Objective Social determinants of health (SDOH) have been shown to be important predictors of health outcomes. Here we assess how best to extract SDOH variables from inpatient electronic medical record (EMR) data. Approach Four social determinants were targeted: patient language barriers, employment status, education, and whether the patient lives alone. Inpatients aged 18 and older with records in the Calgary-wide EMR system were studied. Algorithms were developed on January 2019 hospital admissions (n=8,999), and validated on January 2018 hospital admissions (n=8,839). SDOH documented as structured data, which can be easily queried, were compared against those extracted from unstructured free-text notes. Results More than twice as many patients had an unstructured note documenting a language barrier than in the structured data; 12% of patients indicated by notes to be living alone had a partner in their structured marital status. The Positive Predictive Value (PPV) of the elements extracted from notes was high, at 99% (95% CI 94.0%-100.0%) for language barriers, 98% (95% CI 92.6%-99.9%) for living alone, 96% (95% CI 89.8%-98.8%) for unemployment, and 88% (95% CI 80.0%-93.1%) for retirement. Conclusions It is possible to extract SDOH elements from free text notes with high PPV. SDOH documentation was largely missing in structured data, and sometimes misleading. Implications Free text notes can be a fruitful source of information for projects using SDOH variables, such as machine learning/AI or health services research, and can offer insights not available from the structured data elements.

This study investigated the changing pattern of cannabis-related health care use among the general population and subgroups in Alberta, with insights from two significant events: the Cannabis Act amendment (legalization of edibles, extracts, and topicals (EET)) in October 2019 and the COVID-19 pandemic in April 2020. Incidence rates of cannabis-related emergency department or urgent care center (ED/UCC) visits, hospitalizations, cannabinoid hyperemesis syndrome–related ED/UCC visits, Poison and Drug Information Service (PADIS) calls, and Health Link (HL) calls were calculated. Interrupted time-series design was employed to determine level and slope changes in the post-amendment and pandemic periods. Among the general population, the Cannabis Act amendment led to a slope change in cannabis-related PADIS call, but the COVID-19 pandemic led to significant level changes in almost all outcomes. Furthermore, the impact of Cannabis Act amendment and pandemic on cannabis-related health care use varied by age, sex, geography, and socioeconomic status. The increase in cannabis-related health care utilization suggests that further relaxations of the cannabis regulatory framework should carefully consider the short- and long-term impacts on public health and safety.

Alberta Health Services (AHS) Community Helpers Program (CHP) to enhance mental health among youth. Identifying the impact of CHP on mental illness–related acute care use among adolescents aged 12–18 years in Edmonton and determining cost avoidance. Using administrative data from AHS, public school catchment area data from the Edmonton Public School Board, and area-level socioeconomic deprivation status indicators from the Pampalon deprivation index, we applied geographical regression discontinuity design to estimate the effect of CHP implementation on depression-, anxiety-, and suicide-related acute care use (emergency department visits and inpatient admissions). Cost data were derived from Interactive Health Data Application of Alberta Health. The study period (2002–2022) included pre (2002–2011) and post (2012–2020) CHP implementation periods. CHP had statistically significant impact when distance from the boundary (catchment area identifier to divide the sample into treated and control groups) was between 600 and 800 m. About 90 and 80 fewer anxiety- and depression-related visits (per 1000 visits) were observed among individuals aged 12–15 and 16–18 years, respectively, in catchment areas of the public schools where CHP was implemented. Impact of CHP on suicide-related visits was only statistically significant among individuals aged 12–15 years. Annual cost reduction ranged from 161,117 to269,255 for anxiety- and depression-related visits. Findings show contextual effect of CHP; i.e., being potentially exposed to the program reduced the likelihood of anxiety- and depression-related visits. Costs of CHP implementation could be compared with the avoided costs to assess economic benefits of implementing CHP.

