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The health care system, public and private, is being affected by the COVID-19 pandemic, propelling many hospitals and other medical institutions to look towards technology advancements, like Artificial Intelligence (AI) and advanced MedTech, to pick up where they’re understaffed and overwhelmed.
Capturing data is at the forefront of these issues. For a timely example, those who survive COVID-19 need more efficient health monitoring to understand the long-term effects of this global illness – something that AI has the potential to fulfill.
The Internet of Healthcare Report conducted by Wakefield Research shows that 64% of healthcare executives admit there will never be enough staff to manage the voluminous data in their corporations. However, an astonishing 99% of businesses interested in AI are convinced that AI will shift the employee’s focus to more purposeful, patient-centric actions, which is increasingly vital in today’s health care centers.
Health care systems are incorporating robotic process automation (RPA) and data automation into invoicing to improve tasks like creating employee and patient schedules, analyzing and processing claims, payments, and interpreting medical notes. This is just the tip of the iceberg, though when it comes to what AI can do to help the health care system.
Medical technology (MedTech) covers a broad range of products, services, and solutions – it includes tongue depressors, MRIs used to take medical imaging, wheelchairs, glasses that improve vision, and the systems used to aggregate (and understand) patient data.
MedTech is involved in all phases of medical care, from prevention to diagnosis, monitoring to treatment, and finally general care and well-being.
There is some contention in this definition since it varies worldwide and there’s a good chunk of overlap between “MedTech” and “HealthTech” but, for our purposes, we’ll use MedTech for devices used both within a hospital and outside of it.
Equipping medical technology with Artificial Intelligence (AI) can assist the often overburdened and understaffed healthcare systems. Artificially intelligent MedTech can provide solutions for a variety of healthcare issues, including across a patient’s tenure at multiple health care facilities.
Moreover, AI has the potential to reduce costs and make it easier to obtain and provide healthcare on a global scale through:
Many of these technologies are well on their way to being considered mainstream. Is your healthcare facility capable of taking in, analyzing, and utilizing this broad swathe of data? Spoiler alert: the very same AI that’s revolutionizing the products saving lives can manage storage capacity of large swathes of patient data that would otherwise be left unorganized.
AI can expand the amount of data that can be collected without increasing the administrative work associated with that deluge of data – that alone has numerous potential to do good.
It can augment diagnoses with decision-support algorithms, monitoring minute irregularities in patient information and going so far as to compare patient profiles (medical history, labs, medical imaging) to a massive data repository of patient profiles to find similarities and disparities – this can all lead to more accurate diagnostics and more time for medical professionals to spend with their patients.
In an NCI intramural research program, clinicians used Deep Learning (a subset of Machine Learning and Artificial Intelligence) to process cervical cancer screening images. The Deep Learning program identified precancerous lesions with 91% accuracy, compared to visual inspection (69%) and pap smears (71%).
In fact, according to an MIT study, that 75% of medical staff who have AI agree that it has enabled better predictions in the treatment of disease.
Why isn’t this sort of technology being used everywhere? Frankly, much of it is a trust issue, on both sides. Patients aren’t inclined to let a “computer” diagnose them, and some medical professionals see this sort of AI as threatening their jobs, rather than a valuable resource.
The fact of the matter is that AI also helps actively prevent burnout in healthcare workers on top of providing resource expansion, making it a win-win all around for both sides of the equation.
Viewing AI-enabled MedTech as an augmentation for medical professionals’ knowledge, a trusted asset, a collaborative tool rather than a competitor, can open doors that were otherwise inaccessible.
The goal of ongoing health is to prevent costly, emergency visits to hospitals by detecting problems as early as possible. Doctor-approved wearables for daily use can revolutionize the way doctors view patients and associated data.
In southeast England, hospitals equipped 500,000 patients with a Wi-Fi-enabled armband. This armband remotely monitored vital aspects of health such as pulse, blood pressure, respiratory rate, oxygen levels, and body temperature.
