For the first time in our lives, we have been able to see how artificial intelligence would influence a pandemic from identification and tracking to treatment and vaccination. Two things had to perfectly align to make this happen.
Technology had to advance to a place where it could analyze, predict, and engage with extreme accuracy and a virus had to be dangerous enough to spur massive funding and demand for action. We reached that tipping point in 2020. As the year comes to a close it is time to consider all that AI has done and where it is likely to continue to impact epidemiology and disaster response moving forward.
HealthMap, an AI application run by Boston Children’s Hospital, was launched in 2006 and was one of the first tools used to detect and track the COVID-19 outbreak in China. The algorithm uses online data about infectious disease events from news outlets and social media in more than a dozen languages. It then applied machine learning and natural language processing (NLP) to track outbreaks.
Tracking or predicting where cases might show up is just one step in a long journey to stopping the spread of the virus. An article published in May 2020 by researchers in the U.S. and China would reveal that Artificial Intelligence was accurately diagnosing COVID-19 in 68% of patients who had previously been thought to be negative and had normal results on chest imaging. The AI algorithm used to compare imaging, symptoms, medical history, and exposure was said to have “equal sensitivity as compared to a senior thoracic radiologist.” I have also had the pleasure of reading some yet-to-be-published articles about how AI is helping in the ICU to predictively determine ventilator utilization but it’s not just ventilators.
When it came time to harness AI in the diagnosis of COVID-19, even the CDC jumped on board. In partnership with Microsoft’s Azure platform, they embedded a symptom checker chatbot on their website. Likely out of an abundance of caution, their bot uses what I term “light-AI” to guide patients through a very basic decision tree. Answering simple yes-no questions to determine their likelihood of needing a test.
As long as we continue to prioritize data, AI will have the information needed to analyze and predict, it’s a very logical application of the technology — but what about using it to engage patients and address widespread misinformation and fear?
Technology and the Internet of Things (IoT) are having a big impact on health care and health insurance, with research by Bain predicting that the revenue obtained from IoT and analytics alone will reach 22 billion by 2025.
In the health insurance sector, technologies such as artificial intelligence are enabling companies to sift through millions of pieces of data to find ways to reduce premiums, match products with their ideal target market, and generate new business leads. How can technology empower health insurance brands to deliver better service and build a larger client base?
Current leaders in the health insurance industry often ask beneficiaries to use wearable devices that track activity and calorie intake. Doing so enables them to collect vital information that can be used to offer reward programs.
It also encourages wearers to take vital steps to prevent obesity, Type 2 diabetes, stress, and other diseases and conditions linked to an inactive lifestyle or to a poor diet comprising high percentages of sugar and refined ingredients.
By Dan Schulte, MBA, CHFP, senior vice president, provider operations, HGS.
As outbreaks of COVID-19 continue to crop up around the country, the ongoing public health crisis is just one facet of the situation; economic disruption is another grim reality, including for the healthcare industry itself. The American Hospital Association estimates COVID-19 will result in losses of $202.6 billion for the country’s hospitals and health systems due to factors such as the cancellation of nonemergency procedures; the high cost of treating a patient with COVID-19; and the millions of Americans who could become suddenly uninsured due to the economic implications of the virus.
Providers must improve cash flow to remain stable, which will require new revenue cycle management strategies supported by technology. Artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) together can provide an effective automation strategy that will help healthcare systems recover and retain more of their revenue — while boosting patient satisfaction — as they navigate this costly crisis.
Nine revenue cycle functions ripe for automation include:
Prior authorizations: With manual prior authorizations requiring an average of 21 minutes and as much as 45 minutes per transaction, the opportunity to drive cost savings through automation is significant. Because of well-defined business rules in this area and structured data that systems exchange in conducting prior authorizations, RPA can significantly improve this process: Implementing a “bot” that can perform the same tasks repetitively and without variation can help reduce error rates, so patients can get the authorization they need quickly, and lower the likelihood of claim denials.
Eligibility and benefit verification: While fully electronic transactions account for more than 84% of all eligibility and benefit verification transactions — a positive development — more can be done to reduce wasteful spending in this part of the revenue cycle. As the starting point for care delivery, this function represents a significant potential for improvement via intelligent automation. The focused manager will ensure that the EDI tools bring the right data across to the patient accounting system (timely, accurate and complete data), and will have the necessary add-ons to find the last 15% of data from screen scraping and outsourcing to a reliable service provider.
