Emergency General Surgery: Let’s Get It Right from the Beginning!

This article refers to:

Factors Contributing to Extended Hospital Length of Stay in Emergency General Surgery†

The overall aim of the paper “Factors Contributing to Extended Hospital Length of Stay in Emergency General Surgery” is to determine factors that are independently associated in the preoperative setting with increased length of stay (LOS) in four of the most common procedures in Emergency General Surgery (EGS) using the NSQIP database [1]. Through their work, the authors have identified five variables significantly associated with an increased LOS, which included old age (61+), hypertension, sepsis, cancer and Black race. This work brings up several important issues, in addition to identifying factors that can play a role in risk stratification of these challenging patients.

The right tools for the right job…

This paper is another example of the value of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, which is a voluntary, nationwide database in the US collecting more than 135 pre-, intra- and post-operative data variables from numerous hospitals and health care centers [2]. The ACS-NSQIP and other similar databases will be called upon to play a critical role in any future health care planning, especially since we are entering the age of “Big Data” and Artificial Intelligence (AI). Decisions having to do with health care planning or patient care in the current technological era will ideally be based on the combination of evaluating very large amount of data by machine algorithms that are able to process them and identify patterns. The combination of “Big Data” and AI has already led to significant applications, such as the Johns Hopkins Judy Reitz Capacity Command Center, which is the result of a combination of advanced systems engineering and predictive analytics, in order to achieve an improved patient flow through all the aspects of the hospital, including wards, intensive care unit and the operating room [3]. The result is thus improving the overall patient experience, as well as the financial aspect of patient care. However, before becoming too enthusiastic about the combined use of large databases and AI, we need to consider the significant potential limitations. Specifically, the source and quality of the data is critical as “any recipe is only as good as the ingredients that you use”. Even in a quality database, such as NSQIP, there are still the issues of missing values from different variables, coding errors and, of course, the effect of self-reporting. Additionally, we have to consider issues such as data protection and safeguarding, legal implications and the importance (or not) of the human element and human judgment.

The birth of a new specialty

Once we have the right tools to collect and evaluate the data needed, the next question is how and where we are going to use it. Emergency General Surgery represents an excellent opportunity as, although it is not necessarily a new concept, the last decade has seen the evolution of this new specialty as a way to respond to the changes in Trauma Surgery, the need for better and more efficient coverage of the emergency surgical cases in a hospital in such a manner that it would not affect the regular flow of those surgeries already on the operating room schedule [4]. It is very important to understand the EGS does not simply refer to those surgeons who will be covering the Emergency Room during the night or dealing with those emergency cases that are not the most “popular”; it is rather a specialty which should combine General Surgery, Trauma Surgery and Critical Care. The reason is that the surgeons involved will be responsible for life-threatening conditions for the most part, which, from the hospital administration perspective, is also synonymous to higher cost. These points make it absolutely necessary to collect the necessary data to better evaluate the challenges and opportunities presented by EGS.

Overall, this paper has managed to raise several key issues and add to the discussion of what is the best way to shape Emergency General Surgery and help it evolve. The challenges that were mentioned in the early part of this commentary should not discourage us from the use of large databases, but they should serve as a warning that if we are to get things right, then we need to become surgeons that also have a knowledge of collecting and evaluating data, and (why not?) even an understanding of what AI is really about and how it can help us and, most importantly, our patients.