media support for healthcare, etc.) has further provided air to the fire for innovation in the sector, encouraging healthcare providers to upgrade their technological infrastructure.
Medical Computers Paving the Way in Healthcare
Use of modern technology, such as medical computers, is becoming more and more crucial in healthcare institutions, including hospitals, clinics, and specialized treatment centers. These computers are used in hospitals for a variety of purposes, from better laparoscopic, minimally invasive surgical techniques used by surgeons to patient tracking and health monitoring gadgets.
Medical computers are becoming more prevalent as they help medical professionals make faster, more reliable, and more accurate decisions. Additionally, they enable the emergence of new data, integrate advanced technologies such as artificial intelligence, and enhance decision-making processes, which are particularly crucial when it comes to medical diagnostics and treatment. New computer and technology solutions in the healthcare sector are enabling a wide range of outcomes that were previously unimaginable. They assist medical practitioners in both data collection and data interpretation, enabling them to make decisions that are thoroughly informed by insight. Here are some of the applications that have experienced immense transformation in recent years
Hospital Information Systems
Medical Personnel and Staff Management
Data Analysis in Medicine
Medical Imaging
Computer-assisted Therapy
Laboratory Computing
Critical Patient Care
Computer Assisted Decision-making (CMD)
Patient Check-In and Status
Growing Adoption Encouraging Product Launches
With technologies like medical computers becoming essential for processing numerous day-to-day operations in the healthcare industry, the need for these computers is growing at a rapid pace. Hence, a number of medical equipment providers are emphasizing on offering cutting-edge solutions to modern healthcare facilities.
For instance, in 2021, American Portwell Technology, Inc., a world-leading innovator of the Industrial PC, unveiled two certification-ready all-in-one medical computers - MEDS-P2410-P200 (23.8″) and MEDS-P2210-P200 (21.5″) with features such as true-flat capacitive touchscreen and optional hot-swappable batteries.
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Healthtech Security
Article | November 29, 2023
COVID-19 has been a catalyst for change, with the diagnostics industry taking centre stage and rising to the challenge of a global pandemic. One of the silver linings of this mammoth task has been the unprecedented time and focus dedicated to finding new technologies and solutions within the sector.
The lessons learned from the pandemic now need to be taken forward to improve breast and cervical cancer detection, prevention and treatment across the UK over the coming years.
In the more immediate term, the diagnostics industry, alongside public health leaders, faces a daunting backlog as screening programmes for breast and cervical cancer were put on pause for months. These two life-saving tests have been some of the most overlooked during the pandemic and getting back on track with screening is critical as we start to turn the corner. We believe innovation in diagnostics, particularly artificial intelligence guided imaging, is a key tool to tackle delays in breast and cervical cancer diagnosis.
The scale of the backlog in missed appointments is vast. In the UK, an estimated 600,000 cervical screening appointments were missed in April and May 2020. And an estimated 986,000 women missed their mammograms, of which an estimated 10,700 could be living with undiagnosed breast cancer. It is clear that hundreds of thousands of women have been affected as COVID-19 resulted in the reprioritisation of healthcare systems and resource allocation.
Both cervical and breast cancer screening are well suited for digital technologies and the application of AI, given both require highly trained medical professionals to identify rare, subtle changes visually –a process that can be tedious, time-consuming and error prone. Artificial intelligence and computer vision are technologies which could help to significantly improve this.
What does AI mean in this context?
Before examining the three specific areas where digitisation and AI can help, it is important to define what we mean by AI. It is the application of AI to medical imaging to help accelerate detection and diagnosis. Digitisation is the vital first step in implementing an AI-driven solution – high quality images demand advanced cloud storage solutions and high resolution. The better the quality of the input, the more effectively trained an AI system will be.
The first area where AI-guided imaging can play a role is workflow prioritisation. AI, along with increased screening units and mammographers, has the potential to increase breast cancer screening capacity, by removing the need for review by two radiologists. When used as part of a screening programme, AI could effectively and efficiently highlight the areas that are of particular interest for the reader, in the case of breast screening, or cytotechnologist when considering cervical screening.
Based on a comparison with the average time taken to read a breast screening image, with AI 13% less time is needed to read mammogram images, improving the efficiency with which images are reviewed. This time saving could mean that radiologists could read more cases a day and potentially clear the backlog more quickly.
For digital cytology for cervical cancer screening, the system is able to evaluate tens of thousands of cells from a single patient in a matter of seconds and present the most relevant diagnostic material to a trained medical professional for the final diagnosis. The job of a cytotechnologist is to build a case based on the cells they see. Utilising these tools, we are finding that cytotechnologists and pathologists are significantly increasing their efficiency without sacrificing accuracy to help alleviate the backlog of cervical screening we are seeing in many countries.
Prioritising the most vulnerable patients
Another key opportunity is applying AI to risk stratification, as it could help to identify women who are particularly at risk and push them further up the queue for regular screening. Conversely, it would also allow the screening interval for those women at lower risk to be extended, creating a more efficient and targeted breast screening programme.
For example, women with dense breast tissue have a greater risk factor than having two immediate family members who have suffered from breast cancer. What’s more, dense breasts make it more difficult to identify cancerous cells in standard mammograms. This means that in some cases cancers will be missed, and in others, women will be unnecessarily recalled for further investigation.
A simple way to ensure that those most at risk of developing breast cancer are prioritised for screening and seen more regularly would be to analyse all women on the waiting list with AI-guided breast density software. This would allow clinicians to retrospectively identify those women most at risk and move them to the top of the waiting list for mammograms.
In the short term, to help tackle the screening backlog, prior mammograms of women on the waiting list could be analysed using the breast density software, so that women at highest risk could be seen first.
Finding new workforce models
Being able to pool resources will allow resource to be matched to demand beyond borders. Globally, more than half a million women are diagnosed with cervical cancer each year and the majority of these occur where there is a lack of guidance to conduct the screening programme. The digital transformation of cervical screening can connect populations that desperately need screening to resources where that expertise exists. For example, developing countries in Africa could collect samples from patients and image these locally, but rely on resources in the UK to support the interpretation of the images and diagnoses. Digital diagnostics brings the promise of a ‘taxi-hailing’ type model to cervical cancer screening – connecting groups with resources (drivers with cars) to those who are in need (passengers): this is an efficient way of connecting laboratory professionals to doctors and patients around the world.
It’s going to take many months to get cancer screening programmes up and running at normal levels again, with continued social distancing measures and additional infection control impacting turnaround times. But diagnostic innovation is on a trajectory that we cannot ignore. It will be key to getting cancer screening programmes get back on track. AI is a fundamental piece of the innovation puzzle and we are proud to be at the forefront of AI solutions for our customers and partners.
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Digital Healthcare
Article | December 18, 2021
“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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