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Background Patient engagement (PE) in health‐care planning and improvement is a growing practice. We lack evidence‐based guidance for PE, particularly in hospital settings. This study explored how to optimize PE in hospitals. Methods This study was based on qualitative interviews with individuals in various roles at hospitals with high PE capacity. We asked how patients were engaged, rationale for approaches chosen and solutions for key challenges. We identified themes using content analysis. Results Participants included 40 patient/family advisors, PE managers, clinicians and executives from 9 hospitals (2

Despite growing emphasis on adopting team-based models of primary care to facilitate patient access to a diverse range of care providers, our understanding of team functioning within primary care teams remains limited. This study examined interprofessional teamwork within primary care practices (Family Health Teams [FHT] and Community Health Centers - [CHC]) in Ontario and explored team-level and organizational factors associated with interprofessional teamwork. Interprofessional teamwork was measured using the Collaborative Practice Assessment Tool (CPAT), which was completed by providers in each participating team. The CPAT responses of 988 providers representing on average 12 professions (sd = 2.1) across 66 teams (44 FHTs and 22 CHCs) were included in the analysis. The average CPAT score was 46.6 (sd = 2.5). CHCs had significantly higher CPAT scores than FHTs (mdiff = 1.7, p = .02). Using diverse communication mechanisms to share information, increasing quality improvement capacities, and age of practice, had a statistically significant positive association with CPAT scores. Increasing team size, using centralized administrative processes, a high level of information exchange, and having a mixed governance board were significantly negatively associated with CPAT score. Findings illustrate factors associated with interprofessional teamwork and offer insight into the comparative performance of two team-based primary care models in Ontario.

Purpose/setting To encourage clinical and financial efficiency, the Canadian province of Ontario initiated an integrated care program – Integrated Funding Models (IFMs) that required collaboration and coordination across acute and post-acute care sectors. This research shows how program implementers went beyond policy-makers’ original designs, to make integrated care sustainable for chronic diseases. Methods Forty-five interviews were conducted with program participants at three chronic disease programs, as well as with policymakers. Interviews were conducted over two phases; during early implementation in 2016, and as programs matured in 2018. Data were analyzed through a cultural constructivist lens to understand how participants shaped programs. Findings Participants desired greater accountability and control. Participants in the first program wanted localized control over decision-making. In the second, participants initiated greater control over financial uncertainty. In the third program, hospital participants sought greater control over community care. Participants across programs simultaneously wanted integrated care to be expanded holistically, spatially, and temporally for patients, extending the length of care, and expanding the spaces in which care was provided. Findings also suggest a gap between program implementers’ and policymakers’ conceptualizations of integrated care. Conclusion This work shows how IFMs were reimagined in ways that transcended their original conceptualization as spatially and temporally delimited initiatives aimed at improving coordination and efficiency. It has practical implications for those facing sustainability challenges in other contexts.

Objective: This study examines whether depression is associated with the development of physical illness and multimorbidity, after controlling for socioeconomic, behavioral, and other potential confounders. Methods: This is a retrospective cohort study in which adult respondents to three nationally representative population health surveys were linked to health administrative databases in Ontario, Canada, and followed for 10 years from survey index. Respondents with any of the study outcome conditions at baseline were excluded to create a final cohort of 29,838 participants. The main exposure of interest was depression, measured using the Composite International Diagnostic Interview–Short Form for Major Depression. We controlled for age, body mass index, marital status, immigrant status, annual household income, smoking, alcohol consumption, physical activity, health status, and having a regular doctor. The outcome measure was the development of physical illness over 10 years of follow-up, defined as 1 of 15 common chronic conditions using administrative data. Results: Among the 29,838 participants (15,259 [51%] female), 8% of females and 4% of males had depression at baseline. In this cohort with no comorbidities at baseline, even in the fully adjusted model, depression increased the risk of developing a first physical illness for females (hazard ratio [HR] 1.16; 95% CI, 1.07 to 1.26) and males (HR 1.20; 95% CI, 1.07 to 1.36) and increased the risk of developing a second physical illness for females (HR 1.16; 95% CI, 1.02 to 1.33) over 10 years of follow-up. Conclusions: For individuals with no prior comorbidities, depression is associated with a greater risk of developing subsequent physical illness and multimorbidity over time. Thus, depression identifies a population of people who may benefit from early identification, additional screening, and intervention. Further study needs to be done to determine whether interventions to manage and support people with depression can prevent or delay the increased risk of multimorbidity.

High-income countries face the challenge of providing effective and efficient care to the relatively small proportion of their populations with high health and social care needs. Recent reports sug...

As high-income countries face the challenge of providing better and more efficient integrated health and social care to high-needs and high-cost populations, they may require innovative policy supp...

Objectives The main objective of the study was to investigate annual changes in the sociodemographic characteristics, morbidity, and functional status of new nursing home residents in Ontario, Canada, between 2000 and 2015. A secondary objective was to develop and assess the quality of an algorithm for ascertaining admissions into publicly funded nursing homes in Ontario using a combination of health administrative data sources that indirectly identifies the residential status of new nursing home residents. Design Population-based serial cross-sectional study with an accompanying quality assessment study of algorithms. Setting Publicly funded nursing care homes in Ontario, Canada. Participants The reference standard for the assessment of algorithm performance was 21 544 newly admitted nursing home residents identified from the Resident Assessment Instrument-Minimum Data Set in 2012. The selected algorithm was then used to identify serial cross-sectional cohorts of newly admitted residents between 2000 and 2015 that ranged in size between 14 651 and 23 630 residents. Measurements Sociodemographic characteristics, morbidity, and functional status of new residents were determined upon admission to examine patterns in the cohorts' profiles. Results The proportion of residents aged 85 years and older increased from 45.1% to 53.8% over 16 years. The proportions of individuals with seven or more chronic conditions (from 14.1% to 22.1%) and with nine or more prescription medications (from 44.9% to 64.2%) have also increased in parallel over time. Hypertension, osteoarthritis, and dementia were the most prevalent conditions captured, with the proportion of incoming residents with dementia increasing from 42.3% to 54.1% between 2000 and 2015. Newly admitted residents were more likely to have extensive physical and cognitive impairments upon admission. Conclusion Admission trends show that new residents were older and had greater multimorbidity and limitations in physical functioning over time. J Am Geriatr Soc 68:1293-1300, 2020.

Self-care disability is difficulty with or dependence on others to perform activities of daily living, such as eating and dressing. Disablement is worsening self-care disability measured over time. The disablement process model (DPM) is often used to conceptualize gerontology research on self-care disability and disablement; however, no summary of variables that align with person-level DPM constructs exists. This review summarizes the results of 88 studies to identify the nature and role of variables associated with disability and disablement in older adults according to the person-level constructs (e.g., demographic characteristics, chronic pathologies) in the DPM. It also examines the evidence for cross-sectional applications of the DPM and identifies common limitations in extant literature to address in future research. Researchers can apply these results to guide theory-driven disability and disablement research using routinely collected health data from older adults.

