By Waqaas Al-Siddiq, chairmen, CEO and founder of Biotricity
Going to see the doctor can sometimes feel impersonal – doctors are busy, sifting through a myriad of patient datasets and reports instead of spending crucial face-to-face time with patients. Healthcare organizations are drowning in data thanks to an increase in digitization and electronic tools, but don’t always know how to process all this new information efficiently. A report of over 19,000 physicians surveyed in 2019 found that 70 percent of respondents spend ten or more hours on administrative work, up significantly from 57 percent in 2017. But time spent with patients, and empathy from healthcare workers, are critical for outcomes and quality of care. Artificial intelligence can help give some of that time back to physicians and help make healthcare a more personal experience for patients.
While healthcare has traditionally been slow to adopt new technologies, the promise and potential of AI offers healthcare organizations plenty of reasons to begin implementing these tools. Artificial intelligence has helped improve clinical documentation processes and found connections in data to improve outcomes that would not have been possible otherwise. As artificial intelligence and machine learning models increase in efficacy and accuracy, automation can be applied widely. Processes like administrative tasks and revenue cycle management can be automated, drastically reducing some of the largest cost drivers. The impact of the administrative burden on our healthcare system is astounding – CMS’ 2019 annual report revealed that over 30 percent of our national healthcare expenditure is spent on administration, a disproportionate amount compared to other developed countries. Studies have shown that AI can help reduce administrative tasks for physicians, saving time and energy that can be redirected towards improving patient care.
AI can also assist with predicting health outcomes and emergencies before they occur, making it easier for healthcare workers to focus on the right patients and use their time more effectively, too. Predictive analytics has been especially integral for making healthcare more individualized. Applying advanced algorithms, clinical decision support tools can more efficiently triage patients to the appropriate care or help physicians flag potential problems like dangerous medication interactions. Using population health data, predictive analytics can identify signs of health deterioration in patients in the ICU or those most at risk for hospital readmissions after discharge. The benefits are numerous – patients receive improved care, facilities can direct resources more effectively, and some of the largest cost drivers are avoided entirely. This proactive, personalized approach to healthcare will continue to improve as machine learning models are fine-turned and additional areas of application are identified.
The transition to connected healthcare and digital tools means more data – and more data means more information for physicians to sort through. AI can help doctors makes sense of all this new information by sifting though and synthesizing everything, presenting them with actionable data. In the clinic, artificial intelligence in voice recognition / dictation and natural language processing is being used to improve the clinical documentation process. Automation here helps reduce documentation errors while paving the way for cross referencing of patient data for deeper insights. In image analysis, AI can look at slides and help pathologists and radiologists quickly assess significance. AI overwhelmingly performs better than humans in recognizing features in images, speeding up time to diagnosis and treatment and helping prevent further disease progression.
Maybe most importantly, AI can help give time back to physicians. Extra time spent with patients reduces readmissions, promotes happiness, and increases patient satisfaction. A research paper published in 2018 by the National Bureau of Economic Research studied the effect of the length of home health visits for patients who had been discharged from hospitals after treatment for acute conditions. The researchers found that for every extra minute that a visit lasted, there was a reduction in risk of readmission of 8 percent. Time was the most important of all factors the researchers studied to reducing readmissions. With extra time, and less burnout, clinicians will be able to better lend patients the empathetic care that they need. The more time clinicians spend interacting directly with patients, the more they can detect and recognize the patients’ experiences, worries, and perspectives. Research has shown that the effects of empathy can also help improve patient compliance – which, in turn, can reduce costs.
This isn’t just beneficial for patients. Healthcare workers are dealing with a serious burnout epidemic; several studies have shown that over fifty percent of physicians are experiencing at least one symptoms of burnout (this is significantly higher than the general population). They are tired, stressed, and overwhelmed – and this comes with consequences for patients. Burnout leads to an increase of medical errors, an increased risk of malpractice, reduced patient satisfaction, and poorer quality of care and outcomes.
As a result of the pandemic, hospitals and healthcare workers are even more under-resourced. A survey from Mental Health America indicated in June that 93% of healthcare workers were experiencing stress, while three quarters of them were overwhelmed and reported exhaustion and burnout. Another recent poll from the Washington Post in March found that 3 out of 10 healthcare workers have now considered leaving the industry. Healthcare professionals require years of training in preparation for their roles; the use of artificial intelligence may also be necessary to help prevent the consequences of an increase in demand for care. The time AI gives back to healthcare workers by alleviating their workload can help reduce the risk of burnout and prevent costly errors.
Healthcare today is impacted by administrative burden, copious amounts of data, and overwhelmed healthcare workers. This combination can lead to degradation in care and outcomes, creating an immediate need to seek innovative solutions. Effective healthcare requires an individualized, compassionate approach. AI is a unique technology that has a variety of applications. Applied correctly, it can ease administrative overhead, analyze vast amounts of data, and reduce personnel workload. Most critically, freeing up healthcare workers’ time will enable them to focus on the doctor-patient relationship, improving outcomes. Ultimately healthcare is about taking care of patients; making healthcare a more personal, and less clinical, experience is at the core of that. AI can help drive this transition alongside improvements in administration and data analysis.
Waqaas, the founder of Biotricity, is a serial entrepreneur, a former investment advisor and an expert in wireless communication technology. Academically, he was distinguished for his various innovative designs in digital, analog, embedded, and micro-electro-mechanical products. His work was published in various conferences such as IEEE and the National Communication Council.
Waqaas has held several high-level design positions in IBM, AMD, and Intel. His achievements have been numerous in both the technical and academic world. Coupled with this, Waqaas has vast experience in leading various groups through his board experience and executive roles within start-ups, mid-sized companies, and non-profits.
Waqaas has a dual Bachelor’s degree in Computer Engineering and Economics, a Master’s in Computer Engineering from Rochester Institute of Technology, and a Master’s in Business Administration from Henley Business School. He also holds a Doctorate in Business with a specialty in Transformative Innovations and Billion Dollar Markets.