Abstract Background Maternal depression and anxiety can have a detrimental impact on birth outcomes and healthy child development; there is limited knowledge on its influence on immunization schedule adherence. Therefore, the objectives of this study were to determine the impact of maternal depression and anxiety in the perinatal period on prolonged vaccine delay of childhood vaccines. Methods In this prospective cohort study, we analyzed linked survey and administrative data of 2,762 pregnant women in Calgary, Alberta, Canada. Data were collected at two time-points: prenatal (< 25 weeks of gestation) and postpartum (4 months postpartum). We used multivariable logistic regression to examine the association between depression and anxiety with prolonged immunization delay, adjusting for covariates. Results In multivariable analysis, maternal depression at either time point was not associated with prolonged delay for DTaP-IPV-Hib (OR 1.16, 95% CI 0.74–1.82), MMR/MMRV (OR 1.03, 95% CI 0.72–1.48), or all routine childhood vaccines combined (OR 1.32, 95% CI 0.86–2.04). Maternal anxiety at either time point was also not associated with prolonged delayed for DTaP-IPV-Hib (OR 1.08, 95% CI 0.77–1.53), MMR/MMRV (OR 1.07, 95% CI 0.82–1.40), or all vaccines combined (OR 1.00, 95% CI 0.80–1.26). In both the depression and anxiety models, children of Canadian-born mothers had higher odds of prolonged delay, as did those with low-income mothers. Conclusion Health care providers can be reassured that maternal depression and anxiety do not appear to influence maternal commitment to routine immunization. Findings suggested that low income and household moves may influence adherence to vaccine schedules and health care providers may want to provide anticipatory guidance to these families.

BACKGROUND:Social determinants of health (SDOH) have been shown to be important predictors of health outcomes. Here we developed methods to extract them from inpatient electronic medical record (EMR) data using techniques compatible with current EMR systems. METHODS:Four social determinants were targeted: patient language barriers, employment status, education, and whether the patient lives alone. Inpatients aged 18 and older with records in the Calgary-wide EMR system were studied. Algorithms were developed on the January 2019 hospital admissions (n=8,999) and validated on the January 2018 hospital admissions (n=8,839). SDOH documented as structured data were compared against those extracted from unstructured free-text notes. RESULTS:More than twice as many patients had a note documenting a language barrier in EMR data than in structured data; 12 % of patients indicated by EMR notes to be living alone had a partner noted in their structured marital status. The Positive Predictive Value (PPV) of the elements extracted from notes was high, at 99 % (95 % CI 94.0 %-100.0 %) for language barriers, 98 % (95 % CI 92.6 %-99.9 %) for living alone, 96 % (95 % CI 89.8 %-98.8 %) for unemployment, and 88 % (95 % CI 80.0 %-93.1 %) for retirement. CONCLUSIONS:All SDOH elements were extracted with high PPV. SDOH documentation was largely missing in structured data and sometimes misleading.

IntroductionData unavailability poses multiple challenges in many health fields, especially within ethnic subgroups in Canada, who may be hesitant to share their health data with researchers. Since health information availability is controlled by the participant, it is important to understand the willingness to share health information by an ethnic population to increase data availability within ethnocultural communities. MethodsWe employed a qualitative descriptive approach to better understand willingness to share health information by South Asian participants and operated through a lens that considered the cultural and sociodemographic aspect of ethnocultural communities. A total of 22 in-depth interviews were conducted between March and July 2020. ResultsThe results of this study show that health researchers should aim to develop a mutually beneficial information-sharing partnership with communities, with an emphasis on the ethnocultural and socio-ecological aspects of health within populations. ConclusionThe findings support the need for culturally sensitive and respectful engagement with the community, ethically sound research practices that make participants feel comfortable in sharing their information, and an easy sharing process to share health information feasibly.

Social Determinant of Health (SDOH) data are important targets for research and innovation in Health Information Systems (HIS). The ways we envision SDOH in "smart" information systems will play a considerable role in shaping future population health landscapes. Current methods for data collection can capture wide ranges of SDOH factors, in standardised and nonstandardised formats, from both primary and secondary sources. Advances in automating data linkage and text classification show particular promise for enhancing SDOH in HIS. One challenge is that social communication processes embedded in data collection are directly related to the inequalities that HIS attempt to measure and redress. To advance equity, it is imperative thatcare-providers, researchers, technicians, and administrators attend to power dynamics in HIS standards and practices. We recommend: 1. Investing in interdisciplinary and intersectoral knowledge generation and translation. 2. Developing novel methods for data discovery, linkage and analysis through participatory research. 3. Channelling information into upstream evidence-informed policy.

