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Grady Harp, Amazon Hall of Fame Top 100 Reviewer

Grady Harp


5.0 out of 5 stars

A splendid and timely novel

April 20, 2019

Once again Rick Novak serves up a virulent novel that addresses an ongoing change in medicine that worries most of us – the growing dependence on robotics in surgery and the dehumanization of medicine: doctor patient interaction is altered by EMR and IT reporting of visits to insurance companies and the warmth of communication suffers. Rick takes this information to create a story about the extremes of AI in the form of a glowing globe that is Dr Vita and the struggle computer scientist/anesthesiologist Dr Lucas assumes as he tries to save medicine from the extremes of the ‘new age’ called FutureCare. As expected, Rick’s recreation of the tension in the OR and in interaction of the physicians is on target: his own experiences enhance the veracity of the story’s atmosphere.

Rick Novak writes so extremely well that likely has answered the plea of his readers to continue this `hobby’. He is becoming one of the next great American physician authors – think William Carlos Williams, Theodore Isaac Rubin, Oliver Wolf Sacks, Richard Selzer, and also the Brits Oliver Wendell Holmes et al. Medicine and writing can and do mix well in hands as gifted as Rick Novak. Highly Recommended. Grady Harp, April 19

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On June 5, 2019 the Almanac, the home newspaper for the California communities of Menlo Park, Atherton, Portola Valley and Woodside featured a cover story on Rick Novak and his new novel Doctor Vita.

by Angela Swartz / Almanac 

Dr. Rick Novak poses for a portrait at Stanford Hospital in Palo Alto, May 23. Photo by Magali Gauthier/The Almanac

Between his time in the operating room, teaching, and raising his three sons, Atherton resident Dr. Rick Novak has found time to write two novels. 

Novak, 65, an anesthesiologist at the Waverley Surgery Center in Palo Alto, recently published his latest, “Doctor Vita,” a story about an artificial intelligence (AI) physician module that goes awry.

It’s a science fiction novel that explores how technological breakthroughs like artificial intelligence and robots will affect medical care — and already have.

This is the link to the Almanac article.



Doctor Rick Novak’s editorial “Artificial Intelligence in Anesthesia and Perioperative Medicine is Coming” was just published in EC Anaesthesia. I refer you to the direct link here.

Highlights from the paper follow:

Artificial intelligence in medicine (AIM) will grow in importance in the decades to come and will change anesthesia practice, surgical practice, perioperative medicine in clinics, and the interpretation of imaging. AI is already prevalent in our daily life. Smartphones verbally direct us to our destination through mazes of highways and traffic. Self-driving cars are in advanced testing phases. The Amazon Echo brings us Alexa, an AI-powered personal assistant who follows verbal commands in our homes. AIM advances are paralleling these inventions in three clinical arenas:

1. Operating rooms: Anesthesia robots fall into two groups: manual robots and pharmacological robots. Manual robots include the Kepler Intubation System intubating robot, designed to utilized video laryngoscopy and a robotic arm to place an endotracheal tube [1], the use of the DaVinci surgical robot to perform regional anesthetic blockade [2], and the use of the Magellan robot to place peripheral nerve blocks [3,4]. Pharmacological robots include the McSleepy intravenous sedation machine, designed to administer propofol, narcotic, and muscle relaxant [5], and the iControl-RP machine, described in The Washington Postas a closed-loop system intravenous anesthetic delivery system which makes its own decisions regarding the IV administration of remifentanil and propofol [6]. This device monitors the patient’s EEG level of consciousness via a BIS monitor device as well as traditional vital signs [7]. One of the machine’s developers, Mark Ansermino MD stated, “We are convinced the machine can do better than human anesthesiologists.” The current example of surgical robot technology in the operating room is the DaVinci operating robot. This robot is not intended to have an independent existence, but rather enables the surgeon to see inside the body in three dimensions and to perform fine motor procedures at a higher level. The good news for procedural physicians is that it’s unlikely any AIM robot will be able to independently master manual skills such as complex airway management or surgical excision. No device on the horizon can be expected to replace anesthesiologists. Anesthetizing patients requires preoperative assessment of all medical problems from the history, physical examination, and laboratory evaluation; mask ventilation of an unconscious patient; placement of an airway tube; observation of all vital monitors during surgery; removal of the airway tube at the conclusion of most surgeries; and the diagnosis and treatment of any complication during or following the anesthetic.

2. Clinics: In a clinic setting a desired AIM application would be a computer to input information on a patient’s history, physical examination, and laboratory studies, and via deep learning establish a diagnosis with a high percentage of success. IBM’s Watson computer has been programmed with over 600,000 medical evidence reports, 1.5 million patient medical records, and two million pages of text from medical journals [8]. Equipped with more information than any human physician could ever remember, Watson is projected to become a diagnostic machine superior to any doctor. AIM machines can input new patient information into a flowchart, also known as a branching tree. A flowchart will mimic the process a physician carries out when asking a patient a series of increasingly more specific questions. Once each diagnosis is established with a reasonable degree of medical certainty, an already-established algorithm for treatment of that diagnosis can be applied. Because anesthesiology involves preoperative clinic assessment and perioperative medicine, the role of AIM in clinics is relevant to our field.

