Evaluation of low acuity patients discharged from a virtual emergency department at a major urban academic health sciences centre in Toronto, Canada

ObjectiveIn response to the COVID-19 pandemic, Sunnybrook Health Sciences Centre launched the first virtual emergency department (VED) in Toronto, Ontario. The objective of this pilot project was to leverage linked administrative data to describe the healthcare utilization of VED patients compared to matched patients who attended an ED in person. ApproachEvaluation of the VED program was supported by the ICES Applied Health Research Question Program, which is funded by the Ontario Ministry of Health to answer questions directly related to Ontario healthcare policy, planning, or practice. VED visit records from December 2020 to May 2021 were linked with Ontario administrative data. VED patients with low acuity complaints were matched 1:1 with in-person ED comparators according to visit date, presenting complaint, and a propensity score that incorporated age, sex, comorbidities, and other important potential confounders. The primary outcomes were healthcare utilization within 7 days and all-cause mortality within 30 days. ResultsOf the 609 eligible patients discharged from the VED, 600 (98.5%) were successfully matched to a comparator. Mean (SD) age was 43.0 (21.1) and 64.1% were female. In-person ED revisits and hospitalizations were similar for VED and comparator patients at 72 hours (ED: 12.1% vs. 11.3%; Δ 0.8%, 95%: -2.8, 4.5%; hospitalization:  1.2% vs. 1.5%; Δ 0.3%, 95%: -0.7, 1.4%,) and 7 days (ED: 16.1% vs. 14.4%; Δ 1.7, 95%: -2.4, 5.7%; hospitalization: 1.7% vs. 1.8%; Δ 0.2%, 95%: -0.1, 1.4%) following the index visit. The number of patients visiting a primary care provider within 7 days was also similar between groups (36.7% vs. 32.4%; Δ 4.3, 95%: -1.1, 9.8%). No patients died within 30 days. Conclusion/ImplicationsVED patients and their matched comparators had similar healthcare utilization in the 7 days following their index ED visit. Methodology from this study will inform a province-wide evaluation of VED programs across Ontario.

Advancing multi-regional research in Canada through collaboration

ObjectivesCOVID-19 accentuated the importance of breaking down data siloes and aligning incentives for data access, collection, and use. Health Data Research Network Canada (HDRN Canada) is responding to this challenge, bringing together people and organizations to transform health data use in Canada. ApproachHDRN Canada’s foundation is its partnership of 20 pan-Canadian, provincial and territorial data organizations that together are enabling multi-regional research. This is being enriched with HDRN Canada’s development of the Canada Health Data Research Alliance (HDR Alliance). The HDR Alliance coordinates expansion of sources and types of data available while retaining organizational independence. A project-based pilot approach is underway with two large pan-Canadian, longitudinal, consented cohort studies being linked at HDRN Canada sites. In addition, a collaboration with a pan-Canadian COVID19 clinical trials network is ensuring that clinical data are collected in ways that enables linkage with population-based administrative data. ResultsHDRN Canada has created a single data access portal for researchers with information on over 500 datasets and supported 72 research projects to date. Work on the HDR Alliance adds data from the Canadian Partnership for Tomorrow’s Health and the Canadian Longitudinal Survey on Aging. The former includes 350,000 individuals, and survey data (including related to COVID-19), physical measures and genomics. The latter includes 50,000 individuals with survey data and physical measures. Four multi-region clinical trials are being planned with the support of HDRN Canada.  Even with aligned incentives, challenges navigating data governance and access processes remain. Collaborations are necessary to address these complexities and enable access to richer data in an efficient and timely matter. ConclusionStrong partnerships are critical to unlocking the potential of Canada’s data assets and expertise. The HDR Alliance provides a collaboration mechanism to increase the “findability”, accessibility and utility of data assets, while addressing complex issues in the data landscape. This increases research opportunities and the impact of population-based, linkable data.

Supporting policy and practice in Ontario through ICES’ Applied Health Research Question (AHRQ) Program

ICES upholds a strong reputation for generating high-quality evidence to inform policy and practice through its collaborations with a broad range of health system stakeholders including government policymakers and healthcare providers including clinicians. Supported by the Ontario Ministry of Health and Ministry of Long-Term Care, the ICES Applied Health Research Question (AHRQ) Program leverages the data holdings and, scientific and clinical expertise to generate evidence tailored to the information needs of requestors. This paper outlines the approach, process, strengths, challenges and the resulting influence and impact to the healthcare landscape in Ontario.

A Value-Based Comparison of the Management of Ambulatory Respiratory Diseases in Walk-in Clinics, Primary Care Practices, and Emergency Departments: Protocol for a Multicenter Prospective Cohort Study

BACKGROUND

In Canada, 30%-60% of patients presenting to emergency departments are ambulatory. This category has been labeled as a source of emergency department overuse. Acting on the presumption that primary care practices and walk-in clinics offer equivalent care at a lower cost, governments have invested massively in improving access to these alternative settings in the hope that patients would present there instead when possible, thereby reducing the load on emergency departments. Data in support of this approach remain scarce and equivocal.

OBJECTIVE

The aim of this study is to compare the value of care received in emergency departments, walk-in clinics, and primary care practices by ambulatory patients with upper respiratory tract infection, sinusitis, otitis media, tonsillitis, pharyngitis, bronchitis, influenza-like illness, pneumonia, acute asthma, or acute exacerbation of chronic obstructive pulmonary disease.

METHODS

A multicenter prospective cohort study will be performed in Ontario and Québec. In phase 1, a time-driven activity-based costing method will be applied at each of the 15 study sites. This method uses time as a cost driver to allocate direct costs (eg, medication), consumable expenditures (eg, needles), overhead costs (eg, building maintenance), and physician charges to patient care. Thus, the cost of a care episode will be proportional to the time spent receiving the care. At the end of this phase, a list of care process costs will be generated and used to calculate the cost of each consultation during phase 2, in which a prospective cohort of patients will be monitored to compare the care received in each setting. Patients aged 18 years and older, ambulatory throughout the care episode, and discharged to home with one of the aforementioned targeted diagnoses will be considered. The estimated sample size is 1485 patients. The 3 types of care settings will be compared on the basis of primary outcomes in terms of the proportion of return visits to any site 3 and 7 days after the initial visit and the mean cost of care. The secondary outcomes measured will include scores on patient-reported outcome and experience measures and mean costs borne wholly by patients. We will use multilevel generalized linear models to compare the care settings and an overlap weights approach to adjust for confounding factors related to age, sex, gender, ethnicity, comorbidities, registration with a family physician, socioeconomic status, and severity of illness.

RESULTS

Phase 1 will begin in 2021 and phase 2, in 2023. The results will be available in 2025.