Background Independently, active maternal and environmental tobacco smoke exposure and maternal stress have been linked to an increased risk of preterm birth and low birth weight. An understudied relationship is the potential for interactive effects between these risk factors. Methods Data was obtained from the All Our Families cohort, a study of 3,388 pregnant women < 25 weeks gestation recruited from those receiving prenatal care in Calgary, Canada between May 2008 and December 2010. We investigated the joint effects of active maternal smoking, total smoke exposure (active maternal smoking plus environmental tobacco smoke) and prenatal stress (Perceived Stress Scale, Spielberger State-Trait Anxiety Inventory), measured at two time points (< 25 weeks and 34–36 weeks gestation), on preterm birth and low birth weight. Results A marginally significant association was observed with the interaction active maternal smoking and Spielberger State-Trait Anxiety Inventory scores in relation to low birth weight, after imputation (aOR = 1.02, 95%CI: 1.00-1.03, p = 0.06). No significant joint effects of maternal stress and either active maternal smoking or total smoke exposure with preterm birth were observed. Active maternal smoking, total smoke exposure, Perceived Stress Scores, and Spielberger State-Trait Anxiety Inventory scores were independently associated with preterm birth and/or low birth weight. Conclusions Findings indicate the role of independent effects of smoking and stress in terms of preterm birth and low birthweight. However, the etiology of preterm birth and low birth weight is complex and multifactorial. Further investigations of potential interactive effects may be useful in helping to identify women experiencing vulnerability and inform the development of targeted interventions.

Background: Knowledge pertaining to the health and health care utilization of patients after recovery from acute COVID-19 is limited. We sought to assess the frequency of new diagnoses of disease and health care use after hospitalization with COVID-19. Methods: We included all patients hospitalized with COVID-19 in Alberta between Mar. 5 and Dec. 31, 2020. Additionally, 2 matched controls (SARS-CoV-2 negative) per case were included and followed up until Apr. 30, 2021. New diagnoses and health care use were identified from linked administrative health data. Repeated measures were made for the periods 1–30 days, 31–60 days, 61–90 days, 91–180 days, and 180 and more days from the index date. We used multivariable regression analysis to evaluate the association of COVID-19-related hospitalization with the number of physician visits during follow-up. Results: The study sample included 3397 cases and 6658 controls. Within the first 30 days of follow-up, the case group had 37.12% (95% confidence interval [CI] 35.44% to 38.80%) more patients with physician visits, 11.12% (95% CI 9.77% to 12.46%) more patients with emergency department visits and 2.92% (95% CI 2.08% to 3.76%) more patients with hospital admissions than the control group. New diagnoses involving multiple organ systems were more common in the case group. Regression results indicated that recovering from COVID-19-related hospitalization, admission to an intensive care unit, older age, greater number of comorbidities and more prior health care use were associated with increased physician visits. Interpretation: Patients recovered from the acute phase of COVID-19 continued to have greater health care use up to 6 months after hospital discharge. Research is required to further explore the effect of post-COVID-19 conditions, pre-existing health conditions and health-seeking behaviours on health care use.

