Applying the British Columbia Health System Matrix (BCHSM) population segmentation framework to support integrated care in Ontario, Canada.

Objective To adapt the BCHSM population segmentation methodology to Ontario’s health administrative data to  identify mutually exclusive segments with similar health care needs to support integrated care efforts and population health management in Ontario, Canada. To compare health system related costs across derived segments to identify opportunities for better integrated care. Approach We identified Ontarians alive with valid health card numbers as of April 1, 2020 (n =14,358,565) and created a matrix of prior utilization, cost and diagnoses using linked health administrative databases. Using a hierarchical technique, we assigned individuals into one of 14 BCHSM segments based on the greatest health care needs.  Segments of need range from non-users (low need) to end-of-life patients (greatest need). We report the distribution of individual characteristics, average monthly costs across segments and further stratified health care costs by quintile of material deprivation within segments. Results The largest segment was the healthy (low) users (43%) followed by low chronic conditions (28%) and non-users (10%). Five segments comprised <1% of the total population: end-of-life, frail in care, cancer, frail in the community and child and youth major. Average costs per month alive increased from $28 for the non-user segment to$5,100 for the end-of-life segment (0.5% of the population). Costs in the Frail with high chronic conditions segment ($2,740/mo) were 3-times higher than costs in the high chronic conditions segment ($930/mo),  6-times higher than costs in the medium chronic conditions segment ($450/mo), and 14-times higher than costs in the low chronic conditions segment ($193/mo). Results were generally more favourable in areas of low (vs high) material deprivation overall and within population segments. Conclusion Using Ontario’s linkable health administrative data we have created an Ontario adaptation of the BCHSM needs-based population segmentation approach. Segmentation supports population health management as well as helping  identify opportunities for improvement to strengthen integrated care and potential cost savings

Looking beyond administrative health care data : the role of socioeconomic status in predicting future high-cost patients with mental health and addiction

Introduction: Previous research has shown that the socioeconomic status (SES)-health gradient also extends to high-cost patients; however, little work has examined high-cost patients with mental illness and/or addiction. The objective of this study was to examine associations between individual-, household-, and area-level SES factors and future high-cost use among these patients. Methods: We linked survey data from adult participants (ages 18 and older) of three cycles of the Canadian Community Health Survey (CCHS) to administrative health care data from Ontario, Canada. Respondents with mental illness and/or addiction were identified based on prior mental health and addiction health care use and followed for 5 years for which we ascertained health care costs covered under the public health care system. We quantified associations between SES factors and becoming a high-cost patient (i.e, transitioning into the top 5%) using logistic regression models. For ordinal SES factors, such as income, education and marginalization variables, we measured absolute and relative inequalities using the slope and relative index of inequality. Results: Among our sample, lower personal income (OR=2.11, 95% C.I. [1.54, 2.88] for $0 to$14,999), lower household income (OR=2.11, 95% C.I. [1.49, 2.99] for lowest income quintile), food insecurity (OR=1.87, 95% C.I. [1.38, 2.55]) and non-homeownership (OR=1.34, 95% C.I. [1.08, 1.66]), at the individual and household levels, respectively, and higher residential instability (OR=1.72, 95% C.I. [1.23, 2.42] for most marginalized), at the area level, were associated with higher odds of becoming a high-cost patient within a 5-year period. Moreover, the inequality analysis suggests pro-high-SES gradients in high-cost transitions

Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada.

Objectives There is mixed evidence on the influence of number of conditions on inequalities in mortality, we explored the association between number of conditions and deprivation on mortality whilst assessing the difference between working age and older adults. We replicated the analysis in England and Ontario, to provide a cross-jurisdiction comparison. Approach We used individual level-linked data from primary care activity, secondary care and mortality data in England and Ontario. For both jurisdictions, we took a random sample of 600,000 adults from 1 January 2015 and followed them up till 31 December 2019. We used cox proportional hazard to test the influence of deprivation (measured using area-level deprivation in deciles) and number of conditions (measured at baseline and capped at six conditions) on survival. Age and sex were also measured at baseline. Analyses were stratified by working age (18-64 years) and older adults (65+ years) and were repeated for England and Ontario. Results Deprivation gradient in mortality rate was steeper in working age than older adults in both jurisdictions. Number of conditions was associated with increased mortality rate, this was stronger for working age than older adults, in England (working age HR = 1.60, 95% CI 1.56,1.64 and older adults HR= 1.26, 95% CI 1.25,1.27) and Canada (working age HR=1.69, 95% CI 1.66,1.72 and older adults HR= 1.39, 95% CI 1.38,1.40). After accounting for number of conditions, the mortality rate associated with deprivation decreased but remained significant. The interaction between number of conditions and deprivation showed that adults with more conditions have a higher mortality rate and those living in deprived areas also have a higher mortality rate but having more conditions attenuates the deprivation gradient in mortality. Conclusion Number of conditions contribute to higher mortality rate and inequalities in morality, this is stronger for working age than older adults in England and Ontario. The fragmented health-care system may be contributing to poorer outcomes, further research should help identify which part of the pathway is driving these inequalities further