CONCLUSIONS

The end point of our program will be for deciders, patients, and care providers to be able to determine the most appropriate care setting for the management of ambulatory emergency respiratory conditions, based on the quality and cost of care associated with each alternative.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/25619.

Building A Research Partnership Between Computer Scientists and Health Service Researchers for Access and Analysis of Population-Level Health Datasets

IntroductionThere is widespread enthusiasm to improve health through the application of artificial intelligence and machine learning (AI/ML) methods to large population-level health datasets. Achieving this may require successful collaboration between institutions as well as between computer scientists (CS), machine learning researchers (MLR) and health service researchers (HSR). The objective is to describe lessons learned in creating the Health Artificial Data and Analysis Platform (HAIDAP) in Ontario, Canada. Objectives and ApproachA partnership between a HSR institute (ICES), an AI/ML institute (Vector) and a high-performance computing center (HPC4H) was initiated in 2017 to enable the application of AI/ML methods to population-level health data for the province of Ontario (population 14M). The HAIDAP was launched in 2019. We describe lessons learned (and being learned) following the HAIDAP’s launch. ResultsMajor learnings include: 1)importance of institutional partnerships and alignment with institutional strategies; 2)potential of joint institutional risk-sharing models; 3)need for scientific collaborations bridging disciplines around joint research projects; 4)sensitivity to different scientific cultures (e.g., academic prestige of conference proceedings for MLR vs journal publications for HSR; traditional statistical vs. ML model assumptions); 5)differences in research timeline expectations; 6)different experience with and expectations for access to de-identified routinely collected data (e.g., need for research ethics committee project approvals and privacy impact assessments); 7)developing data access models that enable greater flexibility (e.g. importing code or using open source tools); 8) broadening data access models to allow modern high-dimensional exploratory data analysis; 9)obtaining support of information/privacy regulator; 10)hardware is (relatively) easy part compared to other success factors. Conclusion / ImplicationsThe HAIDAP has enabled multi-disciplinary collaborations and novel AI/ML research of Ontario’s population-level health data. Collectively we have learned that additional effort is required to develop systems and processes enabling more efficient access to data and analytic tools for the analysis of administrative health data.

Improving Quality of Care Through a Mandatory Provincial Audit Program: Ontario's Emergency Department Return Visit Quality Program

The Emergency Department Return Visit Quality Program was launched in Ontario, Canada, to promote a culture of quality. It mandates the province's largest-volume emergency departments (EDs) to audit charts of patients who had a return visit leading to hospital admission, including some of their 72-hour all-cause return visits with admission and all of their 7-day ones with sentinel diagnoses (ie, acute myocardial infarction, subarachnoid hemorrhage, and pediatric sepsis), and submit their findings to a governmental agency. This provides an opportunity to identify possible adverse events and quality issues, which hospitals can then address through quality improvement initiatives. A group of emergency physicians with quality improvement expertise analyzed the submitted audits and accompanying narrative templates, using a general inductive approach to develop a novel classification of recurrent quality themes. Since the Return Visit Quality Program launched in 2016, 125,698 return visits with admission have been identified, representing 0.93% of the 86 participating EDs' 13,559,664 visits. Overall, participating hospitals have conducted 12,852 detailed chart audits, uncovering 3,010 (23.4%) adverse events/quality issues and undertaking hundreds of quality improvement provincewide projects as a result. The inductive analysis revealed 11 recurrent themes, classified into 3 groupings: patient characteristics (ie, patient risk profile and elder care), ED team actions or processes (ie, physician cognitive lapses, documentation, handover/communication between providers, radiology, vital signs, and high-risk medications or medication interactions), and health care system issues (ie, discharge planning/community follow-up, left against medical advice/left without being seen, and imaging/testing availability). The Return Visit Quality Program is the largest mandatory audit program for EDs and provides a novel approach to identify local adverse events/quality issues to target for improved patient safety and quality of care. It provides a blueprint for health system leaders to enable clinicians to develop an approach to organizational quality, as well as for teams to construct an audit system that yields defined issues amenable to improvement.

The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research

Administrative health data is recognized for its value for conducting population-based research that has contributed to numerous improvements in health. In Canada, each province and territory is responsible for administering its own publicly funded health care program, which has resulted in multiple sets of administrative health data. Challenges to using these data within each of these jurisdictions have been identified, which are further amplified when the research involves more than one jurisdiction. The benefits to conducting multi-jurisdictional studies has been recognized by the Canadian Institutes of Health Research (CIHR), which issued a call in 2017 for proposals that address the challenges. The grant led to the creation of Health Data Research Network Canada (HDRN), with a vision is to establish a distributed network that facilitates and accelerates multi-jurisdictional research in Canada. HDRN received funding for seven years that will be used to support the objectives and activities of an initiative called the Strategy for Patient-Oriented Research Canadian Data Platform (SPOR-CDP). In this paper, we describe the challenges that researchers face while using, or considering using, administrative health data to conduct multi-jurisdictional research and the various ways that the SPOR-CDP will attempt to address them. Our objective is to assist other groups facing similar challenges associated with undertaking multi-jurisdictional research.

Building a research partnership between computer scientists and health service researchers for access and analysis of population-level health datasets: what are we learning?

Background and rationale There is widespread enthusiasm to improve health through the application of artificial intelligence and machine learning (AI/ML) methods to large population-level health datasets. Achieving this may require successful collaboration between institutions as well as between computer scientists (CS), machine learning researchers (MLR) and health service researchers (HSR). Main Aim Describe lessons learned in creating the Health Artificial Data and Analysis Platform (HAIDAP) in Ontario, Canada. Methods/Approach A partnership between a HSR institute (ICES), an AI/ML institute (Vector) and a high-performance computing center (HPC4H) was initiated in 2017 to enable the application of AI/ML methods to population-level health data for the province of Ontario (population 14M). We describe lessons learned (and being learned) following the HAIDAP’s launch. Results The HAIDAP was launched in 2019. Major learnings include: 1) importance of institutional partnerships and alignment with institutional strategies; 2) potential of joint institutional risk-sharing models; 3) need for scientific collaborations bridging disciplines around joint research projects; 4) sensitivity to different scientific cultures (e.g., academic prestige of conference proceedings for MLR vs journal publications for HSR; traditional statistical vs. ML model assumptions); 5) differences in research timeline expectations; 6) different experience with and expectations for access to de-identified routinely collected data (e.g., need for research ethics committee project approvals and privacy impact assessments); 7) developing data access models that enable greater flexibility (e.g., importing code or using open source tools); 8) broadening data access models to allow modern high-dimensional exploratory data analysis; 9) obtaining support of information/privacy regulator; 10) the hardware is the (relatively) easy part compared to other success factors. Conclusion The HAIDAP has enabled multi-disciplinary collaborations and novel AI/ML research of Ontario’s population-level health data. Collectively we have learned that additional effort is required to develop systems and processes enabling more efficient access to data and analytic tools for the analysis of administrative health data.

