Tracking emergency response actions during COVID-19 leads to development of an innovative public health evaluation tool.

SETTING: Early in the pandemic, KFL&A Public Health needed a way to capture, organize, and display COVID-19-related events to be accountable for and evaluate our actions. INTERVENTION: We used accessible software (Microsoft Office 365 suite, Microsoft PowerBI) to develop a data collection and visualization system. The Canadian Institute for Health Information (CIHI) developed a timeline and categorization approach for provincial and national COVID-related interventions, which was used to develop a regional version for local events using similar categories. We collected and displayed qualitative data alongside epidemiological data that allowed users to display different timelines of actions and outcomes and evaluate our response. OUTCOMES: In developing the timeline, we took stock of the information and data we wanted to collect, sort, and display locally. Next, we collected information on response actions, case and contact tracing, and staffing changes in a database that we displayed on a timeline. We included CIHI's data set to provide insight into pandemic response across all jurisdictions. IMPLICATIONS: Our timeline tool has many advantages for public health authorities beyond responding to a rapidly evolving emergency. By collecting information on events as they occur, decisions and actions are documented that may otherwise be overlooked. This enables decision-makers to visualize the impact of public health actions on health outcomes over time. The tool is completely customizable and scalable depending on the project scope and we plan to apply this method to other public health programming. Finally, we include lessons learned from quickly developing these tools in a real-time pandemic setting, both locally at KFL&A Public Health and nationally at CIHI.

RéSUMé: LIEU: Au début de la pandémie, le Bureau de santé de Kingston, Frontenac, Lennox et Addington (KFL&A) avait besoin d'un moyen de saisir, d'organiser et de présenter les événements liés à la COVID-19 pour pouvoir en rendre compte et évaluer ses actions. INTERVENTION: Nous avons utilisé des logiciels accessibles (Microsoft Office 365, Microsoft PowerBI) pour mettre au point un système de collecte et de visualisation de données. L'Institut canadien d'information sur la santé (ICIS) a créé un fil d'actualité et une approche de catégorisation pour les interventions provinciales et nationales liées à la COVID; nous avons créé une version régionale de ces outils pour présenter les événements locaux, en utilisant des catégories semblables. Nous avons collecté et affiché des données qualitatives en plus des données épidémiologiques, ce qui a permis aux utilisateurs d'afficher les mesures prises et leurs résultats sur différentes périodes et d'évaluer leurs interventions. RéSULTATS: Pour créer ce fil d'actualité, nous avons fait l'inventaire des informations et des données que nous voulions collecter, trier et présenter localement. Ensuite, nous avons réuni des informations sur les mesures d'intervention, les enquêtes sur les cas, la recherche de contacts et les changements de personnel dans une base de données, et nous les avons présentées dans un fil d'actualité. Nous avons inclus le jeu de données de l'ICIS pour apporter un éclairage sur la lutte contre la pandémie dans toutes les administrations du pays. CONSéQUENCES: Notre fil d'actualité présente de nombreux avantages pour les autorités de santé publique, en plus de la possibilité de réagir à une situation urgence qui évolue rapidement. En collectant des informations sur les événements à mesure qu'ils se produisent, il est possible de documenter des décisions et des mesures qui risquent d'être oubliées sinon. Cela permet aux décideurs de visualiser dans le temps l'effet des mesures de santé publique sur les résultats cliniques. L'outil est entièrement personnalisable et évolutif, selon la portée du projet, et nous avons l'intention de l'appliquer à d'autres programmes de santé publique. Enfin, nous présentons les leçons de la mise au point rapide d'un tel outil pendant une pandémie en temps réel, tant à l'échelle locale (à la Santé publique de KFL&A) qu'à l'échelle nationale (à l'ICIS).

Hospital Stays for Harm Caused by Substance Use among Youth in Canada.

The rise in harms associated with misuse of substances such as cannabis, alcohol and opioids is a public health issue gaining increasing importance in Canada. Taking a closer look at who is being hospitalized, and for which substances, helps inform efforts to improve access to services for youth. Between 2017 and 2018, hospitalizations for harm caused by substance use accounted for about one in 20 of all hospital stays among youths aged 10-24 years in Canada. Cannabis use was documented in nearly 40% of these hospitalizations, while alcohol was associated with 26%. Approximately one in every six youths (17%), who were hospitalized for harm caused by substance use, was hospitalized more than once for substance use within the same year.