BACKGROUND:We studied the impact of fine particulate matter (PM2.5) exposure due to a remote wildfire event in the Pacific Northwest on daily outpatient respiratory and cardiovascular physician visits during wildfire (24-31 August, 2015) and post-wildfire period (1-30 September, 2015) relative to the pre-wildfire period (1-23 August, 2015) in the city of Calgary, Canada.METHODS:A quasi-Poisson regression model was used for modelling daily counts of physician visits due to PM2.5 while adjusting for day of the week (weekday versus weekend or public holiday), wildfire exposure period (before, during, after), methane, relative humidity, and wind direction. A subgroup analysis of those with pre-existing diabetes or hypertension was performed.RESULTS:An elevated risk of respiratory disease morbidity of 33% (relative risk: RR) [95% confidence interval (CI): 10%-59%] and 55% (95% CI: 42%-69%) was observed per 10µg/m3 increase in PM2.5 level during and after wildfire, respectively, relative to the pre-wildfire time period. Increased risk was observed for children aged 0-9 years during (RR = 1.57, 95% CI: 1.21-2.02) and after the wildfire (RR = 2.11, 95% CI: 1.86-2.40) especially for asthma, acute bronchitis and acute respiratory infection. The risk of physician visits among seniors increased by 11% (95% CI: 3%-21%), and 19% (95% CI: 7%-33%) post-wildfire for congestive heart failure and ischaemic heart disease, respectively. Individuals with pre-existing diabetes had an increased risk of both respiratory and cardiovascular morbidity in the post-wildfire period (RR = 1.35, 95% CI: 1.09-1.67; RR = 1.22, 95% CI: 1.01-1.46, respectively).CONCLUSIONS:Wildfire-related PM2.5 exposure led to increased respiratory condition-related outpatient physician visits during and after wildfires, particularly for children. An increased risk of physician visits for congestive heart failure and ischaemic heart disease among seniors in the post-wildfire period was also observed.

BackgroundThe COVID-19 pandemic has seen a large surge in case numbers over several waves, and has critically strained the health care system, with a significant number of cases requiring hospitalization and ICU admission. This study used a decision tree modeling approach to identify the most important predictors of severe outcomes among COVID-19 patients.MethodsWe identified a retrospective population-based cohort (n = 140,182) of adults who tested positive for COVID-19 between 5th March 2020 and 31st May 2021. Demographic information, symptoms and co-morbidities were extracted from a communicable disease and outbreak management information system and electronic medical records. Decision tree modeling involving conditional inference tree and random forest models were used to analyze and identify the key factors(s) associated with severe outcomes (hospitalization, ICU admission and death) following COVID-19 infection.ResultsIn the study cohort, nearly 6.37% were hospitalized, 1.39% were admitted to ICU and 1.57% died due to COVID-19. Older age (>71Y) and breathing difficulties were the top two factors associated with a poor prognosis, predicting about 50% of severe outcomes in both models. Neurological conditions, diabetes, cardiovascular disease, hypertension, and renal disease were the top five pre-existing conditions that altogether predicted 29% of outcomes. 79% of the cases with poor prognosis were predicted based on the combination of variables. Age stratified models revealed that among younger adults (18–40 Y), obesity was among the top risk factors associated with adverse outcomes.ConclusionDecision tree modeling has identified key factors associated with a significant proportion of severe outcomes in COVID-19. Knowledge about these variables will aid in identifying high-risk groups and allocating health care resources.

ObjectiveUnder-immunization increases the risk of acquiring vaccine-preventable diseases in children and the community. The targeted coverage rate for routine childhood immunization in Alberta, especially in disadvantaged communities in rural and remote geographic areas, has not been achieved for many years. This study was conducted to identify reasons for under-immunization in children in low socioeconomic status (SES) communities and propose suggestions to address issues/concerns identified by low SES parents for improving immunization coverage in their communities.MethodsFourteen semi-structured phone interviews of low SES parents with under-immunized children living in rural and remote geographic areas in Northern Alberta were conducted. Transcripts were analyzed to identify relevant themes.ResultsBusy lifestyles of many parents prevented them from taking their children to clinics for immunization, which were exacerbated by long distances to clinics, transportation issues, operating hours of clinics, and lack of reminders. Many disadvantaged parents also exhibited varying levels of vaccine hesitancy due to safety concerns, especially about newer vaccines, thereby causing some parents to delay immunizing their child intentionally.ConclusionImplementing procedures to alleviate access issues, such as offering extended operating hours, opening drop-in clinics/satellite clinics in distant areas, nurse visits to their homes, updating contact information of parents, frequent reminder options and addressing safety and effectiveness concerns about vaccines in plain language using evidence-based communication strategies can promote timely immunization among children of low SES parents.

