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Abstract Background Within the Learning Health System (LHS) model, learning routines, including evaluation, allow for continuous incremental change to take place. Within these learning routines, evaluation assists in problem identification, data collection, and data transformation into contextualized information, which is then re-applied to the LHS environment. Evaluation that catalyzes learning and improvement may also contribute to health innovation sustainability. However, there is little consensus as to why certain evaluations seem to support learning and sustainability, while others impede it. This realist synthesis seeks to understand the contextual factors and underlying mechanisms or drivers that best support health systems learning and sustainable innovation. Methods This synthesis will be guided by Pawson and colleagues’ 2005 and Emmel and colleagues’ 2018 guidelines for conducting realist syntheses. The review process will encompass five steps: (1) scoping the review, (2) building theories, (3) identifying the evidence, (4) evidence selection and appraisal, and (5) data extraction and synthesis. An Expert Committee comprised of leaders in evaluation, innovation, sustainability, and realist methodology will guide this synthesis. Review findings will be reported using the RAMESES guidelines. Discussion The use of a realist review will allow for exploration and theorizing about the contextual factors and underlying mechanisms that make evaluations ‘work’ (or ‘not work’) to support learning and sustainability. Depending on results, we will attempt to synthesize findings into a series of recommendations for evaluations with the intention to support health systems learning and sustainability. Finalized results will be presented at national and international conferences, as well as disseminated via a peer-reviewed publication. Systematic review registration This realist synthesis protocol has been registered with PROSPERO ( https://www.crd.york.ac.uk/prospero/ ID 382690).

Abstract Background Primary care surveys are a key source of evaluative data; understanding how survey respondents compare to the intended population is important to understand results in context. The objective of this study was to examine the physician and patient representativeness of two primary care surveys (TRANSFORMATION and QUALICOPC) that each used different sampling and recruitment techniques. Methods We linked the physician and patient participants of the two surveys to health administrative databases. Patients were compared to other patients visiting the practice on the same day and other randomly selected dates using sociodemographic data, chronic disease diagnosis, and health system utilization. Physicians were compared to other physicians in the same practice, and other physicians in the intended geographic area using sociodemographic and practice characteristics. Results Physician respondents of the TRANSFORMATION survey included more males compared to their practice groups, but not to other physicians in the area. TRANSFORMATION physicians cared for a larger roster of patients than other physicians in the area. Patient respondents of the QUALICOPC survey did not have meaningful differences from other patients who visit the practice. Patient respondents of the TRANSFORMATION survey resided in more rural areas, had less chronic disease, and had lower use of health services than other patients visiting the practice. Conclusion Differences in survey recruitment methods at the physician and patient level may help to explain some of the differences in representativeness. When conducting primary care surveys, investigators should consider diverse methods of ensuring representativeness to limit the potential for nonresponse bias.

Abstract Background There is currently mixed evidence on the influence of long-term conditions and deprivation on mortality. We aimed to explore whether number of long-term conditions contribute to socioeconomic inequalities in mortality, whether the influence of number of conditions on mortality is consistent across socioeconomic groups and whether these associations vary by working age (18–64 years) and older adults (65 + years). We provide a cross-jurisdiction comparison between England and Ontario, by replicating the analysis using comparable representative datasets. Methods Participants were randomly selected from Clinical Practice Research Datalink in England and health administrative data in Ontario. They were followed from 1 January 2015 to 31 December 2019 or death or deregistration. Number of conditions was counted at baseline. Deprivation was measured according to the participant’s area of residence. Cox regression models were used to estimate hazards of mortality by number of conditions, deprivation and their interaction, with adjustment for age and sex and stratified between working age and older adults in England (N = 599,487) and Ontario (N = 594,546). Findings There is a deprivation gradient in mortality between those living in the most deprived areas compared to the least deprived areas in England and Ontario. Number of conditions at baseline was associated with increasing mortality. The association was stronger in working age compared with older adults respectively in England (HR = 1.60, 95% CI 1.56,1.64 and HR = 1.26, 95% CI 1.25,1.27) and Ontario (HR = 1.69, 95% CI 1.66,1.72 and HR = 1.39, 95% CI 1.38,1.40). Number of conditions moderated the socioeconomic gradient in mortality: a shallower gradient was seen for persons with more long-term conditions. Conclusions Number of conditions contributes to higher mortality rate and socioeconomic inequalities in mortality in England and Ontario. Current health care systems are fragmented and do not compensate for socioeconomic disadvantages, contributing to poor outcomes particularly for those managing multiple long-term conditions. Further work should identify how health systems can better support patients and clinicians who are working to prevent the development and improve the management of multiple long-term conditions, especially for individuals living in socioeconomically deprived areas.

