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She was angry about her company's decision to move back to old school sales tactics.

Artificial Intelligence in the workplace

Chatbots, virtual assistants and predictive texting chafe at the surface of how artificial intelligence is transforming companies of all sizes.

AI’s potential to revolutionize different industries prompted Julie Crocker, a partner who sits on both Taft’s Executive Committee and Artificial Intelligence Committee, to parlay her firm’s AI foray into advising clients on how they can use AI to improve efficiency within their business.

Your navigation app takes this a step further when you get in your car on Saturday morning and receive an alert that it will take 11 minutes to drive to your favorite coffee shop.

This, in turn, permits attorneys to spend more time focused on other tasks, such as client communications and legal strategies, instead of searching and reading through hundreds of documents to find an answer.

One of the significant advantages of AI programs is the ability to filter through vast amounts of information in a short amount of time and to provide the results of that computation in summary format.

For example, an employer monitoring email activity with an AI program may receive a notice that a particular employee’s personal email usage has increased exponentially, but the AI monitoring program may not pick up that the employee is using their work computer while on vacation or a leave of absence.

Legal search programs can easily tell you what the time period is for bringing a particular claim, but those programs may not pick up on exceptions to the law that would permit a party to bring a claim outside a limitations period.

AI programs are good at document review and data extraction, but regardless of the type of AI program being used, it is important to analyze the extracted data carefully and to consider the reasons for the resulting information.

Organizations of all sizes already face a number of challenges in managing the security of their data, such as personally identifiable information, trade secrets and intellectual property.

And although smaller companies may think that an AI strategy is not feasible due to size and cost constraints, AI can benefit companies over time by improving efficiency and reducing unnecessary expenses.

Outlining How Artificial Intelligence May Help Adhere to Cardiac Care Guidelines

The consistent provision of guideline-directed medical therapy (GDMT) — care delivered according to established guidelines and safety standards — is crucial for every healthcare encounter, especially when treating patients with chronic disease.

Another study published in the Journal of the American Medical Association (JAMA) confirmed that rates of recommended medical treatments were low and remained essentially unchanged from 2002 to 2013, despite relatively high rates providing recommended diagnostic and preventative care over the same time period.[3]   

A study in the March 2017 issue of JAMA found that among nearly 95,000 patients with a known history of atrial fibrillation (AF) who had an acute ischemic stroke, an astonishing 83 percent “were not receiving therapeutic anticoagulation prior to stroke.”[4]  This was not a case of patient non-adherence, but rather of physicians never having prescribed the medication or failing to adjust drug dosages for individual patients.

Consider the avoidable suffering and savings resulting from pre-empting these strokes, had the patients received optimal therapeutic interventions.  More recently, a study in the July 2018 issue of the Journal of the American College of Cardiology (JACC) explored the use of GDMT in patients with heart failure with reduced ejection fraction (HFrEF), one of the leading causes of admission/readmission in Medicare.

While nothing that “guidelines strongly recommend patients with HFrEF be treated with multiple medications proven to improve clinical outcomes,” the study revealed that this was not occurring in real-world settings.[5] “Among eligible patients, 27%, 33%, and 67% were not prescribed ACEI/ARB/ARNI, beta-blocker, and MRA therapy, respectively,” the study authors wrote.

“When medications were prescribed, few patients were receiving target doses of ACEI/ARB (17%), ARNI (14%), and beta-blocker (28%) … Among patients eligible for all classes of medication, 1% were simultaneously receiving target doses of ACE/ARB/ARNI, beta-blocker, and MRA.” The study authors concluded, “Strategies to improve guideline-directed use of HFrEF medications remain urgently needed.”   

Every patient is now a “big data” challenge, with vast amounts of information on past trajectories and current states…” The authors observe “the complexity of medicine now exceeds the capacity of the human mind.” However, technological advances will provide the solution the authors wrote.  “But there is hope,” they wrote.

something that until relatively recently was the domain of humans alone,” according to a report from technology consulting firm Infosys released in January 2018, titled “Leadership in the Age of AI.”[7]  Of 1,000 business and IT decision makers surveyed for the Infosys report, 51 percent of those in the healthcare industry said their organizations are already experiencing disruption due to AI, while 71 percent of those in the healthcare industry “strongly or somewhat agreed” that their future business plans will be informed and transformed by the development of AI technology.

An example of how AI can work to deliver immediate access to guides is the HealthReveal software, It creates a “digital replica” of each patient, incorporating data from electronic health records, payers and even patient-generated health data (PGHD) from remote monitoring technology (devices that are wearable or implantable, or can be used in the home), such as blood pressure readings and blood sugar tests.

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