My father was diagnosed with diabetes when he was very young and lived his entire life maneuvering various healthcare systems. He had multiple eye surgeries, which is common for diabetes patients. He had pancreatic issues, open heart surgery, and two kidney transplants. It was a lot and, as his daughter, one of the most difficult parts of it all was watching my mother be his primary caregiver, managing doctor appointments, medication prescriptions, treatment plans and insurance claims.
At the time, there was little to no technology on the practice management side of healthcare. Until the internet connected us all, EHR systems were contained to inpatient and outpatient facilities, primarily used as data interchange platforms for claims processing with scanning capabilities to create images of documents. I remember my mother carrying a binder from doctor’s office to doctor’s office – the most effective way for her to keep an easily accessible list of my father’s ailments, healthcare conditions, medications, and all the other details needed by the countless doctors across my father’s continuum of care.
How AI is creating more meaningful patient experiences
Fast-forward two decades and we’re now in an entirely new reality with an ever-expanding healthcare technology ecosystem. Medical office software platforms do so much more than claims processing and digital document storage. Interoperable EHR systems let physicians share treatment plans and easily access medical histories and lab results anywhere and anytime. Patients can schedule appointments online and login to patient portals to get test results in real time. Telehealth has ushered in brand new healthcare delivery models and helped drive greater adoption of behavioral health services. Remote patient monitoring (RPM) technologies have been a game-changer for so many, helping patients better manage chronic illnesses.
And now, with the integration of artificial intelligence (AI), we’re seeing the next wave of healthtech – an advancement that is bringing our entire industry closer to the promise of fully connected or interoperable healthcare systems. AI is having a massive impact on medical practice workflow processes, empowering healthcare providers and medical office staff. AI applications are making it possible to automate tedious and redundant tasks so that medical professionals can focus their time on valuable work that greatly improves the patient experience and outcomes – and that’s just on the business side of things.
The healthcare sector is predicated on protecting all sensitive information for a practice and its patients. Threats come from every direction, whether through email, an attachment, a malicious link, or simply the penetration of a security system.
Solutions are aplenty but with various degrees of effectiveness and durability, not to mention complexity and quality of protection for the practice, all are important factors when measuring benefits versus risk. As healthcare practice leaders attempt to mitigate their continuous onslaughts of threats, possible breaches, and potential bad actors, automating security measures can alleviate trouble, distractions, and chaos caused by a breach or other malicious activity.
While most in healthcare don’t like to discuss the ugly but open secret, email is a significant factor in many data breaches. Therefore, advanced levels of protection for Outlook and other email servers are essential, and add-on solutions solve the problem of misaddressed emails and prevent data leakage.
Technology that scans for sensitive keywords, personally identifiable information (PII), or data patterns inside the email body or attachments can provide practices with a critical layer of security.
Confirm External Recipients and Attachments
Using data loss awareness (DLA) technology, users can confirm the practice’s external recipients (those receiving a message from the practice) before messages are sent. Such an integrated solution “asks” whether everyone on an email recipient list should be seeing the sensitive information contained, so the message is not sent to someone by mistake. Likewise, this prevents misaddressed emails or inadvertent auto-fill email mistakes.
Email breaches from accidental data loss can result in fines, regulatory non-compliance notices, and even litigation for a medical practice. Additionally, medical practices can (and should) seek solutions that proactively help users to prevent accidental data loss and keeps all sensitive information from leaving the organization
In such environments, all settings should be configurable and specified on a per-user or per-group basis. In addition, healthcare organizations should automate activity logs for all potential occurrences with a complete audit trail stored locally or centrally and supporting Outlook local languages, as these are often needed should you be audited.
It’s the 21st century, and 78% of hospitals still “often or sometimes” receive their medical records via mail or fax, according to a 2021 report from the Office of the National Coordinator for Health Information Technology.
This isn’t just an inconvenience, it’s a massive expense and time commitment for providers. It’s also dangerous for patients; when a provider doesn’t have an up-to-date, readable medical history, it can delay vital diagnoses and prevent patients from receiving timely, potentially life-saving care.
