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Background: Observational data and funnel plots are routinely used outside of pathology to understand trends and improve performance. Objective: Extract diagnostic rate (DR) information from free text surgical pathology reports with synoptic elements and assess whether inter-rater variation and clinical history completeness information useful for continuous quality improvement (CQI) can be obtained. Methods: All in-house prostate biopsies in a 6-year period at two large teaching hospitals were extracted and then diagnostically categorized using string matching, fuzzy string matching, and hierarchical pruning. DRs were then stratified by the submitting physicians and pathologists. Funnel plots were created to assess for diagnostic bias. Results: 3,854 prostate biopsies were found and all could be diagnostically classified. Two audits involving the review of 700 reports and a comparison of the synoptic elements with the free text interpretations suggest a categorization error rate of 40 cases and together assessed 3,690 biopsies. There was considerable inter-rater variability and a trend toward more World Health Organization/International Society of Urologic Pathology Grade 1 cancers in older pathologists. Normalized deviations plots, constructed using the median DR, and standard error can elucidate associated over- and under-calls for an individual pathologist in relation to their practice group. Clinical history completeness by submitting medical doctor varied significantly (100% to 22%). Conclusion: Free text data analyses have some limitations; however, they could be used for data-driven CQI in anatomical pathology, and could lead to the next generation in quality of care.

Relatório de estágio de mestrado, Educação e Formação (Área de especialidade em Desenvolvimento Social e Cultural), Universidade de Lisboa, Instituto de Educação, 2016 Submitted by Biblioteca FPIE-ULisboa (bibliorul@fpie.ulisboa.pt) on 2017-03-10T16:14:45Z No. of bitstreams: 2 ulfpie051242_tm_tese.pdf: 4368300 bytes, checksum: 5eaf1e3b91cbb216578d63d87255f0c3 (MD5) ulfpie051242_tm_anexos.pdf: 7137985 bytes, checksum: 77c137342858a07d33c34feef4d5344d (MD5) Made available in DSpace on 2017-03-10T16:15:39Z (GMT). No. of bitstreams: 2 ulfpie051242_tm_tese.pdf: 4368300 bytes, checksum: 5eaf1e3b91cbb216578d63d87255f0c3 (MD5) ulfpie051242_tm_anexos.pdf: 7137985 bytes, checksum: 77c137342858a07d33c34feef4d5344d (MD5) Previous issue date: 2016

70 Background: Administration of chemotherapy is high-risk, requiring multiple safety checks, including pre-treatment laboratory value verification by nursing. A recent series of near misses in our event reporting system highlighted that nurses verified chemotherapy orders with pending pre-treatment or abnormal labs, such as grade 2 hyperbilirubinemia and grade 4 neutropenia. Such laboratory results would normally require holding or modifying planned treatment doses. Methods: Nurses treating patients in the outpatient chemotherapy infusion units were surveyed regarding barriers to pre-treatment lab verification. A team of clinicians, nurses, and pharmacists outlined a process map of the order verification process from acknowledging patient assignment and looking at patient oncologic history to sending the physician order to pharmacy. Pharmacists collected baseline data by tracking near-miss incidents. Results: The survey response rate of outpatient treatment nurses was 18 of 32 (56%). Nurses ranked inconsistent notation of treatment criteria in orders, long lab processing time, and patient frustration with a long wait as the most common barriers to lab verification. At baseline, in six non-consecutive weeks from August-October 2016, 31 of 947 (3%) orders were inappropriately verified by nursing in which pre-treatment lab results were pending or lab results did not meet parameters in the chemotherapy order. The team’s aim is by February 1, 2017, to reduce the number of chemotherapy orders sent to pharmacy without proper lab verification by 50%. Conclusions: Chemotherapy verification fatigue, specifically pre-treatment lab near misses, was identified as an area for improvement from recent patient safety reports. Barriers for nurses include inconsistent notation of treatment criteria in orders, long lab processing time, and patient frustration with a long wait. Interventions are underway to improve nursing adherence to pre-treatment lab verification.