Technology and Healthcare: What Does the Future Hold?
Cecure Intelligence Limited
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By Kubrah Tosin
Most of us are familiar with the typical doctor's visit experience: lengthy hours spent in the waiting room amidst people with various illnesses, which could potentially worsen our own health condition. Once we eventually get our appointment with the physician, it's generally a brief encounter of 15 minutes or less, ending with a costly prescription that may or may not be effective.?
The dynamics of authority are transitioning from healthcare professionals to patients, with self-care and self-evaluation gaining significant influence. Emerging technology is revolutionizing medical practice, driving a shift in power and a complete makeover of the current medical sector. So let’s take a look and see what the future holds.
Smartphones allow greater access to medical information
Smartphones have brought transformative changes to many aspects of our lives. With a simple mobile connection—accessible to 95% of the populace—they offer us vast quantities of information at our fingertips. Undoubtedly, their influence will also be significant in the field of medicine.?
The role of smartphones in enabling autonomous medicine, where individuals can self-diagnose, is soon to be a reality. We already have some tools for it, below, we have highlighted a few such tools and apps.
Symptom Checkers: Apps like Ada, Babylon, and WebMD offer symptom-checker tools. These tools can help users identify potential causes for their symptoms. While they're not a substitute for professional diagnosis, they can help inform discussions with healthcare providers.
Skin Cancer Detection Apps: Apps like SkinVision and MoleScope can analyze photos of skin lesions and use AI algorithms to assess the risk of skin cancer. They provide a preliminary evaluation that can help decide if a professional consultation is needed.
Mental Health Apps: Apps like Moodpath and Woebot can help users monitor their mental health over time by asking a series of questions each day. These can identify patterns indicative of conditions such as depression or anxiety, prompting users to seek professional help.
Vision Tests: Apps like EyeQue use a smartphone and additional hardware to allow individuals to test their eyesight at home. This could help detect changes in vision that require attention from an optometrist.
Heart Rhythm Monitoring: Devices like AliveCor's KardiaMobile, used in conjunction with a smartphone, can record a medical-grade EKG. The smartphone app can detect irregular heart rhythms suggestive of conditions like atrial fibrillation.
Blood Pressure Monitoring: Some devices, like QardioArm, connect with smartphones to measure and track blood pressure over time. High readings can alert users to potentially dangerous health conditions.
And this is just the start with photos. Soon, microscopic scans will possess such high magnification capabilities that we'll be able to self-scan for specific bacteria. For instance, tuberculosis is diagnosed by examining a sputum sample for the presence of Mycobacterium tuberculosis. In the near future, anyone equipped with a smartphone might be able to self-test for tuberculosis.
Furthermore, smartphones hold the power to drastically transform healthcare in regions where access to medical professionals is limited. For instance, in 2018, the average count of doctors and nurses for every 1,000 individuals in Nigeria was merely 0.4. On the other hand, the United States had a ratio of 2.6 (1).
Mobile connectivity also grants people increased access to healthcare information. As of 2019, over 96 million Nigerians were smartphone owners (2). Even basic mobile phones can make a substantial impact on public health, as demonstrated by the South African initiative, Masiluleke (3), which sends millions of daily text messages urging individuals to undergo HIV/AIDS testing.
However, the capabilities of smartphones still outshine those of basic mobile phones. Take for example the recent innovation by the biotech firm Nanobiosym, known as Gene Radar (4), a minuscule chip that connects to a mobile device and can analyze a blood or saliva sample for tuberculosis, malaria, and HIV. Gene Radar will enable individuals to self-diagnose these diseases at a cost that is a fraction—ten times cheaper—of the current market price.
The Power Shift: From Doctors to Patients.
In the current medical paradigm, patients are typically used to adhering to their doctor's instructions. However, this dynamic is set to evolve in the future.
Doctors have historically held an authoritative role in the medical field, with their directives often being the final determinant in a patient's treatment plan, AKA the doctor’s order. Patients generally don't dictate their own treatments and mostly follow their physicians' advice without objections.
Yet, as technology equips patients with better access to their personal genetic information, they will accrue more authority. Being knowledgeable about one's own genetic makeup enables more informed decisions in the realm of healthcare.
