Farming and the risk of developing osteoarthritis in Alberta, Canada.

INTRODUCTION: Because farming is a physically demanding occupation, farmers may be susceptible to developing osteoarthritis (OA). The aim of this study was to determine the risk of developing OA in Canadian farm, non-farm rural and urban residents. METHODS: A retrospective cohort study of five Alberta health administrative databases examined the risk of developing OA among three groups: farm (n=143 431), non-farm rural (n=143 431) and urban (n=143 431) residents over the fiscal years 2000-2001 through 2020-2021. The algorithm for OA ascertainment defined cases based on criteria including one hospital admission, two physician visits within a 2-year interval, or two ambulatory care visits within 2 years. Incidence rates, lifetime risk, and mortality rates were calculated. Cox proportional hazard models compared the incidence of OA for the three groups over the 21 years. RESULTS: A total of 26 957 OA cases were identified among 1 706 256 person-years (PYs) in the farm cohort. The crude incidence rate of OA over a period of 21 years ranged from 19.1 (95% confidence interval (CI) 18.6-19.6) per 1000 PYs in 2001 to 10.0 (95% CI 9.6-10.5) per 1000 PYs in 2021. The overall incidence rate was higher in the farm group (15.8 (95%CI 15.6-16.0) per 1000 PYs) as compared to the non-farm rural (14.7 (95%CI 14.5-14.9) per 1000 PYs) and the urban groups (13.3 (95%CI 13.1-13.4) per 1000 PYs). After adjusting for age and sex, the farm (6%; 95%CI 4-8%), and non-farm rural (9%; 95%CI 7-12%) groups had higher incidence rates than the urban group. The unadjusted non-injury mortality rate for the farm group with OA was lower (13.2 (95%CI 12.9-13.5) per 1000 PYs) than both the urban (14.5; 95%CI 14.1-14.8) and rural (18.0; 95%CI 17.6-18.4) groups. After adjusting for mortality, the lifetime risk of developing OA was 27.7% for farm residents, 25.6% for the non-farm rural cohort, and 24.0% for the urban cohort. CONCLUSION: When accounting for age and sex, farm and non-farm rural residents have a higher risk of developing OA as compared to the urban population. The higher mortality-adjusted lifetime risk of developing OA among farm residents highlights the necessity of specific interventions aimed at reducing the impact of this condition in rural communities. Further research is required to identify specific occupational and lifestyle risk factors associated with OA among farmers and to develop effective strategies for prevention and management.

Human papillomavirus vaccine coverage among immigrant adolescents in Alberta: a population-based cohort study.

BACKGROUND: Little is known about human papillomavirus (HPV) vaccination among immigrant children in Canada. We conducted a study in Alberta, Canada to assess HPV vaccine coverage among school-aged immigrant children compared with non-immigrant children. METHODS: This cohort study analysed population-based linked administrative health data to measure HPV vaccine coverage for 346 749 school-aged children, including 31 656 immigrants. Coverage was examined at 12 y of age from 2008 to 2018 for females, and from 2014 to 2018 for males and both sexes combined; vaccine series completion was considered receipt of three doses, with initiation (one or more dose) as a supplementary analysis. Multivariable logistic regression examined the association of vaccine coverage with migration status, adjusting for sociodemographic variables. RESULTS: Between 2014 and 2018, HPV vaccination coverage among immigrant children at age 12 y was significantly higher (52.58%) compared with non-immigrant children (47.41%). After controlling for place of residence, income quintile, biological sex and year, immigrant children had 1.10 greater odds (95% confidence interval 1.07 to 1.14) of receiving three doses of HPV vaccine compared with non-immigrant children. Immigrants from Asia and Africa had the highest coverage (60.25-68.78%), while immigrants from North America, Oceania and South America had the lowest coverage (39.97-48.36%). CONCLUSIONS: It is encouraging that immigrant children had higher HPV vaccine coverage compared with non-immigrants. Among immigrants, routine immunization promotion strategies should be tailored based on the country of origin.

Predicting 30-day risk from benzodiazepine/Z-drug dispensations in older adults using administrative data: A prognostic machine learning approach.