According to a recent IBM Institute for Business Value survey of more than 5,000 U.S. adults, just over 36% of respondents have already taken advantage of telemedicine services to seek remote care for less urgent health issues since the beginning of the COVID-19 pandemic.
Of those surveyed, 59% plan to keep using these services into the future, despite the fact that only one-fifth of those surveyed sought virtual care before.
As patients and their providers increasingly recognize the value of engaging virtually, and as we transition into our ‘new normal’, healthcare organizations will need to expand their virtual capabilities to keep up with increased demand for telemedicine while ensuring personalized, seamless delivery of high-quality care. But how?
Increased adoption fuels greater acceleration
Virtual health services and capabilities have been available for quite some time. But in light of a strained and reconfigured healthcare system due to COVID-19 – and with many patients self-isolating – the rate of adoption and use has increased. In years to come, this adoption is likely to gain momentum as demand continues to grow.
Routine face-to-face medical care is now limited for most Americans due to the pandemic, prompting many to take advantage of remote services to access the care they need. And as many parts of the country plan ahead for a world with less in-person interaction, more consumers may choose to forego the process of scheduling an in-person appointment with their provider if they know that it’s possible to receive the same high-quality care through virtual visits.
More than half of those surveyed in IBM’s latest poll indicate they have had a positive experience using telehealthcare services, such as telemedicine, telenursing and telepharmacy, either before or during the current crisis – and that positive experience must be upheld.
To maintain and build on the increased traction of virtual care, providers need to work to ensure that these platforms and services are easy to use for those who are not technologically savvy. It is also critical that they support these services with robust and secure infrastructure so their digital offerings are available and reliable at all times – to the benefit of both patients and doctors.
The golden years are becoming that much easier with each passing year thanks to quality of life improvements made possible through technological breakthroughs. Tech is empowering seniors to age in place much longer than anticipated. Furthermore, tech innovation is enhancing medical equipment and medications, ultimately improving seniors’ quality of life.
Data Analysis for Improved Care
Machine learning and artificial intelligence is significantly enhancing healthcare for seniors across the United States as well as the rest of the world. Tech is now capable of analyzing information in an incredibly efficient manner. Between health monitoring systems, smart watches for seniors and in-depth data analysis, there are all sorts of new and creative ways to monitor senior health.
Predictive analytics will likely prove quite important in the future for regular doctors, dentist for sale practices and others, ultimately empowering healthcare workers to predict seniors’ health challenges. It is quite possible predictive analytics will soon accurately predict a patient’s likelihood for a potentially devastating fall, a heart attack, stroke or other medical problem. The prudent use of such predictive analytics will make it easier for seniors to obtain the care they need for high-quality living throughout the entirety of the golden years.
From a senior care perspective, we are starting to see many senior living communities shift their focus towards putting technology first. In fact, the shift over the last three years is exponentially more than all the progress from the last ten years combined.
As we continue to see an increase in the implementation of technology, we’ll also see residents’ quality of life improve because we are enabling them to age in place longer and remain in their preferred care setting.
In actuality, technological advancements and innovation are more likely to come to the senior living industry over any other care setting. Since these types of facilities are largely privately funded, senior living facilities are more likely to adopt these new innovations over those organizations that are funded by the government.
Overall, technology is starting to be more widely implemented to improve senior care by managing resident data more efficiently, all with a primary focus of helping our seniors to maintain the independence, health, and general wellness.
We have officially entered into a New Normal and technology overall will continue to play a larger role within the senior living space. Mobile technology will be even more critical and engaging family in care through the use of family engagement solutions will become foundational.
Leveraging an EHR as an underlying platform to improve overall care quality allows care providers to truly see resident needs and find creative ways to address them.
By taking a comprehensive approach to an EHR, providers in the senior living space can gain insight into the community’s key operating metrics, then adapt and adjust accordingly by regularly tracking clinical outcomes, staffing, and quality indicators.
From a data perspective, more and more senior living communities are recognizing the importance of interoperability. Data being collected shouldn’t just tell us where we are at, it should tell us where we are going by helping us predict potential issues before they happen.