Objective In this study, we investigated the incremental 1-year direct costs of health care associated with frailty among home care recipients in Ontario with and without dementia. Methods We conducted a cohort study of 159,570 home care clients aged 50 years and older in Ontario, Canada in 2014/2015. At index home care assessment, we ascertained dementia status using a validated algorithm and frailty level (robust, prefrail, frail) based on the proportion of accumulated to potential health deficits. Clients were followed for 1-year during which we obtained direct overall and sector-specific publicly-funded health care costs (in 2015 Canadian dollars). We estimated the incremental effect of frailty level on costs using a 3-part survival- and covariate-adjusted estimator. All analyses were stratified by dementia status. Results Among those with dementia (n=42,828), frailty prevalence was 32.1% and the average 1-year cost was $30,472. The incremental cost of frailty (vs. robust) was $10,845 [95% confidence interval (CI): $10,112-$11,698]. Among those without dementia (n=116,742), frailty prevalence was 25.6% and the average 1-year cost was $28,969. Here, the incremental cost of frailty (vs. robust) was $12,360 (95% CI: $11,849-$12,981). Large differences in survival between frailty levels reduced incremental cost estimates, particularly for the dementia group (survival effect: -$2742; 95% CI: -$2914 to -$2554). Conclusions Frailty was associated with greater 1-year health care costs for persons with and without dementia. This difference was driven by a greater intensity of health care utilization among frail clients. Mortality differences across the frailty levels mitigated the association especially among those with dementia.

BackgroundThis study examined the incidence of a person’s first diagnosis of a selected chronic disease, and the relationships between modifiable lifestyle risk factors and age to first of six chronic diseases.MethodsOntario respondents from 2001 to 2010 of the Canadian Community Health Survey were followed up with administrative data until 2014 for congestive heart failure, chronic obstructive respiratory disease, diabetes, lung cancer, myocardial infarction and stroke. By sex, the cumulative incidence function of age to first chronic disease was calculated for the six chronic diseases individually and compositely. The associations between modifiable lifestyle risk factors (alcohol, body mass index, smoking, diet, physical inactivity) and age to first chronic disease were estimated using cause-specific Cox proportional hazards models and Fine-Gray competing risk models.ResultsDiabetes was the most common disease. By age 70.5 years (2015 world life expectancy), 50.9% of females and 58.1% of males had at least one disease and few had a death free of the selected diseases (3.4% females; 5.4% males). Of the lifestyle factors, heavy smoking had the strongest association with the risk of experiencing at least one chronic disease (cause-specific hazard ratio = 3.86; 95% confidence interval = 3.46, 4.31). The lifestyle factors were modelled for each disease separately, and the associations varied by chronic disease and sex.ConclusionsWe found that most individuals will have at least one of the six chronic diseases before dying. This study provides a novel approach using competing risk methods to examine the incidence of chronic diseases relative to the life course and how their incidences are associated with lifestyle behaviours.

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

Background Patient and family engagement (PE) in healthcare planning and improvement achieves beneficial outcomes and is widely advocated, but a lack of resources is a critical barrier. Little prior research studied how organizations support engagement specifically in hospitals. Objective We explored what constitutes hospital capacity for engagement. Methods We conducted descriptive qualitative interviews and complied with criteria for rigour and reporting in qualitative research. We interviewed patient/family advisors, engagement managers, clinicians and executives at hospitals with high engagement activity, asking them to describe essential resources or processes. We used content analysis and constant comparison to identify themes and corresponding quotes and interpreted findings by mapping themes to two existing frameworks of PE capacity not specific to hospitals. Results We interviewed 40 patient/family advisors, patient engagement managers, clinicians and corporate executives from nine hospitals (two Conclusion The findings build on prior research that largely focused on PE in individual clinical care or research or in primary care planning and improvement. The findings closely aligned with existing frameworks of organizational capacity for PE not specific to hospital settings, which suggests that hospitals could use the blended framework to plan, evaluate and improve their PE programs. Further research is needed to yield greater insight into how to promote and enable compensation for patient/family advisors and the role of clinician or staff champions in supporting PE.

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: Conclusions Hospitals with fewer resources can establish favourable PE conditions by deploying PE widely and actively engaging patients. Healthcare policy-makers, hospital executives and PE managers can use these findings to allocate PE resources. Future research should explore how PE modes and methods impact clinical outcomes.

Background Older adults with multimorbidity and complex care needs (CCN) are among those most likely to experience frequent care transitions between settings, particularly from hospital to home. Transition periods mark vulnerable moments in care for individuals with CCN. Poor communication and incomplete information transfer between clinicians and organizations involved in the transition from hospital to home can impede access to needed support and resources. Establishing digitally supported communication that enables person-centered care and supported self-management may offer significant advantages as we support older adults with CCN transitioning from hospital to home. Objective This protocol outlines the plan for the development, implementation, and evaluation of a Digital Bridge co-designed to support person-centered health care transitions for older adults with CCN. The Digital Bridge builds on the foundation of two validated technologies: Care Connector, designed to improve interprofessional communication in hospital, and the electronic Patient-Reported Outcomes (ePRO) tool, designed to support goal-oriented care planning and self-management in primary care settings. This project poses three overarching research questions that focus on adapting the technology to local contexts, evaluating the impact of the Digital Bridge in relation to the quadruple aim, and exploring the potential to scale and spread the technology. Methods The study includes two phases: workflow co-design (phase 1), followed by implementation and evaluation (phase 2). Phase 1 will include iterative co-design working groups with patients, caregivers, hospital providers, and primary care providers to develop a transition workflow that will leverage the use of Care Connector and ePRO to support communication through the transition process. Phase 2 will include implementation and evaluation of the Digital Bridge within two hospital systems in Ontario in acute and rehab settings (600 patients: 300 baseline and 300 implementation). The primary outcome measure for this study is the Care Transitions Measure–3 to assess transition quality. An embedded ethnography will be included to capture context and process data to inform the implementation assessment and development of a scale and spread strategy. An Integrated Knowledge Translation approach is taken to inform the study. An advisory group will be established to provide insight and feedback regarding the project design and implementation, leading the development of the project knowledge translation strategy and associated outputs. Results This project is underway and expected to be complete by Spring 2024. Conclusions Given the real-world implementation of Digital Bridge, practice changes in the research sites and variable adherence to the implementation protocols are likely. Capturing and understanding these considerations through a mixed-methods approach will help identify the range of factors that may influence study results. Should a favorable evaluation suggest wide adoption of the proposed intervention, this project could lead to positive impact at patient, clinician, organizational, and health system levels. Trial Registration ClinicalTrials.gov NCT04287192; https://clinicaltrials.gov/ct2/show/NCT04287192 International Registered Report Identifier (IRRID) PRR1-10.2196/20220

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.

Background: Providing equitable care to patients in need across the life course is a priority for many healthcare systems. Aim: To estimate socioeconomic inequality trends in the proportions of decedents that died in the community and that received palliative care within 30 days of death (including home visits and specialist/generalist physician encounters). Design: Cohort study based on health administrative data. Socioeconomic position was measured by area-level material deprivation. Inequality gaps were quantified annually and longitudinally using the slope index of inequality (absolute gap) and relative index of inequality (relative gap). Setting/Participants: A total of 729,290 decedents aged ⩾18 years in Ontario, Canada from 2009 to 2016. Results: In 2016, the modelled absolute gap (corresponding 95% confidence interval) between the most- and least-deprived neighbourhoods in community deaths was 4.0% (2.9–5.1%), which was 8.6% (6.2–10.9%) of the overall mean (46.6%). Relative to 2009, these inequalities declined modestly. Inequalities in 2016 were evident for palliative home visits (6.8% (5.8–7.8%) absolute gap, 26.3% (22.5–30.0%) relative gap) and for physician encounters (6.8% (5.7–7.9%) absolute gap, 13.2% (11.0–15.3%) relative gap), and widened from 2009 for physician encounters only on the absolute scale. Inequalities varied considerably across disease trajectories (organ failure, terminal illness, frailty, and sudden death). Conclusion: Key measures of end-of-life care are not achieved equally across socioeconomic groups. These data can be used to inform policy strategies to improve delivery of palliative and end-of-life services.

