Identifying Predictive Factors for Incident Reports in Patients Receiving Radiation Therapy

Publication date: 1 April 2016
Source:International Journal of Radiation Oncology*Biology*Physics, Volume 94, Issue 5
Author(s): Shereef M. Elnahal, Amanda Blackford, Koren Smith, Annette N. Souranis, Valerie Briner, Todd R. McNutt, Theodore L. DeWeese, Jean L. Wright, Stephanie A. Terezakis
PurposeTo describe radiation therapy cases during which voluntary incident reporting occurred; and identify patient- or treatment-specific factors that place patients at higher risk for incidents.Methods and MaterialsWe used our institution's incident learning system to build a database of patients with incident reports filed between January 2011 and December 2013. Patient- and treatment-specific data were reviewed for all patients with reported incidents, which were classified by step in the process and root cause. A control group of patients without events was generated for comparison. Summary statistics, likelihood ratios, and mixed-effect logistic regression models were used for group comparisons.ResultsThe incident and control groups comprised 794 and 499 patients, respectively. Common root causes included documentation errors (26.5%), communication (22.5%), technical treatment planning (37.5%), and technical treatment delivery (13.5%). Incidents were more frequently reported in minors (age <18 years) than in adult patients (37.7% vs 0.4%, P<.001). Patients with head and neck (16% vs 8%, P<.001) and breast (20% vs 15%, P=.03) primaries more frequently had incidents, whereas brain (18% vs 24%, P=.008) primaries were less frequent. Larger tumors (17% vs 10% had T4 lesions, P=.02), and cases on protocol (9% vs 5%, P=.005) or with intensity modulated radiation therapy/image guided intensity modulated radiation therapy (52% vs 43%, P=.001) were more likely to have incidents.ConclusionsWe found several treatment- and patient-specific variables associated with incidents. These factors should be considered by treatment teams at the time of peer review to identify patients at higher risk. Larger datasets are required to recommend changes in care process standards, to minimize safety risks.

from #Medicine-SfakianakisAlexandros via o.lakala70 on Inoreader http://ift.tt/1ptOm1g
via IFTTT

from #Med Blogs by Alexandros G.Sfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1XBsNH3
via IFTTT