Much like the formation of New Year’s Resolutions, the prediction of technology trends for the coming year has become a tradition among pundits, analysts and vendors alike. As the calendar turned to 2020, Hyland, like many, took the opportunity to look into a crystal ball to predict what the future might hold for the software industry at large, as well as many of the key vertical markets in which it operates.
For example, Hyland leadership revealed six overarching trends for enterprise technology as well as key trends to watch for health IT. At the time, none of us could have foreseen that a global pandemic was coming that would turn all of these predictions on their collective ears.
Of course, the healthcare industry has been particularly impacted by COVID-19. Provider organizations have justifiably focused their attention on responding to the new patient care and staffing needs brought about by the virus. That said, all of the health IT trends Hyland outlined at the beginning of 2020 (interoperability, artificial intelligence and cloud adoption) still have relevance in today’s unprecedented landscape. Although, admittedly, the reasons these topics are trending are for vastly different reasons than we originally anticipated.
I want to revisit these trends under the lens of COVID-19 as well as add a few more to the list in light of current circumstances.
Original insight: Secure access to patient information at any facility throughout a care continuum is an imperative for delivering a longitudinal digital record that travels with the patient. The key is to ensure tight integration between disparate IT systems, and to include unstructured data in the interoperability equation. As much as 80% of essential patient information is in an unstructured format – such as digital photos and videos, or physician notes – and not natively included in an electronic medical record (EMR) system. When removed from a clinician’s view, the patient record is incomplete.
New relevance: Health IT interoperability was important prior to COVID-19, and it’s even more critical now. Providers, patients and public health officials need all-encompassing data in a standardized format to better understand this evolving illness and develop guidelines. The effort to identify risk, control spread and manage the treatment of afflicted patients is a coordinated effort among multiple healthcare providers and external care partners. The easier information can be shared among these varied stakeholders, the better equipped we’ll be to combat the virus.
Artificial Intelligence (AI)
Original insight: Realistic applications of AI are coming into focus in healthcare, showing where the technology will help providers optimize workflows and better analyze the vast amounts of information needed to support improved decision making. Experts view AI technology as complementary and a true asset when it comes to helping physicians analyze the overwhelming amount of patient data they receive daily. Physicians can implement AI to streamline or eliminate tedious tasks, such as manual documentation and data search, or cull information to help them focus on a key area of interest.
The medical imaging space in particular provides a tremendous area for the growth of AI and machine-learning technologies. Clinicians can use them to analyze thousands of anonymized diagnostic patient images to identify and detect indicators of everything from lung cancer to liver disease. These technologies are also being used to accelerate research.
New relevance: AI is being used in a number of ways to address the challenges of COVID-19. For example, AI algorithms have been used to identify the spread of new clusters of unexplained pneumonia cases. Other AI applications are being used to spot signs of COVID-19 infections in chest X-rays and identify patients at high-risk of coronavirus complications based on their pre-existing medical conditions. Still others are scanning the molecular breakdown of the virus itself as well as those of existing drug compounds to identify medications that can potentially target the virus and shorten the span of the illness or lessen the severity of the symptoms. In all of these scenarios, AI is quickly analyzing large segments of data to accelerate research and treatment. This automation is indispensable in an environment where medical staff are stretched to their limits, and the act of saving time could save lives.
Chatbots, or conversational AI, seem to be everywhere in our daily lives and go-to solutions for digital transformation initiatives. From banks to insurance companies and e-commerce sites, these automated assistants offer help, answer our questions and guide us – often without our really even knowing it. In today’s 24/7 environment, they fulfill the need for always-on service, anytime and anywhere, since it can be a challenge to staff call centers or customer service departments around the clock.
While we’re getting used to chatbots in customer service, there’s an emerging role for them in healthcare – helping to address the COVID-19 crisis.
Knowledge is Power — Easing Public Concerns One Bot at a time
The ability to provide information at a moment’s notice, anytime, anyplace and alleviating the burden on healthcare staff has made chatbots an important tool at Providence St. Joseph Health in Washington State. This health facility treated the first COVID-19 case in the U.S, and it implemented chatbots to help address the public’s demand for information, while at the same time, freeing up their overtaxed healthcare providers from having to deal with a deluge of calls from sick people and the “worried well.”