P3518Men with heart failure have higher readmission rates: a closer review of sex and gender based analyses

Background

There has been increased attention on reducing hospital readmission rates. However, little is known about any difference in readmission rates in heart failure by sex, although evidence exists demonstrating differences in the etiology of heart failure. As a result, strategies to optimize readmission reduction programs and care strategies for women and men remain unclear.

Purpose

(1) To identify studies examining readmission rates according to sex, and (2) to provide a qualitative overview of possible considerations for the impact of sex or gender.

Methods

A scoping protocol was developed using the Arksey and O'Malley framework and the Joanna Briggs Institute methodology. Our search strategy was reviewed according to the peer-review of electronic search strategy (PRESS) checklist. Full text articles published between 2002 and 2017 and drawn from multiple databases (i.e. MEDLINE, EMBASE), grey literature (i.e. National Technical Information, Duck Duck Go), and experts were consulted for additional articles. Screening criteria were established a priori. Once an acceptable inter-rater agreement was established at 80% by two independent reviewers, articles were screened for potential eligibility. A descriptive analytical method was employed to chart primary research articles. Articles were considered relevant if the cohort consisted of adult heart failure patients who were readmitted after an index hospitalization and a sex/gender-based analysis was performed.

Results

The literature search yielded 5887 articles, of which 746 underwent full text assessment for eligibility. Of 164 eligible articles, 34 studies addressed the primary outcome, 103 studies considered sex differences as a secondary outcome and 25 studies included disaggregated data for sex but no subsequent interaction was reported. Good inter-rater agreement was reached: 83% for title and abstract screening; 88% for full text review; kappa: 0.69 (95% CI: 0.526–0.851). Twelve of 34 studies included for the primary outcome reported higher readmission rates for men compared to five studies reporting higher readmission rates for women. However, there were differential readmission rates that were dependent on duration of follow-up. Women were more likely to experience higher readmission rates than men when time to event was less than one year. Readmission rates for men were higher when follow-up was longer than one year.

Conclusion

Sex differences in readmission rates were dependent on follow up time. Most studies used composite outcomes and had short times to event, which may mask underlying effects of sex on readmission.

Acknowledgement/Funding

Ontario SPOR Support Unit

A challenge to all. A primer on inter-country differences of high-need, high-cost patients

BACKGROUND

Across countries, a small group of patients accounts for the majority of health care spending. These patients are more likely than other patients to experience problems with quality and safety in their care, suggesting that efforts targeting efficiency and quality among this population might have significant payoffs for health systems. Better understanding of similarities and differences in patient characteristics and health care use in different countries may ultimately inform further efforts to improve care for HNHC patients in these health systems.

METHODS

We conducted a cross-sectional descriptive study using one year of patient-level data on high-cost patients in seven high-income OECD member countries. Countries were selected based on availability of detailed information (large enough samples of claims, administrative, and survey data of high-cost patients). We studied concentration of spending among high-cost patients, characteristics of high-cost patients, and per capita spending on high-cost patients.

FINDINGS

Cost-concentration of the top 5% of patients varied across countries, from 41% in Japan to 60% in Canada, driven primarily by variation in the top 1% of spenders. In general, high-cost patients were more likely to be female (57.7% on average), had a significant number of multi-morbidities (up to on average 10 major diagnostic categories (ICD chapters), and had a lower socioeconomic status. Characteristics of high-cost patients varied as well: median age ranged from 62 in the Netherlands to 75 in Germany and the difference in socioeconomic status is particularly stark in the US. Lastly, utilization, particularly for inpatient care, varied with an average number of inpatient days ranging from 6.6 nights (US) to 97.7 nights in Japan.

INTERPRETATION

In this descriptive study, there is substantial variation in the cost concentration, characteristics, and per capita spending on high-cost patient populations across high-income countries. Differences in the way that health systems are structured likely explains some of this variation, which suggests the potential of cross-system learning opportunities. Our findings highlight the need for further studies including comparable performance metrics and institutional analysis.

Pan-Canadian Real-World Health Data Network: Building a National Data Platform

IntroductionResearchers and decision makers from across Canada use linked provincial administrative data for analysis and to address research and policy questions. Currently there are several impediments to working harmoniously across provincial boundaries. A group of academic and policy researchers are working to address these multi-jurisdictional obstacles. Objectives and ApproachResearchers and data organizations from across Canada are working together as the Pan-Canadian Real-World Health Data Network PRHDN). PRHDN aims to: (1) create harmonized data, algorithms and analytic protocols, and (2) link administrative databases to other types of data, including electronic medical records, clinical trials records, “omics data” and records from pan-Canadian cohort studies. PRHDN’s vision is to construct a unified, documented infrastructure to advance pan-Canadian population-based research and analysis. This presentation incorporates material that is part of PRHDN’s response to a funding call to create national, collaborative infrastructure. ResultsScientists and staff at PRHDN organizations will create three main categories of infrastructure: 1) Algorithms: Reusable processes, ideally in the form of documented code, which implement a common approach or definition, e.g. to define cases or to create derived variables; 2) Harmonized Common Data: Based on the Sentinel model, we will establish a standardized subset of harmonized common data that are analysis-ready; 3) Common Analytic Protocols: Complementing work of the Canadian Network for Observational Drug Effect Studies (CNODES), we will establish processes for distributed analysis with common analytic protocols and meta-analysis of results to provide pan-Canadian estimates. Source data would remain within jurisdictional boundaries and only aggregate results would be pooled across jurisdictions. Details of these approaches will be presented. Conclusion/ImplicationsThis initiative will improve coordinated access to distributed data from across Canada that is built once then used by many stakeholders for a variety of purposes including: research, benchmarking, performance monitoring to identify gaps and opportunities for improvement, multi-jurisdictional evaluations of novel interventions and inter-jurisdictional comparisons.

