Emergency general surgery verification: Quality improvement and the case for optimal resources and process standards

J Trauma Acute Care Surg. 2024 Jan 1;96(1):e1-e4. doi: 10.1097/TA.0000000000004135. Epub 2023 Sep 6.

Abstract

Patients with emergency general surgery (EGS) diagnoses comprise over 10% of all hospital admissions, resulting in a projected number of 4.2 million admissions for 2023. Approximately 25% will require emergency surgical intervention, half will sustain a postoperative complication, and 15% will have a readmission within the first 30 days of surgery. In the face of this growing public health burden and to better meet the needs of these acutely ill patients, it was recognized that a formal quality improvement program, including standardization of data collection and the development of systems of care specifically for EGS have been lacking. Establishing standardized processes for quality improvement, including a national databank, and maintaining adherence to these processes as ensured by a robust verification process has improved outcomes research and patient care in the field of trauma, another time-sensitive specialty. In response to this perceived deficit, the "Optimal Resources for Emergency General Surgery" was developed. An extension of the current National Surgical Quality Improvement Program platform, specifically for operative and non-operative EGS cases, was developed and implemented. A robust set of standards were outlined to verify EGS programs/services. Defining the elements of an effective EGS program and developing hospital and practice standards consolidated EGS as an integral component of Acute Care Surgery. The verification program addresses a societal need and allows hospitals to better organize EGS care delivery and benchmark their results nationally.

MeSH terms

  • Acute Care Surgery
  • Emergencies
  • General Surgery*
  • Hospitals
  • Humans
  • Postoperative Complications
  • Quality Improvement
  • Registries
  • Retrospective Studies
  • Surgical Procedures, Operative*