Rural and urban disparities in the care of Canadian patients with inflammatory bowel disease: a population-based study.

BACKGROUND AND AIMS: Canada's large geographic area and low population density pose challenges in access to specialized health care for remote and rural residents. We compared health services use, surgical rate, and specialist gastroenterologist care in rural and urban inflammatory bowel disease (IBD) patients in Canada. METHODS: We used validated algorithms that were applied to population-based health administrative data to identify all people living with the following three Canadian provinces: Alberta, Manitoba, and Ontario (ON). We compared rural residents with urban residents for time to diagnosis, hospitalizations, outpatient visits, emergency department (ED) use, surgical rate, and gastroenterologist care. Multivariable regression compared the outcomes in rural/urban patients, controlling for confounders. Provincial results were meta-analyzed using random-effects models to produce overall estimates. RESULTS: A total of 36,656 urban and 5,223 rural residents with incident IBD were included. Outpatient physician visit rate was similar in rural and urban patients. IBD-specific and IBD-related hospitalization rates were higher in rural patients (incidence rate ratio [IRR] 1.17, 95% CI 1.02-1.34, and IRR 1.27, 95% CI 1.04-1.56, respectively). The rate of ED visits in ON were similarly elevated for rural patients (IRR 1.53, 95% CI 1.42-1.65, and IRR 1.33, 95% CI 1.25-1.40). There were no differences in surgical rates or prediagnosis lag time between rural and urban patients. Rural patients had fewer IBD-specific gastroenterologist visits (IRR 0.79, 95% CI 0.73-0.84) and a smaller proportion of their IBD-specific care was provided by gastroenterologists (28.3% vs 55.2%, P<0.0001). This was less pronounced in children <10 years at diagnosis (59.3% vs 65.0%, P<0.0001), and the gap was widest in patients >65 years (33.0% vs 59.2%, P<0.0001). CONCLUSION: There were lower rates of gastroenterologist physician visits, more hospitalizations, and greater rates of ED visits in rural IBD patients. These disparities in health services use result in costlier care for rural patients. Innovative methods of delivering gastroenterology care to rural IBD patients (such as telehealth, online support, and remote clinics) should be explored, especially for communities lacking easy access to gastroenterologists.

Comparing individual and area-based income measures: impact on analysis of inequality in smoking, obesity, and diabetes rates in Canadians 2003-2013.

OBJECTIVES: The aims of this study were to examine (1) the concordance between income measured at the individual and area-based level and (2) the impact of using each measure of income on inequality estimates for three health indicators-the prevalence, respectively, of diabetes, smoking, and obesity. METHODS: Data for the health indicators and individual income among adults came from six cycles of the Canadian Community Health Survey (cycles 2003 through 2013). Area-based income was obtained by linking respondents' residential postal codes to neighbourhood income quintiles derived from the 2006 Canadian census. Relative and absolute inequality between the lowest and highest income quintiles for each measure was assessed using rate ratios and rate differences, respectively. RESULTS: Concordance between the two income measures was poor in the overall sample (weighted Kappa estimates ranged from 0.19 to 0.21 for all years), and for the subset of participants reporting diabetes, smoking, or obesity. Despite the poor concordance, both individual and area-based income measures identified generally comparable levels of relative and absolute inequality in the rates of diabetes, smoking, and obesity over the 10-year study period. CONCLUSION: The results of this study show that individual and area-based income measures categorize Canadians differently according to income quintile, yet both measures reveal striking income-related inequalities in rates of diabetes and smoking, and obesity among women. This suggests that either individual or area-level measures can be used to monitor income-related health inequalities in Canada; however, whenever possible, it is informative to consider both measures since they likely represent distinct social constructs.

Corrigendum: Rural and Urban Residence During Early Life Is Associated with a Lower Risk of Inflammatory Bowel Disease: A Population-Based Inception and Birth Cohort Study.

This corrects the article DOI: 10.1038/ajg.2017.208.