Understanding Patterns of Emergency Department (ED) Use over time in Ontario to plan new EDs for the future

IntroductionThe Applied Health Research Question (AHRQ) portfolio is an initiative funded by the Ontario Ministry of Health and Long-Term Care, leveraging the linked data and scientific expertise at ICES to answer questions that directly impact healthcare policy, planning or practice. Objectives and ApproachThe objective of this project was to evaluate historical patterns of emergency department (ED) use to better plan for a new emergency Department in Kingston and to better understand the factors contributing to increasing ED utilization. Emergency departments across Ontario continue to see consistent increases in volume at rates exceeding expected volume growth due to population growth alone. Some hospitals across the province observe significantly higher volume increases compared to the provincial average. ResultsFrom 2006/07 to 2016/17, rate and volume of emergency department visits in Ontario increased 8.82% and 19.87% respectively. Throughout the same period, emergency department visit rate and volume at Kingston General Hospital increased 20.70%, and 27.2%. Using historical data and projected population growth by age and sex, we were able to estimate that emergency department volume would increase at least 11.94% by 2025 due to estimated shifts in population size and distribution (by age and sex) alone. From 2006/07 to 2016/17, the greatest rate of increase in reason for ED visits was mental/behavioral problems. Throughout this period the increase in volume and rate of ED visits due to mental/behavioural problems was 274.46% and 259.59% respectively. Conclusion/ImplicationsPopulation-specific volume projections and historical trends in ED use can be utilized for planning ED operations to improve efficiency and patient care quality. This has been used to inform the redesign of the ED at the Kingston Health Sciences Centre to ensure it will meet the needs of the community.

Examination of High-Cost Patients in Ontario

IntroductionIn Ontario, the top 5% of high-cost users account for 66% of health care costs. The heavy use of resources combined with perceived inefficiencies offer an imperative to target strategies to redesign care to better meet patient needs and increase value. Objectives and ApproachAs part of a request submitted to the Applied Health Research Question (AHRQ) review team, the main objective of this study was to identify drivers of high health care use in Ontario in order to find better ways to improve the efficiency in healthcare delivery. Using data in fiscal year 2012/13, characteristics of the top 5% of high costs users were described, and further stratified by mental health status. Total spending by sector of care were also described. Data were linked including physician, hospital, medication and long term care databases for each patient. ResultsIn the top 5% of high-cost users, there were 729,870 patients who accounted for $20,179,208,348 of total healthcare spending in 2012/13, with the highest percentage of spending observed among older adults aged 61-80 years old. Mental health high-cost patients accounted for 6.1% of these patients, of which 51.5% were female, had a low socio-economic status and an average age of 44 years. These patients had an average of 4.9 (SD=2.3) ICD chapters and used an average of 8.7 (SD=3.8) drugs. Using the health accounts methodology (ICHA), as described by the OECD and WHO, over 90% of healthcare costs among the top 5% of high-cost patients were from inpatient care, day surgery and clinic care, physician care, outpatients drugs and inpatient rehabilitation and complex/continuing care. Conclusion/ImplicationsThis study provides a systematic description of the needs in a high cost patient group, and serves as a platform for international comparisons across healthcare systems to better understand gaps and identify targets for intervention. These cross-comparisons offer a tool to evaluate performance of healthcare systems and to prioritize policies.

Integrating population-wide laboratory testing data with physician audit-and-feedback reports to improve glycemic and cholesterol control among Ontarians with diabetes

IntroductionImproving the care and management of patients with diabetes, particularly those with extreme blood glucose and/or cholesterol levels, has been identified as a key priority area for healthcare in Ontario. A multi-organizational collaboration produces audit-and-feedback reports distributed to consenting primary care physicians across the province for quality improvement purposes. Objectives and ApproachWe examined the feasibility of linking the Ontario Laboratory Information System (OLIS), a large and nearly population-wide database of laboratory test results in Ontario, with the existing provincial audit-and-feedback reporting structure to integrate aggregated, physician-level measures of glycemic and cholesterol control among patients with diabetes. All Ontario residents alive on March 31, 2014, attached to a primary care physician, and diagnosed with diabetes for at least two years were included. These patients were linked to OLIS to extract laboratory test orders and results for glycated hemoglobin (HbA1C) and low-density lipoproteins (LDL) between April 1, 2013 and March 31, 2014. ResultsThere were 1,108,530 diabetes patients included who were assigned to 10,085 primary care physicians. During fiscal year (FY) 2013, 70%, 64%, and 59% of diabetes patients were tested for HbA1C, LDL, and both measures, respectively. Among the 648,238 diabetes patients with at least one of each test in FY2013, 13% had a HbA1C test exceeding a threshold of 9%, 4% had a LDL test exceeding a threshold of 4 mmol/L, and 0.8% exceeded both thresholds. At the physician-level, the median (Interquartile Range) proportions of diabetes patients exceeding the testing thresholds were 12% (9%-16%) for HbA1c and 4% (2%-6%) for LDL. In a multilevel logistic regression model, there was significant between-physician variability in the proportions of diabetes patients exceeding the HbA1C (p Conclusion/ImplicationsWe developed a mechanism for integrating population-wide, clinical laboratory test results into physician audit-and-feedback reports to improve diabetes care in Ontario. Significant variation observed in the aggregated, physician-level proportions of diabetes patients testing above clinical thresholds for HbA1C and LDL highlights the importance of reporting such information to physicians.

Linkage of whole genome sequencing with administrative health, and electronic medical record data for the study of autism spectrum disorder: Feasibility, Opportunities and Challenges

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) that presents with a high degree of heterogeneity (e.g., co-occurrence of other NDDs and other co-morbid conditions), contributing to differential health system needs. Genetics are known to play an important role in ASD and may be associated with different disease trajectories. Objectives and ApproachIn this proof of principle project, our objective is to link >2,200 children with a confirmed diagnosis of a NDD from the Province of Ontario Neurodevelopmental (POND) Study to administrative health data and electronic medical record (EMR) data in order to identify subgroups of ASD with unique health system trajectories. POND includes detailed phenotype and whole genome sequencing (WGS) data. Identified subgroups will be characterized based on clinical phenotype and genetics. To meet this goal, consideration of WGS-specific privacy and data issues is needed to implement processes which are above and beyond traditional requirements for analyzing individual-level administrative health data. ResultsLinkage of WGS data with administrative health data is an emerging area of research. As such it has presented a number of initial challenges for our study of ASD. Privacy concerns surrounding the use of WGS data and rare-variant analysis are of particular importance. Practical issues required the need for analysts with expertise in administrative data, EMR data and genetic analyses, and specialized software and sufficient processing power to analyze WGS data. Transdisciplinary discussions of the scope and significance of research questions addressed through this linkage were crucial. The identification of genetic determinants of phenotypes and trajectories in ASD could support targeted early interventions; EMR linkage may inform algorithms to identify ASD in broader populations. These approaches could improve both patient outcome and family experience. Conclusion/ImplicationsAs the cost of genetic sequencing decreases, WGS data will become part of the routine clinical management of patients. Linkage of WGS, EMR and administrative data has tremendous potential that has largely not been realized; including population-level ASD research to improve our ability to predict long-term outcomes associated with ASD.