If there is one problem we can solve in healthcare that will positively impact patients, providers and payers alike, this is it. And thanks to some important regulatory and technological advances — including artificial intelligence — we’re starting to see a large group of leaders and innovators come together to tackle this challenge head on.
Has our investment in electronic health records paid off?
The U.S. government has spent more than $30 billion on incentivizing the use of EHRs since the passage of the HITECH Act of 2009. Unfortunately, focusing only on implementation and not on standardization created a new problem to solve.
Without a standard format or structure for records, we ended up with hundreds of thousands of systems exchanging unstructured data — it wasn’t until 2014 that the first official Fast Healthcare Interoperability Resources standards were published.
In addition to the issues around interoperability, we’ve also lacked a standard process for inputting the physician progress note into the EHR. An enormous amount of clinical value is found in that unstructured note, and without a readable format, that information goes to waste.
Because of these problems — along with slow adoption of new technologies among clinicians — healthcare is still faxing billions of pages of medical records every year.
New regulations and standards can help solve the interoperability problem
Recent advances in regulation and standardization are laying the groundwork for important progress in the coming years. Over the past decade, the implementation of standards like FHIR has created a standardized format for medical record data.
And with the 21st Century Cures Act, we’ll soon see the emergence of a regulated, mandated, and interoperable national network under the Trusted Exchange Framework and Common Agreement.
It will take an enormous amount of effort and collaboration to implement these changes at scale. But with the lessons learned since 2009 in mind, these regulations provide a vital foundation that was missing from previous legislation.
Artificial intelligence and machine learning have a vital role to play
Advancements in artificial intelligence and machine learning offer an unprecedented opportunity to synthesize medical record data into a readable, structured form.
Consider the volume of care a patient receives throughout their entire lifetime. Especially for an individual with one or more chronic conditions, one patient’s entire history is often spread across hundreds of pages of documents, with no means to connect them into a structured narrative.
Today, when we pull data on a patient digitally, we get an average of 43 clinical documents per patient. These can be in any format — HL7, FHIR, CCDA, or even a JPEG or TIFF. And then within each file, there’s an enormous amount of unstructured clinical narrative.
Artificial intelligence can play a key role in synthesizing these records — extracting diagnoses, lab results, medications, procedure history, and more — into a finely-tuned, digital record that’s fully searchable and comparable.
These records will reduce both the cost of treatment and time to treatment, making it easier for clinicians to provide the care patients need, when they need it.
Using existing technologies to build a scalable, user-friendly solution for medical records is not just a useful innovation. It is a vital step we must take if we want to solve the $125 billion problem of medical record retrieval and analysis.
By Dan Leibu, co-founder and chief operating officer, League.
In the wake of the COVID-19 pandemic, the healthcare industry rapidly adopted new technologies and processes to improve care delivery and keep patients and staff safe. The adoption of telemedicine and digital front doors has allowed healthcare providers to continue delivering care to patients while minimizing the risk of spreading COVID-19 and making care more accessible to patients. Yet, the pandemic exposed gaps in our healthcare system, including the need for an underlying platform that connects all aspects of patients’ health journeys.
As we move into the endemic stage of COVID, with President Biden set to end all COVID-19 emergency declarations in May 2023, we have the chance to reflect on the successes and shortcomings of our national pandemic response and apply those lessons to make our healthcare system even more resilient and prepared for future pandemics and crises.
A platform approach to contact tracing
When the pandemic reached full force in Spring 2020, it generated a rush to implement solutions for contact tracing to stem the rapid spread of the virus. By December 2020, at least 74 countries had launched apps to automate and assist contact tracing. In the U.S., companies including Apple and Google rushed to provide aid by rolling out their own contact-tracing technology, but these solutions ultimately proved too disjointed and did not gain the necessary traction to be fully effective.
A platform approach to healthcare would allow for much more efficient and widespread contact tracing during the next pandemic. Healthcare platformization could facilitate the wide-spread implementation of a single, unified contract tracing solution that would provide a streamlined and accessible user experience.