3. Diagnosis of images: Applications of image analysis in medicine include machine learning for diagnosis in radiology, pathology, and dermatology. The evaluation of digital X-rays, MRIs, or CT scans requires the assessment of arrays of pixels. Future computer programs may be more accurate than human radiologists. The model for machine learning is similar to the process in which a human child learns–a child sees an animal and his parents tell him that animal is a dog. After repeated exposures the child learns what a dog looks like. Early on the child may be fooled into thinking that a wolf is a dog, but with increasing experience the child can discern with almost perfect accuracy what is or is not a dog. Deep learning is a radically different method of programming computers which requires a massive database entry, much like the array of dogs that a child sees in the example above, until a computer can learn the skill of pattern matching [9]. An AIM computer which masters deep learning will probably not give yes or no answers, but rather a percentage likelihood of a diagnosis, i.e. a radiologic image has a greater than a 99% chance of being normal, or a skin lesion has a greater than 99% chance of being a malignant melanoma. In pathology, computerized digital diagnostic skills will be applied to microscopic diagnose. In dermatology, machine learning will be used to diagnosis skin cancers, based on large learned databases of digital photographs. Imaging advances will not directly affect anesthesiologists, but if you’re a physician who makes his or her living by interpreting digital images, you should have real concern about AIM taking your job in the future.

There’s currently a shortage of over seven million physicians, nurses and other health workers worldwide [10]. Can AIM replace physicians? Contemplate the following: All medical knowledge is available on the Internet; most every medical diagnosis and treatment can be written as a decision tree algorithm; voice interaction software is excellent; the physical exam is of less diagnostic importance than scans and lab tests which can be digitalized; and computers are cheaper than the seven-year post-college education required to train a physician. There is a need for cheaper, widespread healthcare, and the concept of an automated physician is no longer the domain of science fiction. Most sources project an AIM robot doctor will likely look like a tablet computer. For certain applications such as clinical diagnosis or new image retrieval, the AIM robot will have a camera, perhaps on a retractable arm so that the camera can approach various aspects of a patient’s anatomy as indicated. Individual patients will need to sign in to the computer software system via retinal scanners, fingerprint scanners, or face recognition programs, so that the computer can retrieve the individual patient’s EHR data from an Internet cloud. It’s possible individual patients will be issued a card, not unlike a debit or credit card, which includes a chip linking them to their EHR data.

It’s inevitable that AIM will change current medical practice. In all likelihood these changes will be more powerful and more wonderful than we can imagine. A bold prediction: AIM will change medicine more than any development since the invention of anesthesia in 1849. How physicians interact with these machines will be a leading question for the twenty-first century.

For the bibliography click here.


Last week Lawton Burns PhD and Mark Pauly PhD of the Wharton School of Business at the University of Pennsylvania published a landmark economic article entitled, “Detecting BS in Health Care.” Yes, you did not read that wrong—the academic paper used the abbreviation “BS” to describe the bull—- in the healthcare industry.

BS in Health Care


As a practicing physician, I find it to be a fascinating paper, and I recommend you click on the link and read it. The authors begin with a discussion of the art and value of BS detection. They mention that Ernest Hemingway was once asked, “Is there one quality needed to be a good writer, above all others?”

Hemingway replied, “Yes, a built-in, shock-proof, crap detector.”

The authors write, “While flat-out dishonesty for short term financial gains is an obvious answer, a more common explanation is the need to say something positive when there is nothing positive to say. . . . The incentives to generate BS are not likely to diminish—if anything, rising spending and stagnant health outcomes strengthen them—so it is all the more important to have an accurate and fast way to detect and deter BS in health care.”

The authors list their Top 10 Forms of BS in Health Care. The first four forms of BS weave a common theme:

  1. Top-down solutions: High-level executives and top management in the health care industry are supposed to engineer alternative payment models, but nothing has worked to date.
  2. One-size-fits-all, off-the-shelf: Leadership of industry and government assume one solution will work for multiple organizations, without customization.
  3. Silver-bullet prescriptions: A “silver bullet” is described as something that will cure all ills, and must be implemented because it been “decided that it is good for you,” Electronic health records (EHRs) are a prime example of a silver-bullet prescription. The federal government pushed the use of EHRs, claiming the systems would reduce costs and improve quality—but Burns and Pauly argue EHRs “eventually raised costs and only mildly touched a few quality dimensions.”
  4. Follow the guru: We must follow a visionary guru with a mystical revelation about what needs to be done. The authors describe how, in health care, Harvard professor Michael Porter and former CMS (Center of Medicare and Medicaid) administrator Don Berwick launched theories based on population health, and per-capita cost, to little success.

The current U.S. healthcare market is dominated by large corporations, led by businessmen who outline a yellow brick road for physicians to lead patients along. There is minimal effective policy-making from physicians. Healthcare stocks consistently grow in value, with little relationship to an improvement in clinical care, value, or cost. The government is involved as well, as in their mandate for Electronic Health Records (EHRs), a technology change that cost a lot of money, while forging a barrier between clinicians and the patients we are trying to interview, examine, and care for.

Where will the current trends take us? Will businessmen and/or the government prescribe health care? Will more and more computers and machines dominate health care?

Self-driving cars, Siri, Alexa, automated checkouts at Safeway, and IBM’s Watson are technologic realities. Will we someday see a self-driving physician with the voice of Siri and the brains of Watson?

Call that device “Doctor Vita.”

The saga of Doctor Vita, by Rick Novak, arrives in 2019 from All Things That Matter Press.