Principles and methods drawn from decades of work showing that lower socioeconomic status is associated with poorer health should guide efforts to monitor and mitigate the impact of the covid-19 pandemic argue Geoffrey Anderson and colleagues

Background Higher staffing levels in long-term care have been associated with better outcomes for residents in several landmark studies. However previous systematic reviews found mixed results, calling into question the effectiveness of higher levels of staff. With persistent concerns about quality, rising resident acuity, and a growing demographic of seniors requiring more services, understanding the relationship between quality and long-term care staffing is a growing concern. Objectives This review considered the following question: What is the influence of nursing and personal care staffing levels (registered nurse, licensed practical nurse, and nursing assistant) and / or skill mix on long-term care residents, measured by quality of care indicators? Design Preferred Reporting Items for Systematic Review and Meta-analysis Protocols guided the report of this systematic review. Data sources Published articles focused on quality and nursing and personal care staffing in long-term care in peer-reviewed databases (MEDLINE, CINAHL, and AGELINE) and several Cochrane databases to retrieve studies published between January 2008 and June 2020. Review methods A systematic review was conducted. 11,096 studies were identified, of which 34 were included in this review. The Strengthening the Reporting of Observational Studies in Epidemiology checklist was used to evaluate study quality and risk of bias, and five quality measures were selected for in-depth analyses: pressure ulcers, hospitalizations, physical restraints, deficiencies and catherization. Results This review confirms previous review findings that evidence on the relationships between quality and long-term care staffing level and skill mix, remain mixed. Higher staffing levels and skill mix generally supported better rather than worse outcomes. Significant and consistent findings were more evident when staffing levels were further analyzed by indicator and staffing category. For example, registered nurses were consistently associated with significantly fewer pressure ulcers, hospitalizations, and urinary tract infections. Few studies examined the impact of total nursing and personal care hours compared to the impact of specific categories or classes of nursing staff on outcomes. Conclusions Evidence on the relationship between quality and long-term care staffing remains mixed, however some categories of nursing staff may be more effective at improving the quality of certain indicators. Study quality has improved minimally over the last decade. Although research continues to standardize units of measurement, and longitudinal and instrumental variable analyses are increasingly being used, very few studies controlled for endogeneity, conducted adequate risk-adjustment, and used resident-level data. Additional strides must still be made to improve the rigor of long-term care staffing research.

Introduction: Providers, managers, health system leaders, and researchers could learn across countries implementing system-wide models of integrated care, but require accessible methods to do so. This study assesses if a common framework could describe and compare key components of international models of integrated care. Theory and methods: A framework developed for an international study of programs that address high needs high cost patients was used to describe and compare 11 case studies analyzed in two international research projects; the Implementing Integrated Care for Older Adults with Complex Health Needs (iCOACH) study in Canada and New Zealand, and the Vilans research group exploring models in the Netherlands. Comparative summaries were generated, with findings discussed at a 2019 International Conference on Integrated Care workshop. Results: The template was found to be useful to compare integrated case analyses in different contexts, and stands apart from other case comparison approaches as it is easily applied and can provide practical guidance for frontline staff and managers. Areas of improvement for the template are identified and two updated versions are presented. Conclusions and discussion: There is value to using a common template to provide guidance in international comparison of models of integrated care. We discuss the applicability of the approach to support scale and spread of integrated care internationally.

Policy Points Policymakers interested in advancing integrated models of care may benefit from understanding how integration itself is generated. Integration is analyzed as the generation of connectivity and consensus-the coming together of people, practices, and things. Integration was mediated by chosen program structures and generated by establishing partnerships, building trust, developing thoughtful models, engaging clinicians in strategies, and sharing data across systems. This study provides examples of on-the-ground integration strategies in 6 programs, suggests contexts that better lend themselves to integration initiatives, and demonstrates how programs may be examined for the very thing they seek to implement-integration itself. Context By bundling services and encouraging interprofessional and interorganizational collaboration, integrated health care models counter fragmented health care delivery and rising system costs. Building on a policy impetus toward integration, the Ministry of Health and Long-Term Care in the Canadian province of Ontario chose 6 programs, each comprising multiple hospital and community partners, to implement bundled care, also referred to as integrated-funding models. While research has been conducted on the facilitators and challenges of integration, there is less known about how integration is generated. This article explores the generation of integration through the dynamic interplay of contexts and mechanisms and of structures and subjects. Methods For this qualitative study, we conducted 48 interviews with program stakeholders, from organization leaders and managers to physicians and integrated care coordinators, across the hospital-community spectrum. We then used content analysis to explore the extent to which themes were shared across programs and to identify idiosyncrasies, followed by a realist evaluation approach to understand how integration was produced in structural and everyday ways in local program contexts. Findings Integration was generated through the successful production of connectivity and consensus-the coming together of people, practice, and things, as perceived and experienced by stakeholders. When able, the programs harnessed existing cultures of clinician engagement, and leveraged established partnerships. However, integration could be achieved even without these histories, by building trust, developing thoughtful models, using clinicians' existing engagement strategies, and implementing shared systems and technologies. The programs' structures (from their scale to their chosen patient population) also contextualized and mediated integration. Conclusions This article has both practical and theoretical implications. It provides transferable insights into the strategies by which integration is generated. It also contributes conceptually to realist approaches to evaluation by advancing an understanding of mechanisms as contextually and temporally contingent, with the capacity to produce new contexts, which in turn generate new sets of mechanisms.

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

This issue of Healthcare Quarterly introduces a three-part series featuring international perspectives on health service delivery models that improve system integration and ensure seamless services and better coordination. The series, developed by Ontario's Change Foundation, will feature Chris Ham, chief executive of the London-based King's Fund think tank; Geoff Huggins, director for health and social care integration in Scotland; and Helen Bevan, chief transformation officer of England's National Health Service.

BACKGROUND: Although a delay of 24 hours for hip fracture repair is associated with medical complications and costs, it is unknown how long patients wait for surgery for hip fracture. We describe novel methods for measuring exact urgent and emergent surgical wait times (in hours) and the factors that influence them. METHODS: Adults aged 45 years and older who underwent surgery for hip fracture (the most common urgently performed procedure) in Ontario, Canada, between 2009 and 2014 were eligible. Validated data from linked health administrative databases were used. The primary outcome was the time elapsed from hospital arrival recorded in the National Ambulatory Care Reporting System until the time of surgery recorded in the Discharge Abstract Database (in hours). The influence of patient, physician and hospital factors on wait times was investigated using 3-level, hierarchical linear regression models. RESULTS: Among 42 230 patients with hip fracture, the mean (SD) wait time for surgery was 38.76 (28.84) hours, and 14 174 (33.5%) patients underwent surgery within 24 hours. Variables strongly associated with delay included time for hospital transfer (adjusted increase of 26.23 h, 95% CI 25.38 to 27.01) and time for preoperative echocardiography (adjusted increase of 18.56 h, 95% CI 17.73 to 19.38). More than half of the hospitals (37 of 72, 51.4%), compared with 4.8% of surgeons and 0.2% of anesthesiologists, showed significant differences in the risk-adjusted likelihood of delayed surgery. INTERPRETATION: Exact wait times for urgent and emergent surgery can be measured using Canada’s administrative data. Only one-third of patients received surgery within the safe time frame (24 h). Wait times varied according to hospital and physician factors; however, hospital factors had a larger impact.

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.

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. Electronic supplementary material The online version of this article (10.1186/s12939-018-0800-6) contains supplementary material, which is available to authorized users.

