All Boxes Are Black.

February 2016 • Volume 122 • Number 2 www.anesthesia-analgesia.org 309 Copyright © 2016 International Anesthesia Research Society DOI: 10.1213/ANE.0000000000001122 This issue of Anesthesia & Analgesia features an article by Barker et al.1 discussing the potential of noninvasive hemoglobin measurement derived from the pulse oximeter waveform analysis. In an unusual accompanying editorial, Shelley and Barker2 debate the importance of “disclosures” for the understanding of medical technologies. Barker et al.1 have a potential stake in the technology they describe. The discussion between Shelley and Barker2 highlights the importance of an open and straightforward conversation among the academic, clinical, and industrial communities about conflict of interest. Novel technologies have played a major role in the maturation of anesthesiology as a safe medical specialty. Novel technologies keep our patient safe throughout the perioperative encounter. Novel technologies will help propel anesthesiology to the next level of patient-centric care and patient safety. Anesthesiologists are extensively trained on physiology, pharmacology, anatomy, and other fields of medicine. However, very few anesthesiologists have the knowledge and expertise necessary to understand the signal-processing requirements for even the most basic technologies we use on a daily basis. Our clinical care is anchored in the data provided by our monitoring instruments. We depend on these devices to keep our patients alive. We should at least have a superficial understanding of how basic technologies work. However, very few of us could explain how an automated blood pressure cuff determines systolic, diastolic, and mean blood pressure. The result is the “black box effect.” This applies to our existing technologies and to new technologies being introduced into the clinical care. Few clinicians have the expertise in signal processing to know whether the algorithm that converts physiologic signals to clinically interpretable numbers is good or bad. Not understanding the signal-processing algorithms, we may disparage using “black boxes” to support clinical decisions. In his debate with Barker, Shelley says “I personally will not allow ‘black boxes’ into my operating rooms.”2 We are concerned that Dr. Shelley will be standing in the operating room (OR) with his stethoscope and little else. All boxes are black. Every monitor we use involves digital signal-processing algorithms that are black boxes. This is not only true for our monitors but also for our computercontrolled anesthesia machines, ventilators, and infusion pumps. It is also true for the imaging advances we use in the OR: ultrasound for block and line placement, transesophageal echocardiography for cardiac monitoring, 3-dimensional echo imaging, and, of course, the amazing magnetic resonance imaging–guided 3-dimensional images that gracefully rotate on huge liquid crystal display screens while the surgeons operate. These are all black boxes, whose algorithms may (or may not) be understood by the mathematicians, engineers, and scientists who created them. Is it reasonable to believe that anesthesiologists should understand the algorithms before using the device? If not, then why should companies disclose the algorithms they invented, which give them a competitive advantage? We agree with Dr. Shelley that publication of algorithms is a worthy goal. All things being equal, more information is better than less information. In addition, for the academician developing novel algorithms, disclosure is not only worthy but also essential to advance the science. However, as Dr. Barker noted in his reply: “Protecting ‘intellectual property’ is something that all private companies must do to survive in a free enterprise world.”2 He is right. Molecules are easy to patent. A novel drug is protected by a patent called “composition of matter” that provides very strong protection of intellectual property. A novel device often does not have such strong protection. Indeed, it is so easy to copy software, and so difficult to prove infringement, that insistence on publishing algorithms might do more harm than good. Companies developing medical technologies invest millions of dollars to bring them to the bedside. The intellectual property must be protected to make the system sustainable for the long run. We pose this question to the readership of Anesthesia & Analgesia: Do you want to see next-generation ventilators, pulse oximeters, ultrasound machines, real-time ST analysis, processed electroencephalograms, infusion pumps, or anesthesia information management systems? If you do, then don’t require that the algorithms be disclosed. If you remove the economic incentive for innovation, there will be none. The US Constitution provides the basis for a patent system in which the federal government enforces a time-limited All Boxes Are Black

[1]  James C. Scott,et al.  Electroencephalographic quantitation of opioid effect: comparative pharmacodynamics of fentanyl and sufentanil. , 1991, Anesthesiology.

[2]  Michael Bührer,et al.  Electroencephalographic effects of benzodiazepines. I. Choosing an electroencephalographic parameter to measure the effect of midazolam on the central nervous system , 1990, Clinical pharmacology and therapeutics.

[3]  S. Barker,et al.  Continuous Noninvasive Hemoglobin Monitoring: A Measured Response to a Critical Review , 2015, Anesthesia and analgesia.

[4]  S L Shafer,et al.  The influence of age on propofol pharmacodynamics. , 1999, Anesthesiology.

[5]  H. Hotelling Relations Between Two Sets of Variates , 1936 .

[6]  D R Stanski,et al.  EEG quantitation of narcotic effect: the comparative pharmacodynamics of fentanyl and alfentanil. , 1985, Anesthesiology.

[7]  Kirk H. Shelley,et al.  Disclosures, What Is Necessary and Sufficient? , 2016, Anesthesia and analgesia.

[8]  S. Shafer,et al.  Validation of the Alfentanil Canonical Univariate Parameter as a Measure of Opioid Effect on the Electroencephalogram , 1995, Anesthesiology.

[9]  Dr Frank E. Block Jr,et al.  Minimizing interference and false alarms from electrocautery in the Nellcor N-100 pulse oximeter , 2005, Journal of clinical monitoring.

[10]  S L Shafer,et al.  Thiopental pharmacodynamics. I. Defining the pseudo-steady-state serum concentration-EEG effect relationship. , 1992, Anesthesiology.

[11]  S. Shafer,et al.  Application of semilinear canonical correlation to the measurement of opioid drug effect , 1992, Journal of Pharmacokinetics and Biopharmaceutics.

[12]  D. Stanski,et al.  Chronic alcohol intake does not change thiopental anesthetic requirement, pharmacokinetics, or pharmacodynamics. , 1990, Anesthesiology.

[13]  F E Block,et al.  Minimizing interference and false alarms from electrocautery in the Nellcor N-100 pulse oximeter , 1986, Journal of clinical monitoring.

[14]  D R Stanski,et al.  Increased Sensitivity to Etomidate in the Elderly: Initial Distribution versus Altered Brain Response , 1986, Anesthesiology.

[15]  William H. Press,et al.  Numerical recipes in C , 2002 .

[16]  Beverley A. Orser,et al.  Depth-of-anesthesia monitor and the frequency of intraoperative awareness. , 2008, The New England journal of medicine.

[17]  D R Stanski,et al.  Decreased fentanyl and alfentanil dose requirements with age. A simultaneous pharmacokinetic and pharmacodynamic evaluation. , 1987, The Journal of pharmacology and experimental therapeutics.

[18]  S. Shafer,et al.  Semilinear Canonical Correlation Applied to the Measurement of the Electroencephalographic Effects of Midazolam and Flumazenil Reversal , 1996, Anesthesiology.