Abstract Background Despite the potential for community-based exercise programs supported through healthcare-community partnerships (CBEP-HCPs) to improve function post-stroke, insufficient trial evidence limits widespread program implementation and funding. We evaluated the feasibility and acceptability of a CBEP-HCP compared to a waitlist control group to improve everyday function among people post-stroke. Methods We conducted a 3-site, pilot randomized trial with blinded follow-up evaluations at 3, 6, and 10 months. Community-dwelling adults able to walk 10 m were stratified by site and gait speed and randomized (1:1) to a CBEP-HCP or waitlist control group. The CBEP-HCP involved a 1-h, group exercise class, with repetitive and progressive practice of functional balance and mobility tasks, twice a week for 12 weeks. We offered the exercise program to the waitlist group at 10 months. We interviewed 13 participants and 9 caregivers post-intervention and triangulated quantitative and qualitative results. Study outcomes included feasibility of recruitment, interventions, retention, and data collection, and potential effect on everyday function. Results Thirty-three people with stroke were randomized to the intervention (n = 16) or waitlist group (n = 17). We recruited 1–2 participants/month at each site. Participants preferred being recruited by a familiar healthcare professional. Participants described a 10- or 12-month wait in the control group as too long. The exercise program was implemented per protocol across sites. Five participants (31%) in the intervention group attended fewer than 50% of classes for health reasons. In the intervention and waitlist group, retention was 88% and 82%, respectively, and attendance at 10-month evaluations was 63% and 71%, respectively. Participants described inclement weather, availability of transportation, and long commutes as barriers to attending exercise classes and evaluations. Among participants in the CBEP-HCP who attended ≥ 50% of classes, quantitative and qualitative results suggested an immediate effect of the intervention on balance, balance self-efficacy, lower limb strength, everyday function, and overall health. Conclusion The CBEP-HCP appears feasible and potentially beneficial. Findings will inform protocol revisions to optimize recruitment, and program and evaluation attendance in a future trial. Trial registration ClinicalTrials.gov , NCT03122626 . Registered April 21, 2017 — retrospectively registered.

Abstract 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

Abstract Background Many countries, including Canada, have introduced primary care reforms to improve health system functioning and value. The purpose of this study was to examine the association between receiving care from interprofessional primary care teams and after-hours access to care, patient-reported walk-in clinic visits and emergency department use. Methods We conducted a retrospective cohort study linking population-based administrative databases to Ontario’s Health Care Experience Survey (HCES) between 2012 and 2018. We adjusted for physician group characteristics as well as individual physician and patient characteristics while assessing the relationship between receiving care from interprofessional teams and the outcomes of interest. Results As of March 31st, 2015, there were 465 physician groups with HCES respondents of which 177 (38.0%) were interprofessional teams and 288 (62.0%) were non-interprofessional teams in the same blended capitation reimbursement model. In this period, there were 4518 physicians with HCES respondents, of whom 2131 (47.2%) were in interprofessional teams and 2387 (52.8%) were in non-interprofessional teams. There were 10,102 HCES respondents included in this study, of whom 42.4% were in interprofessional teams and 42.3% were in non-interprofessional teams. After adjustment, we found that being in an interprofessional team was associated with an increase in the odds of patients reporting same/next day access to care by 12.0% (OR = 1.12 CI = 1.00 to 1.24 p-value 0.0436) and a decrease in the odds of patients reporting walk-in clinic use by 16% (OR = 0.84 CI = 0.75 to 0.94 p-value 0.0019). After adjustment, there were no significant differences in patient-reported after-hours access to care and emergency department use. Conclusions Ontario has invested heavily in interprofessional primary care teams. As compared to patients in non-interprofessional teams, patients in interprofessional teams self-reported more timely access to care and less walk-in clinic use but no significant difference in self-reported access to after-hours care or in emergency department use. For jurisdictions aiming to expand physician voluntary participation in interprofessional teams, our study results inform expectations around access to care and health services utilization.

