Is the co-CEO and co-founder of South Florida-based ModMed?®A healthcare technology company pioneering innovative, specialty-focused solutions to revolutionize care delivery and drive superior patient results.
As of February 2010, the company had expanded to employ more than 1,200 individuals and had secured over $332 million in total funding through various investments. Recognized globally for its innovative advancements in medical expertise, ModMed consistently earns accolades nationwide and regionally under the leadership of Daniel, solidifying its reputation as a pioneer in the industry. In 2020, the corporation was recognized as one of the Best Places to Work in America by Inc. journal. Between 2016 and 2018, the corporation earned a prestigious distinction as one of the fastest-growing companies in North America on the Deloitte Technology Fast 500.™ record. Starting in 2015, the company was consistently recognized annually by Inc. magazine as one of its fastest-growing private businesses.
The prestigious compilation, featuring 5,000 records, showcases the country’s most rapidly expanding personal businesses.
I pursued a career in technology during my time at Cornell University, where I had the opportunity to co-found Blackboard. We revamped traditional training by digitising lecture notes and developing a platform that granted college students and educators unparalleled flexibility and interaction. Blackboard’s triumph peaked in 2004 with its initial public offering, as our innovative solutions revolutionized the education technology landscape. Despite our impressive track record, I found myself eager to take on fresh challenges.
During a regular consultation with my dermatologist, a particular concern arose. We engaged in a thought-provoking conversation about the challenges of relying on antiquated paper-based approaches to address repair issues. By synergistically combining his medical expertise with my technological capabilities, we decided to launch ModMed, a pioneering EHR platform that seamlessly bridges the gap between healthcare and technology.
Despite early existence of electronic health records (EHRs), they were often identified as a significant contributor to physician burnout in academic studies. By developing an innovative approach, we created an Electronic Health Record system that seamlessly integrates a clinician’s expertise with the distinctive workflow patterns of a specific medical discipline. As the pioneer of cloud-based electronic health records, EMA remains uniquely positioned, having been conceptualized and crafted by a team of medical professionals, exclusively for the medical community – this distinct approach being the cornerstone of our success story. Over time, we’ve broadened our product portfolio to offer a comprehensive range of solutions that enable medical suppliers to optimize their workflow, reduce complexity, and accelerate the delivery of quality care.
The incorporation of AI technology into professional practices is gaining momentum, as organizations seek to optimize processes and enhance productivity. As AI increasingly takes on more nuanced tasks, such as recommending therapy or providing other clinical-support suggestions, it is crucial to establish accurate data and AI training methods that ensure their effectiveness. While AI presents a significant opportunity to augment expertise for patients and providers, driving systemic change in healthcare, its actualization hinges on massive amounts of high-quality data utilized to train models.
Poor-quality information has a direct impact on the performance of AI systems, compromising their ability to deliver optimal results with precision and accuracy. As a result, the very lives of patients in a healthcare environment could potentially be jeopardized. Despite the uncertainty surrounding AI’s potential to revolutionize healthcare, a more pressing concern is that adverse experiences may erode both patients’ and providers’ trust in the technology, potentially stalling its positive impact and slowing progress.
In the examination room, cutting-edge AI-powered ambient listening devices are engineered to provide insightful audio recordings that inform medical notes, allowing healthcare professionals to review, evaluate, and ultimately approve them. By streamlining documentation within the electronic health record (EHR), suppliers can reduce the time spent on recording information, freeing up more time to focus on delivering high-quality patient care. Poorly sourced information and inadequately trained AI tools can have a counterintuitive effect, forcing suppliers to dedicate an excessive amount of time correcting mistakes and rewriting notes, thereby undermining the very efficiency they were designed to achieve.
Moreover, the risk of bias inherent in AI algorithms poses a significant threat, underscoring the pivotal role that high-quality information plays in addressing healthcare disparities effectively. Artificial intelligence systems can analyze patterns tailored to a specific individual or population, often favoring one group over others, including legally protected groups. Through continuous monitoring of input data and expert guidance on accurate and consultative insights, AI-generated outputs are likely to become increasingly comprehensive and precise.
At ModMed, we leverage comprehensive specialty-specific intelligence to train our AI models with pinpoint accuracy. Over the past 14 years, we have developed de-identified, specialty-specific structured information units that adhere to privacy regulations, and are now utilizing these in-house data assets to train our AI models effectively. Our ambient listening instrument, ModMed Scribe, has undergone extensive training in dermatology, its inaugural specialty offering, utilizing thousands of structured parameters gleaned from a massive dataset comprising anonymized patient information culled from over 500 million clinical interactions.
The risk that AI may harbor biases or disseminate flawed information, manifesting as “hallucinations” or omissions, has the capacity to significantly impact individuals’ lives. Since this is the case, moral AI in healthcare aims to establish an exceptionally high standard for accuracy and precision. Developing sophisticated algorithms with utmost precision and accountability, leveraging a diverse array of premium data sources to empower accurate forecasts tailored to individual needs.
