Assessment of clinically significant urolithiasis positivity rate using CT KUB for suspected renal colic.

BACKGROUND: Unenhanced low-dose computed tomography of the kidneys, ureter and bladder (CT KUB) is the gold standard diagnostic imaging modality in the assessment of suspected renal colic. As the radiation dose is not negligible, it is important to monitor the diagnostic yield of CT KUBs. The aim of this study is to evaluate the diagnostic yield of CT KUB studies performed for suspected renal colic in patients presenting to the emergency department. METHODS: A retrospective review was performed of 500 patients who underwent CT KUB for suspected renal colic over a seven month period from June 2019 to January 2020. Clinical information and imaging was reviewed for each patient. Statistical analysis was performed using GraphPad Prism 8 (GraphPad Software, San Diego, CA, USA). RESULTS: Forty-nine percent of patients in the series were female (248/500) and the mean age was 45. The positivity rate for obstructing ureteral calculus was 34% (169/500). Concerningly, there was a significantly lower positivity rate in females compared to males (19% versus 48%; p < 0.0001) which raises the issue of unnecessary radiation exposure to this cohort. In the 200 female patients who were negative for obstructing urolithiasis, the mean age was 43. Females also had a significantly higher rate of negative CT KUB (62% versus 37%; p < 0.0001) where no underlying alternative pathology was diagnosed. CONCLUSIONS: Women are less likely than men to have obstructing urolithiasis on CT KUB for suspected renal colic. This difference is not accounted for by a higher rate of alternative diagnoses among female patients. The findings of this study should prompt clinicians to exercise caution when considering this imaging modality in this patient cohort.

Development and validation of a data dictionary for a feasibility analysis of emergency department key performance indicators.

OBJECTIVES: The primary study objective was to describe the development of a data dictionary for a feasibility analysis of 11 emergency department (ED) key performance indicators (KPIs). The secondary objective was to internally validate the data dictionary by measuring the inter-observer agreement between data abstractors at participating study sites. METHODS: A list of data variables based on the minimum data set elements relevant to the KPIs was developed by a panel of emergency medicine (EM) specialists and from the EM literature. A summit involving the relevant stakeholders, including ED frontline staff, a health economist, an ED clinical data manager and a health care informatician, was convened. For the feasibility analysis project, each data abstractor was furnished with a copy of the data dictionary and attended a one-hour training session prior to commencing data abstraction. Data was independently abstracted for each KPI by two abstractors at each of 12 participating EDs. Inter-rater agreement between abstractors was calculated using Cohen's kappa and results were reported using the Landis and Koch criteria. RESULTS: A data dictionary was developed by creating clear definitions and establishing abstraction instructions for each variable. A total of 43 data variables were included in the study data dictionary: 4 on patient demographics; 19 time variables; 5 outcome variables; 8 ED service and staffing units and 7 medical definitions. A clear definition and a set of data abstraction instructions including data sources were developed for each variable to aid data abstraction during the feasibility analysis. Overall 9,276 ED patient records were used for data abstraction to internally validate the data dictionary. The median Cohen kappa score ranged between 0.56 to 0.81. CONCLUSION: There is a continued need to standardize definitions of KPIs for the purpose of comparing ED performance and for research purposes. This is a necessary first step in the implementation of valid and reliable ED performance measures. This study successfully developed an internally valid data dictionary that can be used for day-to-day ED operations and for research purposes.

An economic cost analysis of emergency department key performance indicators in Ireland.

OBJECTIVES: High quality data is fundamental to using key performance indicators (KPIs) for performance monitoring. However, the resources required to collect high quality data are often significant and should usually be targeted at high priority areas. As part of a study of 11 emergency department (ED) KPIs in Ireland, the primary objective of this study was to estimate the relative cost of collecting the additional minimum data set (MDS) elements for those 11 KPIs. METHODS: An economic cost analysis focused on 12 EDs in the Republic of Ireland. The resource use data were obtained using two separate focus group interviews. The number of available MDS elements was obtained from a sample of 100 patient records per KPI per participating ED. Unit costs for all resource use were taken at the midpoint of the relevant staff salary scales. RESULTS: An ED would need to spend an estimated additional &OV0556;3561 per month on average to capture all the MDS elements relevant to the 11 KPIs investigated. The additional cost ranges from 14.8 to 39.2%; this range is 13.9-32.3% for small EDs, whereas the range for medium EDs is 11.7-40%. Regional EDs have a higher additional estimated cost to capture all the relevant MDS elements (&OV0556;3907), compared with urban EDs (&OV0556;3353). CONCLUSION: The additional cost of data collection, contingent on that already collected, required to capture all the relevant MDS elements for the KPIs examined, ranges from 14.8 to 39.2% per KPI, with variation identified between regional and urban hospitals.