The Ontario Data Safe Haven: Bringing High Performance Computing to Population-wide Data Assets

IntroductionCanadian provincial health systems have a data advantage – longitudinal population-wide data for publicly funded health services, in many cases going back 20 years or more. With the addition of high performance computing (HPC), these data can serve as the foundation for leading-edge research using machine learning and artificial intelligence. Objectives and ApproachThe Institute for Clinical Evaluative Sciences (ICES) and HPC4Health are creating the Ontario Data Safe Haven (ODSH) – a secure HPC cloud located within the HPC4Health physical environment at the Hospital for Sick Children in Toronto. The ODSH will allow research teams to post, access and analyze individual datasets over which they have authority, and enable linkage to Ontario administrative and other data. To start, the ODSH is focused on creating a private cloud meeting ICES’ legislated privacy and security requirements to support HPC-intensive analyses of ICES data. The first ODSH projects are partnerships between ICES scientists and machine learning. ResultsAs of March 2018, the technological build of the ODSH was tested and completed and the privacy and security policy framework and documentation were completed. We will present the structure of the ODSH, including the architectural choices made when designing the environment, and planned functionality in the future. We will describe the experience to-date for the very first analysis done using the ODSH: the automatic mining of clinical terminology in primary care electronic medical records using deep neural networks. We will also present the plans for a high-cost user Risk Dashboard program of research, co-designed by ICES scientists and health faculty from the Vector Institute for artificial intelligence, that will make use of the ODSH beginning May 2018. Conclusion/ImplicationsThrough a partnership of ICES, HPC4Health and the Vector Institute, a secure private cloud ODSH has been created as is starting to be used in leading edge machine learning research studies that make use of Ontario’s population-wide data assets.

Integrating Ontario Health and Social Services Data to for Research and Policy Development

IntroductionIntegrating health and social services data is critical to understanding social determinants of health and responding to public expectations for evidence-based policies amidst changing demographics and fiscal constraint. While academia has long understood the importance of social determinants of health, real and perceived obstacles have slowed their evaluation in Ontario. Objectives and ApproachThis report describes how the Institute for Clinical Evaluative Sciences (ICES) and the Ministry and Community and Social Services (MCSS) have partnered to bring social services data and health data together to better understand the Ontario population and better support decision makers across various sectors. We present how ICES and MCSS tackled barriers to data access and cultural challenges to data sharing in the Ontario context, provide an overview of their unique data and research partnership - including the new collaboration research and data access platforms created, highlight research findings to date, and identify key topics of interest moving forward. ResultsOver the last decade, ICES and MCSS have led the way in Ontario linking health administrative and social services data. An initial single year linkage enabled the success of the Health Care Access Research and Developmental Disabilities project. This cross-sectoral initiative provided a clearer sense of how people with developmental disabilities experienced health care in Ontario. Building on this work, ICES and MCSS recently expanded their partnership bringing together 15 years of social services and health data through a broader data sharing agreement. This agreement allows greater data access to researchers. In addition, ICES and MCSS have been successful in creating a new integrated research platform that will increase the depth and quality of health and social services research and policy evaluation in Ontario. Conclusion/ImplicationsA broader collaborative research community will now be able to answer questions of interest, do self-directed integrated data analytics and leverage respective program data expertise to tackle joint research projects. Importantly, MCSS analytics teams will now also have access to linked data on this platform to conduct their own research.

Building a Pan-Canadian Real World Health Data Network

BackgroundIn December 2017 the Canadian Institutes of Health Research (CIHR) issued a request for proposals to develop a pan-Canadian health data platform. This platform will enable cross-jurisdictional research by facilitating the use of rich provincial and national data and ensure engagement with patients and specific populations including Indigenous partners. Academics and policy makers from across Canada operating under the banner of the Pan-Canadian Real-World Health Data Network (PRHDN) have joined forces to address this call. ObjectivesCreate national infrastructure that is built once then made available for research, benchmarking, performance monitoring, multi-jurisdictional evaluations and inter-jurisdictional comparisons to address pressing health and social policy problems in Canada. MethodsOur approach will address several issues including creating significant efficiencies in data access, streamlining cross provincial/ territorial ethics and access approvals, establishing standards for data and methods harmonization and providing innovative and privacy-conscious solutions to data access and use. The presentation will focus on the plan to create harmonized common data, algorithms and analytic protocols, and link administrative data to electronic medical records and clinical trials to create an integrated and documented infrastructure for pan-Canadian studies. Comparisons to PopMedNet and the Sentinel Initiative in the US will be made. ConclusionProvincial centres across Canada hold rich sources of health and social data that are linkable at the person-level. With the exception of standardized data managed by the Canadian Institute for Health Information (CIHI), these data are often not comparable from one province to another, thereby limiting use to single-province studies. There is growing interest in Canada in creating an environment that would enable cross-jurisdictional data sharing and analysis’ and in sharing experiences to make effective use of linkable administrative data.

A Position Statement on Population Data Science: The Science of Data about People

Information is increasingly digital, creating opportunities to respond to pressing issues about human populations using linked datasets that are large, complex, and diverse. The potential social and individual benefits that can come from data-intensive science are large, but raise challenges of balancing individual privacy and the public good, building appropriate socio-technical systems to support data-intensive science, and determining whether defining a new field of inquiry might help move those collective interests and activities forward. A combination of expert engagement, literature review, and iterative conversations led to our conclusion that defining the field of Population Data Science (challenge 3) will help address the other two challenges as well. We define Population Data Science succinctly as the science of data about people and note that it is related to but distinct from the fields of data science and informatics. A broader definition names four characteristics of: data use for positive impact on citizens and society; bringing together and analyzing data from multiple sources; finding population-level insights; and developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few people possess all of the requisite knowledge and skills of Population Data Science, so this is by nature a multi-disciplinary field. Other implications include the need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. These implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, can catalyze significant advances in our understanding of trends in society, health, and human behavior.

A qualitative study of emergency physicians' perspectives on PROMS in the emergency department

INTRODUCTION

There is a growing emphasis on including patients' perspectives on outcomes as a measure of quality care. To date, this has been challenging in the emergency department (ED) setting. To better understand the root of this challenge, we looked to ED physicians' perspectives on their role, relationships and responsibilities to inform future development and implementation of patient-reported outcome measures (PROMs).

METHODS

ED physicians from hospitals across Canada were invited to participate in interviews using a snowballing sampling technique. Semistructured interviews were conducted by phone with questions focused on the role and practice of ED physicians, their relationship with their patients and their thoughts on patient-reported feedback as a mechanism for quality improvement. Transcripts were analysed using a modified constant comparative method and interpretive descriptive framework.

RESULTS

Interviews were completed with 30 individual physicians. Respondents were diverse in location, training and years in practice. Physicians reported being interested in 'objective' postdischarge information including adverse events, readmissions, other physicians' notes, etc in a select group of complex patients, but saw 'patient-reported' feedback as less valuable due to perceived biases. They were unsure about the impact of such feedback mainly because of the episodic nature of their work. Concerns about timing, as well as about their legal and ethical responsibilities to follow-up if poor patient outcomes are reported, were raised.