Rural and Urban Residence During Early Life is Associated with Risk of Inflammatory Bowel Disease: A Population-Based Inception and Birth Cohort Study

OBJECTIVES: To determine the association between inflammatory bowel disease (IBD) and rural/urban household at the time of diagnosis, or within the first 5 years (y) of life. METHODS: Population-based cohorts of residents of four Canadian provinces were created using health administrative data. Rural/urban status was derived from postal codes based on population density and distance to metropolitan areas. Validated algorithms identified all incident IBD cases from administrative data (Alberta: 1999-2008, Manitoba and Ontario: 1999-2010, and Nova Scotia: 2000-2008). We determined sex-standardized incidence (per 100,000 patient-years) and incident rate ratios (IRR) using Poisson regression. A birth cohort was created of children in whom full administrative data were available from birth (Alberta 1996-2010, Manitoba 1988-2010, and Ontario 1991-2010). IRR was calculated for residents who lived continuously in rural/urban households during each of the first 5 years of life. RESULTS: There were 6,662 rural residents and 38,905 urban residents with IBD. Incidence of IBD per 100,000 was 33.16 (95% CI 27.24-39.08) in urban residents, and 30.72 (95% CI 23.81-37.64) in rural residents (IRR 0.90, 95% CI 0.81-0.99). The protective association was strongest in children <10 years (IRR 0.58, 95% CI 0.43-0.73) and 10-17.9 years (IRR 0.72, 95% CI 0.64-0.81). In the birth cohort, comprising 331 rural and 2,302 urban residents, rurality in the first 1-5 years of life was associated with lower risk of IBD (IRR 0.75-0.78). CONCLUSIONS: People living in rural households had lower risk of developing IBD. This association is strongest in young children and adolescents, and in children exposed to the rural environment early in life.

Assessing potentially inappropriate prescribing (PIP) and predicting patient outcomes in Ontario's older population: a population-based cohort study applying subsets of the STOPP/START and Beers' criteria in large health administrative databases.

INTRODUCTION: Adverse drug events (ADEs) are common in older people and contribute significantly to emergency department (ED) visits, unplanned hospitalisations, healthcare costs, morbidity and mortality. Many ADEs are avoidable if attention is directed towards identifying and preventing inappropriate drug use and undesirable drug combinations. Tools exist to identify potentially inappropriate prescribing (PIP) in clinical settings, but they are underused. Applying PIP assessment tools to population-wide health administrative data could provide an opportunity to assess the impact of PIP on individual patients as well as on the healthcare system. This would open new possibilities for interventions to monitor and optimise medication management on a broader, population-level scale. METHODS AND ANALYSIS: The aim of this study is to describe the occurrence of PIP in Ontario's older population (aged 65 years and older), and to assess the health outcomes and health system costs associated with PIP-more specifically, the association between PIP and the occurrence of ED visits, hospitalisations and death, and their related costs. This will be done within the framework of a population-based retrospective cohort study using Ontario's large health administrative and population databases. Eligible patients aged 66 years and older who were issued at least 1 prescription between 1 April 2003 and 31 March 2014 (approximately 2 million patients) will be included. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Ottawa Health Services Network Ethical Review Board and from the Bruyère Research Institute Ethics Review Board. Dissemination will occur via publication, presentation at national and international conferences, and ongoing exchanges with regional, provincial and national stakeholders, including the Ontario Drug Policy Research Network and the Ontario Ministry of Health and Long-Term Care. TRIAL REGISTRATION NUMBER: Registered with clinicaltrials.gov (registration number: NCT02555891).

Potentially inappropriate prescribing (PIP) in long-term care (LTC) patients: validation of the 2014 STOPP-START and 2012 Beers criteria in a LTC population--a protocol for a cross-sectional comparison of clinical and health administrative data.