Measuring the value of medical imaging is challenging, in part, due to the lack of conceptual frameworks underlying potential mechanisms where value may be assessed. To address this gap, this article proposes a framework that builds on the large body of literature on quality of hospital care and the classic structure-process-outcome paradigm. The framework was also informed by the literature on adoption of technological innovations and introduces 2 distinct though related aspects of imaging technology not previously addressed specifically in the literature on quality of hospital care: adoption (a structural hospital characteristic) and use (an attribute of the process of care). The framework hypothesizes a 2-part causality where adoption is proposed to be a central, linking factor between hospital structural characteristics, market factors, and hospital outcomes (ie, quality and efficiency). The first part indicates that hospital structural characteristics and market factors influence or facilitate the adoption of high technology medical imaging within an institution. The presence of this technology, in turn, is hypothesized to improve the ability of the hospital to deliver high quality and efficient care. The second part describes this ability throughout 3 main mechanisms pointing to the importance of imaging use on patients, to the presence of staff and qualified care providers, and to some elements of organizational capacity capturing an enhanced clinical environment. The framework has the potential to assist empirical investigations of the value of adoption and use of medical imaging, and to advance understanding of the mechanisms that produce quality and efficiency in hospitals.

Objective To determine the lifetime cost-of-illness of chronic ulcers from the perspective of the Ontario public health care payer. Methods We calculated health care costs for a cohort of individuals hospitalized for a diabetic foot ulcer, pressure ulcer or leg ulcer between 2005 and 2011 using Ontario administrative health care data. Lifetime costs for this cohort were estimated using phase-based costing methods. Net cost was determined by calculating the difference in lifetime costs between the chronic ulcer cohort and a matched non-chronic ulcer cohort. Matching was conducted using a combination of hard matching and propensity score methods. The chronic ulcer cohort represents all individuals residing in Ontario, Canada. Results A total of 7316 individuals with chronic ulcers were identified and matched with a non-chronic ulcer cohort (5583 diabetic foot ulcer, 1470 pressure ulcer, 262 leg ulcer). Lifetime net modeled cost of diabetic foot ulcer was $619,300 (95% CI $593,900–$642,800), for pressure ulcer $98,500 (95% CI $88,300–$109,100) and for leg ulcer $548,100 (95% CI $524,400–$569,500). Conclusions Chronic ulcers present a substantial economic burden to the health care system. Health care decision makers are encouraged to consider additional resources to preventative interventions for chronic ulcers to reduce downstream costs.

With falling mortality rates for several diseases, patients are living longer with complex multimorbidities. We explored the burden of multimorbidity at the time of death, how it varies by socioeconomic status, and trends over time in Ontario, Canada. We calculated the proportions of decedents with varying degrees of multimorbidity and types of conditions at death, and we analyzed the trend from 1994 to 2013 in the number of conditions at the time of death. The prevalence of multimorbidity at death increased from 79.6 percent in 1994 to 95.3 percent in 2013. An upward trend in the number of conditions per person at death was observed for all chronic conditions except chronic coronary syndrome, congestive heart failure, and stroke. Chronic respiratory diseases and diabetes were disproportionately represented in low-income and deprived neighborhoods. The trend toward greater multimorbidity burden over time and the existence of steep socioeconomic gradients underscore the importance of integrated health care planning for preventing and managing multiple complex conditions.

Complex adaptive systems (CAS) theory views healthcare as numerous sub-systems characterized by diverse agents that interact, self-organize, and continuously adapt. We apply this complexity science perspective to examine the extent to which CAS theory is a useful lens for designing and implementing health policies. We present the case of Health Links, a "low rules" policy intervention in Ontario, Canada aimed at stimulating the development of voluntary networks of health and social organizations to improve care coordination for the most frequent users of the healthcare system. Our sample consisted of stakeholders from regional governance bodies and organizations partnering in Health Links. Qualitative interview data were coded using the key complexity concepts of sensemaking, self-organization, interconnections, coevolution, and emergence. We found that the complexity-compatible policy design successfully stimulated local dynamics of flexibility, experimentation, and learning and that important mediating factors include leadership, readiness, relationship-building, role clarity, communication, and resources. However, we saw tensions between preferences for flexibility and standardization. Desirable developments occurred only in some settings and failed to flow upward to higher levels, resulting in a piecemeal and patchy landscape. Attention needs to be paid not only to local dynamics and processes, but also to regional and provincial levels to ensure that learning flows to the top and informs decision-making. We conclude that implementation of complexity-compatible policies needs a balance between flexibility and consistency and the right leadership to coordinate the two. Complexity-compatible policy for integrated healthcare is more than simply 'letting a thousand flowers bloom'.

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/). Electronic supplementary material The online version of this article (10.1186/s41512-018-0026-5) contains supplementary material, which is available to authorized users.

BACKGROUND: There is no reliable estimate of costs incurred by motorcycle crashes. Our objective was to calculate the direct costs of all publicly funded medical care provided to individuals after motorcycle crashes compared with automobile crashes. METHODS: We conducted a population-based, matched cohort study of adults in Ontario who presented to hospital because of a motorcycle or automobile crash from 2007 through 2013. For each case, we identified 1 control absent a motor vehicle crash during the study period. Direct costs for each case and control were estimated in 2013 Canadian dollars from the payer perspective using methodology that links health care use to individuals over time. We calculated costs attributable to motorcycle and automobile crashes within 2 years using a difference-in-differences approach. RESULTS: We identified 26 831 patients injured in motorcycle crashes and 281 826 injured in automobile crashes. Mean costs attributable to motorcycle and automobile crashes were $5825 and $2995, respectively (p INTERPRETATION: Considering both the attributable cost and higher rate of injury, we found that each registered motorcycle in Ontario costs the public health care system 6 times the amount of each registered automobile. Medical costs may provide an additional incentive to improve motorcycle safety.

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.

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-for-Service (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 enhanced-FFS (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.

PURPOSE The patient medical home (PMH) model aims to improve patient satisfaction and health outcomes in Canada, but since its introduction in 2009, there has been no evaluation of the extent to which primary care conforms with PMH attributes. Our objective was to compare current primary care across Canada with the 10 goals of the PMH model. METHODS A cross-sectional survey of primary care organization and delivery was conducted in Canadian provinces to evaluate the PMH-based attributes of primary care practices. Family physician and patient responses were mapped to the 10 goals of the PMH model. We used regression models to describe the provinces’ success in meeting the goals, taking specific practice characteristics into account. We created a PMH composite score by weighting each goal equally for each practice and aggregating these by province. The PMH score is the sum of the values for each goal, which were scored from 0 to 1; a score of 10 indicates that all 10 goals of the PMH model were achieved. RESULTS Seven hundred seventy-two primary care practices and 7,172 patients participated in the survey. The average national PMH score was 5.36 (range 4.75–6.23) of 10. Ontario was the only province to score significantly higher than Canada as a whole, whereas Quebec, Newfoundland/Labrador, and New Brunswick/Prince Edward Island scored below the national average. There was little variation, however, among provinces in achieving the 10 PMH goals. CONCLUSIONS Provincial PMH scores indicate considerable room for improvement if the PMH goals are to be fully implemented in Canada.