CONCLUSIONS

Data collection and feedback are key elements of a learning health system. While patient-reported outcomes may have a role in feedback, ED physicians are conflicted about the actionability of such data and ethical implications, given the inherently episodic nature of their work. These findings have important implications for PROM design and implementation in this unique clinical setting.

Building Bridges to Integrate Care (BRIDGES): Incubating Health Service Innovation across the Continuum of Care for Patients with Multiple Chronic Conditions

Integrating care for people with complex needs is challenging. Indeed, evidence of solutions is mixed, and therefore, well-designed, shared evaluation approaches are needed to create cumulative learning. The Toronto-based Building Bridges to Integrate Care (BRIDGES) collaborative provided resources to refine and test nine new models linking primary, hospital and community care. It used mixed methods, a cross-project meta-evaluation and shared outcome measures. Given the range of skills required to develop effective interventions, a novel incubator was used to test and spread opportunities for system integration that included operational expertise and support for evaluation and process improvement.

Institute for Clinical Evaluative Sciences (ICES) Exploratory Data & Analytic Services Private Sector Pilot Project

ABSTRACTObjectivesPrior to the launch of ICES Data & Analytic Services (DAS) in March 2014, only ICES scientists and analysts could access ICES data, and data could only be accessed at physical ICES locations. The DAS infrastructure, which allows public sector researchers to work with coded record level data remotely through a secure virtual environment, together with broader trends including high profile reports that call for increased access to data and the Ontario government’s Open Data initiative, prompted ICES to launch a pilot project to explore potential DAS work with the private sector. ApproachThree mandatory principles were established for all work with the private sector: (i) alignment with ICES’ mission, vision and values; (ii) transparency; (iii) private sector work must not detract from ICES’ research institute work. The pilot included: a jurisdictional scan; informal conversations with private sector organizations to determine potential services/studies of interest; extensive discussions with data partners; the selection and conduct of two pilot studies; focus groups with members of the general public and scientists; external advice on business model options; and an external evaluation of the pilot. No changes to data sharing agreements or ICES processes were required as work with the private sector and public sector are equally allowed under Ontario law. ResultsThe two pilot studies were successfully completed. The first study “The disease burden of gout in Ontario: A real world data retrospective study” was performed by researchers at IMS Brogan (a healthcare analytic services provider) who were provided with access to coded record-level data using the DAS iDAVE environment and performed their own analyses. In the second pilot study, “The impact of adherence to biologics on healthcare resource utilization in rheumatoid arthritis”, Janssen researchers established the research question and study design, and DAS staff and scientists provided advice about data holdings, performed the analyses, and provided Janssen and three government-funded decision making bodies with results tables. Research Ethics Board approval was required for both studies, and both private sector organizations are in the process of publishing findings. ConclusionsICES was able to work with private sector organizations without compromising the three principles. Based on the evaluation of the private sector pilot, and the findings from the focus groups, ICES will begin offering limited analytic services to private sector researchers beginning June 2016 under ICES’ existing corporate structure, and bring recommendations regarding ongoing operations to the ICES Board in June 2017.

CAEP 2015 Academic Symposium: Recommendations for University Governance and Administration for Emergency Medicine

OBJECTIVE

1) To identify the strengths and challenges of governance structures in academic emergency medicine (EM), and 2) to make recommendations on principles and approaches that may guide improvements.

METHODS

Over the course of 9 months, eight established EM leaders met by teleconference, reviewed the literature, and discussed their findings and experiences to arrive at recommendations on governance in academic units of EM. The results and recommendations were presented at the annual Canadian Association of Emergency Physicians (CAEP) Academic Symposium, where attendees provided feedback. The updated recommendations were subsequently distributed to the CAEP Academic Section for further input, and the final recommendations were decided by consensus.

RESULTS

The panel identified four governance areas of interest: 1) the elements of governance; 2) the relationships between emergency physicians and academic units of EM, and between the academic units of EM and faculty of medicine; 3) current status of governance in Canadian academic units of EM; and 4) essential elements of good governance. Six recommendations were developed around three themes, including 1) the importance of good governance; 2) the purposes of an academic unit of EM; and 3) essential elements for better governance for academic units of EM. Recommendations included identifying the importance of good governance, recognizing the need to adapt to the different models depending on the local environment; seeking full departmental status, provided it is mutually beneficial to EM and the faculty of medicine (and health authority); using a consultation service to learn from the experience of other academic units of EM; and establishing an annual forum for EM leaders.

CONCLUSION

Although governance of academic EM is complex, there are ways to iteratively improve the mission of academic units of EM: providing exceptional patient care through research and education. Although there is no one-size-fits-all guide, there are practical recommended steps for academic units of EM to consider.

Capturing the experiences of patients across multiple complex interventions: a meta-qualitative approach

OBJECTIVES

The perspectives, needs and preferences of individuals with complex health and social needs can be overlooked in the design of healthcare interventions. This study was designed to provide new insights on patient perspectives drawing from the qualitative evaluation of 5 complex healthcare interventions.

SETTING

Patients and their caregivers were recruited from 5 interventions based in primary, hospital and community care in Ontario, Canada.

PARTICIPANTS

We included 62 interviews from 44 patients and 18 non-clinical caregivers.

INTERVENTION

Our team analysed the transcripts from 5 distinct projects. This approach to qualitative meta-evaluation identifies common issues described by a diverse group of patients, therefore providing potential insights into systems issues.

OUTCOME MEASURES

This study is a secondary analysis of qualitative data; therefore, no outcome measures were identified.

RESULTS

We identified 5 broad themes that capture the patients' experience and highlight issues that might not be adequately addressed in complex interventions. In our study, we found that: (1) the emergency department is the unavoidable point of care; (2) patients and caregivers are part of complex and variable family systems; (3) non-medical issues mediate patients' experiences of health and healthcare delivery; (4) the unanticipated consequences of complex healthcare interventions are often the most valuable; and (5) patient experiences are shaped by the healthcare discourses on medically complex patients.

CONCLUSIONS

Our findings suggest that key assumptions about patients that inform intervention design need to be made explicit in order to build capacity to better understand and support patients with multiple chronic diseases. Across many health systems internationally, multiple models are being implemented simultaneously that may have shared features and target similar patients, and a qualitative meta-evaluation approach, thus offers an opportunity for cumulative learning at a system level in addition to informing intervention design and modification.

Are reductions in emergency department length of stay associated with improvements in quality of care? A difference-in-differences analysis

Background

We sought to determine whether patients seen in hospitals who had reduced overall emergency department (ED) length of stay (LOS) in the 2 years following the introduction of the Ontario Emergency Room Wait Time Strategy were more likely to experience improvements in other measures of ED quality of care for three important conditions.

