Hospitalizations for ambulatory care sensitive conditions across primary care models in Ontario, Canada

The study analyzes the relationship between the risk of a hospitalization for an ambulatory care sensitive condition (ACSC), and the primary care payment and the organizational model used by the patient (fee-for-service, enhanced fee-for-service, blended capitation, blended capitation with interdisciplinary teams).The study used linked patient-level health administrative databases and census data housed at the Institute for Clinical Evaluative Sciences in Ontario. Since the province provides universal health care, the data capture all patients in Ontario, Canada's most populous province, with about 13 million inhabitants. All Ontario patients diagnosed with an ACSC prior to April 1, 2012, who had at least one visit with a physician between April 1, 2012, and March 31. 2013, were included in the study (n=1,710,310). Each patient was assigned to the primary care model of his/her physician. The different models were categorized as Fee-forService (FFS), enhanced-FFS, blended capitation, and interdisciplinary team. A logistic regression was used to model the risk of having an ACSC hospitalization during the one-year observation period. Adjustments were made for patient characteristics (age, sex, health status, and socio-economic status) and for the geographic location of the practice. Using patients belonging to FFS models as the reference group, the risk of an ACSC hospitalization was higher for patients belonging to the blended-capitation model using interdisciplinary teams (Adjusted Odds Ratio [AOR] = 1.06, 95% confidence interval [CI] = 1.00-1.12) and lower for enhancedFFS (AOR = 0.78, CI= 0.74-0.82) and blended capitation patients (AOR = 0.91, CI= 0.86-0.96). Using patients with hypertension as the reference group, the odds of an ACSC hospitalization were much higher for patients with any other ACSC and increased with patients' morbidity. The risk was lower for patients of higher socio-economic status (AOR=0.63, CI=0.60-0.67) in the highest neighborhood income quintile

Disability in Long-Term Care Residents Explained by Prevalent Geriatric Syndromes, Not Long-Term Care Home Characteristics: A Cross-Sectional Study

Self-care disability is dependence on others to conduct activities of daily living, such as bathing, eating and dressing. Among long-term care residents, self-care disability lowers quality of life and increases health care costs. Understanding the correlates of self-care disability in this population is critical to guide clinical care and ongoing research in Geriatrics. This study examines which resident geriatric syndromes and chronic conditions are associated with residents’ self-care disability and whether these relationships vary across strata of age, sex and cognitive status. It also describes the proportion of variance in residents’ self-care disability that is explained by residents’ geriatric syndromes versus long-term care home characteristics

Factors Impacting Primary Care Engagement in a New Approach to Integrating Care in Ontario, Canada.

INTRODUCTION: In 2019, Ontario\u27s Ministry of Health (the Ministry) introduced Ontario Health Teams (OHTs) to provide population-based integrated healthcare. Primary care was foundational to this approach. We sought to identify factors that impacted primary care engagement during OHT formation from different perspectives. METHODS: Interviews with 111 participants (administrators n = 80; primary care providers n = 17; patient family advisors = 14) from 11 OHTs were conducted following a semi-structured guide. Interviews were transcribed, coded, and thematically analyzed. RESULTS: Participants felt that primary care engagement was an ongoing, continuous cycle. Four themes were identified: 1) \u27A low rules environment\u27: limited direction from the Ministry (system-level), 2) \u27They\u27re at different starting points\u27: impact of local context (initiative-level); 3) \u27We want primary care to be actively involved\u27: engagement efforts made by OHTs (initiative-level); 4) \u27Waiting to hear a little bit more\u27: primary care concerns about the OHT approach (sector-level). Thirteen factors impacting primary care engagement were identified across the four themes. DISCUSSION AND CONCLUSION: The 13 factors influencing primary care engagement were interconnected and operated at health system, integrated care initiative, and sector levels. Future research should focus on integrated care initiatives as they mature, to address potential gaps in the involvement of primary care physicians

Case managers’ reflections of a brief case management intervention in Canada

IntroductionAs demand for intensive case management services continues to outpace supply, community mental health agencies in Toronto, Ontario, introduced Short-Term Case Management (STCM).ObjectiveThis study sought to explore case managers’ perspectives and experiences with this new service delivery model.MethodsFocus groups were conducted with twenty-one case managers, and transcripts analyzed using thematic analysis.ResultsEmerging themes suggest that despite embracing a recovery approach, case managers expressed mixed views on the acceptability and appropriateness of this service delivery model as an intervention.ConclusionThe ideal population for this intervention are adults with mental health issues in need of system navigation, and those motivated to address their goals. Further research is needed to establish fidelity criteria