Abstract Background Patient engagement (PE) in planning or improving hospital facilities or services is one approach for improving healthcare delivery and outcomes. To provide evidence on hospital capacity needed to support PE, we described the attributes of hospital PE capacity associated with clinical quality measures. Methods We conducted a cross-sectional survey of general and specialty hospitals based on the Measuring Organizational Readiness for Patient Engagement framework. We derived a PE capacity index measure, and with Multiple Correspondence Analysis, assessed the association of PE capacity with hospital type, and rates of hand-washing, C. difficile infection rates and 30-day readmission. Results Respondents (91, 66.4%) included general:

Abstract Background Improving health system value and efficiency are considered major policy priorities internationally. Ontario has undergone a primary care reform that included introduction of interprofessional teams. The purpose of this study was to investigate the relationship between receiving care from interprofessional versus non-interprofessional primary care teams and ambulatory care sensitive condition (ACSC) hospitalizations and hospital readmissions. Methods Population-based administrative databases were linked to form data extractions of interest between the years of 2003–2005 and 2015–2017 in Ontario, Canada. The data sources were available through ICES. The study design was a retrospective longitudinal cohort. We used a “difference-in-differences” approach for evaluating changes in ACSC hospitalizations and hospital readmissions before and after the introduction of interprofessional team-based primary care while adjusting for physician group, physician and patient characteristics. Results As of March 31st, 2017, there were a total of 778 physician groups, of which 465 were blended capitation Family Health Organization (FHOs); 177 FHOs (22.8%) were also interprofessional teams and 288 (37%) were more conventional group practices (“non-interprofessional teams”). In this period, there were a total of 13,480 primary care physicians in Ontario of whom 4848 (36%) were affiliated with FHOs—2311 (17.1%) practicing in interprofessional teams and 2537 (18.8%) practicing in non-interprofessional teams. During that same period, there were 475,611 and 618,363 multi-morbid patients in interprofessional teams and non-interprofessional teams respectively out of a total of 2,920,990 multi-morbid adult patients in Ontario. There was no difference in change over time in ACSC admissions between interprofessional and non-interprofessional teams between the pre- and post intervention periods. There were no statistically significant changes in all cause hospital readmission s between the post- and pre-intervention periods for interprofessional and non-interprofessional teams. Conclusions Our study findings indicate that the introduction of interprofessional team-based primary care was not associated with changes in ACSC hospitalization or hospital readmissions. The findings point for the need to couple interprofessional team-based care with other enablers of a strong primary care system to improve health services utilization efficiency.