Methods

Retrospective medical record review using difference-in-differences analysis to compare changes in performance on quality indicators over the 3-year period between 11 Ontario hospitals where the median ED LOS had improved from fiscal year 2008 to 2010 and 13 matched sites where ED LOS was unchanged or worsened. Patients with acute myocardial infarction (AMI), asthma and paediatric and adult upper limb fractures in these hospitals in 2008 and 2010 were evaluated with respect to 18 quality indicators reflecting timeliness and safety/effectiveness of care in the ED. In a secondary analysis, we examined shift-level ED crowding at the time of the patient visit and performance on the quality indicators.

Results

Median ED LOS improved by up to 26% (63 min) from 2008 to 2010 in the improved hospitals, and worsened by up to 47% (91 min) in the unimproved sites. We abstracted 4319 and 4498 charts from improved and unimproved hospitals, respectively. Improvement in a hospital's overall median ED LOS from 2008 to 2010 was not associated with a change in any of the other ED quality indicators over the same time period. In our secondary analysis, shift-level crowding was associated only with indicators that reflected timeliness of care. During less crowded shifts, patients with AMI were more likely to be reperfused within target intervals (rate ratio 1.59, 95% CI 1.03 to 2.45), patients with asthma more often received timely administration of steroids (rate ratio 1.88, 95% CI 1.59 to 2.24) and beta-agonists (rate ratio 1.47, 95% CI 1.25 to 1.74), and adult (but not paediatric) patients with fracture were more likely to receive analgesia or splinting within an hour (rate ratio 1.66, 95% CI 1.22 to 2.26).

Conclusions

These results suggest that a policy approach that targets only reductions in ED LOS is not associated with broader improvements in selected quality measures. At the same time, there is no evidence that efforts to address crowding have a detrimental effect on quality of care.

Implementing wait-time reductions under Ontario government benchmarks (Pay-for-Results): a Cluster Randomized Trial of the Effect of a Physician-Nurse Supplementary Triage Assistance team (MDRNSTAT) on emergency department patient wait times

Background

Internationally, emergency departments are struggling with crowding and its associated morbidity, mortality, and decreased patient and health-care worker satisfaction. The objective was to evaluate the addition of a MDRNSTAT (Physician (MD)-Nurse (RN) Supplementary Team At Triage) on emergency department patient flow and quality of care.

Methods

Pragmatic cluster randomized trial. From 131 weekday shifts (8:00–14:30) during a 26-week period, we randomized 65 days (3173 visits) to the intervention cluster with a MDRNSTAT presence, and 66 days (3163 visits) to the nurse-only triage control cluster. The primary outcome was emergency department length-of-stay (EDLOS) for patients managed and discharged only by the emergency department. Secondary outcomes included EDLOS for patients initially seen by the emergency department, and subsequently consulted and admitted, patients reaching government-mandated thresholds, time to initial physician assessment, left-without being seen rate, time to investigation, and measurement of harm.

Results

The intervention’s median EDLOS for discharged, non-consulted, high acuity patients was 4:05 [95^th% CI: 3:58 to 4:15] versus 4:29 [95^th% CI: 4:19–4:38] during comparator shifts. The intervention’s median EDLOS for discharged, non-consulted, low acuity patients was 1:55 [95^th% CI: 1:48 to 2:05] versus 2:08 [95^th% CI: 2:02–2:14]. The intervention’s median physician initial assessment time was 0:55 [95^th% CI: 0:53 to 0:58] versus 1:21 [95^th% CI: 1:18 to 1:25]. The intervention’s left-without-being-seen rate was 1.5% versus 2.2% for the control (p = 0.06). The MDRNSTAT subgroup analysis resulted in significant decreases in median EDLOS for discharged, non-consulted high (4:01 [95^th% CI: 3:43–4:16]) and low acuity patients (1:10 95^th% CI: 0:58–1:19]), as well as physician initial assessment time (0:25 [95^th% CI: 0:23–0:26]). No patients returned to the emergency department after being discharged by the MDRNSTAT at triage.

Conclusions

The intervention reduced delays and left-without-being-seen rate without increased return visits or jeopardizing urgent care of severely ill patients.

Trial registration number

NCT00991471 ClinicalTrials.gov

The role of full capacity protocols on mitigating overcrowding in EDs

OBJECTIVE

Overcrowding is an important issue facing many emergency departments (EDs). Access block (admitted patients occupying ED stretchers) is a leading contributor, and expeditious placement of admitted patients is an area of research interest. This review examined the effectiveness of full capacity protocols (FCPs) on mitigating ED overcrowding.

METHODS

A comprehensive literature search was undertaken to identify potentially relevant studies between 1966 and 2009. Intervention studies in which an FCP was used to influence ED/hospital length of stay and ED/hospital access block were included as a single program or part of a systemwide intervention. Two reviewers independently assessed citation relevance, inclusion, study quality, and extracted data; because of limited data, pooling was not undertaken.

RESULTS

From 14 446 potentially relevant studies, 2 abstracts from the same comparative study were included. From 29 studies on systemwide intervention, 4 contained an FCP component. The included study was a single-center ED study using a before-after design; its methodological quality was rated as weak. One of the abstracts reported that an FCP was associated with less ED length of stay (5-hour reduction) when compared with the comparison period; the other reported that an FCP decreased ED and hospital access block (28% and 37% reduction, respectively). The ED triggers, format, and implementation of FCP protocols varied widely.

CONCLUSION

Although FCPs may be a promising alternative for overcrowded EDs, the available evidence upon which to support implementation of an FCP is limited. Additional efforts are required to improve the outcome reporting of FCP research using high-quality research methods.

The role of triage liaison physicians on mitigating overcrowding in emergency departments: a systematic review

OBJECTIVES

The objective was to examine the effectiveness of triage liaison physicians (TLPs) on mitigating the effects of emergency department (ED) overcrowding.

METHODS

Electronic databases (Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, Web of Science, HealthSTAR, Dissertation Abstracts, and ABI/INFORM Global), controlled trial registry websites, conference proceedings, study references, contact with experts in the field, and correspondence with authors were used to identify potentially relevant TLP studies. Intervention studies in which a TLP was used to influence ED overcrowding metrics (length of stay [LOS] in minutes, physician initial assessment [PIA], and left without being seen [LWBS]) were included in the review. Two reviewers independently conducted data extraction and assessed the citation relevance, inclusion, and study quality. For continuous outcomes, weighted mean differences (WMD) were calculated and reported with corresponding 95% confidence intervals (CIs). For dichotomous variables, individual and pooled statistics were calculated as relative risk (RR) with 95% CI.