Exploring the perspectives of primary care providers on use of the electronic Patient Reported Outcomes tool to support goal-oriented care:a qualitative study

BACKGROUND: Digital health technologies can support primary care delivery, but clinical uptake in primary care is limited. This study explores enablers and barriers experienced by primary care providers when adopting new digital health technologies, using the example of the electronic Patient Reported Outcome (ePRO) tool; a mobile application and web portal designed to support goal-oriented care. To better understand implementation drivers and barriers primary care providers’ usage behaviours are compared to their perspectives on ePRO utility and fit to support care for patients with complex care needs. METHODS: This qualitative sub-analysis was part of a larger trial evaluating the use of the ePRO tool in primary care. Qualitative interviews were conducted with providers at the midpoint (i.e. 4.5–6 months after ePRO implementation) and end-point (i.e. 9–12 months after ePRO implementation) of the trial. Interviews explored providers’ experiences and perceptions of integrating the tool within their clinical practice. Interview data were analyzed using a hybrid thematic analysis and guided by the Technology Acceptance Model. Data from thirteen providers from three distinct primary care sites were included in the presented study. RESULTS: Three core themes were identified: (1) Perceived usefulness: perceptions of the tool’s alignment with providers’ typical approach to care, impact and value and fit with existing workflows influenced providers’ intention to use the tool and usage behaviour; (2) Behavioural intention: providers had a high or low behavioural intention, and for some, it changed over time; and (3) Improving usage behaviour: enabling external factors and enhancing the tool’s perceived ease of use may improve usage behaviour. CONCLUSIONS: Multiple refinements/iterations of the ePRO tool (e.g. enhancing the tool’s alignment with provider workflows and functions) may be needed to enhance providers’ usage behaviour, perceived usefulness and behavioural intention. Enabling external factors, such as organizational and IT support, are also necessary to increase providers’ usage behaviour. Lessons from this study advance knowledge of technology implementation in primary care. TRIAL REGISTRATION: Clinicaltrials.gov Identified NCT02917954. Registered September 2016, https://www.clinicaltrials.gov/ct2/show/study/NCT02917954 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-021-01734-0

Sex differences among children, adolescents and young adults for mental health service use within inpatient and outpatient settings, before and during the COVID-19 pandemic: a population-based study in Ontario, Canada

Objectives The pandemic and public health response to contain the virus had impacts on many aspects of young people’s lives including disruptions to daily routines, opportunities for social, academic, recreational engagement and early employment. Consequently, children, adolescents and young adults may have experienced mental health challenges that required use of mental health services. This study compared rates of use for inpatient and outpatient mental health services during the pandemic to pre-pandemic rates. Design Population-based repeated cross-sectional study. Setting Publicly delivered mental healthcare in primary and secondary settings within the province of Ontario, Canada. Participants All children 6–12 years of age (n=2 043 977), adolescents 13–17 years (n=1 708 754) and young adults 18–24 years (n=2 286 544), living in Ontario and eligible for provincial health insurance between March 2016 and November 2021. Primary outcome measures Outpatient mental health visits to family physicians and psychiatrists for: mood and anxiety disorders, alcohol and substance abuse disorders, other non-psychotic mental health disorders and social problems. Inpatient mental health visits to emergency departments and hospitalisations for: substance-related and addictive disorders, anxiety disorders, assault-related injuries, deliberate self-harm and eating disorders. All outcomes were analysed by cohort and sex. Results During the pandemic, observed outpatient visit rates were higher among young adults by 19.01% (95% CI: 15.56% to 22.37%; 209 vs 175 per 1000) and adolescent women 24.17% (95% CI: 18.93% to 29.15%; 131 vs 105 per 1000) for mood and anxiety disorders and remained higher than expected. Female adolescents had higher than expected usage of inpatient care for deliberate self-harm, eating disorders and assault-related injuries. Conclusions Study results raise concerns over prolonged high rates of mental health use during the pandemic, particularly in female adolescents and young women, and highlights the need to better monitor and identify mental health outcomes associated with COVID-19 containment measures and to develop policies to address these concerns