OBJECTIVE: To develop a machine-learning (ML) model using administrative data to estimate risk of adverse outcomes within 30-days of a benzodiazepine (BZRA) dispensation in older adults for use by health departments/regulators. DESIGN, SETTING AND PARTICIPANTS: This study was conducted in Alberta, Canada during 2018-2019 in Albertans 65 years of age and older. Those with any history of malignancy or palliative care were excluded. EXPOSURE: Each BZRA dispensation from a community pharmacy served as the unit of analysis. MAIN OUTCOMES AND MEASURES: ML algorithms were developed on 2018 administrative data to predict risk of any-cause hospitalization, emergency department visit or death within 30-days of a BZRA dispensation. Validation on 2019 administrative data was done using XGBoost to evaluate discrimination, calibration and other relevant metrics on ranked predictions. Daily and quarterly predictions were simulated on 2019 data. RESULTS: 65,063 study participants were included which represented 633,333 BZRA dispensation during 2018-2019. The validation set had 314,615 dispensations linked to 55,928 all-cause outcomes representing a pre-test probability of 17.8%. C-statistic for the XGBoost model was 0.75. Measuring risk at the end of 2019, the top 0.1 percentile of predicted risk had a LR + of 40.31 translating to a post-test probability of 90%. Daily and quarterly classification simulations resulted in uninformative predictions with positive likelihood ratios less than 10 in all risk prediction categories. Previous history of admissions was ranked highest in variable importance. CONCLUSION: Developing ML models using only administrative health data may not provide health regulators with sufficient informative predictions to use as decision aids for potential interventions, especially if considering daily or quarterly classifications of BZRA risks in older adults. ML models may be informative for this context if yearly classifications are preferred. Health regulators should have access to other types of data to improve ML prediction.

Predicting falls-related admissions in older adults in Alberta, Canada: a machine-learning falls prevention tool developed using population administrative health data.

OBJECTIVE: To construct a machine-learning (ML) model for health systems with organised falls prevention programmes to identify older adults at risk for fall-related admissions. DESIGN: This prognostic study used population-level administrative health data to develop an ML prediction model. SETTING: This study took place in Alberta, Canada during 2018-2019. PARTICIPANTS: Albertans aged 65 and older with at least one prior admission. Those with palliative conditions or emigrated out of Alberta were excluded. EXPOSURE: Unit of analysis was the individual person. MAIN OUTCOMES/MEASURES: We identified fall-related admissions. A CatBoost model was developed on 2018 data to predict risk of fall-related emergency department visits or hospitalisations. Temporal validation was done using 2019 data to evaluate model performance. We reported discrimination, calibration and other relevant metrics measured at the end of 2019 on both ranked predictions and predicted probability thresholds. A cost-savings simulation was performed using 2019 data. RESULTS: Final number of study participants was 224 445. The validation set had 203 584 participants with 19 389 fall-related events (9.5% pretest probability) and an ML model c-statistic of 0.70. The highest ranked predictions had post-test probabilities ranging from 40% to 50%. Net benefit analysis presented mixed results with some net benefit using the ML model in the 6%-30% range. The top 50 percentile of predicted risks represented nearly $C60 million in health system costs related to falls. Intervening on the top 25 or 50 percentiles of predicted risk could realise substantial (up to $C16 million) savings. CONCLUSION: ML prediction models based on population-level administrative data can assist health systems with fall prevention programmes identify older adults at risk of fall-related admissions and reduce costs. ML predictions based on ranked predictions or probability thresholds could guide subsequent interventions to mitigate fall risks. Increased access to diverse forms of data could improve ML performance and further reduce costs.

Incidence and risk factors for revision and contralateral anterior cruciate ligament reconstruction: A population-based retrospective cohort study.

There is a limited data on epidemiology of primary and recurrent anterior cruciate ligament reconstruction (ACLR) in Canada. The objectives of this study were to examine the incidence and factors associated with recurrent ACLR (revision and contralateral ACLR) in a western Canadian province of Alberta. We conducted a retrospective cohort study with an average follow up of 5.7 years. Albertans aged 10 to 60 years with a history of primary ACLR between 2010/11 to 2015/16 were included in the study. Participants were followed up until March 2019 to observe outcomes: Ipsilateral revision ACLR and contralateral ACLR. Kaplan Meir approach was used to estimate event free survival and Cox proportional hazard regression analysis was conducted to identify associated factors. Of the total participants with a history of primary ACLR on a single knee (n = 9292), n = 359, 3.9% (95% confidence interval: 3.5-4.3) underwent a revision ACLR. A similar proportion among those having primary ACLR on either knee (n = 9676), n = 344, 3.6% (95% confidence interval: 3.2-3.9) underwent a contralateral primary ACLR. Young age (<30 years) was associated with increased risk of contralateral ACLR. Similarly, young age (<30 years), having initial primary ACLR in winter and having allograft were associated with a risk of revision ACLR. Clinicians can use these findings in their clinical practice and designing rehabilitation plans as well as to educate patients about their risk for recurrent anterior cruciate ligament tear and graft failure.