Expanding care access
During spikes of the COVID-19 pandemic, overburdened providers, high patient loads, and limited hospital beds necessitated hospitals to triage care. Likewise, many patients avoided visiting hospitals and doctors’ offices to protect themselves or were turned away. A study by the Center for Disease Control found that by June 30, 2020, an estimated 41% of U.S. adults had delayed or avoided seeking medical care because of COVID-19, including emergency care (12%) and routine care (32%). Avoidance of emergency care was more prevalent among those with underlying medical conditions and disabilities, unpaid caregivers for adults, and Black and Hispanic adults, demonstrating the effect of social determinants of health on care access.
In addition to the obvious risks associated with delaying emergency care, persistent difficulty accessing routine and preventive care can lead to serious medical conditions going undiagnosed or unchecked. Many patients with chronic conditions such as diabetes, heart disease, and autoimmune disorders were forced to manage their health at home.
For most people, going to the doctor for a quick check-up usually just means driving to the hospital. However, some people either don’t have the means to travel or they might require special equipment or arrangements when being transported. But while their need to access medical services can be considered an essential need, these patients don’t typically require ambulance because they’re not experiencing a medical emergency.
This is where non-emergency medical transportation (NEMT) comes in. For an affordable fee, patients can book NEMTs that will transport them to their destination hospitals or healthcare facilities. Unlike most private vehicles and modes of public transport, NEMTs are designed to carry patients that need special equipment or assistance. NEMTs can smoothly transport people in wheelchairs and stretchers which regular taxi cabs and buses are unable to easily accommodate, if at all.
If you’re thinking about using non-emergency transport services or just curious about how they work, here are a few things about NEMTs that you should keep in mind.
NEMT Providers Use Software to Connect with Patients
NEMT providers and brokers typically take advantage of software solutions to ensure that patients connect quickly with an available NEMT service. By using a custom-made platform, transportation providers can easily schedule the deployment of NEMTs for patients in need. Similar to emergency dispatch in EMS, non emergency medical services software allows NEMT providers to dispatch transports to users who are requesting transports.
NEMT software solutions assess the available vehicles based on their capacity to accommodate equipment such as walkers, gurneys, wheelchairs, and mobility scooters. Upon booking, the NEMT software will also provide billing information with a breakdown of accumulated costs.
By Lu Zhang, founder and managing partner of Fusion Fund.
In theory, artificial intelligence has the potential to transform the healthcare industry for the better in a number of important ways. AI and machine learning’s predictive capabilities, for example, can improve accuracy in diagnosis and treatment. AI can also be put to use for boosting efficiency in the areas of administration and operations.
However, it appears that many healthcare institutions are reluctant to put this promise to the test. Compared to other industries, AI adoption in healthcare is not keeping up — this isn’t altogether surprising. Healthcare has several barriers to entry for AI and ML that are unique to its industry and need to be considered by anyone innovating in the space.
Why AI Adoption in Healthcare Has Fallen Behind
When it comes to the collection and storing of data — which is essentially the lifeblood of an effective AI solution — there are both regulatory and privacy concerns that need to be taken into consideration. In the United States, the Health Insurance and Portability Accountability Act (or HIPAA) has specific rules around the ways in which patients’ private information can be managed and shared. The General Data Protection Regulation (or GDPR) plays a similar role in the European Union. Beyond these legal questions, providers are also keenly aware of how important it is to ensure that sensitive patient data is kept secure and private for the sake of maintaining good reputations and healthy relationships with patients.
What’s more, even if all regulatory and privacy concerns can be addressed, there are still other issues at play when it comes to data. Specifically, the time and effort it takes to collect the amount needed to ensure AI is delivering accurate and unbiased analysis can be immense. The most efficacious way to get enough data quickly would be to share it among organizations. This is easier said than done, thanks to a lack of standards around data storage and a reluctance to entrust patient information with third parties.
