Picking the right surgeon: Quantitative approach
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Abstract
There is an abundance of useful verbal information and recommendations on how to make the best choice when referring a patient for surgery or when seeking the right surgeon for your own operation. A quantitative approach is suggested here on how this could be done through assessing the probability of success and/or the Mean-Time-To-Failure (MTTF) of the planned operation by considering and comparing the skills of two highly qualified candidates. Then the chooser could continue this effort by comparing the background and the probability of success of the best one of these two candidates with the next suitable candidate, and then go on with the process for as many candidates as he/she would like to evaluate. The approach suggests using the double-exponential highly flexible and highly physically meaningful probability Distribution Function (DEPDF) as a suitable model. This function was introduced about a decade ago in the reliability physics to quantify, on the probabilistic basis, the outcome of a particular engineering, ergonomics or medical undertaking of importance. The surgeon’s qualifications are identified in our approach as Human Capacity Factor (HCF). Figures of Merit (FoM) of this factor consider many relevant human qualities, as well as the durations and the outcomes of the surgeon’s previous, both successful and failed, operations. The mental (cognitive) workload (MWL) reflects the complexity of the operation and, in the present analysis, is assumed to be the same for the two surgeon’s considered. The role of an anesthesiologist is not taken into account directly in our approach: it is the surgeon who decides on his/hers partner, and the surgeon’s choice is viewed as part of his/hers HCF. The general concepts are illustrated by a numerical example.
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Marsa L (2017) Act As If Your Choice Is Life or Death - Because It Often Is. AARP Bulletin.
Karpecki PM (2020) How to Pick the Right Surgeon. Review of Optometry.
Suhir E (2010) Probabilistic Modeling of the Role of the Human Factor in the Helicopter-Landing-Ship (HLS) Situation. Int J Human Factor Modeling Simulation 1. Link: https://bit.ly/3qfGOR1
Suhir E (2012) Miracle-on-the-Hudson: Quantified Aftermath. Int J Human Factor Modeling Simulation 4.
Suhir E (2012) Human in the Loop: Predicted Likelihood of Vehicular Mission Success and Safety. J Aircraft 49. Link: https://bit.ly/3Ja8Q90
Suhir E (2014) Human-in-the-Loop: Probabilistic Predictive Modeling, Its Role, Attributes, Challenges and Applications. Theor Issues Ergon Sci 16: 99-123. Link: https://bit.ly/30Ld9q4
Suhir E (2015) Analytical Modeling Enables Explaining Paradoxical Situations in the Behavior and Performance of Electronic Materials and Products: Review. J Physical Mathematics 07.
Suhir E (2017) Human-in-the-Loop: Application of the Double Exponential Probability Distribution Function Enables Quantifying the Role of the Human Factor. Int J Human Factor Modeling Simulation 5: 354-377. Link: https://bit.ly/3eagHFt
Suhir E (2019) Human-in-the-Loop: Probabilistic Modeling of an Aerospace Mission Outcome. CRC Press.
Suhir E (2020) Quantifying Unquantifiable: the Outcome of a Clinical Case Must Be Quantified to Make it Successful. Glob J Medical Clin Case Rep 7: 123-129. Link: https://bit.ly/3ecMTYT
Suhir E (2019) Mental Workload (MWL) vs. Human Capacity Factor (HCF): A Way to Quantify Human Performance: Gregory and Inna Bedny eds., Applied and Systemic-Structural Activity Theory, CRC Press.
Suhir E (2019) Adequate Trust, Human-Capacity-Factor, Probability-Distribution-Function of Human Non-Failure and its Entropy. Int J Human Factor Modeling Simulation 7: 75-83. Link: https://bit.ly/3J6ssuW
Suhir E (2019) Assessment of the Required Human Capacity Factor (HCF) Using Flight Simulator as an Appropriate Accelerated Test Vehicle. Int Journal Human Factor Modeling Simulation (IJHFMS) 7: 71-74. Link: https://bit.ly/3poGeRX
Suhir E (2020) Quantifying Unquantifiable: the Outcome of a Clinical Case Must Be Quantified to Make it Successful. Glob J Medical Clin Case Rep 7: 123-129. Link: https://bit.ly/3mmjgsu
Suhir E (2020) Risk-Analysis in Aerospace Human-Factor-Related Tasks: Review and Extension. J Aerosp Eng Mech 4: 265-272. Link: https://bit.ly/3J8cWhV
Suhir E (2020) Aerospace Electronics Reliability Must Be Quantified to Be Assured: Application of the Probabilistic Design for Reliability Concept. Int J Aeronautics Aerospace Res 7: 235-243. Link: https://bit.ly/3qedGtx
Suhir E (2020) Quanifying Unquantifyable in Aerospace Electronics and Ergonomics Engineering: Review. J Aerosp Eng Mech 4: 306-347. Link: https://bit.ly/3FgIJuX
Suhir E (2020) Astronaut's Performance vs. His/Hers Human-Capacity-Factor and State-of-Health: Application of Double-Exponential-Probability-Distribution Function. Acta Astronaut 178.
Suhir E, Paul G (2021) Probabilistic HSI Models. International Ergonomics Associate Triennial (IEA) Conf., Vancouver, CA, Track on Transport Ergonomics and Human Factor.
Suhir E (2021) Driver Propensity to Fatigue and Drowsiness: A Probabilistic Approach. Theor Issues Ergon Sci. Link: https://bit.ly/328tBBG
Suhir E (2021) Medical Undertakings Should Be Quantified to Have A Potential to Be Improved. J Electron Sensors 4: 1-12. Link: https://bit.ly/327ZNoN
Laider KJ (1987) Chemical Kinetics, Third Edition, Harper & Row 42. Link: https://bit.ly/3qj7OPL