The Effectiveness of Workplace Musculoskeletal Injury Risk Factor Screening Tools for Reducing Injury: A Systematic Review.

INTRODUCTION: Musculoskeletal injury (MSI) contributes to global health burdens. Effective MSI prevention is necessary. MSI risk factor screening tools can be used by employers to identify and mitigate occupational hazards. Rigorous synthesis of the effectiveness of these tools has not taken place. We synthesized literature on effectiveness of MSI risk factor screening tools for reducing injury through informing prevention interventions. MATERIALS AND METHODS: A literature search of Medline, Embase, Cochrane Library (Trials), CINAHL, Scopus and PsycINFO databases was performed. Included studies required an analytic design, used an MSI risk factor screening tool to inform an intervention in a working-age population and reported an outcome of MSI development, injury or compensation/work absence. Data extraction and study quality rating (Downs and Black criteria) were completed. Studies were sub-categorized as having used a single MSI screening tool (single-tool) to inform an injury prevention intervention or involving multiple simultaneous screening tools (multiple-tool). Study outcomes were synthesized when possible. RESULTS: Eighteen articles representing fourteen studies met our inclusion criteria. No high-quality studies were identified (maximum Downs and Black score of 19). Studies did not employ previously validated tools but instead, typically, those purpose-built for a single use. The results were inconsistent both when using tools alone and in combination with other tools. Outcome measure heterogeneity precluded meaningful meta-analysis. CONCLUSIONS: There is limited evidence regarding use of MSI risk factor screening tools for preventing injury. Rigorous studies that utilize previously validated tools are needed.

Increasing incidence of anterior cruciate ligament reconstruction: a 17-year population-based study.

PURPOSE: Anterior cruciate ligament (ACL) injuries are one of the most frequently studied injuries in orthopedic care and research. However, limited epidemiological data are available in Canada regarding trend and distribution of anterior cruciate ligament reconstruction (ACLR). In this paper, our purpose was to assess trends of ACLR between 2002/03 and 2018/19 by age, sex, season of surgery, and location (inpatient vs outpatient) of surgery. METHODS: In this descriptive epidemiological study of retrospective data available from Alberta Ministry of Health, we report annual incidence of ACLR between 2002/03 until 2018/19 among Albertans aged 10 years and older. Information was collected by authors from physician claims database for primary ACLR and revision ACLR and linked with other databases. Incidence proportions (number of ACLR/100,000 population) were calculated and compared by age category and gender over the study period. RESULTS: A total of 28,401 primary ACLR and 2085 revision ACLR were identified during the study period. Age-standardized annual incidence of primary ACLR increased from 40.6 to 51.2 per 100,000 population aged 10 years and older. Average annual increase in ACLR incidence was higher among females (1.8% per years) compared to males (0.96% per year). The overall peak incidence and peak incidence among males was observed in 20-29 year age group, whereas peak incidence in females was observed in 10-19 years of age. The number of ACLR in females outnumbers those among males for 10-19 year age group. Generally, a lower proportion of ACLR were conducted in summer compared to other seasons. Primary ACLR conducted in outpatient setting increased from 72% in 2002/03 to 97% in 2018/19. CONCLUSION: The incidence of ACLR is increasing in Alberta, especially among females and among younger cohorts under 20 years of age. This information can help clinicians to provide patient education and policy-makers to design and implement targeted ACL injury prevention programs. LEVEL OF EVIDENCE: Level III.

Development and Validation of a Machine Learning Model to Estimate Risk of Adverse Outcomes Within 30 Days of Opioid Dispensation.