Objective: To systematically review the published academic literature on the cost of chronic ulcers. Methods: A literature search was conducted in MEDLINE, EMBASE, HealthSTAR, Econlit and CINAHL up to 12 May 2016 to identify potential studies for review. Cost search terms were based on validated algorithms. Clinical search terms were based on recent Cochrane reviews of interventions for chronic ulcers. Titles and abstracts were screened by two reviewers to determine eligibility for full text review. Study characteristics were summarised. The quality of reporting was evaluated using a modified cost-of-illness checklist. Mean costs were adjusted and inflated to 2015 $US and presented for different durations and perspectives. Results: Of 2267 studies identified, 36 were eligible and included in the systematic review. Most studies presented results from the health-care public payer or hospital perspective. Many studies included hospital costs in the analysis and only reported total costs without presenting condition-specific attributable costs. The mean cost of chronic ulcers ranged from $1000 per year for patient out of pocket costs to $30,000 per episode from the health-care public payer perspective. Mean one year cost from a health-care public payer perspective was $44,200 for diabetic foot ulcer (DFU), $15,400 for pressure ulcer (PU) and $11,000 for leg ulcer (LU). Conclusions: There was large variability in study methods, perspectives, cost components and jurisdictions, making interpretation of costs difficult. Nevertheless, it appears that the cost for the treatment of chronic ulcers is substantial and greater attention needs to be made for preventive measures.

Small randomized trials demonstrated that a lower compared with higher dialysate temperature reduced the average drop in intradialytic blood pressure. Some observational studies demonstrated that a lower compared with higher dialysate temperature was associated with a lower risk of all-cause mortality and cardiovascular mortality. There is now the need for a large randomized trial that compares the effect of a low vs high dialysate temperature on major cardiovascular outcomes.The purpose of this study is to test the effect of outpatient hemodialysis centers randomized to (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol for 4 years on cardiovascular-related death and hospitalizations.The design of the study is a pragmatic, registry-based, open-label, cluster randomized controlled trial.Hemodialysis centers in Ontario, Canada, were randomized on February 1, 2017, for a trial start date of April 3, 2017, and end date of March 31, 2021.In total, 84 hemodialysis centers will care for approximately 15 500 patients and provide over 4 million dialysis sessions over a 4-year follow-up.Hemodialysis centers were randomized (1:1) to provide (1) a personalized temperature-reduced dialysate protocol or (2) a standard-temperature dialysate protocol of 36.5°C. For the personalized protocol, nurses set the dialysate temperature between 0.5°C and 0.9°C below the patient's predialysis body temperature for each dialysis session, to a minimum dialysate temperature of 35.5°C.A composite of cardiovascular-related death or major cardiovascular-related hospitalization (a hospital admission with myocardial infarction, congestive heart failure, or ischemic stroke) captured in Ontario health care administrative databases.The primary analysis will follow an intent-to-treat approach. The hazard ratio of time-to-first event will be estimated from a Cox model. Within-center correlation will be considered using a robust sandwich estimator. Observation time will be censored on the trial end date or when patients die from a noncardiovascular event.www.clinicaltrials.gov; identifier: NCT02628366.De petits essais à répartition aléatoire ont montré que l’utilisation d’un dialysat à basse température réduisait le risque d’hypotension intra-dialytique. De même, certaines études observationnelles ont démontré qu’un dialysat à basse température était associé à un plus faible risque de mortalité toute cause ou d’origine cardiovasculaire. Le temps est venu de procéder à un vaste essai à répartition aléatoire comparant les effets d’un dialysat à basse température et à température standard sur les principaux résultats cardiovasculaires.Répartir aléatoirement des centres d’hémodialyse ambulatoire pour qu’ils suivent pendant quatre ans (i) un protocole personnalisé de dialysat à basse température ou (ii) un protocole de dialysat à température standard, et tester l’effet sur les hospitalisations et la mortalité attribuables à des événements cardiovasculaires.Un essai clinique à répartition aléatoire en grappes.Le 1er février 2017, des centres d’hémodialyse de l’Ontario (Canada) ont été répartis aléatoirement en vue d’un essai qui a débuté le 3 avril 2017 et qui se poursuivra jusqu’au 31 mars 2021.Quatre-vingt-quatre centres d’hémodialyse qui prendront en charge environ 15 500 patients pendant les quatre ans de suivi.Les centres d’hémodialyse ont été répartis aléatoirement (1:1) pour offrir (i) un protocole personnalisé de dialysat à température réduite ou (ii) un protocole de dialysat à 36,5°C. Pour le protocole personnalisé, les infirmières règlent la température du dialysat entre 0,5 et 0,9°C sous la température corporelle du patient mesurée avant la dialyse, jusqu’à une température minimale de 35,5°C.Un ensemble d’hospitalisations attribuables à un événement cardiovasculaire majeur (accident ischémique cérébral non fatal, infarctus du myocarde ou insuffisance cardiaque congestive) et de décès d’origine cardiovasculaire consignés dans les bases de données de santé de l’Ontario.L’analyse primaire adoptera une approche fondée sur l’intention de traiter. Un modèle de Cox servira à estimer le rapport de risque du temps écoulé jusqu’au premier événement. La corrélation intra-centre sera prise en compte à l’aide d’un estimateur sandwich robuste. Le temps d’observation sera censuré à la date de fin de l’essai ou au moment d’un décès non lié à un événement cardiovasculaire.

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.

Background We report on the impact of two system-level policy interventions (the Long-Term Care Homes Act [LTCHA] and Public Reporting) on publicly reported physical restraint use and non-publicly reported potentially inappropriate use of antipsychotics in Ontario, Canada. Methods We used interrupted time series analysis to model changes in the risk-adjusted use of restraints and antipsychotics before and after implementation of the interventions. Separate analyses were completed for early ([a] volunteered 2010/2011) and late ([b] volunteered March 2012; [c] mandated September 2012) adopting groups of Public Reporting. Outcomes were measured using Resident Assessment Instrument Minimum Data Set (RAI-MDS) data from January 1, 2008 to December 31, 2014. Results For early adopters, enactment of the LTCHA in 2010 was not associated with changes in physical restraint use, while Public Reporting was associated with an increase in the rate (slope) of decline in physical restraint use. By contrast, for the late-adopters of Public Reporting, the LTCHA was associated with significant decreases in physical restraint use over time, but there was no significant increase in the rate of decline associated with Public Reporting. As the LTCHA was enacted, potentially inappropriate use of antipsychotics underwent a rapid short-term increase in the early volunteer group, but, over the longer term, their use decreased for all three groups of homes. Conclusions Public Reporting had the largest impact on voluntary early adopters while legislation and regulations had a more substantive positive effect upon homes that delayed public reporting.

BACKGROUND: There is a lack of data in Canada on the longitudinal effects of adverse events that occur in hospital, specifically in the period after discharge. Our objective was to quantify the impact of adverse events on hospital length of stay, length of person-centred episodes of care (PCEs) and costs of PCEs, as well as their impact on the total health system. METHODS: We conducted a population-based, retrospective cohort study using linked health administrative databases. We included adults in Ontario who had an acute hospital admission between Apr. 1, 2015, and Mar. 31, 2016. We grouped hospital admissions into 1 of 9 episode types and used the Canadian Institute for Health Information methodology for hospital harm to measure adverse events. We specified generalized linear models to estimate the impact of hospital harm on the following: incremental length of index acute hospital admission, incremental length of the PCE, and incremental costs of the PCE. RESULTS: Out of 610 979 hospital admissions, 36 004 (5.9%) involved an occurrence of harm. The impact of harm on the incremental length of hospital stay ranged from 0.4 to 24.2 days (p INTERPRETATION: We found that experiencing harm in hospital significantly affects both in-hospital and post-discharge use of health services and costs of care, and constitutes an enormous expense to Ontario’s publicly funded health system.