BACKGROUND:To expand research and strategies to prevent disease, comprehensive and real-time data are essential. Health data are increasingly available from platforms such as pharmaceuticals, genomics, health care imaging, medical procedures, wearable devices, and internet activity. Further, health data are integrated with an individual's sociodemographic information, medical conditions, genetics, treatments, and health care. Ultimately, health information generation and flow are controlled by the patient or participant; however, there is a lack of understanding about the factors that influence willingness to share health information. A synthesis of the current literature on the multifactorial nature of health information sharing preferences is required to understand health information exchange. OBJECTIVE:The objectives of this review are to identify peer-reviewed literature that reported factors associated with health information sharing and to organize factors into cohesive themes and present a narrative synthesis of factors related to willingness to share health information. METHODS:This review uses a rapid review methodology to gather literature regarding willingness to share health information within the context of eHealth, which includes electronic health records, personal health records, mobile health information, general health information, or information on social determinants of health. MEDLINE and Google Scholar were searched using keywords such as electronic health records AND data sharing OR sharing preference OR willingness to share. The search was limited to any population that excluded health care workers or practitioners, and the participants aged ≥18 years within the US or Canadian context. The data abstraction process using thematic analysis where any factors associated with sharing health information were highlighted and coded inductively within each article. On the basis of shared meaning, the coded factors were collated into major themes. RESULTS:A total of 26 research articles met our inclusion criteria and were included in the qualitative analysis. The inductive thematic coding process revealed multiple major themes related to sharing health information. CONCLUSIONS:This review emphasized the importance of data generators' viewpoints and the complex systems of factors that shape their decision to share health information. The themes explored in this study emphasize the importance of trust at multiple levels to develop effective information exchange partnerships. In the case of improving precision health care, addressing the factors presented here that influence willingness to share information can improve sharing capacity for individuals and allow researchers to reorient their methods to address hesitation in sharing health information.

Accurate and reliable short-term forecasts of influenza-like illness (ILI) visit volumes at emergency departments can improve staffing and resource allocation decisions within hospitals. In this paper, we developed a stacked ensemble model that averages the predictions from various competing methodologies in the current frontier for ILI-related forecasts. We also constructed a back-of-the-envelope prediction interval for the stacked ensemble, which provides a conservative characterization of the uncertainty in the stacked ensemble predictions. We assessed the accuracy and reliability of our model with 1 to 4 weeks ahead forecast targets using real-time hospital-level data on weekly ILI visit volumes during the 2012-2018 flu seasons in the Alberta Children's Hospital, located in Calgary, Alberta, Canada. Our results suggest the forecasting performance of the stacked ensemble meets or exceeds the performance of the individual models over all forecast targets.

OBJECTIVES:Childhood immunization coverage rates are known to be disproportionate according to population's socioeconomic status (SES). This systematic review examined and appraised quality of interventions deemed effective to increase routine childhood immunization uptake in low SES populations in developed countries. METHODS:A literature search was conducted using Medline, Embase, CINAHL, EBMR, PsycInfo, PubMed, and Health STAR. We systematically searched and critically appraised articles published between January 1990 and December 2019 using the Effective Public Health Practice Project Quality Assessment tool. This systematic review provides a synthesis of the available evidence for childhood immunization interventions deemed effective for low SES parents or families of children ≤ 5 years of age. SYNTHESIS:The search yielded 3317 records, of which 2975 studies met the inclusion criteria. From the 100 relevant studies, a total of 40 were included. The majority of effective and strongly rated studies synthesized consisted of multi-component interventions. Such interventions addressed access, community-based mobilization, outreach, appointment reminders, education, clinical tracking and incentives, and were language and health literacy appropriate to support low SES parents. Improving access to low SES parents was deemed effective in the vast majority of strongly rated studies. Incorrect contact information of low SES parents due to increased social mobility (i.e. household moves) rendered reminders ineffective, and therefore, updating contact information should be pursued proactively by front-line healthcare providers. In addition, plain language communication with low SES parents regarding immunization was deemed effective in improving immunization uptake. CONCLUSION:Comprehensive multi-component interventions including improved access, appointment reminders, education and precision health communication are effective for addressing health inequities in immunization coverage amongst marginalized populations. Most low SES parents still believe that the benefits of immunization outweigh the risks.