Importance: Machine learning approaches can assist opioid stewardship by identifying high-risk opioid prescribing for potential interventions. Objective: To develop a machine learning model for deployment that can estimate the risk of adverse outcomes within 30 days of an opioid dispensation as a potential component of prescription drug monitoring programs using access to real-world data. Design, Setting, and Participants: This prognostic study used population-level administrative health data to construct a machine learning model. This study took place in Alberta, Canada (from January 1, 2018, to December 31, 2019), and included all patients 18 years and older who received at least 1 opioid dispensation from a community pharmacy within the province. Exposures: Each opioid dispensation served as the unit of analysis. Main Outcomes and Measures: Opioid-related adverse outcomes were identified from administrative data sets. An XGBoost model was developed on 2018 data to estimate the risk of hospitalization, an emergency department visit, or mortality within 30 days of an opioid dispensation; validation on 2019 data was done to evaluate model performance. Model discrimination, calibration, and other relevant metrics are reported using daily and weekly predictions on both ranked predictions and predicted probability thresholds using all data from 2019. Results: A total of 853 324 participants represented 6 181 025 opioid dispensations, with 145 016 outcome events reported (2.3%); 46.4% of the participants were men and 53.6% were women, with a mean (SD) age of 49.1 (15.6) years for men and 51.0 (18.0) years for women. Of the outcome events, 77 326 (2.6% pretest probability) occurred within 30 days of a dispensation in the validation set (XGBoost C statistic, 0.82 [95% CI, 0.81-0.82]). The top 0.1 percentile of estimated risk had a positive likelihood ratio (LR) of 28.7, which translated to a posttest probability of 43.1%. In our simulations, the weekly measured predictions had higher positive LRs in both the highest-risk dispensations and percentiles of estimated risk compared with predictions measured daily. Net benefit analysis showed that using machine learning prediction may not add additional benefit over the entire range of probability thresholds. Conclusions and Relevance: These findings suggest that prescription drug monitoring programs can use machine learning classifiers to identify patients at risk of opioid-related adverse outcomes and intervene on high-risk ranked predictions. Better access to available administrative and clinical data could improve the prediction performance of machine learning classifiers and thus expand opioid stewardship efforts.

Comparing rural traffic safety in Canada and Australia: a scoping review of the literature.

INTRODUCTION: The reduction of road fatalities is a priority established by the WHO and ratified by the UN. Rates of road fatalities are disproportionately high in rural areas in both Australia and Canada, two Commonwealth countries with comparable healthcare systems and rural health challenges. The purpose of this review was to compare and contrast the epidemiology, risk factors and prevention strategies of rural road fatalities in both countries to inform the next steps for prevention. METHODS: A scoping literature review was undertaken systematically to search for peer-reviewed literature published from January 2000 to June 2021. Articles were reviewed from five databases (EMCARE, Medline, CINAHL, Scopus and Informit). Search terms were adapted to suit each database and included combinations of keywords such as 'traffic accident', 'fatality', 'rural/remote', 'Australia' and 'Canada'. Themes and data associated with the research outcomes were extracted and tabulated. RESULTS: Forty-three papers were identified as relevant: 14 exploring epidemiology, 25 investigating risk factors and 37 proposing prevention strategies. People living in rural locations were 3.2 (95% confidence interval: 3.0-3.5) times more likely than urban dwellers to die in road-related incidents, with rates of motor vehicle fatalities universally higher. Common risk factors included drugs and alcohol, speed, driver error and biological sex. Key prevention strategies included improved infrastructure, vehicle design, impaired driving prevention and education. CONCLUSION: Further research regarding preventative measures and significant investment in rural road safety in both Australia and Canada are needed to prevent future incidents.

Risk Factors for Developing Concurrent Posttraumatic Stress Injury After Work-Related Musculoskeletal Injury: A Case-Control Study.

OBJECTIVE: This study aimed to study risk factors for developing concurrent posttraumatic stress injury (PTSI) among workers experiencing work-related musculoskeletal injury (MSI). METHODS: A case-control study was conducted using workers' compensation data on injured workers undergoing rehabilitation programs for concurrent MSI and PTSI (cases) and MSI only (controls). A variety of measures known at the time of the compensable injury were entered into logistic regression models. RESULTS: Of the 1948 workers included, 215 had concurrent MSI and PTSI. Concurrent MSI and PTSI were predicted by type of accident (adjusted odds ratio [OR], 25.8), experiencing fracture or dislocation fracture or dislocation (adjusted OR, 3.7), being public safety personnel (adjusted OR, 3.1), and lower level of education (adjusted OR, 1.9). CONCLUSIONS: Experiencing a concurrent PTSI diagnosis with MSI after work-related accident and injury appears related to occupation, type of accident, and educational background.