ObjectiveTo identify the relationships between the context in which integrated care programmes (ICPs) for community-dwelling frail older people are applied, the mechanisms by which the programmes do (not) work and the outcomes resulting from this interaction by establishing a programme theory.DesignRapid realist review.Inclusion criteriaReviews and meta-analyses (January 2013–January 2019) and non-peer-reviewed literature (January 2013–December 2019) reporting on integrated care for community-dwelling frail older people (≥60 years).AnalysisSelection and appraisal of documents was based on relevance and rigour according to the Realist And Meta-narrative Evidence Syntheses: Evolving Standards criteria. Data on context, mechanisms, programme activities and outcomes were extracted. Factors were categorised into the five strategies of the WHO framework of integrated people-centred health services (IPCHS).Results27 papers were included. The following programme theory was developed: it is essential to establish multidisciplinary teams of competent healthcare providers (HCPs) providing person-centred care, closely working together and communicating effectively with other stakeholders. Older people and informal caregivers should be involved in the care process. Financial support, efficient use of information technology and organisational alignment are also essential. ICPs demonstrate positive effects on the functionality of older people, satisfaction of older people, informal caregivers and HCPs, and a delayed placement in a nursing home. Heterogeneous effects were found for hospital-related outcomes, quality of life, healthcare costs and use of healthcare services. The two most prevalent WHO-IPCHS strategies as part of ICPs are ‘creating an enabling environment’, followed by ‘strengthening governance and accountability’.ConclusionCurrently, most ICPs do not address all WHO-IPCHS strategies. In order to optimise ICPs for frail older people the interaction between context items, mechanisms, programme activities and the outcomes should be taken into account from different perspectives (system, organisation, service delivery, HCP and patient).

Objectives To evaluate the impact of comorbidity on diabetes care quality and diabetes-related hospitalizations and to examine whether associations between the likelihood of diabetes-related hospitalizations and compliance with diabetes testing are modified by type of comorbidity. Methods A population-based cohort study of 861 354 adults with diabetes was conducted in Ontario, Canada. The diabetes cohort was categorized into 4 groups defined by their comorbidity statuses: no comorbidity, diabetes-concordant only, diabetes-discordant only, and both concordant and discordant. Outcome variables were defined as having had at least 1 hospitalization for diabetes-related short- or long-term complications between 2009 and 2011. Diabetes-care quality measures included testing for glycated hemoglobin (A1C) and low-density lipoprotein-cholesterol levels and eye examinations between 2007 and 2009. Multivariable logistic regression models were performed to examine the associations between diabetes testing and diabetes-related hospitalizations and the modifying role of comorbidity type. Results Compliance with all 3 monitoring tests by patients with diabetes had a strong positive impact on reducing hospitalizations for diabetes-related long-term complications, especially in patients with diabetes-concordant conditions. The highest levels of adherence to all 3 diabetes monitoring tests were observed in patients with diabetes-concordant conditions only and in patients with diabetes-discordant conditions. The highest odds of hospitalizations for diabetes-related short-term complications were observed in patients having both discordant and concordant conditions. Conclusions Meeting diabetes testing goals has the potential to reduce hospitalizations for diabetes-related complications; however, this depends on types of coexisting chronic conditions and diabetes-related complications in patients with diabetes.

To examine the relative impact of 16 common chronic conditions and increasing morbidity on health-related quality of life (HRQL) in a population-based sample of home care clients in Ontario, Canada.Participants were adult clients assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between January and June 2009 and diagnosed with one (or more) of 16 common chronic conditions. HRQL was evaluated using the Minimum Data Set-Health Status Index (MDS-HSI), a preference-based measure derived from items captured in the RAI-HC. Multivariable linear regression models assessed the relative impact of each condition, and increasing number of diagnoses, on MDS-HSI scores.Mean (SD) MDS-HSI score in the study population (n = 106,159) was 0.524 (0.213). Multivariable analysis revealed a statistically significant (p 0.05) and clinically important (difference ≥ 0.03) decrease in MDS-HSI scores associated with stroke (-0.056), osteoarthritis (-0.036), rheumatoid arthritis (-0.033) and congestive heart failure (CHF, -0.030). Differences by age and sex were observed; most notably, the negative impact associated with dementia was greater among men (-0.043) than among women (-0.019). Further, HRQL decreased incrementally with additional diagnoses. In all models, chronic conditions and number of diagnoses accounted for a relatively small proportion of the variance observed in MDS-HSI.Clinically important negative effects on HRQL were observed for clients with a previous diagnosis of stroke, osteo- and rheumatoid arthritis, or CHF, as well as with increasing levels of multimorbidity. Findings provide baseline preference-based HRQL scores for home care clients with different diagnoses and may be useful for identifying, targeting and evaluating care strategies toward populations with significant HRQL impairments.

