title: Using a hybrid electronic medical record system for the surveillance of adverse surgical events and human error in a developing world surgical service.
abstract: BACKGROUND
  The quantification and analysis of adverse events is essential to benchmark surgical outcomes and establish a foundation for quality improvement interventions. We developed a hybrid electronic medical record (HEMR) system for the accurate collection and integration of data into a structured morbidity and mortality (M&M) meeting.
  
  
  METHODS
  The HEMR system was implemented on January 1, 2013. It included a mechanism to capture and classify adverse events using the ICD-10 coding system. This was achieved by both prospective reporting by clients and by retrospective sentinel-event-trawling performed by administrators.
  
  
  RESULTS
  From January 1, 2013 to March 20, 2014, 6,217 patients were admitted within the tertiary surgical service of Greys Hospital. A total of 1,314 (21.1 %) adverse events and 315 (5.1 %) deaths were recorded. The adverse events were divided into 875 "pathology-related" morbidities and 439 "error-related" morbidities. Pathology-related morbidities included 725 systemic complications and 150 operative complications. Error-related morbidities included 257 cognitive errors, 158 (2.5 %) iatrogenic injuries, and 24 (1.3 %) missed injuries. Error accounted for 439 (33 %) of the total number of adverse events. A total of 938 (71.4 %) adverse events were captured prospectively, whereas the remaining 376 (28.6 %) were captured retrospectively. The ICD-10 coding system was found to have some limitations in its classification of adverse events.
  
  
  CONCLUSIONS
  The HEMR system has provided the necessary platform within our service to benchmark the incidence of adverse events. The use of the international ICD-10 coding system has identified some limitations in its ability to classify and categorise adverse events in surgery.
authors.affiliation: Surgery, UKZN, Durban, South Africa, grantlaing@me.com.
authors.forename: Grant
authors.initials: G
authors.lastname: Laing
authors.forename: John
authors.initials: J
authors.lastname: Bruce
authors.forename: David
authors.initials: D
authors.lastname: Skinner
authors.forename: Nikki
authors.initials: N
authors.lastname: Allorto
authors.forename: Colleen
authors.initials: C
authors.lastname: Aldous
authors.forename: Sandie
authors.initials: S
authors.lastname: Thomson
authors.forename: Damian
authors.initials: D
authors.lastname: Clarke
mesh_terms: D003199:Computer Systems; D003906:Developing Countries; D057286:Electronic Health Records / Q000458:organization & administration*; D006801:Humans; D015994:Incidence; D019300:Medical Errors / Q000706:statistics & numerical data*; D011446:Prospective Studies; D012189:Retrospective Studies; D013019:South Africa; D013514:Surgical Procedures, Operative / Q000009:adverse effects*