Road traffic fatalities in rural and remote Australia from 2006 to 2017: The need for targeted action.

OBJECTIVE: To explore rural motor vehicle collision (MVC) fatalities by trends over time, mode of transport, age, state, sex, and Aboriginal and Torres Strait Islander status. DESIGN: A retrospective total population-based time series was conducted using the Australian Bureau of Statistics (ABS) death registration data. SETTING: All statistical local area (SLA) within Australia from 2006 to 2017. PARTICIPANTS: Australian residents whose deaths were registered with the ABS between 01 January 2006 and 31 December 2017 where the underlying cause of death was related to unintentional transport accidents. MAIN OUTCOME MEASURES: Fatality rates were determined using population data collected from the 2006, 2011 and 2016 census. Trends over time by rurality were analysed by financial year. Rates of transport deaths by vehicle type were determined by rurality. Risk ratios were calculated to compare demographic groups based on sex, Aboriginal and Torres Strait Islander status and age. A 3-year scorecard was organised by state and rurality using 99.7% confidence intervals. RESULTS: Motor vehicle collision fatalities increase with increasing remoteness. Females, children from 0 to 14 years, pedestrians, and Aboriginal and Torres Strait Islander peoples are at a significantly higher risk of fatal MVCs than their respective metropolitan counterparts. The 3-year scorecard indicates that road fatality rates in the NT, WA, and all rural and remote areas required immediate attention and targeted action. CONCLUSIONS: There is a need for investment in MVC fatality prevention in rural Australia from inner regional to remote areas in order to meet the road safety targets established by the National Road Safety Strategy.

Epidemiology of dementia onset captured in Canadian primary care electronic medical records.

BACKGROUND: Dementia is an increasing concern in many countries, especially in those experiencing rapid growth in the proportion of older adults in their population. OBJECTIVE: This study aims to describe trends and demographic characteristics of incident dementia cases in community-dwelling older adults managed by primary care physicians. METHODS: We used electronic medical records from the Canadian Primary Care Sentinel Surveillance Network database to conduct a retrospective analysis to determine the number of, and trends for, incident diagnoses of dementia. Age-standardized annual incidence rates were calculated. Participants in our cohort are Canadian community dwelling seniors aged 65+ years who were not diagnosed with dementia before baseline with at least six years of record at their primary care clinics. RESULTS: The cohort consisted of 39 067 patients of whom 57% were females; the mean (SD) follow-up was 8.4 (1.5) years. During follow-up, 4935 patients were diagnosed with dementia. The risk for dementia diagnosis increased with increasing age but decreased in the last four years among people aged 80 and older at baseline (P < 0.001). People with dementia were more likely to be females (P = 0.001) and urban residents (P < 0.001), they are less likely to be classified into the least deprived group (P = 0.012). CONCLUSIONS: The incidence of dementia diagnosis increased with age except in the oldest old in both sexes. This may be attributed to the effect of mortality competing risk. Future research on the association between risk factors and dementia should consider studying dementia among the oldest old separately to minimize bias.

Dementias are conditions that may cause mental symptoms such as forgetfulness, confusion, or disorientation. As the population gradually ages, the number of dementia cases is also increasing. Among people aged 65 and over, the rate of dementia onset increases as people get older. However, among people aged 85 and over, the rate of developing dementia is slower, which might reflect that people who reach the age of 85 are usually healthier in general. Since family practitioners are normally the first contact when patients and their family notice symptoms, primary care plays an important role in diagnosing and managing dementia. Early recognizing dementia for early support is very helpful. According to our study, health-related information recorded in primary care in Canada is sufficient to be used for research. It is a valuable opportunity to study the characteristics of people with dementia, including their health conditions, risks and protective factors that may contribute to the development of the disease.

Risk factors for incidence of dementia in primary care practice: a retrospective cohort study in older adults.

