Experiences with Prescribing Large Quantities of Systemic Anticancer Therapy Near Death.

Background: The most important decision after diagnosing terminal cancer is whether to provide active therapy or withhold treatment. Objective: To analyze the aggressiveness of care by evaluating systemic anticancer therapy (SACT) given near to death, describing this care and identifying factors that determine its use. Design: This involves retrospective observational cohorts study. Setting/Subjects: This involves patients with metastatic tumors who died at a University Hospital in Spain between 2015 and 2016. Measurements: Data obtained from prescribing oncologists and patients' clinical records, type of cancer, and information on treatment. The dependent variable used was the interval between the date of the last dose and date of death. Results: Ninety-four (32.60%) of 288 patients received SACT in the last month of life. This cohort had a higher frequency of lung cancer (OR: 1.58; CI 95%: 1.14-2.18), received more care from oncologist 2 (OR: 1.50; CI 95%: 1.08-2.08), had fewer last-line treatment cycles (OR: 1.28; CI 95%: 1.13-1.45), a lower subjective response (OR: 3.13; CI 95%: 1.34-7.29), less clinical benefit (OR: 2.38; CI 95%: 1.04-5.55), more visits to the Emergency Department (OR: 1.59; CI 95%: 1.06-2.38), and less care from the Palliative Care Unit (OR: 4.55; CI 95%: 2.69-7.70). In multivariate analysis, the predictors of having received SACT close to death remained: receiving fewer cycles of treatment (OR: 1.28; CI 95%: 1.12-1.47) and less palliative care (OR: 4.54; CI 95%: 2.56-7.69). Conclusions: A third of cancer patients received SACT in the last month of life with less efficacy and poorer quality of care than patients not receiving it.

Impact of computerised chemotherapy prescriptions on the prevention of medication errors.

OBJECTIVES: The authors sought to evaluate the impact of computerised chemotherapy prescription on the reduction of medication errors. The purpose of this study was to assess the incidence of errors present in electronic versus manual prescription. MATERIAL AND METHODS: The data gathered from computerised chemotherapy prescription sheets were submitted to a prospective analysis as cases of the intervention groups. The control group was comprised of the handwritten chemotherapy prescription sheets. Chemotherapy prescriptions for consecutive oncology patients were analysed by 2 independent examiners, who investigated errors of omission, commission, interpretation of dates, abbreviations and illegible handwriting. The proportion of treatment prescriptions containing one or more errors and the median of errors were calculated in order in both groups. RESULTS: At least one error was detected in 100% of the manual prescriptions and in 13% of computerised prescriptions (p < 0.001). The median of errors per computerised prescription was 0 (range: 0- 1), whereas in manual prescriptions the median was 5 (range: 1-12) (p < 0.001). Errors of omission were predominant in manual prescriptions. Errors of commission were limited to 1 case of unjustified cytostatic agent infra-dosage in a computerised prescription. This error was present in 3 cases in handwritten prescriptions and, in addition, 1 case of premedication drug substitution was detected. Errors of interpretation of the date, use of abbreviations and illegible handwriting were frequent among manual prescriptions and were absent from computerised prescriptions. CONCLUSIONS: Electronic chemotherapy prescription is a powerful tool. In this study it has been shown to decrease chemotherapy-related medication errors and ensure that safe chemotherapy practices were followed.