Abstract Background A small proportion of the population consumes the majority of health care resources. High-cost health care users are a heterogeneous group. We aim to segment a provincial population into relevant homogenous sub-groups to provide actionable information on risk factors associated with high-cost health care use within sub-populations. Methods The Canadian Institute for Health Information (CIHI) Population Grouping methodology was used to define mutually exclusive and clinically relevant health profile sub-groups. High-cost users (> = 90th percentile of health care spending) were defined within each sub-group. Univariate analyses explored demographic, socio-economic status, health status and health care utilization variables associated with high-cost use. Multivariable logistic regression models were constructed for the costliest health profile groups. Results From 2015 to 2017, 1,175,147 individuals were identified for study. High-cost users consumed 41% of total health care resources. Average annual health care spending for individuals not high-cost were $642; high-cost users were $16,316. The costliest health profile groups were ‘long-term care’, ‘palliative’, ‘major acute’, ‘major chronic’, ‘major cancer’, ‘major newborn’, ‘major mental health’ and ‘moderate chronic’. Both ‘major acute’ and ‘major cancer’ health profile groups were largely explained by measures of health care utilization and multi-morbidity. In the remaining costliest health profile groups modelled, ‘major chronic’, ‘moderate chronic’, ‘major newborn’ and ‘other mental health’, a measure of socio-economic status, low neighbourhood income, was statistically significantly associated with high-cost use. Interpretation Model results point to specific, actionable information within clinically meaningful subgroups to reduce high-cost health care use. Health equity, specifically low socio-economic status, was statistically significantly associated with high-cost use in the majority of health profile sub-groups. Population segmentation methods, and more specifically, the CIHI Population Grouping Methodology, provide specificity to high-cost health care use; informing interventions aimed at reducing health care costs and improving population health.

Abstract Background Much of the research on high-cost patients in healthcare has taken a static approach to studying what is actually a dynamic process. High-cost patients often utilize services across multiple sectors along care pathways, but due to the cross-sectional nature of many study designs, we lack a clear understanding of the temporal relationship between high-cost spending in community and acute care. Studying care trajectories for high cost patients with cardiovascular disease (CVD) can shed light on the dynamic interplay between community-based and acute care along the care continuum, and provide information about signals in community care that may indicate future elective and urgent hospitalizations. Methods Using linked health administrative data in Ontario, Canada, 74,683 incident cases with cardiovascular disease were identified between the years 2009 and 2011. Patients were followed for 36 months (total study duration 2009–2014) until the first urgent or elective admission to hospital for a heart-related condition. We used an extended Cox survival model with competing risks to study the relationship between high-cost spending in community care with two mutually exclusive outcomes: urgent or elective hospitalizations. Results Elective hospitalizations were most clearly signaled by a high-cost utilization of community-based specialist services in the month prior to hospital admission (hazard ratio 9.074, p

Abstract Background As the population is aging, the number of persons living with multiple chronic conditions (MCC) is expected to increase. This review seeks to answer two research questions from the perspectives of older adults with MCC, their caregivers and their health care providers (HCPs): 1) What are the health and social care needs of community-dwelling older adults with MCC and their caregivers? and 2) How do social and structural determinants of health impact these health and social care needs? Methods We conducted a scoping review guided by a refinement of the Arksey & O’Malley framework. Articles were included if participants were 55 years or older and have at least two chronic conditions. We searched 7 electronic databases. The data were summarized using thematic analysis. Results Thirty-six studies were included in this review: 28 studies included participants with MCC; 12 studies included HCPs; 5 studies included caregivers. The quality of the studies ranged from moderate to good. Five main areas of needs were identified: need for information; coordination of services and supports; preventive, maintenance and restorative strategies; training for older adults, caregivers and HCPs to help manage the older adults’ complex conditions; and the need for person-centred approaches. Structural and social determinants of health such as socioeconomic status, education and access influenced the needs of older adults with MCC. Conclusion The review highlights that most of the needs of older adults with MCC focus on lack of access to information and coordination of care. The main structural and social determinants that influenced older adults’ needs were their level of education/health literacy and their socioeconomic status.