BACKGROUND: The dementias are long-term, chronic conditions caused by progressive neurological degeneration. Current literature suggests that cardiovascular disease risk factors may contribute to the onset of dementia; however, evidence of these associations is inconsistent. OBJECTIVES: This study aimed to examine the impact of risk factors on dementia onset in older adults diagnosed and managed in Canadian primary care settings. METHODS: A retrospective cohort study was employed utilizing electronic medical records data in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). Patients aged 65+ years with no dementia diagnosis at baseline who were followed from 2009 to 2017 with a run-in year to exclude existing undiagnosed dementia cases. Multivariate Cox proportional hazard models were used to estimate risk. RESULTS: Age was associated with an increased incidence risk of dementia in both examined age groups: 65-79 years (13%) and 80+ years (5%). History of depression increased dementia risk by 38% and 34% in the age groups. There were significant associations with lower social deprivation area quintile, smoking history, osteoarthritis, and diabetes mellitus in patients aged 65-79 years but not in those aged 80+ years. Sex, hypertension, obesity, dyslipidemia, and the use of antihypertensive medications and statins were not associated with risk of incident dementia diagnosis. CONCLUSIONS: The association between chronic health conditions and dementia onset is complicated. Primary care electronic medical record data might be useful for research in this topic, though follow-up time is still relatively short to observe a clear causal relationship. Future studies with more complete data may provide evidence for dementia preventive strategies within primary care practice.

Predicting 30-Day Readmissions in Patients With Heart Failure Using Administrative Data: A Machine Learning Approach.

BACKGROUND: We sought to develop machine learning (ML) models trained on administrative data which predict risk of readmission in patients with heart failure and to evaluate and compare the ML model with the currently used LaCE score using clinically informative metrics. METHODS AND RESULTS: This prognostic study was conducted in Alberta, Canada, on 9845 patients with confirmed heart failure admitted to hospital between 2012 and 2019. The outcome was unplanned all-cause hospital readmission within 30 days of discharge. We used 80% of the data for the ML model development and 20% for independent validation. We reported, using the validation set, c-statistics (area under the receiver operating characteristic curves)and performance metrics (likelihood ratio, positive predictive values) for the XGBoost model and a modified LaCE score within their respective predictive thresholds. Boosted tree-based classifiers had higher area under the receiver operating characteristic curves (0.65 for XGBoost) compared with others (0.58 for neural networks) and 0.57 for the modified LaCE. Within the predicted threshold range of the XGBoost classifier, the positive likelihood ratio was 1.00 at the low end of predicted risk and 6.12 at the high end, resulting in a positive predictive value (post-test probability) range of 21%-62%; the pretest probability of readmission was 20.9% using prevalence. The corresponding positive likelihood ratios and positive predictive values across LaCE score thresholds were 1.00-1.20 and 21%-24%, respectively. CONCLUSIONS: Despite predicting readmissions better than the LaCE, even the best ML model trained on administrative health data (XGBoost) did not provide substantially informative prediction performance as it only generated a moderate shift from pre to post-test probability. Health systems wishing to deploy such a tool should consider training ML models with additional data. Adding other techniques like natural language processing, along with ML, to use other clinical information (like chart notes) might improve prediction performance.

Cohort study of medical cannabis authorization and motor vehicle crash-related healthcare visits in 2014-2017 in Ontario, Canada.

BACKGROUND: With increasing numbers of countries/jurisdictions legalizing cannabis, cannabis impaired driving has become a serious public health concern. Despite substantive research linking cannabis use with higher rates of motor vehicle crashes (MVC), there is an absence of conclusive evidence linking MVC risk with medical cannabis use. In fact, there is no clear understanding of the impact of medical cannabis use on short- and long-term motor vehicle-related healthcare visits. This study assesses the impact of medical cannabis authorization on motor vehicle-related health utilization visits (hospitalizations, ambulatory care, emergency department visits, etc) between 2014 and 2017 in Ontario, Canada. METHODS: A matched cohort study was conducted on patients authorized to use medical cannabis and controls who did not receive authorization for medical cannabis - in Ontario, Canada. Overall, 29,153 adult patients were identified and subsequently linked to the administrative databases of the Ontario Ministry of Health, providing up to at least 6 months of longitudinal follow-up data following the initial medical cannabis consultation. Interrupted time series analyses was conducted to evaluate the change in rates of healthcare utilization as a result of MVC 6 months before and 6 months after medical cannabis authorization. RESULTS: Over the 6-month follow-up period, MVC-related visits in medical cannabis patients were 0.50 visits/10000 patients (p = 0.61) and - 0.31 visits/10000 patients (p = 0.64) for MVC-related visits in controls. Overall, authorization for medical cannabis was associated with an immediate decrease in MVC-related visits of - 2.42 visits/10000 patients (p = 0.014) followed by a statistically significant increased rate of MVC-related visits (+ 0.89 events/10,000 in those authorized medical cannabis) relative to controls in the period following their authorization(p = 0.0019). Overall, after accounting for both the immediate and trend effects, authorization for medical cannabis was associated with an increase of 2.92 events/10,000 (95%CI 0.64 to 5.19) over the entire follow-up period. This effect was largely driven by MVC-related emergency department visits (+ 0.80 events/10,000, p < 0.001). CONCLUSIONS: Overall, there was an association between medical cannabis authorization and healthcare utilization, at the population level, in Ontario, Canada. These findings have public health importance and patients and clinicians should be fully educated on the potential risks. Continued follow-up of medically authorized cannabis patients is warranted to fully comprehend long-term impact on motor vehicle crash risk.

