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Dr. Joel Arun Sursas Shares How AI Can Be Used to Help Hospitals Securely Share Data

Originally published on agreensign.com

Health systems and hospitals are often resistant to sharing patient data due to strict legal and privacy protocols. Therefore, it can be difficult for multiple medical providers to obtain an accurate health history for a patient. Artificial intelligence could potentially help bridge this gap using a combination of learning algorithms and centralized servers that store data. AI has the potential to store data from multiple sources securely, therefore maintaining patient privacy and increasing providers’ access to accurate information. Here, Dr. Joel Arun Sursas shares how AI can be used to help hospitals securely share data.

Using AI to Identify Potential Issues

Hospitals can use AI to spot behavioral patterns within the hospital’s infrastructure and applications to flag any abnormal usage [1]. By detecting anomalous or suspicious activity and spotting potential intruders before accessing data, AI prevents patient information from being accessed by hackers and keeps it secure.

Using AI to Process Patients’ Data

AI also makes it easier for doctors and other healthcare professionals to sort through patient data [2]. This is because AI is so good at combing through and identifying patterns even when the numbers are expansive.

With the assistance of AI, doctors can have an easier time getting all of a patient’s medical records even when they come from multiple sources. Instead of doctors having to spend their valuable time sorting through patient data, they can focus on what matters most: their patients’ health and treatment.

The AI will do the searching, and the doctor will do the diagnosing and treating with access to complete medical history. AI will never come in contact with the patient, but rather prepare the doctor to treat the patient more effectively. Since AI sorts through the documents, there are fewer human eyes at play and fewer people accessing the patient data, therefore, keeping it secure.

Using AI to process patient data will also help tremendously to prevent physician burnout. On top of diagnosing and treating patients, many physicians are expected to complete manual tasks such as documenting, taking notes and entering them into the system, entering orders, billing and coding, managing their inboxes. These tasks add up to the point that some physicians spend hours upon hours at their computers instead of treating patients. When all of the functions are done by AI, it frees up the physician to focus on their patients and takes away the menial tasks that can lead to burnout.

Additionally, sharing patient data securely with AI may even help to improve the health of entire communities. AI can provide state and human services departments with critical insights to data that can then be used to improve a population’s health by reducing substance abuse, unemployment, and even homelessness [3].

Using AI to Personalize Treatments

Securely sharing data has the potential to connect hospitals, clinics, government agencies, and community organizations to provide a more accurate and complete picture of a person and their individualized healthcare needs. Analyzing broad data from different sources allows AI to develop potential solutions that would be otherwise impossible to a human. While there are many misconceptions surrounding AI, computerized intelligence is a vital tool for healthcare professionals.

To advance and continue meeting patient needs in an exceedingly digital world, using AI to share and process patient data is crucial. Humans can no longer manage the astronomical amount of data in our healthcare systems, and artificial intelligence is here to help.

With the implementation of AI into our hospitals, we can build a safer and more efficient form of communication to exchange vital medical data. AI has the potential to eliminate many of the errors that human beings naturally make, thus streamlining the passing of data between departments and guaranteeing secure storage of data in compliance with legal and privacy protocols.

About Joel Arun Sursas:

Joel Arun Sursas holds a Bachelor’s Degree in Medicine and Bachelor’s Degree in Surgery from the National University of Singapore and is continuing his education to obtain a Certificate in Safety, Quality, Informatics and Leadership from the Harvard Medical School, and Masters in Applied Health Science Informatics from the Johns Hopkins University (both expected in 2020). His technical skills include SPSS, RevMan, and Python. Dr. Joel Arun Sursas‘ most recent engagement is with a medical device start-up company Biorithm where he serves as Head of Clinical Affairs, working to take fetal surveillance out of the hospital and into the home, revolutionizing the obstetric practice globally.

References

  1.  Cohen, Jessica Kim. “3 Ways Hospitals Can Use AI to Boost Cybersecurity .” Becker’s Hospital Review, www.beckershospitalreview.com/healthcare-information-technology/3-ways-hospitals-can-use-ai-to-boost-cybersecurity.html.
  2. Published on May 5, 2020. “AI in Healthcare: How It’s Changing the Industry.” HIMSS, 14 Aug. 2020, www.himss.org/resources/ai-healthcare-how-its-changing-industry.
  3. EHRIntelligence. “How Can Artificial Intelligence (AI) Improve Clinician EHR Use?” EHRIntelligence, 2 Dec. 2019, ehrintelligence.com/news/how-can-artificial-intelligence-ai-improve-clinician-ehr-use.
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