Providence Saint Joseph Health turned to technology to help it more effectively manage three critical stages of care: triage, testing and treatment, relying on chatbots to particularly assist during the triage phase of the process. By visiting its Coronavirus Assessment Tool online, people can find out more about which symptoms might indicate the virus, and figure out if they should be seen by a health professional. This chatbot is connected to a virtual patient care visit which enables people to discuss their symptoms with a nurse practitioner. It has had overwhelming success with the public; in its first day of use alone, more than 500,000 people used the chatbot.
Chatbots have been able to step up and meet these types of needs because they combine natural language processing with machine learning capabilities. This allows them to understand and communicate in a free flowing, conversational discussion. Because of the benefits it provides, market opportunities for the technology is growing rapidly: the global market for chatbots is predicted to reach $15.7 billion in 2024, up from $4.2 billion in 2019. And the market for chatbots in healthcare is expected to be over 314 million by 2023.
It’s no wonder that conversational AI has a bright future in healthcare. In an industry where professionals are busy and continually strapped for time, chatbots can provide and collect information, conduct outreach, send reminders and schedule appointments. It can also provide support to patients, their families and the public and offers the convenience of meeting consumers wherever they are – whether it’s on their phone, through messaging, social media or elsewhere.
Although electronic health records (EHR) are firmly established in the medical landscape, ongoing progress necessitates that providers keep up with emerging trends. Here are five of them.
1. Combining Artificial Intelligence and Voice Recognition with EHR
Artificial intelligence (AI) has already shown promise for assisting doctors with making diagnoses or recognizing historical trends about a patient’s condition. However, several companies are investigating bringing AI to EHR via voice recognition capabilities.
At Vanderbilt University Medical Center, providers can query the tools by posing questions in natural language. For example, a physician could ask a voice-enabled EHR system for details about a patient’s last recorded iron levels from blood tests. The system would inform the doctor of those levels, plus tell them whether they’re in a healthy range.
Allscripts and Northwell Health also recently struck a deal for a platform that blends AI with EHR and collects data from clinicians. Using voice commands within patient care could be especially useful for providers who have their hands full.
2. An Increased Emphasis on Mitigating EHR Errors
When the ECRI Institute released its 2020 report containing the top 10 health technology errors to be aware of in the coming year, EHR issues were mentioned multiple times. The first instance related to providers potentially being overwhelmed with notifications from EHR platforms, ignoring some of them and perhaps overlooking a genuine issue with a patient as a result.
The report also brought up the risk of medical data not including information about implants in patients that are sent for medical imaging. The study recommended providing a single place to enter or check for the presence of implant data in an EHR. Finally, the ECRI Institute cautioned that EHR mistakes could happen when a medication administration order sent by an EHR platform does not match the dosage time the provider intended.
This coverage of such mistakes will likely cause health care facilities to assess their systems and see if the issues exist there. If so, they’ll look for ways to reduce those problems.
Vital — AI-powered software in hospital emergency rooms — announces its inaugural development partnership with Emory Healthcare. As part of the strategic collaboration, Emory Healthcare becomes a lead research partner in developing and implementing Vital’s software to improve overall efficiency and satisfaction for patients and clinicians across multiple Emory emergency rooms. Vital was conceptualized and co-founded by Justin Schrager, assistant professor of emergency medicine and ER doctor; with award-winning technical CEO Aaron Patzer.
Vital’s software is the first partnership out of the Emory University Innovation Hub, designed to identify unmet patient needs and find innovative solutions to put the patient at the center of care delivery. Vital’s live track board and real-time predictions of patients are being developed in the Emergency Departments of Emory University Hospital, Emory Johns Creek Hospital, Emory University Hospital Midtown, and Emory Saint Joseph’s Hospital. The goal of this pilot program is to measurably reduce wait times and overall length of stay for patients, while increasing patient satisfaction.
“We are overjoyed to have Emory Healthcare as our primary development partner and pilot sites,” said Patzer. “We are impressed with the commitment Emory leadership has made towards technological innovation and tackling truly challenging problems in emergency medicine. Working closely with top emergency physicians and nurses is essential to producing software that meets the needs of clinicians.”
Vital uses artificial intelligence (AI) and natural language processing (NLP) to triage patients,, making it easier and faster for providers to coordinate care and prioritize patients with a fast, reliable, and incredibly user-friendly system.