Angelina Jolie took such an informed medical decision when she opted for a double mastectomy. By analyzing her family's medical history and corroborating it with a genetic analysis of her blood, she discovered her heightened risk of developing breast and ovarian cancer.
Jolie was found to have an 87 percent likelihood of developing breast cancer due to a BRCA1 gene mutation. Consequently, she made the preemptive choice to have both of her breasts surgically removed.
Jolie disclosed her decision publicly with the intent of raising awareness about the significance and power of genetic testing. As genetic testing becomes increasingly accessible, it will continue to gain such high-profile attention.
Here are some real-life examples that illustrate the impact of patients having access to their own genetic information:
Direct-to-Consumer Genetic Testing: Companies like 23andMe and AncestryDNA provide services that allow individuals to access genetic information without going through a healthcare provider. People can find out their genetic predisposition to various health conditions like breast cancer, Parkinson's disease, or late-onset Alzheimer's disease, among others. This information can influence lifestyle choices, preventative measures, and treatment plans.
Pharmacogenomic Testing: This is genetic testing that predicts a patient's likelihood to experience an adverse event or not respond to a medication. Knowing this information can guide doctors in prescribing the best medication for the patient. For example, genetic tests can predict how a patient will respond to anticoagulant drugs, like warfarin, which is important to prevent dangerous bleeding or clotting events.?
Preimplantation Genetic Diagnosis (PGD): Couples undergoing IVF (in-vitro fertilization) can choose to have their embryos tested for genetic disorders before implantation. This allows them to make informed decisions about which embryos to implant, reducing the risk of passing on inherited genetic disorders.
As smartphones empower individuals further, the landscape of healthcare is set to transform as well. Technology will transform existing medical infrastructure. One significant shift will be the reduced need for physical visits to the doctor.?
Telemedicine services such as Doctor on Demand, MD Live, and Teladoc are already enabling patients to consult with physicians without leaving their homes. A typical Teladoc appointment costs about the same as a traditional in-person consultation, but the service operates round the clock, and there's no waiting time. This convenience significantly outweighs the traditional experience of waiting for an hour to consult a doctor for a mere ten minutes.
The British National Health Service (NHS) has noted that the average hospital stay has decreased from 8 days in 2008 to 5 days in 2018 (5).
Google Maps, for Humans….
We now possess remarkably powerful tools for gathering and storing data, a technological advancement poised to significantly influence the medical field.
We're currently progressing towards the creation of a kind of human "Google Maps": a Graphic Information System (GIS) capable of overlaying multiple layers of information onto a single digital map.
GIS has been used in the analysis of traffic, satellite, and structural data. Soon, we'll be able to construct a human-centric GIS, enabling individuals to overlay diverse types of critical medical information onto a digital map.
This would encompass physiological details such as heart rate, genetic data about your DNA and its mutations, as well as anatomical information concerning the structure of your bones and organs.
Certain components of the human GIS will be simpler to develop than others. The physiological layer is relatively advanced, as we already have the capacity to monitor physiological functions such as heart rate and eye pressure using commercially available portable sensors.
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However, other layers, like the genetic one, are significantly more complex. We have already gathered considerable information about genes: the Human Genome Project has sequenced about 90 percent of human DNA. The cost of genome sequencing has also dramatically fallen: from $28 million in 2004 to less than $1,500 now.
Still, we have a considerable distance to cover. Each person's genome comprises around 3.5 million variants, and approximately 19,000 of these variants are currently undetectable using modern technology. A substantial investment in genetic research is necessary before we can generate comprehensive genomic layers for the human GIS.
A Human GIS + Big Data = Radical improvement in Health Care.
How will we utilize the extensive information derived from the human GIS?
The human GIS will pave the way for the application of numerous innovative treatment methodologies. The physiological layer will assist in symptom tracking, for instance, using biosensors to monitor the airways of a child with asthma. This would allow parents to anticipate the next potential asthma attack, ensuring the child's inhaler is readily available.
The genetic layer will contribute significantly to disease prevention. Genetic data already serve as a crucial alert system for parents since most diseases have genetic predispositions. For instance, nearly one in 40 individuals carry dangerous recessive genes for cystic fibrosis, and one in 35 carry for spinal muscular atrophy.
If a couple is aware of the high risk of passing a specific disease to their offspring, they might contemplate other options like adoption.