Characteristics and Prognostic Factors for Return to Work in Public Safety Personnel with Work-Related Posttraumatic Stress Injury Undergoing Rehabilitation.

PURPOSE: Public safety personnel (PSP) are at risk of developing posttraumatic stress injury (PTSI) due to exposure to traumatic experiences and accidents. Rehabilitation programs are available, but their success varies. We studied: (1) characteristics of PSP undergoing PTSI rehabilitation in comparison to non-PSP workers; and (2) predictive value of various factors for return to work. Methods A population-based cohort study was conducted using data on injured workers undergoing PTSI rehabilitation. Of the 488 workers included, 131 were PSP. Outcome measures were: (1) return to pre-accident work at rehabilitation discharge; (2) days receiving wage replacement benefits in the year following rehabilitation. Results PSP were mainly employed (90.8%), male (59.5%), paramedics/ambulance workers (58.0%); a minority (43.5%) returned to pre-accident work after rehabilitation. Compared to non-PSP workers, PSP were more likely to initially be diagnosed with psychological injuries (94.7% versus 59.4%, p < 0.001) rather than musculoskeletal injuries. Return to pre-accident work was predicted by shorter injury duration, having a primary mental health diagnosis, working at time of admission, and not having symptoms requiring treatment in a complex rehabilitation program. PSPs were slower to experience full recovery in the year after rehabilitation. Factors predicting fewer benefit days included not having a secondary psychological injury, being employed, and working at time of admission. Conclusions Most PSP did not return to work in full after PTSI rehabilitation. Outcomes are likely to improve by starting treatment earlier and maintaining connections with the workplace.

Child drowning on farms in Canada and associated demographic and risk factors.

OBJECTIVES: This study aimed to examine the occurrence and characteristics of child drowning deaths on farms compared with other child injury deaths on farms. METHODS: This study uses cross-sectional data from the Canadian Agricultural Injury Reporting Program for the years 1990 through 2012. Using χ2 tests and regression, it compares the occurrence of demographics and potential risk factors between drowning deaths and all other injury deaths among children (< 19 years of age) on farms. RESULTS: There were 44 drowning deaths and 306 non-drowning deaths identified. Drowning deaths were at younger age (mean age of 5.4 versus 8.8 years old), non-work-related (25% versus 79%), and less likely to occur during adult supervision (36.4% versus 53.5%). CONCLUSIONS: Drowning disproportionately affects the very young. Improving supervision of young children may prevent some farm drowning deaths, but installing effective barriers to water hazards is likely more effective.

RéSUMé: OBJECTIFS: Examiner la survenue et les caractéristiques des décès d'enfants par noyade sur les fermes comparativement aux autres décès d'enfants attribuables aux blessures sur les fermes. MéTHODE: L'étude fait appel aux données transversales de 1990 à 2012 du programme de Surveillance des blessures dans le secteur agricole au Canada. À l'aide de tests du Χ2 et d'analyses de régression, elle compare l'existence de facteurs démographiques et de facteurs de risque potentiels entre les décès par noyade et les autres décès attribuables aux blessures chez les enfants (< 19 ans) survenus sur les fermes. RéSULTATS: Quarante-quatre décès par noyade et 306 décès autres que par noyade ont été répertoriés. Les décès par noyade ont touché des enfants plus jeunes (âge moyen de 5,4 ans contre 8,8 ans), n'étaient pas liés au travail (25 % contre 79 %) et étaient moins susceptibles de se produire sous la surveillance d'un adulte (36,4 % contre 53,5 %). CONCLUSIONS: Les noyades touchent démesurément les très jeunes enfants. Une meilleure surveillance des jeunes enfants pourrait prévenir certains décès par noyade sur les fermes, mais l'installation de barrières contre les risques aquatiques est probablement plus efficace.