But data isn’t the only obstacle to AI adoption. AI’s typical lack of transparency is another. In an environment where there’s hardly any room for error, it’s crucial to understand not only the thinking behind a decision, but also the variables that were used in the decision-making process. With modern AI, gaining access to this information can be difficult or, in some cases, even impossible.
Perhaps the most difficult barrier to entry for AI, however, is also a more subtle one: mindset. Many healthcare professionals are reluctant to bring in new technology that might disrupt carefully calibrated workflows or even replace human healthcare workers with computer counterparts. AI’s role in healthcare is to complement existing professionals — not replace them — but it’s understandable to be concerned about the ways in which AI could change how the industry operates.
With all these challenges and concerns, it’s perhaps no surprise that AI adoption is happening at a slower rate. However, none of these impediments should be seen as deal breakers. The healthcare industry needs to open its eyes to the benefits of AI. This technology will allow employees to deliver better patient outcomes quicker, easier, and cheaper. In the future, the doctors and nurses who know how to use AI tools will replace those who don’t. If AI developers want to help make this future happen, they need to take some steps to tailor the adoption process to the needs of healthcare professionals.
3 Ways Providers Can Make AI Tech Easier to Implement in Healthcare Environments
1. Work on augmenting workflows — not disrupting them.
The healthcare system is a complex organism that relies on tried-and-true processes to keep it running smoothly. Inserting AI into the equation has the potential to disrupt this equilibrium, undercutting any benefits it might bring.
However, AI also has the potential to make these processes more efficient and less prone to errors. AI and ML have the power to make healthcare operations truly intelligent. Creators who offer specific solutions for hospitals looking to improve their existing administrative and operational workflows can provide great entry points for wider AI adoption.
2. Focus on compatibility.
For ML to provide accurate diagnoses and treatment options, it needs diverse training data to learn from. While some larger organizations might be able to provide this data on their own, many others will lack the amount of data necessary for algorithms to be effective. Ideally, these institutions could aggregate data with other providers to create robust AI models that are not only more accurate, but also more generalizable with less bias.
To do this, the method for storing and processing this data would need to be compatible across companies. To provide AI solutions that work within the healthcare industry, developers should steer clear of proprietary data formats. Instead, they should embrace standards where they exist within the industry while encouraging the adoption of those standards where they’re missing.
3. Offer natural language processing.
The beauty of NLP systems is that they can be put to use in a variety of ways without needing a large amount of healthcare-specific data to be effective. NLP can be used to organize clinical documents as well as analyze unstructured notes to offer digestible summaries and actionable insights.
NLP can also be used to augment the work of experts in other areas, such as to improve the interpretation of patient imaging by radiologists. This type of AI solution is a simple and effective way to move the needle on AI adoption.
Even if adoption has been relatively slow, AI is already proving itself a valuable part of healthcare where it has been implemented. From diagnosis to health risk assessment to new drug development, AI has proven itself a useful tool in the world of healthcare. But for it to reach its full potential, AI developers need to create solutions that address the legitimate concerns of healthcare professionals and patients in order to get everyone on board and help the industry move forward.
Love.Life, a health and wellness company leading the convergence of food, medicine, and wellness therapies, is pleased to announce the acquisition of Plant Based TeleHealth Inc., a nationwide telemedicine service focused on the prevention and reversal of chronic disease utilizing lifestyle medicine. The company has been rebranded as Love.Life Telehealth and will add to the robust suite of medical offerings that Love.Life will feature in its physical locations.
“Love.Life is about making lasting health and vitality achievable, and acquiring Plant Based TeleHealth accelerates our ability to help more people without geographic limitations,” said John Mackey, Love.Life’s CEO and co-founder and co-founder of Whole Foods Market. “Appointments are available now, and we’re excited to offer telehealth services as part of the comprehensive medical offering available in our physical locations, which will begin opening in 2024.”
