Improved outcomes for emergency department patients whose ambulance off-stretcher time is not delayed.

OBJECTIVE: To describe and compare characteristics and outcomes of patients who arrive by ambulance to the ED. We aimed to (i) compare patients with a delayed ambulance offload time (AOT) >30 min with those who were not delayed; and (ii) identify predictors of an ED length of stay (LOS) of >4 h for ambulance-arriving patients. METHODS: A retrospective, multi-site cohort study was undertaken in Australia using 12 months of linked health data (September 2007-2008). Outcomes of AOT delayed and non-delayed presentations were compared. Logistic regression analysis was undertaken to identify predictors of an ED LOS of >4 h. RESULTS: Of the 40 783 linked, analysable ambulance presentations, AOT delay of >30 min was experienced by 15%, and 63% had an ED LOS of >4 h. Patients with an AOT <30 min had better outcomes for: time to triage; ambulance time at hospital; time to see healthcare professional; proportion seen within recommended triage time frame; and ED LOS for both admitted and non-admitted patients. In-hospital mortality did not differ. Strong predictors of an ED LOS >4 h included: hospital admission, older age, triage category, and offload delay >30 min. CONCLUSION: Patients arriving to the ED via ambulance and offloaded within 30 min experience better outcomes than those delayed. Given that offload delay is a modifiable predictor of an ED LOS of >4 h, targeted improvements in the ED arrival process for ambulance patients might be useful.

Ideal colonoscopic surveillance intervals to reduce incidence of advanced adenoma and colorectal cancer.

BACKGROUND AND AIMS: There is limited information about the interplay between multiple risk factors contributing to the risk of advanced neoplasia. We determined the actual risk for advanced neoplasia in relation to lapsed time between colonoscopies in people enrolled in a structured surveillance program. This risk information can be used to guide the selection of optimal surveillance intervals. METHODS: Patients were recruited into programs at two major tertiary hospitals, with a personal or family history of advanced neoplasia. Five thousand one hundred forty-one patients had an index and one or more surveillance colonoscopies. Fifty-one percent had a family history of colorectal neoplasia while the remainder had a personal history. RESULTS: Patients with an immediately prior colonoscopy result (prior result) of advanced adenoma had a risk for advanced neoplasia 7.1 times greater than those with a normal prior result. Cancer as a prior result did not confer a greater risk than either a hyperplastic polyp or a nonadvanced adenoma. Being female reduced risk, age increased risk. Only a family history of a first-degree relative diagnosed under 55, or definite or suspected hereditary nonpolyposis colorectal cancer (HNPCC) conferred an increased risk over a personal history of advanced neoplasia. CONCLUSIONS: Most family history categories did not confer excess risk above personal history of advanced neoplasia. A prior cancer poses less of a risk than a prior advanced adenoma. Based on our models, a person with an advanced adenoma should be scheduled for colonoscopy at 3 years, corresponding to a 15% risk of advanced neoplasia for a male aged under 56. Guidelines should be updated that uses a 15% risk as a benchmark for calculating surveillance intervals.

Expanding emergency department capacity: a multisite study.

OBJECTIVES: The aims of the present study were to identify predictors of admission and describe outcomes for patients who arrived via ambulance to three Australian public emergency departments (EDs), before and after the opening of 41 additional ED beds within the area. METHODS: The present study was a retrospective comparative cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (LOS), admission requirement, access block, hospital LOS and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. RESULTS: Almost one-third of all 286037 ED presentations were via ambulance (n=79196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED LOS, admission requirement, access block and hospital LOS did not improve. Strong predictors of admission before and after increased capacity included age >65 years, Australian Triage Scale (ATS) Category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS >4h. With additional capacity, the odds ratios for these predictors increased for age >65 years and ED LOS >4h, and decreased for ATS category and ED diagnoses. CONCLUSIONS: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes, but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing or decreasing) ED bed numbers, the whole healthcare system needs to be considered.

Linking ambulance, emergency department and hospital admissions data: understanding the emergency journey.

OBJECTIVE: To assess the accuracy of data linkage across the spectrum of emergency care in the absence of a unique patient identifier, and to use the linked data to examine service delivery outcomes in an emergency department (ED) setting. DESIGN: Automated data linkage and manual data linkage were compared to determine their relative accuracy. Data were extracted from three separate health information systems: ambulance, ED and hospital inpatients, then linked to provide information about the emergency journey of each patient. The linking was done manually through physical review of records and automatically using a data linking tool (Health Data Integration) developed by the CSIRO (Commonwealth Scientific and Industrial Research Organisation). Match rate and quality of the linking were compared. SETTING: 10,835 patient presentations to a large, regional teaching hospital ED over a 2-month period (August - September 2007). RESULTS: Comparison of the manual and automated linkage outcomes for each pair of linked datasets demonstrated a sensitivity of between 95% and 99%; a specificity of between 75% and 99%; and a positive predictive value of between 88% and 95%. CONCLUSIONS: Our results indicate that automated linking provides a sound basis for health service analysis, even in the absence of a unique patient identifier. The use of an automated linking tool yields accurate data suitable for planning and service delivery purposes and enables the data to be linked regularly to examine service delivery outcomes.