Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada

Objective To determine whether patients who are not admitted to hospital after attending an emergency department during shifts with long waiting times are at risk for adverse events

The International Population Data Linkage Network – Banff and Beyond

We write to you, here in the pages of the International Journal of Population Data Science, for the second time in our capacity of co-directors of the International Population Data Linkage Network (IPDLN – www.ipdln.org). Time has certainly passed quickly since our first communication, where we introduced ourselves, and discussed planned initiatives for our tenure as leads of the IPDLN. Our network’s scientific community is steadily growing and thriving in an era of heightened interest around all things ‘data’. Indeed, there is great enthusiasm for all initiatives that explore ways of harnessing information systems and multisource data to enhance collective knowledge of health matters so that better decisions can be made by governments, system planners, providers, and patients. Never before have such initiatives attracted more attention. It is in this context of heightened interest and relevance around IPDLN and its science that we prepare to convene in Banff, Alberta, Canada for the 5th biennial IPDLN Conference – September 11-14. The conference, to be held at the inspiring Banff Centre (www.banffcentre.ca), is almost sold out, with only limited space remaining for late registrants. A tremendous program has been created through the oversight of Scientific Program co-chairs, Drs. Astrid Guttman and Hude Quan. A compelling roster of plenary lectures from Drs. Diane Watson, Jennifer Walker, and Osmar Zaïane is eagerly anticipated, as are topical panel discussions, an entertaining Science Slam session, and a terrific social program. These sessions will be surrounded by rich scientific oral and poster presentations arising from the more than 450 scientific abstracts submitted for review. We are so pleased to see this vibrant scientific engagement from the IPDLN membership and students, and look forward to hosting all delegates in Banff. The Banff conference will also be the venue at which we announce the new Directorship of the IPDLN for the next two years (2019 and 2020). As co-directors, we engaged with a number of individuals and organizations with interest in leading the IPDLN. In the end, two compelling Directorship applications were submitted – one a joint bid from Australia’s Population Health Research Network and the South Australia Northern Territory DataLink, and the other from the US-based Actionable Intelligence for Social Policy. IPDLN members submitted votes on these strong leadership bids through an online voting process, and while the excellence and appeal of both bids was apparent in strong voter support for both, a winning bid has been confirmed, and it will (as mentioned) be announced at the upcoming September conference. As we look forward to the Banff meeting with great anticipation, we are compelled to acknowledge the growing IPDLN legacy created by past directors. We are particularly indebted to our immediate predecessor, Dr. David Ford, and his team at Swansea University. Their work in hosting the 2016 IPDLN conference has been an inspiration to us in the planning of this year’s conference, and their crucial and foundational work in creating an IT platform for the IPDLN website, the membership database, and the new International Journal for Population Data Science has brought the IPDLN to a new level of organizational sophistication. Over the last 18 months, our co-directorship teams from the Institute for Clinical Evaluative Sciences in Ontario and the O’Brien Institute for Public Health at the University of Calgary have built on the foundation established by prior directors to update/enhance the IPDLN website and membership database. The IPDLN has more members than ever before representing a greater number of countries, and we have a more formalized governance structure with the creation of an Executive Committee that will include immediate past-Directors in order to better ensure continuity. A new Executive Committee will be elected by the IPDLN membership following the Banff conference. The waiting is almost over and IPDLN 2018 is upon us! Our scientific domain has never had the prominence or level of anticipation that we currently see. And the IPDLN has grown in its size, vibrancy and scientific scope. The opportunities for us are boundless, and the timing of our upcoming conference could not be better. We are honoured, with our respective organizations, to have had this opportunity to serve as co-directors over the past two years, and look forward to seeing many of you very soon. For those of you who are unable to travel to Canada’s Rocky Mountains this year, we look forward to connecting with you at a later time in the IPDLN’s continuing upward journey

Users\u27 Guides to the Medical Literature: How to Use an Article about Mortality in a Humanitarian Emergency

The accurate interpretation of mortality surveys in humanitarian crises is useful for both publichealth responses and security responses. Recent examples suggest that few medical personnel andresearchers can accurately interpret the validity of a mortality survey in these settings. Using anexample of a mortality survey from the Democratic Republic of Congo (DRC), we demonstrateimportant methodological considerations that readers should keep in mind when reading amortality survey to determine the validity of the study and the applicability of the findings to theirsettings

Comparison of emergency department time performance between a Canadian and an Australian academic tertiary hospital