Using secure video conferencing and patient portal technologies, Love.Life Telehealth provides virtual medical care for patients who are focused on optimal wellness or have chronic disease and other medical conditions including, but not limited to, diabetes, high blood pressure, high cholesterol, heart disease, obesity, autoimmune diseases, inflammation, and digestive issues. These conditions and overall wellness needs are addressed through lifestyle medicine—the powerful, evidence-based practice of promoting healthy behaviors and lifestyle modification, including a whole food, plant-based diet.
Patients can sign up for 30- and 60-minute appointments using the online portal at https://love.life/telehealth for $175 and $350. In addition to licensed physicians practicing in all 50 states and Washington D.C., the current international patient reach spans 27 countries.
As part of the acquisition, co-founder and former CEO of Plant Based TeleHealth, Anthony Masiello, has joined the executive leadership team of Love.Life, which includes Mackey and multiple former Whole Foods Market leaders.
“Plant Based TeleHealth and Love.Life are both mission-based companies and we’re thrilled to be part of an integrated health solution that aspires to move beyond medical care that simply treats symptoms and manages disease with medications,” said Masiello. “Whether you’re someone seeking overall wellness, preventative care, or a better path for treating existing conditions, our physicians make achieving personal health goals attainable by looking at the total health of an individual, addressing root cause of disease, and creating an environment where the body can heal.”
Healthcare is continually evolving, with bariatric innovations transforming the weight loss industry. From the many artificial intelligence applications to the latest adaptive technologies, bariatrics constantly improves and grows while enhancing the surgery’s effectiveness. This article outlines four bariatric innovations that are transforming the weight loss industry.
1. Robotic procedures
Surgical robots are a game-changer and an exciting bariatric innovation. They arm surgeons with extraordinary precision, expanding and boosting their natural abilities to constantly enhance bariatric surgical procedures’ efficiency and accuracy, including gastric sleeve surgery. Surgical robots provide enhanced ergonomics and safety that can help address the growing physician burnout in the healthcare industry. This can be rewarding to the surgical field’s sustainability.
Patients are assured of accurate and safe weight loss through bariatric robotic systems. The systems feature 3D views and high-magnification cameras to ensure surgeons have an excellent range of motion. This increases their precision and allows them more control during the procedures, reducing complication risks after and during the surgery.
Unlike the traditional laparoscopic weight loss procedure, bariatric robotic surgery has more possible benefits, including quicker recovery, shortening your time in hospital beds, lowering infection rates, minimizing pain and scarring, and lowering attached follow-up risk after surgery. Since bariatric robotic procedures are less invasive, you may get back to your routine much sooner.
2. Artificial intelligence
Artificial intelligence is at the top of various technological advancements in the healthcare sector. The algorithms that help computers learn and conduct cognitive functions are transforming the world of bariatrics. Here are the opportunities AI unlocks in bariatrics:
Artificial neural networks assess and forecast surgical risk, arming surgeons with good decision-making details and administrators with information for informing initiatives, such as bundled payments
Machine learning lets computers learn and foretell depending on datasets, enabling clinicians to foresee specific outcomes and look for unfamiliar patterns. This efficiently and quickly offers surgeons insights to inform surgical teams to expand bariatric innovation while fueling better results
Computer vision offers real-time improvement to surgical imagery. Its study of video in laparoscopic surgery automatically identifies a sleeve gastrectomy’s steps with high accuracy and helps determine complications and missing stages to help surgeons
Natural language processing helps computers recognize human language plus its meaning. It can be used in automated post-operative care for efficient complication identification
3. Adaptive and interactive technology
Patient engagement, an essential element in each bariatric journey, has improved. mHealth technology’s focus has so far been on text message-based interventions. However, innovations are unraveling real-time sensing potential to develop adaptive interventions. These interventions utilize wearable sensors to wirelessly connect to smartphones, computers, and smartwatches to track patient behavior constantly. The sensor can monitor diet, physical activity, sleep, sedentary behavior, social context, and behavior.
4. Acceptance-based behavioral procedures
Weight gain post-bariatric surgery is common. This results in the loss of the rewards the surgery helps patients gain, causing dangerous or adverse health impacts. Acceptance-based behavioral treatments provide patients with special psychological skills for boosting lasting exercise and dietary program adherence. These treatments help patients learn to make mindful decisions instead of automatic choices caused by external signals. They also help them develop a desire to face discomfort instead of making the experience more pleasurable.