INTRODUCTION: Potentially inappropriate prescribing (PIP) is frequent and problematic in older patients. Identifying PIP is necessary to improve prescribing quality; ideally, this should be performed at the population level. Screening Tool of Older Persons' potentially inappropriate Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) and Beers criteria were developed to identify PIP in clinical settings and are useful at the individual patient level; however, they are time-consuming and costly to apply. Only a subset of these criteria is applicable to routinely collected population-level health administrative data (HAD) because the clinical information necessary to implement these tools is often missing from databases. The performance of subsets of STOPP/START and Beers criteria in HAD compared with clinical data from the same patients is unknown; furthermore, the performance of the updated 2014 STOPP-START and 2012 Beers criteria compared with one another is also unknown. METHODS AND ANALYSIS: A cross-sectional study of linked HAD and clinical data will be conducted to validate the subsets of STOPP/START and Beers criteria applicable to HAD by comparing their performance when applied to clinical and HAD for the same patients. Eligible patients will be 66 years and over and recently admitted to 1 of 6 long-term care facilities in Ottawa, Ontario. The target sample size is 275, but may be less if statistical significance can be achieved sooner. Medication, diagnostic and clinical data will be collected by a consultant pharmacist. The main outcome measure is the proportion of PIP missed by the subset of STOPP/START and Beers criteria applied to HAD when compared with clinical data. ETHICS AND DISSEMINATION: The study was approved by the Ottawa Health Services Network Research Ethics Board, the Bruyère Continuing Care Research Ethics Board and the ethics board of the City of Ottawa Long Term Care Homes. Dissemination will occur via publication, national and international conference presentations, and exchanges with regional, provincial and national stakeholders. TRIAL REGISTRATION NUMBER: NCT02523482.

Use of Preoperative Magnetic Resonance Imaging for Breast Cancer: A Canadian Population-Based Study.

IMPORTANCE: Contrary to practice guidelines, breast magnetic resonance imaging (MRI) is commonly used in the preoperative evaluation of women with breast cancer. While existing literature has found little benefit to MRI in most patients, potential downstream consequences associated with breast MRI are not well described. OBJECTIVE: To describe patterns of preoperative breast MRI utilization in a health care system with universal insurance and its association with downstream investigations and clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS: This was a population-based retrospective cohort study using administrative heath care databases in Ontario, Canada (2012 population, 13.5 million) over 14 geographic regions were evaluated within the data set. Participants comprised 53 015 patients with primary operable breast cancer treated from 2003 to 2012. MAIN OUTCOMES AND MEASURES: Use of preoperative breast MRI by year, geographic region, and breast cancer stage. Postdiagnosis imaging, biopsy, and short-term surgical outcomes were also evaluated between those who did and did not receive MRI. RESULTS: Overall, 14.8% of patients (7824 of 53 015) had a preoperative MRI. During the 10-year study period, MRI use increased across all stages by 8-fold (from 3% to 24%; P < .001 for trend). Factors associated with MRI use were younger age, higher socioeconomic status, higher Charlson comorbidity score, surgery performed in a teaching hospital, and fewer years of surgeon experience. Multivariate analyses showed that preoperative breast MRI was associated with higher likelihood of the following: postdiagnosis breast imaging (odds ratio [OR], 2.09; 95% CI, 1.92-2.28), postdiagnosis breast biopsies (OR, 1.74; 95% CI, 1.57-1.93), postdiagnosis imaging to assess for distant metastatic disease (OR, 1.51; 95% CI, 1.42-1.61), mastectomy (OR, 1.73; 95% CI, 1.62-1.85), contralateral prophylactic mastectomy (OR, 1.48; 95% CI, 1.23-1.77), and a greater than 30-day wait to surgery (OR, 2.52; 95% CI, 2.36-2.70) (all ORs are adjusted). CONCLUSIONS AND RELEVANCE: Preoperative breast MRI use has increased substantially in routine clinical practice and is associated with a significant increase in ancillary investigations, wait time to surgery, mastectomies, and contralateral prophylactic mastectomies.

Imaging for distant metastases in women with early-stage breast cancer: a population-based cohort study.