IntroductionA recent WHO multi-country study on maternal and newborn health concluded that there was no evidence of an association between high coverage with essential interventions and reduced mortality in health care facilities, or improvement in other outcomes.1 According to Horton the missing ingredient in this relation is quality of care.2 Quality improvement in healthcare has adopted techniques mainly from industries such as manufacturing and has been used widely in Europe and US. However, evidence of success of these techniques in healthcare is not very conclusive, especially in low and middle-income countries. There have been limited efforts to critically analyse the techniques used in quality improvement interventions. One of the main challenges in evaluating quality improvement is the complexity of the interventions themselves and the complex nature of the systems in which they are implemented. Robust evidence regarding quality improvement interventions for resource poor settings is generally lacking.The MaiKhanda trial looked at the effect of QI interventions and community women's groups on maternal and newborn mortality in 3 central districts in Malawi.3 The impact evaluation measuring effect on newborn mortality for the QI interventions, using a cluster RCT approach, remained inconclusive. We use a Theory-Based Evaluation (TBE) approach to understand why improvement interventions undertaken by MaiKhanda for new-born care did not show an effect. Absence of effect could be attributed to a failure of theory, a failure of implementation, an evaluation failure or a combination of these.Our primary objective was to understand the mechanisms by which the QI interventions worked (or not) and explore the interaction between the various factors that mediated the lack of effect on neonatal mortality that was observed in the cluster randomized control trial.MethodsOur research strategy consisted of developing a post-hoc Theory of Change, consolidating and synthesizing all the available evidence using an appropriate framework, and analysing the program and implementation theory using theory based approaches to evaluation.Data synthesis was conducted using the Consolidate Framework for Implementation Research (CFIR).4 The synthesis takes into consideration the various reports and documents accumulated through the life of the project and complements the process evaluation studies conducted during the same period. In doing so, it draws a picture of the intervention with a multi-dimensional perspective, which provides insights into the evolution of the project. The framework is very comprehensive covering 5 major domains and a range of constructs, not all of which were included in our study. As this was post-hoc analysis, the choice of constructs was based on the availability of data rather than prioritizing the key constructs to consider.CFIR helps to produce structured and comprehensive data that is then used for analysing the program theory in relation to the intervention outcome. The program theory thus generated for the MaiKhanda intervention is compared with the program theories of the Michigan Keystone Project, which used similar collaborative methods to successfully reduce their central venous line blood stream infections in 106 participating ICUs.5 The rationale for such a comparison is that while the interventions per se are very unique and specific to their context, the program theories underlying the use of collaborative methods in both the interventions is the same and therefore comparable. Theories offer a higher level of abstraction that can be comparable across different settings.6 ResultsThe key finding from analysis of the program theory is that similar intervention strategies that triggered successful mechanisms for improvement in the Keystone Project failed to generate such mechanisms in MaiKhanda project.The Model for Improvement used in MaiKhanda was built around Deming's improvement theory7 and Roger's diffusion of innovation theory.8 The former theory considers improvement as a product of subject matter knowledge and profound knowledge. Subject matter knowledge on essential and emergency newborn care was generally lacking among health care providers in Malawi. Similarly, understanding variations within the health systems is an acquired skill. While the implementing partners, provided ample opportunities for the Malawian health system to learn the Institute for Healthcare Improvement (IHI) model for improvement, in general, QI teams lacked capacity to collate data and analyse the variations between the health facilities. QI was a fairly new concept in Malawi and MaiKhanda's attempts to embed it within existing health system was limited by challenges of the health systems context, MaiKhanda's own organizational transition and QI and clinical capacity of health care providers.The main challenge for MaiKhanda was to simultaneously implement and sustain the various change packages it had introduced in the different facilities. While there were isolated instances of successful intervention activities within MaiKhanda, it did not build enough momentum to generate mechanisms across a critical mass of the facilities that would eventually result in improved newborn outcomes. This can be attributed to the implementation strength, context and complexity of MaiKhanda's interventions. This is explored further using the implementation theory.Implementation was based on diffusion theories where better performing facilities were to act as role models for other facilities to emulate. The cRCT design for measuring impact evaluation required a random allocation of the improvement facilities and this conflicted with innovation diffusion theories, which prescribed a gradual organic spread of the interventions by strategically engaging the innovators and early adapters.Limitations of the evaluation design notwithstanding, the implementation strength characterized by the dose, duration, intensity and specificity of the intervention was sub-optimal.Implementation strength is not the only factor triggering an intervention mechanism and cannot be measured independent of the intervention complexity or the intervention context. For example, MaiKhanda struggled to show an effect of its interventions, despite having a long pre-intervention period to refine its interventions, while the Michigan study produced results within 18 month period. This could be because of other factors related to intervention complexity such as the long implementation chain for intervention delivery, the subjective perception of the agency (QI teams) regarding QI and contextual factors such as organizational readiness, the health systems context, QI team capacity to deliver QI interventions and MaiKhanda's own internal capacity.Human agency is at the heart of implementation and the intervention required a continuous and prolonged time and effort, than was anticipated, to engage and train the health facility QI teams on the improvement model.One of the key factors affecting the uptake of strategies was MaiKhanda's positioning within the health system and the degree of influence it could exert on other actors. This factor has a significant role to play in country where projects are donor supported and perhaps also donor driven. The period of the intervention also saw MaiKhanda going through a period of rapid organizational transition, which affected intervention implementation on the ground. Furthermore, MaiKhanda's own understanding of QI concepts was evolving gradually and this coupled with its long implementation chain, influenced the subjective understanding of the QI teams regarding QI concepts. Health facility staff also lacked the necessary skills and knowledge related to management of newborn health.Limited resources within the health facilities meant that gains achieved in some aspects of the intervention could not be sustained in the long run. External contextual factors such as fuel shortages contributed to poor implementation. Changes in policy such as government ban on TBAs, affected intervention uptake and resulted in an increase in health facility deliveries, overwhelming the already under-resourced staff capacity in the health facilities. It is conceivable that quality improvement was not on top of their priority list. But, ‘motivation’ to be involved in QI Collaboratives remained high. In resource constrained settings, ‘motivation’ can be influenced by the lure of personal incentives (such as per diems for attending workshops and meetings) as much as individual's commitment to broader social gains (ie reduction in newborn case fatality rates in their facility). The improvement model was competing against other existing models and it was difficult to get enough stakeholder commitment to the prescribed model as there were huge expectations fuelled by the poverty and poor governance structures and a culture of “perdiemitis” was prevalent in Malawian health care system.9 DiscussionAs is evident from the study, a single research method will not be able to provide justice to evaluation of a complex set of factors that influence newborn outcomes. We propose a research strategy that includes developing a Theory of Change, followed by evaluation of the program theory, measuring implementation strength, analysing implementation theory and comparing this in relation to the outcomes of the intervention observed through the impact evaluation. The results arising from such a comprehensive evaluation will contribute to the growth of improvement science with the accumulation of knowledge and explanation rather than being just a bedrock of observational facts.More generally, we propose that design, implementation and evaluation of QI activities, particularly in resource-poor settings, should consider five key principles i.e it should include whole systems thinking, accountability, participatory approach, should be evidence-based and adapt innovative methods.10

Background: A plethora of performance measurement indicators for palliative and end-of-life care currently exist in the literature. This often leads to confusion, inconsistency and redundancy in efforts by health systems to understand what should be measured and how. The objective of this study was to conduct a scoping review to provide an inventory of performance measurement indicators that can be measured using population-level health administrative data, and to summarize key concepts for measurement proposed in the literature. Methods: A scoping review using MEDLINE and EMBASE, as well as grey literature was conducted. Articles were included if they described performance or quality indicators of palliative and end-of-life care at the population-level using routinely-collected administrative data. Details on the indicator such as name, description, numerator, and denominator were charted. Results: A total of 339 indicators were extracted. These indicators were classified into nine health care sectors and one cross-sector category. Extracted indicators emphasized key measurement themes such as health utilization and cost and excessive, unnecessary, and aggressive care particularly close to the end-of-life. Many indicators were often measured using the same constructs, but with different specifications, such as varying time periods used to ascribe for end-of-life care, and varying patient populations. Conclusions: Future work is needed to achieve consensus ‘best’ definitions of these indicators as well as a universal performance measurement framework, similar to other ongoing efforts in population health. Efforts to monitor palliative and end-of-life care can use this inventory of indicators to select appropriate indicators to measure health system performance.

Purpose We investigated natural direct and indirect pathways between low-income status and high-cost user (HCU) transitions considering health risk behaviors as potential mediators. Methods We analyzed data from respondents (aged 18+) from four pooled cycles of the Canadian Community Health Survey (2005–2010/2011) linked to administrative data in Ontario, Canada. HCUs were defined as the top 5% of the population, ranked by cost consumption in any of the five years after survey interview. Low-income status was defined from the provincial distribution of self-reported household income, with missing values imputed from neighborhood-level data. In mediation analyses based on marginal structural models, we quantified the contributions of smoking, physical inactivity, alcohol consumption, and body mass index to income-HCU associations. Results 115,091 respondents (representative of 9,661,764 Ontarians) were included in the study, of which 7.2% became HCUs. The odds of becoming HCUs were 1.36 times (95% CI: 1.25–1.48) greater for low (vs. high) income status respondents. Smoking, physical activity, alcohol consumption, and body mass index contributed 9.4%, 6.5%, 10.6%, and 4.4% to this association, respectively. Tests for exposure-mediator interactions were not statistically significant. Conclusions Health risk behaviors only partially explain income inequalities in future HCU transitions.

The objectives of this paper are to: (1) identify contextual factors such as policy that impacted the implementation of community-based primary health care (CBPHC) innovations among 12 Canadian research teams and (2) describe strategies used by the teams to address contextual factors influencing implementation of CBPHC innovations. In primary care settings, consideration of contextual factors when implementing change has been recognized as critically important to success. However, contextual factors are rarely recorded, analyzed or considered when implementing change. The lack of consideration of contextual factors has negative implications not only for successfully implementing primary health care (PHC) innovations, but also for their sustainability and scalability. For this evaluation, data collection was conducted using self-administered questionnaires and follow-up telephone interviews with team representatives. We used a combination of directed and conventional content analysis approaches to analyze the questionnaire and interview data. Representatives from all 12 teams completed the questionnaire and 11 teams participated in the interviews; 40 individuals participated in this evaluation. Four themes representing contextual factors that impacted the implementation of CBPHC innovations were identified: (I) diversity of jurisdictions (II) complexity of interactions and collaborations (III) policy, and (IV) the multifaceted nature of PHC. The teams used six strategies to address these contextual factors including: (1) conduct an environmental scan at the beginning (2) maintaining engagement among partners and stakeholders by encouraging open and inclusive communication; (3) contextualizing the innovation for different settings; (4) anticipating and addressing changes, delays, and the need for additional resources; (5) fostering a culture of research and innovation among partners and stakeholders; and (6) ensuring information about the innovation is widely available. Implementing CBPHC innovations across jurisdictions is complex and involves navigating through multiple contextual factors. Awareness of the dynamic nature of context should be considered when implementing innovations.