Endnote
Bariatric innovations enable the obese care industry to enhance health outcomes and minimize costs while continuously offering better services to patients. Familiarize yourself with these bariatric innovations that are transforming the weight loss industry.
Healthcare organizations undoubtedly felt a sense of relief as 2022 faded in the distance, taking with it a devastating financial performance that resulted in negative profit margins for more than half of U.S. hospitals – the worst year hospitals have faced since the start of the pandemic, according to Kaufman Hall. Not only were operating margins down for most of 2022, but hospitals also struggled with higher labor costs in a more competitive market plagued by chronic clinical and administrative skill shortages.
Physician practices fared no better, with 90% saying that soaring expenses outpaced revenues last year, according to a survey by the Medical Group Management Association. Staffing and labor costs were cited most often as the source of rising costs. Other common culprits were lower reimbursement rates, significant increases in lab supply and drug costs, higher utility costs, lower patient volumes, and rising malpractice premiums.
The new year does not mean healthcare organizations are out of the financial woods, however. A plethora of new challenges to the bottom line have emerged, led by a sharp uptick in third-party audits. Supported by a $2.5 billion budget for the Healthcare Fraud and Abuse Control and Medicaid Integrity programs, federal payers are stepping up both pre-payment and retrospective claim audits – and private payers are following suit. This not only increases the risk of penalties and claw backs, but it also slows claims processing and, subsequently, reimbursements and puts greater pressure on providers to submit clean claims the first time.
Five Revenue Integrity Trends
To avoid a repeat of 2022’s dismal financial performance, revenue integrity leaders surveyed by MDaudit are placing a priority on revenue opportunities (34%), compliance pressures (29%), revenue risks (29%), and staffing issues (9%). For 37% of respondents, all these issues are top of mind for 2023.
These concerns align closely with the focus on growth, revenue, and profitability that dominate most organizational planning – and is evident in the following key revenue integrity trends identified in the 2022 Annual Benchmark Report.
Of late, the healthcare industry is going through a tornado of technological revolution. Among them, the introduction of mental health practice software has taken over the healthcare industry by storm.
A handful of practitioners have already integrated practice management software for mental health to simplify their day-to-day operations. However, quite a few are still unsure if leveraging mental health practice software will be a boon.
As reported in recent research by HIMSS, about 80% of healthcare providers are resolute in investing in digital solutions and technologies in the next five years. With the majority of industry giants turning to advanced technologies to deliver holistic care, there’s no reason not to invest in mental health practice software.
In this article, we’ve discussed a few benefits of integrating the best mental health practice software. Let’s check them out.
6 Benefits of Mental Health EHR Software
In the past few years, mental health EHR (electronic health record) has gained popularity among para-professionals and medical providers because of the numerous benefits it offers. They are as follows:
1. Improved Care Coordination
By using mental health practice software, collaborating with other medical providers has become easier than ever. Wondering how? Let us simplify it for you.
Such software allows clinic staff to maintain patient records, from medical history to diagnosis. You can access those details whenever a patient visits you and even share them with other healthcare providers to make informed decisions.
Conversely, patients can also access and modify them with the click of a button as and when required.
2. Enhanced Clinic Efficiency
A lot of day-to-day operations like billing operations, scheduling appointments, reminding patients of their next sessions, and many more are time-consuming tasks.
When staff members are busy carrying out these humdrum tasks, patient care is ignored considerably. To provide excellent patient care, you need to stop overburdening your staff with ancillary tasks that otherwise could be done by integrating software.
Access patient details and other data with a click as against browsing several spreadsheets
Maintain a record of invoices and billing information of patients
Solutions like Owl Practice’s mental health practice software simplify operations like invoicing, collecting and managing payments, and client schedules by syncing your calendar. Also, the software can send clients reminders via email and SMS and allow them to book appointments online.
