See the Positive Impact Artificial Intelligence Has on Healthcare

See the Positive Impact Artificial Intelligence Has on Healthcare

IBM Watson pioneers the technology that can improve patient outcomes, healthcare efficiency, and costs.

Artificial intelligence — specifically IBM Watson — has demonstrated that it can help improve patient outcomes and efficiency in healthcare, while also reducing healthcare costs. The effects already have been demonstrated in oncology, imaging, and drug research and development.

Powerful Computing Integrates Disparate Information

IBM Watson consists of 90 servers and 15 terabytes of memory, and can process millions of documents and read 800 million pages per second. (Rose 2017; Shacklett 2017) All this computing power allows them to analyze and organize unstructured data to help people make healthcare decisions.
IBM Watson has the ability to integrate with a large healthcare system’s electronic health record (EHR) such as EPIC. This can improve the interpretation of radiology imaging, as well as enhance patient outcomes in oncology. Their technology can also improve the speed of research and development of pharmaceuticals used to treat patients.
IBM Watson creates a strong clinical decision support system to improve diagnostic accuracy and treatment efficacy, which leads to better outcomes for the patients. Providers can access the information at their fingertips in less time than it would take them to leave the patient in the exam room and look up information. The information retrieved by the provider may have multiple options or treatment choices. Based on the provider’s training and experience, they can choose the best option or treatment for the patient’s condition or symptoms. (Yuan 2011)


IBM Watson has assisted with treatment options/suggestions for more than 30,000 cancer patients at Memorial Sloan Kettering Cancer Center (2014). Initially, breast cancer and lung cancer were the main targets, but many other types of cancer are targeted.
IBM Watson can match a patient’s medical record with those of cancer patients who are treated with the same disease(s). Each time a patient is treated, IBM Watson “learns” by collecting data about different diseases and different treatments used for each patient. The database of information includes published literature, scientific journals, and medical meetings, according to Memorial Sloan Kettering Cancer Center (2014). The data processing produces treatment options/suggestions for the patient in a clinical format that providers can use. Oncologists can treat patients much quicker and with more precision based on the data given to them by IBM Watson.


IBM Watson’s artificial intelligence has had a positive impact in radiology/imaging, as well. For example, 30 radiologists from Strategic Radiology’s 26 member practices played an integral part in training IBM Watson in radiology. (Imaging Technology News, 2017) IBM Watson uses two different tools to help enhance radiology imaging reading and interpretation.
The Imaging Clinical Review tool looks at diagnoses and current problems the patient has and updates the patient problem list. (Artificial Intelligence Medical Imaging Solutions, Watson Health Imaging, 2018) This capability can minimize unnecessary repeat testing.
The Patient Synopsis tool gathers a patient’s information from their medical record and displays a summary on the computer. This tool works with the picture archiving communication system. Using these tools together helps radiologists diagnose more accurately. The reports generated are more customized and succinct, which enhances radiologists’ decision-making about further testing (or whatever the next step is for that patient). Clinicians may detect diseases much earlier with this technology. (IBM Watson Imaging Patient Synopsis, AI Medical Imaging Solutions, 2018)
According to Kim Thomas’ report in 2017, IBM Watson may reduce radiology errors, including missing fractures and missed lung cancers. This would also result in decreased lawsuits related to these errors in radiology.

Clinical Trials

The Mayo Clinic is conducting a study using IBM Watson technology to improve patient selection in clinic trials. Traditionally, a patient is matched to a clinical trial by way of clinical trial coordinators. The Mayo Clinic has more than 8,000 (Nellis, 2014) clinical trials, which makes this task cumbersome. IBM Watson’s ability to scan information quickly provides an efficient process for determining if a patient is suitable for a clinical trial and, if so, which one. Clinical trial coordinators can concentrate on other things because the process of finding candidates is less cumbersome with IBM Watson. (IBM, 2018, Clinical Trial Matching)
A less cumbersome candidate process will increase enrollment in clinical trials, as well as significantly reduce the time it takes to initiate and stop a clinical trial. This leads to more complete investigations” (Nellis, 2014), as well as increased chances of discovering new treatments for patients.
IBM Watson also helps a provider know which therapy may be better for that patient’s specific cancer diagnosis. The technology analyzes the patient’s progress notes, including test results. Then, it scans numerous medical journals, text books, and other literature related to oncology to suggest evidence-based treatment options appropriate for that patient. This enables the provider to determine the course of treatment that will produce the best outcome for the patient.

Drug Research and Development

IBM Watson’s technology can also help with drug research and development. According to Center Watch Online News, it can take up to 20 years and $2.5 billion to develop a new drug, and IBM Watson potentially can make the process more cost effective by saving time. According to their Drug Discovery – Overview webpage, through the use of predictive analytics, new drugs and indications are created more efficiently than using traditional methods. For example, with more precise calculations, more drugs that block the growth of cancer cells are created. (IBM 2018, Drug Discovery) This makes state-of-the-art cancer treatment more readily available and accessible to patients.
One pharmaceutical company that intends to excel in drug research and development using IBM Watson is Pfizer. Their focus is on “immuno-oncology” drugs for cancer patients. (IBM 2016) By using IBM Watson’s collection of information, Pfizer would be able to produce and test medications more rapidly, which can change how a patient’s immune system responds to cancer treatment.
For more information on how artificial intelligence can become your friend, read the article “Medical Coding, Meet Artificial Intelligence” in the March issue of Healthcare Business Monthly (pages 51-53) or on AAPC’s Knowledge Center.

Center Watch. Oct. 31, 2016. Teva Pharmaceuticals, IBM expand drug development with Watson.
Gruessner, V. May 5, 2015. IBM’s Watson Extracts EHR Patient Data to Improve Care.
IBM. Dec. 1, 2016. IBM & Pfizer Collaborate to Uncover New Cancer Treatments.
IBM. May 30, 2017. Product Vignette: IBM Watson for Oncology.
IBM. 2018. IBM Watson Stories.
IBM Watson Health, Artificial Intelligence Medical Imaging Solutions, Watson Health Imaging. 2018.
IBM. 2018. IBM Watson for Clinical Trial Matching – Overview – United States.
IBM. 2018. IBM Watson for Drug Discovery – Overview.
IBM Watson Imaging Patient Synopsis, AI Medical Imaging Solutions. 2018.
Imaging Technology News. Oct. 2, 2017. Strategic Radiology to Contribute to IBM Watson’s Education.
Nellis, B. Sept. 9, 2014. Mayo Clinic and IBM Task Watson to Improve Clinical Trial Research.
Rose, C. June 26, 2017. CBS News’ 60 Minutes, Artificial intelligence positioned to be a game-changer.
Shacklett, M. July 28, 2017. IBM Watson. The smart person’s guide.
Memorial Sloan Kettering Cancer Center. April 11, 2014. Memorial Sloan Kettering Trains IBM Watson to Help Doctors Make Better Cancer Treatment Choices.
Thomas, K. April 21, 2017. Digital Health, How will artificial intelligence change radiology?
Yuan, M. April 12, 2011. Watson and healthcare.

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