Risk Management: Gaining Control of Medical Malpractice Litigation

Authors

  • Howard N. Smith -

DOI:

https://doi.org/10.47672/ajsas.1431
Abstract views: 156
PDF downloads: 142

Keywords:

Risk Management, ACE V, CCC C, Medical Malpractice, Lawsuit, Intervention

Abstract

The purpose of risk management is to anticipate a crisis and prepare an actionable strategy, which accurately predicts the most successful outcome for the crisis. For doctors, a malpractice lawsuit is a crisis. It is always foreshadowed by a complication from a medical intervention. The complication can result from a medical error. However, it, also, can result from an error-of-nature. CCC+C is a risk management tool that is data driven and uses the scientific method to define, measure, analyze, improve, and control processes so that a medical error can be distinguished from an error-of-nature with 95% confidence. An error-of-nature is not preventable but a resulting frivolous lawsuit can be dismissed. Likewise, a medical error is preventable and a resulting meritorious lawsuit can be settled. Both outcomes depend on damage control. CCC+C is the damage control tool. When used by doctors as soon as a complication occurs, it manages all other obstacles presenting upstream from actuaries in medical malpractice insurance companies, plaintiff attorneys, defense attorneys and medical experts.  In court, CCC+C is a forensic science designed to work in the same way as ACE+V, which is a forensic science that identifies fingerprints. Lastly, because CCC+C is transparent, it exposes unscrupulous tactics by any party on either side of litigation. It accurately predicts outcomes and controls litigation because it effectively protects from, defends against and prevents unscrupulous tactics. Therefore, CCC+C is a game changer in the arena of medical malpractice litigation.

 

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Author Biography

Howard N. Smith, -

 

 

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Published

2023-04-24

How to Cite

Smith, H. . (2023). Risk Management: Gaining Control of Medical Malpractice Litigation. American Journal of Statistics and Actuarial Sciences, 4(2), 1 - 17. https://doi.org/10.47672/ajsas.1431

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