Abstract Background Population-based risk prediction tools exist for individual chronic diseases. From a population health perspective, studying chronic diseases together provides a comprehensive view of the burden of disease in the population. Thus, public health officials and health policymakers would benefit from a prediction tool that measures the incidence of chronic diseases compositely. This study protocol proposes the development and validation of the Chronic Disease Population Risk Tool (CDPoRT) that will predict the incidence of six chronic diseases in the population setting using multivariable modeling techniques. Methods CDPoRT will be built using population-based responses to the first six cycles of the Canadian Community Health Survey linked to health administrative data in Ontario and Manitoba from 2000 to 2014. Predictors including modifiable lifestyle risk factors (i.e., alcohol consumption, cigarette smoking, diet, and physical activity) will be used to predict time-to-chronic disease incidence (i.e., congestive heart failure, chronic obstructive pulmonary disease, diabetes, lung cancer, myocardial infarction, and stroke including transient ischemic heart attack). Sex-specific Royston-Parmar models will be used for model development and validation with death free of chronic disease as a competing risk. CDPoRT will be developed using an Ontario derivation cohort consisting of 47,960 females and 38,267 males with 7035 and 6220 chronic disease events, respectively. The model will be validated using split-sample validation using an Ontario validation cohort consisting of 20,325 females and 16,627 males with 2972 and 2658 chronic disease events, respectively. The model will be externally validated in the Manitoba validation cohort (i.e., geographic validation) expected to consist of 11,800 females and 9700 males with 1650 and 1550 chronic disease events, respectively. Measures of overall predictive accuracy (e.g., Nagelkerke’s R 2), discrimination (e.g., Harrell’s concordance statistic), and calibration (e.g., calibration plots) will be used to assess predictive performance. Discussion To the extent of our knowledge, CDPoRT will be the first population-based regression prediction model that will predict the incidence of multiple chronic diseases simultaneously at the population level.

Abstract Background The identification of contextual factors that modify associations between client frailty and their health and service use outcomes is essential for informed home health care and policy planning. Our objective was to examine variation in the associations between frailty and select 1-year health outcomes by caregiver distress and client sex among community-residing older care recipients. Methods We conducted a retrospective cohort study using linked population-based clinical and health administrative databases for all long-stay home care clients (n = 234,552) aged 66+ years assessed during April 2010–2013 in Ontario, Canada. Frailty was assessed using a previously validated 72-item frailty index (FI). Presence of caregiver distress was derived from clinical assessment items administered by trained home care assessors. Multivariable log-binomial regression models were used to examine variations in the associations between frailty and outcomes of interest (mortality, nursing home [NH] placement, all-cause and prolonged hospitalization) by caregiver distress, with further model stratification by client sex. Results Frailty prevalence varied little by sex (19.3% women, 19.9% men) despite significant sex-differences in clients’ sociodemographic and health characteristics. In both sexes, frailty was significantly associated with all outcomes, particularly NH placement (RR = 3.84, 95%CI 3.75–3.93) and death (RR = 2.32, 95%CI 2.27–2.37), though risk ratios were greater for women. Caregiver distress was more common with increasing frailty and for male clients, and a significant independent predictor of NH placement and prolonged hospitalization in both sexes. The association between frailty and NH placement (but not other outcomes) varied by caregiver distress for both men and women (p

Abstract Background The burden of multimorbidity is a growing clinical and health system problem that is known to be associated with socioeconomic status, yet our understanding of the underlying determinants of inequalities in multimorbidity and longitudinal trends in measured disparities remains limited. Methods We included all adult respondents from four cycles of the Canadian Community Health Survey (CCHS) (between 2005 to 2011/12), linked at the individual-level to health administrative data in Ontario, Canada (pooled n = 113,627). Multimorbidity was defined at each survey response as having ≥2 (of 17) high impact chronic conditions, based on claims data. Using a decomposition method of the Erreygers-corrected concentration index (CErreygers), we measured household income inequality and the contribution of the key determinants of multimorbidity (including socio-demographic, socio-economic, lifestyle and health system factors) to these disparities. Differences over time are described. We tested for statistically significant changes to measured inequality using the slope index (SII) and relative index of inequality (RII) with a 2-way interaction on pooled data. Results Multimorbidity prevalence in 2011/12 was 33.5% and the CErreygers was − 0.085 (CI: -0.108 to − 0.062), indicating a greater prevalence among lower income groups. In decomposition analyses, income itself accounted more than two-thirds (69%) of this inequality. Age (21.7%), marital status (15.2%) and physical inactivity (10.9%) followed, and the contribution of these factors increased from baseline (2005 CCHS survey) with the exception of age. Other lifestyle factors, including heavy smoking and obesity, had minimal contribution to measured inequality (1.8 and 0.4% respectively). Tests for trends (SII/RII) across pooled survey data were not statistically significant (p = 0.443 and 0.405, respectively), indicating no change in inequalities in multimorbidity prevalence over the study period. Conclusions A pro-rich income gap in multimorbidity has persisted in Ontario from 2005 to 2011/12. These empirical findings suggest that to advance equality in multimorbidity prevalence, policymakers should target chronic disease prevention and control strategies focused on older adults, non-married persons and those that are physically inactive, in addition to addressing income disparities directly.