BACKGROUND: Practice guidelines recommend that imaging to detect metastatic disease not be performed in the majority of patients with early-stage breast cancer who are asymptomatic. We aimed to determine whether practice patterns in Ontario conform with these recommendations. METHODS: We used provincial registry data to identify a population-based cohort of Ontario women in whom early-stage, operable breast cancer was diagnosed between 2007 and 2012. We then determined whether imaging of the skeleton, thorax, and abdomen or pelvis had been performed within 3 months of tissue diagnosis. We calculated rates of confirmatory imaging of the same body site. RESULTS: Of 26,547 patients with early-stage disease, 22,811 (85.9%) had at least one imaging test, and a total of 83,249 imaging tests were performed (mean of 3.7 imaging tests per patient imaged). Among patients with pathologic stage I and II disease, imaging was performed in 79.6% (10,921/13,724) and 92.7% (11,882/12,823) of cases, respectively. Of all imaging tests, 19,784 (23.8%) were classified as confirmatory investigations. Imaging was more likely for patients who were younger, had greater comorbidity, had tumours of higher grade or stage or had undergone preoperative breast ultrasonography, mastectomy or surgery in the community setting. INTERPRETATION: Despite recommendations from multiple international guidelines, most Ontario women with early-stage breast cancer underwent imaging to detect distant metastases. Inappropriate imaging in asymptomatic patients with early-stage disease is costly and may lead to harm. The use of population datasets will allow investigators to evaluate whether or not strategies to implement practice guidelines lead to meaningful and sustained change in physician practice.

Next generation neonatal health informatics with Artemis.

This paper describes the deployment of a platform to enable processing of currently uncharted high frequency, high fidelity, synchronous data from medical devices. Such a platform would support the next generation of informatics solutions for neonatal intensive care. We present Artemis, a platform for real-time enactment of clinical knowledge as it relates to multidimensional data analysis and clinical research. Through specific deployment examples at two different neonatal intensive care units, we demonstrate that Artemis supports: 1) instantiation of clinical rules; 2) multidimensional analysis; 3) distribution of services for critical care via cloud computing; and 4) accomplishing 1 through 3 using current technology without a negative impact on patient care.

Multi-dimensional knowledge translation: enabling health informatics capacity audits using patient journey models.

This paper presents a multi-dimensional approach to knowledge translation, enabling results obtained from a survey evaluating the uptake of Information Technology within Neonatal Intensive Care Units to be translated into knowledge, in the form of health informatics capacity audits. Survey data, having multiple roles, patient care scenarios, levels, and hospitals, is translated using a structured data modeling approach, into patient journey models. The data model is defined such that users can develop queries to generate patient journey models based on a pre-defined Patient Journey Model architecture (PaJMa). PaJMa models are then analyzed to build capacity audits. Capacity audits offer a sophisticated view of health informatics usage, providing not only details of what IT solutions a hospital utilizes, but also answering the questions: when, how and why, by determining when the IT solutions are integrated into the patient journey, how they support the patient information flow, and why they improve the patient journey.

Multi-dimensional temporal abstraction and data mining of medical time series data: trends and challenges.

This paper presents emerging trends in the area of temporal abstraction and data mining, as applied to multi-dimensional data. The clinical context is that of Neonatal Intensive Care, an acute care environment distinguished by multi-dimensional and high-frequency data. Six key trends are identified and classified into the following categories: (1) data; (2) results; (3) integration; and (4) knowledge base. These trends form the basis of next-generation knowledge discovery in data systems, which must address challenges associated with supporting multi-dimensional and real-world clinical data, as well as null hypothesis testing. Architectural drivers for frameworks that support data mining and temporal abstraction include: process-level integration (i.e. workflow order); synthesized knowledge bases for temporal abstraction which combine knowledge derived from both data mining and domain experts; and system-level integration.

Predicting high-risk preterm birth using artificial neural networks.

A reengineered approach to the early prediction of preterm birth is presented as a complimentary technique to the current procedure of using costly and invasive clinical testing on high-risk maternal populations. Artificial neural networks (ANNs) are employed as a screening tool for preterm birth on a heterogeneous maternal population; risk estimations use obstetrical variables available to physicians before 23 weeks gestation. The objective was to assess if ANNs have a potential use in obstetrical outcome estimations in low-risk maternal populations. The back-propagation feedforward ANN was trained and tested on cases with eight input variables describing the patient's obstetrical history; the output variables were: 1) preterm birth; 2) high-risk preterm birth; and 3) a refined high-risk preterm birth outcome excluding all cases where resuscitation was delivered in the form of free flow oxygen. Artificial training sets were created to increase the distribution of the underrepresented class to 20%. Training on the refined high-risk preterm birth model increased the network's sensitivity to 54.8%, compared to just over 20% for the nonartificially distributed preterm birth model.