Background: Electronic Health Records (EHRs) are key tools for integrating patient data into health information systems (IS). Advances in automated data collection methodology, particularly the collection of social determinants of health (SDOH), provide opportunities to advance health promotion and illness prevention through advanced analytics (i.e. “Big Data” techniques). We ask how current data collection processes in EHRs permit SDOH data to flow throughout health systems. Methods: Using a scoping review framework, we searched through medical literature to identify current practices in SDOH data collection within EHR systems. We extracted relevant information on data collection methodology, specifically focusing on uses of automated technology. We discuss our findings in the context of research methodology and potential for health equity. Results: Practitioners collect a variety of SDOH data at point of care through EHR, predominantly via embedded screening tools and clinical notes, and primarily capturing data on financial security, housing status, and social support. Health systems are increasingly using digital technology in data collection, including natural language processing algorithms. However overall use of automated technology is limited to date. End uses of data pertain to improving system efficiency, patient care-coordination, and addressing health disparities. Discussion & Conclusion: EHRs can realistically promote collection and meaningful use of SDOH data, although EHRs have not extensively been used to collect and manage this type of information. Future applied research on systems-level application of SDOH data is necessary, and should incorporate a range of stakeholders and interdisciplinary teams of researchers and practitioners in fields of health, computing, and social sciences.

BackgroundUnderstanding reasons for and against vaccination from the parental perspective is critical for designing vaccination campaigns and informing other interventions to increase vaccination uptake in Canada. The objective of this study was to understand maternal vaccination decision making for children.MethodsMothers participating in a longitudinal community-based pregnancy cohort, the All Our Babies study in Calgary, Alberta, completed open-ended survey questions providing explanations for the vaccination status of their child by 24months postpartum. Qualitative responses were linked to administrative vaccination records to examine survey responses and recorded child vaccination status.ResultsThere were 1560 open-ended responses available; 89% (n=1391) provided explanations for vaccinating their children, 5% (n=79) provided explanations for not vaccinating/delaying, and 6% (n=90) provided explanations for both. Themes were similar for those vaccinating and not vaccinating/delaying; however, interpretations were different. Two broad themes were identified: Sources of influence and Deliberative Processes. Sources of influence on decision making included personal, family, and external experiences. Deliberative Processes included risk, research, effectiveness, and balancing risks/benefits. Under Deliberative Processes, responsibility was a category for those vaccinating; while choice, instrumental/practical, and health issues were categories for those not vaccinating/delaying. Mothers' levels of conviction and motivation provided a Context for understanding their decision making perspectives.ConclusionsVaccination decision making is complex and impacted by many factors that are similar but contribute to different decisions depending on mothers' perspectives. The results of this study indicate the need to examine new intervention approaches to increase uptake that recognize and address feelings of pressure and parental commitment to choice.

Clinical mastitis (CM) is one of the most frequent and costly diseases in dairy cows. A frustrating aspect of CM is its recurrent nature. This review was conducted to synthesize knowledge on risk of repeated cases of CM, effects of recurrent CM cases, and risk factors for CM recurrence. A systematic review methodology was used to identify articles for this narrative review. Searches were performed to identify relevant scientific literature published after 1989 in English or French from 2 databases (PubMed and CAB Abstracts) and 1 search platform (Web of Science). Fifty-seven manuscripts were selected for qualitative synthesis according to the inclusion criteria. Among the 57 manuscripts selected in this review, a description of CM recurrence, its risk factors, and effects were investigated and reported in 33, 37, and 19 selected manuscripts, respectively. Meta-analysis and meta-regression analyses were used to compute risk ratio comparing risk of CM in cows that already had 1 CM event in the current lactation with risk of CM in healthy cows. For these analyses, 9 manuscripts that reported the total number of lactations followed and the number of lactations with ≤1 and ≤2 CM cases were used. When summarizing results from studies requiring ≥5 d between CM events to consider a CM event as a new case, we observed no significant change in CM susceptibility following a first CM case (risk ratio: 0.99; 95% confidence interval: 0.86-1.14). However, for studies using a more liberal CM recurrence definition (i.e., only 24 h between CM events to consider new CM cases), we observed a 1.54 times greater CM risk (95% confidence interval: 1.20-1.97) for cows that already had 1 CM event in the current lactation compared with healthy cows. The most important risk factors for CM recurrence were parity (i.e., higher risk in older cows), a higher milk production, pathogen species involved in the preceding case, and whether a bacteriological cure was observed following the preceding case. The most important effects of recurrent CM were the milk yield reduction following a recurrent CM case, which was reported to be similar to that of the first CM case, and the increased risk of culling and mortality, which were reported to surpass those of first CM cases.

