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Background: Canadian health systems fare poorly in providing timely access to elective surgical care, which is crucial for quality, trust, and satisfaction. Methods: We conducted a cross-sectional analysis of surgical wait times for adults receiving non-urgent cataract surgery, knee arthroplasty, hip arthroplasty, gallbladder surgery, and non-cancer uterine surgery in Ontario, Canada, between 2013 and 2019. We obtained data from the Wait Times Information System (WTIS) database. Inter- and intra-hospital and surgeon variations in wait time were described graphically with caterpillar plots. We used non-nested 3-level hierarchical random effects models to estimate variation partition coefficients, quantifying the proportion of wait time variance attributable to surgeons and hospitals. Results: A total of 942,605 procedures at 107 healthcare facilities, conducted by 1,834 surgeons, were included in the analysis. We observed significant intra- and inter-provider variations in wait times across all five surgical procedures. Inter-facility median wait time varied between six-fold for gallbladder surgery and 15-fold for knee arthroplasty. Inter-surgeon variation was more pronounced, ranging from a 17-fold median wait time difference for cataract surgery to a 216-fold difference for non-cancer uterine surgery. The proportion of variation in wait times attributable to facilities ranged from 6.2% for gallbladder surgery to 23.0% for cataract surgery. In comparison, surgeon-related variation ranged from 16.0% for non-cancer uterine surgery to 28.0% for cataract surgery. Implications: There is extreme variability in surgical wait times for five common, high-volume, non-urgent surgical procedures. Strategies to address surgical wait times must address the variation between service providers through better coordination of supply and demand. Approaches such as single-entry models could improve surgical system performance. [ABSTRACT FROM AUTHOR]

Objective: Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10th revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study design and setting: Influenza and RSV laboratory data from the 2014–15, 2015–16, 2016–17 and 2017–18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results: 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion: We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections. [ABSTRACT FROM AUTHOR]

Background: The management of complex, multi-morbid patients is challenging for solo primary care providers (PCPs) with limited access to resources. The primary objective of the intervention was to reduce the overall rate of Emergency Department (ED) visits among patients in participating practices., Methods and Findings: An interrupted time series design and qualitative interviews were used to evaluate a multifaceted intervention, SCOPE (Seamless Care Optimizing the Patient Experience), offered to solo PCPs whose patients were frequent users of the ED. The intervention featured a navigation hub (nurse, homecare coordinator) to link PCPs with hospital and community resources, a general internist on-call to provide phone advice or urgent assessments, and access to patient results on-line. Continuous quality improvement (QI) strategies were employed to optimize each component of the intervention. The primary outcome was the relative pre-post intervention change in ED visit rate for patients of participating practices compared with that for a propensity-matched control group of physicians over the contemporaneous period. Themes were identified from semi-structured interviews on PCP's experiences and influential factors in their engagement. Twenty-nine physicians agreed to participate and were provided access to the intervention over an 18-month time period. There were a total of 1,525 intervention contacts over the 18-months (average: 50.6±60.8 per PCP). Both intervention and control groups experienced a trend towards lower rates of ED use by their patients over the study time period. The pre-post difference in trend for the intervention group compared to the controls was not significant at 1.4% per year (RR = 1.014; p = 0.59). Several themes were identified from qualitative interviews including: PCPs felt better supported in the care of their patients; they experienced a greater sense of community, and; they were better able to provide shared primary-specialty care., Conclusions: This multifaceted intervention to support solo PCPs in the management of their complex patients did not result in a reduced rate of ED visits compared to controls, likely related to variable uptake among PCPs. It did however result in more comprehensive and coordinated care for their patients. Future directions will focus on increasing uptake by improving ease of use, increasing the range of services offered and expanding to a larger number of PCPs., Competing Interests: Dr. Noah Ivers was supported by New Investigator Awards from the Canadian Institutes of Health Research and the Department of Family and Community Medicine, University of Toronto. Dr. Gillian A. Hawker has received research support as the Sir John and Lady Eaton Professor and Chair of Medicine, Department of Medicine, University of Toronto. The other authors declare no competing interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Estimates of the effectiveness of influenza vaccines in older adults may be biased because of difficulties identifying and adjusting for confounders of the vaccine-outcome association. We estimated vaccine effectiveness for prevention of serious influenza complications among older persons by using methods to account for underlying differences in risk for these complications., Methods: We conducted a retrospective cohort study among Ontario residents aged ≥ 65 years from September 1993 through September 2008. We linked weekly vaccination, hospitalization, and death records for 1.4 million community-dwelling persons aged ≥ 65 years. Vaccine effectiveness was estimated by comparing ratios of outcome rates during weeks of high versus low influenza activity (defined by viral surveillance data) among vaccinated and unvaccinated subjects by using log-linear regression models that accounted for temperature and time trends with natural spline functions. Effectiveness was estimated for three influenza-associated outcomes: all-cause deaths, deaths occurring within 30 days of pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations., Results: During weeks when 5% of respiratory specimens tested positive for influenza A, vaccine effectiveness among persons aged ≥ 65 years was 22% (95% confidence interval [CI], -6%-42%) for all influenza-associated deaths, 25% (95% CI, 13%-37%) for deaths occurring within 30 days after an influenza-associated pneumonia/influenza hospitalization, and 19% (95% CI, 4%-31%) for influenza-associated pneumonia/influenza hospitalizations. Because small proportions of deaths, deaths after pneumonia/influenza hospitalizations, and pneumonia/influenza hospitalizations were associated with influenza virus circulation, we estimated that vaccination prevented 1.6%, 4.8%, and 4.1% of these outcomes, respectively., Conclusions: By using confounding-reducing techniques with 15 years of provincial-level data including vaccination and health outcomes, we estimated that influenza vaccination prevented ~4% of influenza-associated hospitalizations and deaths occurring after hospitalizations among older adults in Ontario.