Objective To compare performance and factors predicting failure to reach Ontario and Australian government time targets between a Canadian (Sunnybrook Hospital) and an Australian (Austin Health) academic tertiary-level hospitals in 2012, and to assess for change of factors and performance in 2016 between the same hospitals. Methods This was a retrospective, observational study of patient administrative data in two calendar years. The main outcome measure was reaching Ontario and Australian ED time targets for admissions, high and low urgency discharges. Secondary outcomes were factors predicting failure to reach these targets. Results Between 2012 and 2016, Sunnybrook and Austin experienced increased patient volume of 10.2% and 19.2%, respectively. Bed capacity decreased at Sunnybrook (-10.8%) but increased at the Austin (+30.3%). For both years, Austin failed to achieve the Australian time target, but succeeded for all Ontario targets except for low urgency discharges. Sunnybrook failed all targets irrespective of year. The top factors for failing Ontario ED length-of-stay targets for both hospitals in 2012 and 2016 were bed request greater than 6 h, access block greater than 1 h, use of cross-sectional imaging, consultation and waiting for the emergency physician greater than 2 h. Conclusion Austin outperformed Sunnybrook for Ontario and Australian government time targets. Both hospitals failed the Australian targets. Factors predicting failure to achieve targets were different between hospitals, but were mainly clinical resources. Sunnybrook focussed on increasing human resources. Austin focussed on increasing human resources, observation unit and hospital beds. Intrinsic hospital characteristics and infrastructure influenced target success.Peer reviewe

Notches on the dial: a call to action to develop plain language communication with the public about users and uses of health data

Population data science [1] researchers are not alone in recognizing the value of health and health-related data. In the era of big data, and with advent of machine learning and other artificial intelligence methods, organizations around the world are actively working to turn data into knowledge, and, in some cases, profit. The media and members of the public have taken notice, with high profile news stories about data breaches and privacy concerns [2-4] alongside some stories that call for increased use of data [5,6]. In response, public and private sector data-holding organizations and jurisdictions are turning their attention to policies, processes and regulations intended to ensure that personal data are used in ways that that the public supports. In some cases, these efforts include involving “publics” in decisions about data, such as using patient and lay person advice and other inputs to help shape policies [7-10]

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

Introduction Integrating 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 Approach This 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. Results Over 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/Implications A 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

Users' Guides to the Medical Literature: How to Use an Article About Mortality in a Humanitarian Emergency

The accurate interpretation of mortality surveys in humanitarian crises is useful for both public health responses and security responses. Recent examples suggest that few medical personnel and researchers can accurately interpret the validity of a mortality survey in these settings. Using an example of a mortality survey from the Democratic Republic of Congo (DRC), we demonstrate important methodological considerations that readers should keep in mind when reading a mortality survey to determine the validity of the study and the applicability of the findings to their settings

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

Introduction Canadian 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 Approach The 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. Results As 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/Implications Through 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

A matched-pair cluster design study protocol to evaluate implementation of the Canadian C-spine rule in hospital emergency departments: Phase III

BACKGROUND: Physicians in Canadian emergency departments (EDs) annually treat 185,000 alert and stable trauma victims who are at risk for cervical spine (C-spine) injury. However, only 0.9% of these patients have suffered a cervical spine fracture. Current use of radiography is not efficient. The Canadian C-Spine Rule is designed to allow physicians to be more selective and accurate in ordering C-spine radiography, and to rapidly clear the C-spine without the need for radiography in many patients. The goal of this phase III study is to evaluate the effectiveness of an active strategy to implement the Canadian C-Spine Rule into physician practice. Specific objectives are to: 1) determine clinical impact, 2) determine sustainability, 3) evaluate performance, and 4) conduct an economic evaluation. METHODS: We propose a matched-pair cluster design study that compares outcomes during three consecutive 12-months "before," "after," and "decay" periods at six pairs of "intervention" and "control" sites. These 12 hospital ED sites will be stratified as "teaching" or "community" hospitals, matched according to baseline C-spine radiography ordering rates, and then allocated within each pair to either intervention or control groups. During the "after" period at the intervention sites, simple and inexpensive strategies will be employed to actively implement the Canadian C-Spine Rule. The following outcomes will be assessed: 1) measures of clinical impact, 2) performance of the Canadian C-Spine Rule, and 3) economic measures. During the 12-month "decay" period, implementation strategies will continue, allowing us to evaluate the sustainability of the effect. We estimate a sample size of 4,800 patients in each period in order to have adequate power to evaluate the main outcomes. DISCUSSION: Phase I successfully derived the Canadian C-Spine Rule and phase II confirmed the accuracy and safety of the rule, hence, the potential for physicians to improve care. What remains unknown is the actual change in clinical behaviors that can be affected by implementation of the Canadian C-Spine Rule, and whether implementation can be achieved with simple and inexpensive measures. We believe that the Canadian C-Spine Rule has the potential to significantly reduce health care costs and improve the efficiency of patient flow in busy Canadian EDs