Contains fulltext : 208468.pdf (Publisher’s version ) (Open Access) BACKGROUND: Across countries, a small group of patients accounts for the majority of health care spending. These patients are more likely than other patients to experience problems with quality and safety in their care, suggesting that efforts targeting efficiency and quality among this population might have significant payoffs for health systems. Better understanding of similarities and differences in patient characteristics and health care use in different countries may ultimately inform further efforts to improve care for HNHC patients in these health systems. METHODS: We conducted a cross-sectional descriptive study using one year of patient-level data on high-cost patients in seven high-income OECD member countries. Countries were selected based on availability of detailed information (large enough samples of claims, administrative, and survey data of high-cost patients). We studied concentration of spending among high-cost patients, characteristics of high-cost patients, and per capita spending on high-cost patients. FINDINGS: Cost-concentration of the top 5% of patients varied across countries, from 41% in Japan to 60% in Canada, driven primarily by variation in the top 1% of spenders. In general, high-cost patients were more likely to be female (57.7% on average), had a significant number of multi-morbidities (up to on average 10 major diagnostic categories (ICD chapters), and had a lower socioeconomic status. Characteristics of high-cost patients varied as well: median age ranged from 62 in the Netherlands to 75 in Germany and the difference in socioeconomic status is particularly stark in the US. Lastly, utilization, particularly for inpatient care, varied with an average number of inpatient days ranging from 6.6 nights (US) to 97.7 nights in Japan. INTERPRETATION: In this descriptive study, there is substantial variation in the cost concentration, characteristics, and per capita spending on high-cost patient populations across high-income countries. Differences in the way that health systems are structured likely explains some of this variation, which suggests the potential of cross-system learning opportunities. Our findings highlight the need for further studies including comparable performance metrics and institutional analysis.

Key Points Question What are the population-level trends in health care utilization and expenditures in the 2 years before death among adults in Ontario, Canada? Findings This cohort study found that health care expenditures in the last 2 years of life increased in Ontario from CAD$5.12 billion in 2005 to CAD$7.84 billion in 2015, and the intensity of health care utilization and deaths in hospital varied by resource utilization gradients. Meaning In this study, the observed trends demonstrated that costs and hospital-centered care before death are high in Ontario., This cohort study examines population-level trends in health care utilization and expenditures in the 2 years before death among adults in Canada’s single-payer health system., Importance Measuring health care utilization and costs before death has the potential to initiate health care improvement. Objective To examine population-level trends in health care utilization and expenditures in the 2 years before death in Canada’s single-payer health system. Design, Setting, and Participants This population-based cohort included 966 436 deaths among adult residents of Ontario, Canada, from January 2005 to December 2015, linked to health administrative and census data. Data for deaths from 2005 to 2013 were analyzed from November 1, 2016, through January 31, 2017. Analyses were updated from May 1, 2019, to June 15, 2019, to include deaths from 2014 and 2015. Exposures Sociodemographic exposures included age, sex, and neighborhood income quintiles, which were obtained by linking decedents’ postal codes to census data. Aggregated Diagnosis Groups were used as a general health service morbidity-resource measure. Main Outcomes and Measures Health care services accessed for the last 2 years of life, including acute hospitalization episodes of care, intensive care unit visits, and emergency department visits. Total health care costs were calculated using a person-centered costing approach. The association of area-level income with high resource use 1 year before death was analyzed with Poisson regression analysis, controlling for age, sex, and Aggregated Diagnosis Groups. Results Among 966 436 decedents (483 038 [50.0%] men; mean [SD] age, 76.4 [14.96] years; 231 634 [24.0%] living in the lowest neighborhood income quintile), health care expenditures increased in the last 2 years of life during the study period (CAD$5.12 billion [US $3.83 billion] in 2005 vs CAD$7.84 billion [US $5.86 billion] in 2015). In the year before death, 758 770 decedents (78.5%) had at least 1 hospitalization episode of care, 266 987 (27.6%) had at least 1 intensive care unit admission, and 856 026 (88.6%) had at least 1 emergency department visit. Overall, deaths in hospital decreased from 37 984 (45.6%) in 2005 to 39 474 (41.5%) in 2015. Utilization in the last 2 years, 1 year, 180 days, and 30 days of life varied by resource utilization gradients. For example, the proportion of individuals visiting the emergency department was slightly higher among the top 5% of health care users compared with other utilization groups in the last 2 years of life (top 5%, 45 535 [94.2%]; top 6%-50%, 401 022 [92.2%]; bottom 50%, 409 469 [84.7%]) and 1 year of life (top 5%, 43 007 [89.0%]; top 6%-50%, 381 732 [87.8%]; bottom 50%, 380 859 [78.8%]); however, in the last 30 days of life, more than half of individuals in the top 6% to top 50% (223 262 [51.3%]) and bottom 50% (288 480 [59.7%]) visited an emergency department, compared with approximately one-third of individuals in the top 5% (16 916 [35.0%]). No meaningful associations were observed in high resource use between individuals in the highest income quintile compared with the lowest income quintile (rate ratio, 1.02; 95% CI, 0.99-1.05) after adjusting for relevant covariates. Conclusions and Relevance In this study, health care use and spending in the last 2 years of life in Ontario were high. These findings highlight a trend in hospital-centered care before death in a single-payer health system.

AimTo describe the process by which the 12 community-based primary health care (CBPHC) research teams worked together and fostered cross-jurisdictional collaboration, including collection of common indicators with the goal of using the same measures and data sources.BackgroundA pan-Canadian mechanism for common measurement of the impact of primary care innovations across Canada is lacking. The Canadian Institutes for Health Research and its partners funded 12 teams to conduct research and collaborate on development of a set of commonly collected indicators.MethodsA working group representing the 12 teams was established. They undertook an iterative process to consider existing primary care indicators identified from the literature and by stakeholders. Indicators were agreed upon with the intention of addressing three objectives across the 12 teams: (1) describing the impact of improving access to CBPHC; (2) examining the impact of alternative models of chronic disease prevention and management in CBPHC; and (3) describing the structures and context that influence the implementation, delivery, cost, and potential for scale-up of CBPHC innovations.FindingsNineteen common indicators within the core dimensions of primary care were identified: access, comprehensiveness, coordination, effectiveness, and equity. We also agreed to collect data on health care costs and utilization within each team. Data sources include surveys, health administrative data, interviews, focus groups, and case studies. Collaboration across these teams sets the foundation for a unique opportunity for new knowledge generation, over and above any knowledge developed by any one team. Keys to success are each team’s willingness to engage and commitment to working across teams, funding to support this collaboration, and distributed leadership across the working group. Reaching consensus on collection of common indicators is challenging but achievable.

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 R2), 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. Electronic supplementary material The online version of this article (10.1186/s41512-018-0042-5) contains supplementary material, which is available to authorized users.