The scope of accessible medical treatment will expand even further as the human GIS integrates with Big Data, enhancing areas such as cancer therapy.
At present, we have several cancer treatment options, including chemotherapy, surgery, radiation, and medications. However, what proves effective for one cancer patient might not yield the same results for another. Here, GIS information collected from previously treated patients can play a crucial role. Researchers can use this data to determine which treatments best align with a patient's specific genetic makeup.
Big GIS data could significantly enhance diagnostic accuracy. Currently, there is limited assistance available for patients with rare or unidentified diseases, but a comprehensive GIS database would facilitate scientists in better understanding these conditions.
Big data may even allow us to predict common diseases.
You likely know someone with diabetes given its prevalence as one of the most common chronic illnesses. Approximately 6 million Nigerians (6) and more than 37 million Americans (7) live with this condition.
Chronic illnesses pose treatment challenges due to their often incurable nature. The primary focus is on symptom management, which can lead to patients enduring these symptoms for their entire lives.
Chronic illnesses also put a substantial strain on medical resources. In fact, around 80% of all healthcare expenditure in the EU is directed towards chronic diseases (8).
Big data has the potential to transform this scenario; it could help us predict and prevent chronic illnesses.
Take Post-Traumatic Stress Disorder (PTSD) as an example. PTSD impacts an estimated 24.4 million Americans. If we could analyze this data, we might be able to anticipate the onset of this condition.
If healthcare professionals could predict that a returning war veteran was on the verge of experiencing PTSD, they could provide preemptive treatment, potentially shielding the individual from the condition.
While this level of advanced disease prediction might seem distant, we're already making strides toward it. In fact, a computer algorithm named Healthmap successfully predicted the 2014 West African Ebola outbreak nine days before the World Health Organization (WHO) did.
Healthmap's prediction analyzed data from tens of thousands of online media providers, including news sites, social networks, and government websites, mapping search engine results for symptoms and their geographical locations.
The algorithm was able to deduce that Ebola was the cause of the epidemic more than a week before doctors started diagnosing it. By that time, it had already spread to some hospitals. This showcases some other big data applications in healthcare.
Predictive Analytics for Diabetes: Google's Verily and Sanofi have created a joint venture, Onduo, aiming to combine devices, software, medicine, and professional care to enable simple and intelligent disease management for people with diabetes. It uses big data analytics to predict blood sugar changes and provide actionable advice.
Cardiovascular Disease Prevention: Aetna's Healthagen subsidiary uses machine learning algorithms to predict patients' future health status based on their health records and other data. It identifies patients at risk of developing chronic conditions like cardiovascular disease and provides preventive care options, aiming to avoid costly future treatments.
Asthma Monitoring: Propeller Health's digital health tool uses big data to predict asthma attacks. The tool connects to inhalers and tracks when and where they're used. Aggregating this data from thousands of patients allows Propeller to identify patterns in asthma attacks, predicting high-risk periods and prompting preventive measures.
Though these are impressive ways big data helps in health, we still have a lot of work to do to make them useful in individual diagnoses.
The Danger of Detailed Medical Data.
Big Data holds enormous potential to revolutionize the healthcare sector. However, this power can also be misused.
Medical identity theft is already a prevalent issue in today's world. Individuals can steal your medical identity to acquire treatments such as prescription medications. They can also exploit your insurance information to cover their own medical treatments, or those of others.
Since 2009, sixty-eight U.S. medical records have been breached. Hackers can execute this in various ways, like infiltrating hospital databases or purloining hardware storing medical data.
The protection of our medical privacy is crucial. However, hackers and thieves aren't the only threats we need to guard against.
Privacy concerns regarding genetic information also exist. Insurance companies could potentially discriminate against individuals with genetic predispositions for chronic diseases by denying them coverage. To prevent this, some states have already passed laws prohibiting insurance companies from accessing genetic information.
Genetic information could also fall prey to questionable practices by marketing companies. Data brokers such as Acxiom profit by selling people's personal data to marketing agencies. Currently, Acxiom holds data on names, income, home valuations, and medical history of over 200 million Americans.
If companies like Acxiom were to access our genetic information, the marketing implications could become even more intrusive than they are now. Imagine receiving an ad for a cystic fibrosis treatment even before you become aware of your susceptibility to the disease.
In the end, the control over your personal information should rest solely with you.
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