As a result, costly home visits have dropped by 22% thanks to constant monitoring and algorithms that can predict health crises before they even happen. Long-term projected results? This program hopes to increase adherence to treatment plans to 90%, blowing the average 50% out of the water.
Moreover, this arm band can help remind, track, and monitor lifestyle choices to better one’s health, down to taking medications on time, which can improve effectiveness of treatment and quality of life.
Between better leveraging hospital staffers, digitized automatic reminders for increased patient health and wellness, and the increased visibility of patients’ vital aspects, healthcare professionals can better diagnose and treat patients in a cost-effective, efficient way, all with the use of data provided by AI wearables.
Telehealth has exploded in usage over the past two years, largely due to the pandemic. Despite the world opening and closing as variants have emerged and slowly receded, telehealth is around to stay – and can be used to do a lot of good all around, with special emphasis on those in need of specialized care that may not be nearby.
On top of wearables to collect necessary vital stats and using expansive data repositories for accurate diagnosis (all of which can be done remotely), AI can improve the quality of TeleHealth visits by creating better, real-time Electronic Health Records (EHR).
One of the largest struggles, especially towards the initial boom of telehealth appointments, was accessing all necessary client data while also maintaining the live, two-way audiovisual interactions of a patient appointment. Different systems require different clinical information, then there was the act of recording what went on in the session, and also trying to be present for patients.
AI can eliminate these inefficiencies by pulling all relevant data together from any variety of EHRs. It can go so far as handling visit notes, capturing and transcribing data – though this may be difficult in terms of privacy, security, and more, but the capability is there.
AI has also shown promise in remotely monitoring insulin adjustments, as show in this 6-month, multinational, parallel, randomized controlled, noninferiority trial in 108 type 1 diabetics using insulin pump therapy where the Artificially Intelligence-based Decision Support System (AI-DSS) had zero diabetes-related crises, versus three reported in the physician-controlled insulin adjustment arm.
This sort of remote adjustment, weighing in all of the collected data and reacting to it without scheduling appointments or traveling, can have big improvements on treatment, increase accessibility, and return critical time to healthcare workers.
The TeleHealth world is ripe with opportunity, and much of this is just the beginning.
MedTech and Artificial Intelligence (AI), in particular the combination of, is going to flood healthcare technologies with petabytes of data – data that healthcare providers will need to not only have room for but be able to analyze and leverage for improved patient care.
This can (and likely should) begin with an advanced, cloud-based Customer Relationship Management (CRM) tool combined with a secure data warehouse.
A Customer Relationship Management (CRM) technology, such as Salesforce, provides a 360-degree view of patient data. This full view strengthens doctor-patient relationships in the health care industry by organizing all patient data and corroborating information (labs, imaging) in one place, making it easier to manage.
Specific channels or departments can have customized channels to meet healthcare provider needs, while automated emails make for a collaborative, customer-centric, and personalized approach, as well as an effective communication method.
MedTech companies can use Salesforce to connect teams, integrate diverse data sources from older systems, and provide data-driven insights to support patient-centric interactions.
Leveraging artificial intelligence to reorganize and leverage data such as patient schedules, payments, claims, and medical notes on procedures can be a good start to a strategy, forming part of a longer agile implementation that leverages the enormous possibilities of AI MedTech Wearables, AI for TeleHealth, and AI-augmented diagnostics, for starters.
The bottom line is that AI systems can help healthcare organizations reveal patterns in voluminous data while at the same time increasing the effectiveness – a benefit for both patients and medical professionals alike.
Spaulding Ridge provides best-in-cloud solutions for even the most complex business situations, including leveraging Salesforce and AI to not only manage but analyze and use massive quantities of data. Improve the health of both patients and your medical professionals; transform the way you manage data and be ready when the future of AI-driven MedTech becomes mainstream.
Speak with Jeff Garrah today to talk about revolutionizing the way you use data and AI.