Abstract Background Information communication technology (ICT) is a critical enabler of integrated models of community-based primary health care; however, little is known about how existing technologies have been used to support new models of integrated care. To address this gap, we draw on data from an international study of integrated models, exploring how ICT is used to support activities of integrated care and the organizational and environmental barriers and enablers to its adoption. Methods We take an embedded comparative multiple-case study approach using data from a study of implementation of nine models of integrated community-based primary health care, the Implementing Integrated Care for Older Adults with Complex Health Needs (iCOACH) study. Six cases from Canada, three each in Ontario and Quebec, and three in New Zealand, were studied. As part of the case studies, interviews were conducted with managers and front-line health care providers from February 2015 to March 2017. A qualitative descriptive approach was used to code data from 137 interviews and generate word tables to guide analysis. Results Despite different models and contexts, we found strikingly similar accounts of the types of activities supported through ICT systems in each of the cases. ICT systems were used most frequently to support activities like care coordination by inter-professional teams through information sharing. However, providers were limited in their ability to efficiently share patient data due to data access issues across organizational and professional boundaries and due to system functionality limitations, such as a lack of interoperability. Conclusions Even in innovative models of care, managers and providers in our cases mainly use technology to enable traditional ways of working. Technology limitations prevent more innovative uses of technology that could support disruption necessary to improve care delivery. We argue the barriers to more innovative use of technology are linked to three factors: (1) information access barriers, (2) limited functionality of available technology, and (3) organizational and provider inertia.

Abstract Background QUALICOPC is an international survey of primary care performance. QUALICOPC data have been used in several studies, yet the representativeness of the Canadian QUALICOPC survey is unknown, potentially limiting the generalizability of findings. This study examined the representativeness of QUALICOPC physician and patient respondents in Ontario using health administrative data. Methods This representativeness study linked QUALICOPC physician and patient respondents in Ontario to health administrative databases at the Institute for Clinical Evaluative Sciences. Physician respondents were compared to other physicians in their practice group and all Ontario primary care physicians on demographic and practice characteristics. Patient respondents were compared to other patients rostered to their primary care physicians, patients rostered to their physicians’ practice groups, and a random sample of Ontario residents on sociodemographic characteristics, morbidity, and health care utilization. Standardized differences were calculated to compare the distribution of characteristics across cohorts. Results QUALICOPC physician respondents included a higher proportion of younger, female physicians and Canadian medical graduates compared to other Ontario primary care physicians. A higher proportion of physician respondents practiced in Family Health Team models, compared to the provincial proportion for primary care physicians. QUALICOPC patient respondents were more likely to be older and female, with significantly higher levels of morbidity and health care utilization, compared with the other patient groups examined. However, when looking at the QUALICOPC physicians’ whole rosters, rather than just the patient survey respondents, the practice profiles were similar to those of the other physicians in their practice groups and Ontario patients in general. Conclusions Comparisons revealed some differences in responding physicians’ demographic and practice characteristics, as well as differences in responding patients’ characteristics compared to the other patient groups tested, which may have resulted from the visit-based sampling strategy. Ontario QUALICOPC physicians had similar practice profiles as compared to non-participating physicians, providing some evidence that the participating practices are representative of other non-participating practices, and patients selected by visit-based sampling may also be representative of visiting patients in other practices. Those using QUALICOPC data should understand this limited representativeness when generalizing results, and consider the potential for bias in their analyses.