Agriculture-related Injuries: Discussion in Canadian Media.

Objectives: This study examined news media reporting on farm injuries in Canada for the occurrence of prevention messages and factors related to whether an event was reported in more than one article. Methods: This study used a media database maintained by the Canadian Agricultural Safety Association (CASA), which stores publicly available news media reports of agricultural injuries and fatalities in Canada. Media reports were obtained for the years 2010 through 2017. Reports were coded as whether they reported a fatal or non-fatal injury, age and gender of those affected, urban or rural media, as well as whether they involved machinery, or were in French. Logistic regression was used to determine which variables predicted an event being reported more than once, and whether a report included a prevention message. Results: The database identified 856 relevant articles. Only 6.3% of the articles included a prevention message, and 34.7% were duplicate articles. Fatal injuries were more likely to be reported in multiple articles (odds ratio: 2.44). There was also significant variation in the occurrence of multiple reports across the years of the study. Prevention messages were more likely to occur when at least one child or female victim was involved in an event. However, only year of publication remained significantly associated with the occurrence of a prevention message in multivariable regression (odds ratio: 0.85). Conclusion: Prevention messages are rare in media reporting of farm injuries and are decreasing over time. Improved reporting is needed to aid in farm injury prevention.

Falls and fear of falling in older adults with total joint arthroplasty: a scoping review.

BACKGROUND: Patients waiting or recovering from total joint arthroplasty (TJA) are at risk for falls which can lead to restriction of activity and negatively impact recovery. The objective of this scoping review is to critically appraise and synthesize the evidence in the reported number of falls, fear of falling, and risk factors associated with falls in older patients waiting for or recovering from TJA. METHODS: Seven electronic databases were searched with no date limits and using language restriction (English). The inclusion criteria were 1) cohorts that included older adults 60+ years of age, 2) reported prevalence of falls, fear of falling, and/or risk factors for falls in patients who were waiting or recovering from TJA and 3) cross-sectional studies, cohort studies, and case control study designs. The quality assessment of selected articles was assessed using the SIGN Guidelines Checklist. RESULTS: Of the 866 citations identified, 12 studies met the inclusion criteria and were reviewed. Prevalence of falls in pre-operative TJA patients and post-operative TJA patients ranged from 23 to 63%, and 13 to 42%, respectively. Of those five studies that examined fear of falling, pre-operative TJA patients reported greater fear of falling than post-operative patients. Modifiable risk factors for falls included fear of falling, joint range of motion, and depression. CONCLUSIONS: An increased risk of falls in patients with TJA was reported both for patients waiting for and recovering from surgery. A number of modifiable risk factors were identified including fear of falling that could be targeted in fall prevention programs for TJA.

Injury-related health services use and mortality among Métis people in Alberta.

OBJECTIVES: To examine injury-related health services use, defined as hospital admissions and emergency department (ED) visits, as well as mortality among Métis people in Alberta, and to compare those results with the entire Alberta population. METHODS: This population-based descriptive epidemiological research used administrative data maintained by the Alberta Ministry of Health (AH), for the year 2013. Hospital morbidity data and Alberta Vital Statistics registry were extracted and included a unique personal number to identify individuals across multiple records. To identify injury and mortality cases among the Métis people in Alberta, administrative databases were linked to the Métis Nation of Alberta (MNA) Identification Registry. Age-standardized rates of injury-related health services usage and mortality were calculated and compared between Métis people and the entire Alberta population. RESULTS: Age-standardized incidence rates (ASIRs) of all causes combined of injury-related visits to the ED and hospital admissions were 35% (p < 0.01) and 26% (p = 0.05) higher among Métis people compared with the overall Alberta population. Among the MNA, ASIRs of health service use were higher in rural areas (p < 0.01) and among men (p < 0.01). The injury-related mortality rate was not significantly higher among the MNA compared with the Alberta population. However, among the MNA, Métis males had a significantly higher injury mortality rate than females (p < 0.02). CONCLUSION: Results from the current study suggest that injuries are a concern among Métis people. Health planners should design and implement strategies directed to reduce the burden of injury and associated complications for Métis people, especially in rural areas and among Métis males.