Moral AI can ensure individuals adhere to a predetermined framework. While an AI shouldn’t supplant human judgment, it can effectively alleviate the administrative burden on physicians, freeing up their time and energy to concentrate on patient care.
By leveraging our proprietary approach to curated content, which entails assembling top-notch information units from respected consultants and coaches, we are able to bring accountability-driven AI into reality. Through the aggregation of de-identified data from a diverse range of practices, leveraging advanced EHR methodologies, we gain access to a broad spectrum of coaching insights that illustrate distinct patient demographics.
Furthermore, our improvement team excels at data purification, ensuring seamless collection and utilization of top-tier intelligence. This course enables groups to establish consistency, correct errors, and remove ambiguities from the data set. Through regular maintenance, we are able to consistently update the AI system using efficiency data, including medical information, where patient outcomes can be directly influenced.
Transparency is crucial for ensuring accountability, thereby making it a fundamental component of any AI-driven solution in healthcare, as it fosters trust and enables effective evaluation. Given physicians’ paramount concerns for patient care and safety, it is unsurprising that they must stay abreast of the characteristics and options for designing, improving, and deploying AI tools.
Not all information holds equal value; some insights are more reliable and valuable than others. Knowing the place where information is stored, its source, and how often it’s updated is crucial. Given our commitment to ModMed since its inception, we have remained resolute in employing an information strategy that emphasizes transparency and precision. We now possess a profound comprehension of the origins of our data, coupled with its exceptional quality, ensuring that our AI integrations will yield substantial value to our customers.
Across our comprehensive portfolio, we have successfully leveraged machine learning technologies for an extended period, further solidifying our investment in advanced and generative artificial intelligence to streamline the practice of medicine and accelerate the delivery of high-quality care. We’re developing an end-to-end AI-powered observation experience that commences prior to a patient’s arrival, seamlessly integrates throughout the examination room, and culminates in the billing department.
In the final stages of our artificial intelligence-powered ambient listening pilot project for EMA, we believe this innovation has the potential to revolutionize downstream performance by streamlining recommended structured content. Our AI-driven documentation solution streamlines the clinical documentation process by going beyond simple transcription or drafting of comprehensive SOAP notes. Utilizing vast amounts of structured data, we train our AI models to extract crucial information from doctor-patient dialogues, seamlessly integrating with our electronic health records (EHRs) to provide informed content suggestions for visit notes, including ICD-10 codes, procedural codes, and prescription recommendations. This measure safeguards physicians’ precious time, allowing them to focus on delivering exceptional care to their patients.
Medicine’s unique diversity lies in its distinct specialties. Healthcare professionals navigate diverse caseloads of patients, complex scenarios, and a myriad of medical codes necessary for accurate billing and reimbursement. To achieve significant efficiency, AI solutions must be carefully tailored to adapt to diverse scenarios and nuances.
ModMed’s electronic health records (EHRs) and AI-powered ambient listening instruments are designed specifically for each medical specialty, providing highly specialized and precise assistance to clinicians. Each specialization’s documentation demands unique components within a formatted framework, including distinct medical codes and terminology. This specialisation enables the AI to more accurately comprehend and forecast the unique requirements and workflows of diverse specialty practices, thereby leading to a more efficient implementation, swifter adoption, and enhanced overall performance in optimising operational efficiency.
As the pace of technological advancements accelerates, it is inevitable that artificial intelligence will increasingly infuse every aspect of healthcare, revealing transformative implications that will unfold before our very eyes. As AI becomes increasingly adept at handling routine tasks, it’s poised to revolutionize administrative functions in the near future.
I envision a future where AI is organically integrated throughout doctor-patient interactions, with the user interface being almost imperceptible. Instead of relying solely on screen-based interactions, AI has the potential to seamlessly integrate reality with augmented reality. This potential future AI might potentially utilize wellbeing data to derive crucial insights, thereby forecasting an individual’s susceptibility to various diseases. The vast expanse of medical data offers AI an opportunity to forecast future healthcare needs and develop, then support the implementation of proactive care treatment regimens.
As this expertise extends beyond the observation period, it becomes an integral part of a patient’s daily life. AI-powered wearables may offer personalized assistance, respond to inquiries, and schedule appointments among other benefits. AI can remotely monitor crucial performance metrics, promptly detecting and notifying suppliers of potential health concerns. Personalized therapy plans, tailored to individual sufferers based on unique information and preferences, may become the norm.
This is a groundbreaking era for healthcare innovation! The next 5-10 years hold a wealth of opportunities to reimagine and revitalize the organization, ultimately elevating the customer experience through targeted enhancements.
