Improving Patient Flow:

How to provide diagnostics accuracy while lacking time

Poor systems deliver poor results, and, in case of the US healthcare, the pile of problems has been growing for years. From high costs and lack of transparency to administrative inefficiency, the system has created an environment where not only patients but also medical staff suffer. In the midst of the global pandemic of COVID-19, all of those pain points have only intensified and got worse.


In this article, we will delve into only one of the many facets of the US healthcare system that need reform — inefficient patient flow. We will explore how overworked medical personnel in the United States are, cover the consequences of the coronavirus pandemic in terms of diagnostics efficiency, and demonstrate how automation and AI can help doctors serve more patients while staying safe and protected.

High Patient Flow: is it even a problem?

According to The Physicians Foundation 2018 Physician Survey, doctors in the US on average work 51 hours a week and see 20 patients a day, having to cover from 1,800 to 2,500 patients nationwide. In addition to that, almost 25% of their time is taken up with tedious non-clinical paperwork.

These figures perfectly correlate (and explain) the findings of the 2018 study on burnout of healthcare professionals, according to which:

Burnout has reached rampant levels among United States healthcare professionals, with over one-half of physicians and one-third of nurses experiencing symptoms… Burnout among physicians has shown signs of increasing since 2013.

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Obviously, high workloads, stress, and burnout not only affect the well-being of healthcare workers but also negatively impact patient care causing higher mortality among patients and much faster dissemination of hospital-transmitted infections.

In comparison, doctors in the European Union on average work no more than 48 hours a week, ranging from 37 hours for experienced physicians to 56 hours for junior doctors. Most countries in Europe employ more physicians per 1000 of the population. Nonetheless, doctor burnout is also a serious issue in the EU (mostly, due to rapid population aging, reductions in financing, and a shortage of doctors).

To sum up

High (and inefficient) patient flow is a universal challenge. Not only in the US but also in countries as diverse as Germany, Japan, Argentina, and China doctors suffer under workloads beyond their capacity. The coronavirus pandemic has only aggravated the situation, increasing burnout rates while bringing down diagnostics efficiency and accuracy.

Coronavirus, Patient Flow, and Diagnostics Efficiency

The COVID-19 pandemic has placed an immense physical and mental strain on healthcare workers across the globe. One of the earlier studies on the effects of coronavirus on doctors’ mental health showed that physicians treating COVID-19 patients in China suffered from depression, distress, anxiety, and insomnia at a disproportionately high rate.

Since the first days of the pandemic, the response by the governments and the healthcare systems has only mounted, which meant longer working days and higher risk for acquiring COVID-19 for medical personnel. Those, combined with the lack of personal protective equipment (PPE) and testing kits, were the leading factors to cause stress and anxiety, and, respectively, negatively impact the accuracy of diagnostic decision‐making.


To remedy the situation, “flatten the curve” measures, from quarantine to social distancing, were implemented. Eventually, the strategy enabled healthcare services to better manage the same volume of patients while allowing doctors and nurses to rest more at home.

As to the patient flow, healthcare organizations were pushed to implement various diversion mechanisms to better manage capacity. By default, all patients were sent to alternative care sites, to limit the spread of COVID-19 in hospitals.

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Despite all the measures, the pandemic has made the US health care access problems even worse. For instance, while healthcare professionals on the frontline of COVID-19 had to work double shifts, primary care doctors stayed out of work.


Fortunately for both doctors and patients, the solution to a significant portion of healthcare problems, encompassing care access, doctor workloads, diagnostics efficiency, and red tape —  specifically in the dire times of coronavirus — lies in the domain of technology. Artificial intelligence (AI) and machine learning (ML) have all the “tools” to aid humanity in our combat against SARS-CoV-2. Let’s take a look at some of them!

AI to improve patient flow during COVID-19 pandemic

High and efficient patient flow is critical to any healthcare system (specifically in times of crisis). Patients must be served with minimal delay at every stage of care, to increase their chances to rehabilitate without complications, on the one hand, and to drastically reduce the mortality rate for vulnerable populations, on the other. 


In case of the COVID-19 pandemic, it is of vital importance to optimize patient flow. Because the virus is highly contagious but oftentimes develops asymptomatically, care providers must be able to diagnose and triage faster than usual, in a healthy and safe environment. Otherwise, healthy patients can be misdiagnosed (and catch the virus in the care facility) while medical personnel can get infected as well.


To address the challenges the novel coronavirus presents, the team at VITechLab has designed and built several AI-powered COVID-19 solutions:

Medical Detector for Epidemiological Safety

By applying computer vision and image analysis, the solution allows healthcare organizations to ensure both medical staff and patients comply with PPE requirements like wearing face masks, protective gloves, glasses, and coats. It measures a person’s body temperature in real time to report anomalies to epidemiological safety professionals. Since all employees get IDs assigned, violations are addressed quickly and efficiently.

AI platform for Computer-Assisted COVID-19 and Pneumonia Diagnosis

The solution’s machine learning algorithms are trained to accurately detect and diagnose such conditions as pneumothorax, pneumonia (bacterial or viral), and COVID-19 by “looking” at medical images and lung scans. By serving as a doctor’s intelligent assistant, it allows them to assess the risks faster and speed up diagnostics, thus potentially saving more patients through correct treatment.


In combination, the two solutions enable care providers to protect their personnel and patients, and to diagnose much faster through automation.


COVID-19 has become a challenge of the century for the global healthcare systems. Faced with a surge of COVID-19 patients, they had to act reactively to increase capacity and improve patient flow. Already suffering from burnout, doctors and nurses had to buckle up and fight against the pandemic, often without proper PPE and testing kits.


AI and machine learning might be the solution that overstrained healthcare systems need. By offering a wide range of automation and enhanced decision-making use cases, they can shift the burden from humans to machines, to improve safety, increase diagnostics accuracy, and improve patient flow.


One such high-potential solution is the AI platform for Computer-Assisted COVID-19 and Pneumonia Diagnosis. To learn more about the platform, request a demo and experience the new approach to diagnostics.

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