RESULTS

From 14,446 potentially relevant studies, 28 were included in the systematic review. Thirteen were journal publications, 12 were abstracts, and three were Web-based articles. Most studies employed before-after designs; 23 of the 28 studies were considered of weak quality. Based on the statistical pooling of data from two randomized controlled trials (RCTs), TLP resulted in shorter ED LOS compared to nurse-led triage (WMD = -36.85 min; 95% CI = -51.11 to -22.58). One of these RCTs showed a significant reduction in the PIA associated to TLP presence (WMD = -30.00 min; 95% CI = -56.91 to -3.09); the other RCT showed no change in LWBS due to a CI that included unity (RR = 0.82; 95% CI = 0.67 to 1.00).

CONCLUSIONS

While the evidence summarized here suggests that to have a TLP is an effective intervention to mitigate the effects of ED overcrowding, due to the weak research methods identified, more research is required before its widespread implementation.

The effect of emergency department crowding on clinically oriented outcomes

BACKGROUND

An Institute of Medicine (IOM) report defines six domains of quality of care: safety, patient-centeredness, timeliness, efficiency, effectiveness, and equity. The effect of emergency department (ED) crowding on these domains of quality has not been comprehensively evaluated.

OBJECTIVES

The objective was to review the medical literature addressing the effects of ED crowding on clinically oriented outcomes (COOs).

METHODS

We reviewed the English-language literature for the years 1989-2007 for case series, cohort studies, and clinical trials addressing crowding's effects on COOs. Keywords searched included "ED crowding,""ED overcrowding,""mortality,""time to treatment,""patient satisfaction,""quality of care," and others.

RESULTS

A total of 369 articles were identified, of which 41 were kept for inclusion. Study quality was modest; most articles reflected observational work performed at a single institution. There were no randomized controlled trials. ED crowding is associated with an increased risk of in-hospital mortality, longer times to treatment for patients with pneumonia or acute pain, and a higher probability of leaving the ED against medical advice or without being seen. Crowding is not associated with delays in reperfusion for patients with ST-elevation myocardial infarction. Insufficient data were available to draw conclusions on crowding's effects on patient satisfaction and other quality endpoints.

CONCLUSIONS

A growing body of data suggests that ED crowding is associated both with objective clinical endpoints, such as mortality, as well as clinically important processes of care, such as time to treatment for patients with time-sensitive conditions such as pneumonia. At least two domains of quality of care, safety and timeliness, are compromised by ED crowding.

Frequency, determinants and impact of overcrowding in emergency departments in Canada: a national survey

Several reports have documented the prevalence and severity of emergency department (ED) overcrowding at specific hospitals or cities in Canada; however, no study has examined the issue at a national level. A 54-item, self-administered, postal and web-based questionnaire was distributed to 243 ED directors in Canada to collect data on the frequency, impact and factors associated with ED overcrowding. The survey was completed by 158 (65% response rate) ED directors, 62% of whom reported overcrowding as a major or severe problem during the past year. Directors attributed overcrowding to a variety of issues including a lack of admitting beds (85%), lack of acute care beds (74%) and the increased length of stay of admitted patients in the ED (63%). They perceived ED overcrowding to have a major impact on increasing stress among nurses (82%), ED wait times (79%) and the boarding of admitted patients in the ED while waiting for beds (67%). Overcrowding is not limited to large urban centres; nor is it limited to academic and teaching hospitals. The perspective of ED directors reinforces the need for further examination of effective policies and interventions to reduce ED overcrowding.

Effectiveness of emergency department asthma management strategies on return visits in children: a population-based study

BACKGROUND

Emergency departments play an important role in the care of children with asthma. Emergency department return-visit rates provide a measure of the quality of acute asthma care.

OBJECTIVE

Our goal was to describe the characteristics of children treated in emergency departments for asthma, the resources and asthma management strategies used by emergency departments, and their effect on return visits within 72 hours.

DESIGN, SETTING, AND PATIENTS

We used a population-based cohort study that incorporated both comprehensive administrative heath and survey data from all 152 emergency departments in Ontario, Canada. We studied all 2- to 17-year-old children who had a visit to an emergency department for asthma from April 2003 to March 2005.

RESULTS

A total of 32,996 children (>9% of children with asthma in Ontario) had at least 1 visit to an emergency department for the care of asthma, and most of these visits (68.5%) were triaged as high acuity. The vast majority (148 of 152 [97%]) of emergency departments reported using at least 1 asthma management strategy, and 74% used 3 or more. The overall return-visit rate was 5.6%. Logistic regression models that accounted for the clustering of patients in emergency departments and controlled for patient and emergency department characteristics indicated that preprinted order sheets and access to a pediatrician for consultation were strategies significantly associated with a reduction in return visits. The 11 (17%) emergency departments that used both of these strategies had return visit rates of 4.4% compared with 6.9% in the 95 (63%) that used neither strategy.

CONCLUSIONS

Emergency departments use a range of strategies to manage asthma in children. Preprinted order sheets and access to pediatricians are associated with important reductions in return-visit rates, and more emergency departments should consider using these strategies.

Data collection on patients in emergency departments in Canada

OBJECTIVE

Relatively little is known about the ability of Canadian emergency departments (EDs) and the federal, provincial and territorial governments to quantify ED activity. The objectives of this study were to determine the use of electronic patient data in Canadian EDs, the accessibility of provincial data on ED visits, and to identify the data elements and current methods of ED information system (EDIS) data collection nationally.

METHODS

Surveys were conducted of the following 3 groups: 1) all ED directors of Canadian hospitals located in communities of >10,000 people, 2) all electronic EDIS vendors, and 3) representatives from the ministries of health from 13 provincial and territorial jurisdictions who had knowledge of ED data collection.

RESULTS

Of the 243 ED directors contacted, 158 completed the survey (65% response rate) and 39% of those reported using an electronic EDIS. All 11 EDIS vendor representatives responded. Most of the vendors provide a similar package of basic EDIS options, with add-on features. All 13 provincial or territorial government representatives completed the survey. Nine (69%) provinces and territories collect ED data, however the source of this information varies. Five provinces and territories collect triage data, and 3 have a comprehensive, jurisdiction-wide, population-based ED database. Thirty-nine percent of EDs in larger Canadian communities track patients using electronic methods. A variety of EDIS vendor options are available and used in Canada.

CONCLUSION

The wide variation in methods and in data collected presents serious barriers to meaningful comparison of ED services across the country. It is little wonder that the majority of information regarding ED overcrowding in Canada is anecdotal, when the collection of this critical health information is so variable. There is an urgent need to place the collection of ED information on the provincial and national agenda and to ensure that the collection of this information consistent, comprehensive and mandatory.