Abstract Background Prognostic models incorporating survival analysis predict the risk (i.e., probability) of experiencing a future event over a specific time period. In 2002, Royston and Parmar described a type of flexible parametric survival model called the Royston-Parmar model in Statistics in Medicine, a model which fits a restricted cubic spline to flexibly model the baseline log cumulative hazard on the proportional hazards scale. This feature permits absolute measures of effect (e.g., hazard rates) to be estimated at all time points, an important feature when using the model. The Royston-Parmar model can also incorporate time-dependent effects and be used on different scales (e.g., proportional odds, probit). These features make the Royston-Parmar model attractive for prediction, yet their current uptake for prognostic modeling is unknown. Thus, the objectives were to conduct a scoping review of how the Royston-Parmar model has been applied to prognostic models in health research, to raise awareness of the model, to identify gaps in current reporting, and to offer model building considerations and reporting suggestions for other researchers. Methods Five electronic databases and gray literature indexed in web sources from 2001 to 2016 were searched to identify articles for inclusion in the scoping review. Two reviewers independently screened 1429 articles, and after applying exclusion criteria through a two-step screening process, data from 12 studies were abstracted. Results Since 2001, only 12 studies were identified that used the Royston-Parmar model in some capacity for prognostic modeling, 10 of which used the model as the basis for their prognostic model. The restricted cubic spline varied across studies in the number of interior knots (range 1 to 6), and only three studies reported knot placement. Three studies provided details about the baseline function, with two studies using a figure and the third providing coefficients. However, no studies provided adequate information on their restricted cubic spline to permit others to validate or completely use the model. Conclusions Despite the advantages of the Royston-Parmar model for prognostic models, they are not widely used in health research. Better reporting of details about the restricted cubic spline is needed, so the prognostic model can be used and validated by others. Registration The protocol was registered with Open Science Framework (https://osf.io/r3232/).

Abstract Background Despite the growing interest in assessing the quality of care for depression, there is little evidence to support measurement of the quality of primary care for depression. This study identified evidence-based quality indicators for monitoring, evaluating and improving the quality of care for depression in primary care settings. Methods Ovid MEDLINE and Ovid PsycINFO databases, and grey literature, including relevant organizational websites, were searched from 2000 to 2015. Two reviewers independently selected studies if (1) the study methodology combined a systematic literature search with assessment of quality indicators by an expert panel and (2) quality indicators were applicable to assessment of care for adults with depression in primary care settings. Included studies were appraised using the Appraisal of Indicators through Research and Evaluation (AIRE) instrument, which contains four domains and 20 items. A narrative synthesis was used to combine the indicators within themes. Quality indicators applicable to care for adults with depression in primary care settings were extracted using a structured form. The extracted quality indicators were categorized according to Donabedian’s ‘structure-process-outcome’ framework. Results The search revealed 3838 studies. Four additional publications were identified through grey literature searching. Thirty-nine articles were reviewed in detail and seven met the inclusion criteria. According to the AIRE domains, all studies were clear on purpose and stakeholder involvement, while formal endorsement and usage of indicators in practice were scarcely described. A total of 53 quality indicators were identified from the included studies, many of which overlap conceptually or in content: 15 structure, 33 process and four outcome indicators. This study identified quality indicators for evaluating primary care for depression among adult patients. Conclusions The identified set of indicators address multiple dimensions of depression care and provide an excellent starting point for further development and use in primary care settings.