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

Introduction Canadian provincial health systems have a data advantage – longitudinal population-wide data for publicly funded health services, in many cases going back 20 years or more. With the addition of high performance computing (HPC), these data can serve as the foundation for leading-edge research using machine learning and artificial intelligence. Objectives and Approach The Institute for Clinical Evaluative Sciences (ICES) and HPC4Health are creating the Ontario Data Safe Haven (ODSH) – a secure HPC cloud located within the HPC4Health physical environment at the Hospital for Sick Children in Toronto. The ODSH will allow research teams to post, access and analyze individual datasets over which they have authority, and enable linkage to Ontario administrative and other data. To start, the ODSH is focused on creating a private cloud meeting ICES’ legislated privacy and security requirements to support HPC-intensive analyses of ICES data. The first ODSH projects are partnerships between ICES scientists and machine learning. Results As of March 2018, the technological build of the ODSH was tested and completed and the privacy and security policy framework and documentation were completed. We will present the structure of the ODSH, including the architectural choices made when designing the environment, and planned functionality in the future. We will describe the experience to-date for the very first analysis done using the ODSH: the automatic mining of clinical terminology in primary care electronic medical records using deep neural networks. We will also present the plans for a high-cost user Risk Dashboard program of research, co-designed by ICES scientists and health faculty from the Vector Institute for artificial intelligence, that will make use of the ODSH beginning May 2018. Conclusion/Implications Through a partnership of ICES, HPC4Health and the Vector Institute, a secure private cloud ODSH has been created as is starting to be used in leading edge machine learning research studies that make use of Ontario’s population-wide data assets

Primary care bonus payments and patient-reported access in urban Ontario: a cross-sectional study

BACKGROUND: Rurality strongly correlates with higher pay-for-performance access bonuses, despite higher emergency department use and fewer primary care services than in urban settings. We sought to evaluate the relation between patient-reported access to primary care and access bonus payments in urban settings. METHODS: We conducted a cross-sectional, secondary data analysis using Ontario survey and health administrative data from 2013 to 2017. We used administrative data to calculate annual access bonuses for eligible urban family physicians. We linked this payment data to adult (≥ 16 yr) patient data from the Health Care Experiences Survey to examine the relation between access bonus achievement (in quintiles of the proportion of bonus achieved, from lowest [Q1, reference category] to highest [Q5]) and 4 patient-reported access outcomes. The average survey response rate to the patient survey during the study period was 51%. We stratified urban geography into large, medium and small settings. In a multilevel regression model, we adjusted for patient-, physician- and practice-level covariates. We tested linear trends, adjusted for clustering, for each outcome. RESULTS: We linked 18 893 respondents to 3940 physicians in 414 bonus-eligible practices. Physicians in small urban settings earned the highest proportion of their maximum potential access bonuses. Access bonus achievement was positively associated with telephone access (Q2 odds ratio [OR] 1.18, 95% confidence interval [CI] 0.98-1.42; Q3 OR 1.34, 95% CI 1.10-1.63; Q4 OR 1.46, 95% CI 1.19-1.79; Q5 OR 1.87, 95% CI 1.50-2.33), after hours access (Q2 OR 1.26, 95% CI 1.09-1.47; Q3 OR 1.46, 95% CI 1.23-1.74; Q4 OR 1.77, 95% CI 1.46-2.15; Q5 OR 1.88, 95% CI 1.52-2.32), wait time for care (Q2 OR 1.01, 95% CI 0.85-1.20; Q3 OR 1.17, 95% CI 0.97-1.41; Q4 OR 1.27, 95% CI 1.05-1.55; Q5 OR 1.63, 95% CI 1.32-2.00) and timeliness (Q2 OR 1.29, 95% CI 0.98-1.69; Q3 OR 1.29, 95% CI 0.94-1.77; Q4 OR 1.58, 95% CI 1.16-2.13; Q5 OR 1.98, 95% CI 1.38-2.82). When stratified by geography, we observed several of these associations in large urban settings, but not in small urban settings. Trend tests were statistically significant for all 4 outcomes. INTERPRETATION: Although the access bonus correlated with access in larger urban settings, it did not in smaller settings, aligning with previous research questioning its utility in smaller geographies. The access bonus may benefit from a redesign that considers geography and patient experience