INTRODUCTION:Parental reporting of childhood vaccination status is often used for policy and program evaluation and research purposes. Many factors can bias parental reporting of childhood vaccination status, however, to our knowledge, no analysis has assessed whether time since vaccination impacts reporting accuracy. Therefore, using the Calgary electronic vaccine registry (PHANTIM) as the gold standard, we aimed to test the accuracy of parental reporting of childhood vaccination status at three different time-points since vaccination. METHODS:The All Our Families (AOF) cohort study asked parents to report their child's 2, 4, 6, 12 and 18 month vaccines (vaccination time-point) on questionnaires given when the child was 1, 2 and 3 years of age (survey time-point). We linked the AOF parental reporting of vaccination status to the PHANTIM registry and calculated the percent agreement and difference in coverage estimates between PHANTIM and AOF at each vaccination and survey time-point combination. Furthermore, we measured the sensitivity and specificity, and negative (NPV) and positive predictive values (PPV) of parental vaccine recall across time. RESULTS:AOF parent reports of coverage rates were consistently higher than the PHANTIM estimates. While we saw significant differences in percent agreement for certain vaccination time-points, we saw no consistent directional difference by survey time-point, suggesting that parental accuracy did not change with time. We found a uniformly high sensitivity across all vaccination and survey time-points, and no consistent patterns in the specificity, PPV and NPV results. CONCLUSION:Time since vaccination may not be the most important consideration when designing and implementing a vaccination survey. Other factors that may contribute to the bias associated with parental reporting of vaccination status include the complexity of the vaccine schedule, schedule changes over time, and the wording and structure of the questionnaires.

IntroductionWildfires are increasing in frequency and severity due to climate change. Fine particulate matter (PM2.5) in wildfire smoke is an important indicator of health effects of most combustion sources. The evidence based on adverse health impacts of PM2.5 from wildfire smoke are increasingly being studied but some gaps still remain. Objectives and ApproachWe examined the association of PM2.5 from Pacific Northwest wildfires with multiple respiratory and cardiovascular morbidity events related physician and emergency department visits, hospital admissions, health-link calls and medications dispensed among Calgary city population from August 1 – September 30, 2015. Physician billing claims, discharge abstract, Pharmaceutical Information Network, Health-link calls databases were linked with the air quality monitoring information database. Quasi-Poisson regression model for time lags of zero to five days and a three-day moving average, and conditional logistic regression model was used with adjustment for air pollutants and meteorological variables. Age and disease-specific stratified analyses were performed. ResultsCompared to the pre-wildfire period (Aug 1 – Aug 23), a 10 µg/m3 increase in PM2.5 increased the risk for respiratory physician visits by 54.8% (95% CI: 41.6% - 69.3%) and 32.6% (95% CI: 10.4% - 58.9%) in the respective post (Sep 1- Sep 30) and during (Aug 24 – Aug 31) wildfire periods. The strongest association of PM2.5 with respiratory physician visits was observed for children aged 0-9 years in the post-wildfire period (Relative Risk [RR] = 2.11, 95% CI: 1.86 - 2.39) compared to during wildfire period (RR = 1.56, 95% CI: 1.21 - 2.02) and was consistent for asthma, acute bronchitis and acute respiratory infection. Statistically significant effects of PM2.5 on cardiovascular hospitalizations, ED and physician visits were not observed during the wildfire period. Conclusion/ImplicationsWildfire-related PM2.5 led to increased physician visits due to respiratory morbidity during and after the wildfires, particularly for asthma, acute bronchitis and acute respiratory infections in children. The absence of cardiovascular health impact in general population during wildfires provides useful information for targeted public health messaging during adverse air quality events.