Abstract Background Mental illness is a substantial and rising contributor to the global burden of disease. Access to and utilization of mental health care, however, is limited by structural barriers such as specialist availability, time, out-of-pocket costs, and attitudinal barriers including stigma. Innovative solutions like virtual care are rapidly entering the health care domain. The advancement and adoption of virtual care for mental health, however, often occurs in the absence of rigorous evaluation and adequate planning for sustainability and spread. Methods A pragmatic randomized controlled trial with a nested comparative effectiveness arm, and concurrent realist process evaluation to examine acceptability, effectiveness, and cost-effectiveness of the Big White Wall (BWW) online platform for mental health self-management and peer support among individuals aged 16 and older who are accessing mental health services in Ontario, Canada. Participants will be randomized to 3 months of BWW or treatment as usual. At the end of the 3 months, participants in the intervention group will have the opportunity to opt-in to an intervention extension arm. Those who opt-in will be randomized to receive an additional 3 months of BWW or no additional intervention. The primary outcome is recovery at 3 months as measured by the Recovery Assessment Scale-revised (RAS-r). Secondary outcomes include symptoms of depression and anxiety measured with the Personal Health Questionnaire-9 item (PHQ-9) and the Generalized Anxiety Disorder Questionnaire-7 item (GAD-7) respectively, quality of life measured with the EQ-5D-5L, and community integration assessed with the Community Integration Questionnaire. Cost-effectiveness evaluations will account for the cost of the intervention and direct health care costs. Qualitative interviews with participants and stakeholders will be conducted throughout. Discussion Understanding the impact of virtual strategies, such as BWW, on patient outcomes and experience, and health system costs is essential for informing whether and how health system decision-makers can support these strategies system-wide. This requires clear evidence of effectiveness and an understanding of how the intervention works, for whom, and under what circumstances. This study will produce such effectiveness data for BWW, while simultaneously exploring the characteristics and experiences of users for whom this and similar online interventions could be helpful. Trial registration Clinicaltrials.gov NCT02896894 . Registered on 31 August 2016 (retrospectively registered).

Abstract Background Patient engagement (PE) in hospital planning and improvement is widespread, yet we lack evidence of its impact. We aimed to identify benefits and harms that could be used to assess the impact of hospital PE. Methods We interviewed hospital-affiliated persons involved in PE activities using a qualitative descriptive approach and inductive content analysis to derive themes. We interpreted themes by mapping to an existing framework of healthcare performance measures and reported themes with exemplar quotes. Results Participants included 38 patient/family advisors, PE managers and clinicians from 9 hospitals (2

Abstract Background The purpose of this study is to analyze the relationship between newly introduced primary care models in Ontario, Canada, and patients’ primary care and total health care costs. A specific focus is on the payment mechanisms for primary care physicians, i.e. fee-for-service (FFS), enhanced-FFS, and blended capitation, and whether providers practiced as part of a multidisciplinary team. Methods Utilization data for a one year period was measured using administrative databases for a 10% sample selected at random from the Ontario adult population. Primary care and total health care costs were calculated at the individual level and included costs from physician services, hospital visits and admissions, long term care, drugs, home care, lab tests, and visits to non-medical health care providers. Generalized linear model regressions were conducted to assess the differences in costs between primary care models. Results Patients not enrolled with a primary care physicians were younger, more likely to be males and of lower socio-economic status. Patients in blended capitation models were healthier and wealthier than FFS and enhanced-FFS patients. Primary care and total health care costs were significantly different across Ontario primary care models. Using the traditional FFS as the reference, we found that patients in the enhanced-FFS models had the lowest total health care costs, and also the lowest primary care costs. Patients in the blended capitation models had higher primary care costs but lower total health care costs. Patients that were in multidisciplinary teams (FHT), where physicians are also paid on a blended capitation basis, had higher total health care costs than non-FHT patients but still lower than the FFS reference group. Primary care and total health care costs increased with patients’ age, morbidity, and lower income quintile across all primary care payment types. Conclusions The new primary care models were associated with lower total health care costs for patients compared to the traditional FFS model, despite higher primary care costs in some models.