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications

To compare the timeliness of nongovernmental and governmental communications of infectious disease outbreaks and evaluate trends for each over time, we investigated the time elapsed from the beginning of an outbreak to public reporting of the event. We found that governmental sources improved the timeliness of public reporting of infectious disease outbreaks during the study period

Primary care and health inequality : Difference-in-difference study comparing England and Ontario

BACKGROUND: It is not known whether equity-oriented primary care investment that seeks to scale up the delivery of effective care in disadvantaged communities can reduce health inequality within high-income settings that have pre-existing universal primary care systems. We provide some non-randomised controlled evidence by comparing health inequality trends between two similar jurisdictions-one of which implemented equity-oriented primary care investment in the mid-to-late 2000s as part of a cross-government strategy for reducing health inequality (England), and one which invested in primary care without any explicit equity objective (Ontario, Canada). METHODS: We analysed whole-population data on 32,482 neighbourhoods (with mean population size of approximately 1,500 people) in England, and 18,961 neighbourhoods (with mean population size of approximately 700 people) in Ontario. We examined trends in mortality amenable to healthcare by decile groups of neighbourhood deprivation within each jurisdiction. We used linear models to estimate absolute and relative gaps in amenable mortality between most and least deprived groups, considering the gradient between these extremes, and evaluated difference-in-difference comparisons between the two jurisdictions. RESULTS: Inequality trends were comparable in both jurisdictions from 2004-6 but diverged from 2007-11. Compared with Ontario, the absolute gap in amenable mortality in England fell between 2004-6 and 2007-11 by 19.8 per 100,000 population (95% CI: 4.8 to 34.9); and the relative gap in amenable mortality fell by 10 percentage points (95% CI: 1 to 19). The biggest divergence occurred in the most deprived decile group of neighbourhoods. DISCUSSION: In comparison to Ontario, England succeeded in reducing absolute socioeconomic gaps in mortality amenable to healthcare from 2007 to 2011, and preventing them from growing in relative terms. Equity-oriented primary care reform in England in the mid-to-late 2000s may have helped to reduce socioeconomic inequality in health, though other explanations for this divergence are possible and further research is needed on the specific causal mechanisms

Does source matter? Using ProMED-mail to compare the timeliness of outbreak communications from governmental and nongovernmental sources

Background: Nongovernmental (or informal) information sources have been credited with raising earlier warnings of disease threats than traditional governmental reporting systems, thus facilitating the rapid recognition and response to potential pandemics and emerging disease outbreaks. Despite an increased global reliance on informal reporting systems, little empirical evidence exists to support this assertion. In this project we examined (1) whether the original source of outbreak information (governmental or nongovernmental) was an explanatory factor in the timely reporting of outbreaks, and (2) trends in outbreak communication by governmental and nongovernmental sources. Methods: Using a database of 398 unique human infectious disease outbreaks reported in the World Health Organization's "Disease Outbreak News" from 1996-2009, we identified the source(s) and date of the earliest outbreak communication from ProMED-mail's archives. Negative binomial regression models were used to estimate the effect of reporting source (i.e., governmental or nongovernmental) on the timeliness of outbreak communication. Results: Over the period 1996–2009, we found no statistically significant difference in communication timeliness for outbreaks reported first by nongovernmental sources compared to outbreaks communicated first by governmental sources (IRR=0.95, 95% CI [0.77, 1.18]). We observed a trend towards communicating outbreaks more quickly over time for both governmental and nongovernmental sources, but this trend was statistically significant only for governmental sources (IRR=0.94, 95% CI [0.91, 0.97]). Conclusion: To our knowledge, this study is the first to quantify the timeliness of outbreak communications from governmental and nongovernmental sources over time and across a range of diseases. While we observed no statistically significant differences in reporting speed between these sources, our study was limited to a small sample of WHO-confirmed outbreaks. Further research is therefore needed to build upon our results.Historique : Comparé aux systèmes de déclaration gouvernementaux traditionnels, les sources d'information non gouvernementales (ou informelles) sont réputées produire des avertissements plus précoces en terme d'éclosion de maladies, facilitant ce faisant la reconnaissance rapide et une réponse prompte aux flambées épidémiques naissantes et aux potentielles pandémies. Malgré un recours accru aux systèmes de déclaration informels, il existe peu de preuves empiriques pour supporter cette affirmation. Dans ce projet, nous avons examiné (1) si la source originale de l'information sur une flambée épidémique (gouvernemental ou non gouvernementale) était un facteur explicatif dans la déclaration précoce de flambées épidémiques et (2) l'évolution des communications sur les flambées épidémiques par les sources gouvernementales et non gouvernementales.Méthodes : En utilisant une base de données comptant 398 flambées épidémiques infectieuses distinctes sélectionnées à partir du « Disease Outbreak News » de l'Organisation Mondiale de la Santé de 1996 à 2009, nous avons identifié la ou les sources et la date de la première communication au sujet de cette flambée épidémique, au moyen des archives de ProMED-mail. Des modèles de régression négative binomiale ont été utilisés pour évaluer les différences et améliorations en terme de déclaration rapide de flambées épidémiques (comparé à la date présumée de leur début), par type de sources.Résultats : Nous n'avons trouvé aucune différence statistiquement significative dans la rapidité des communications au sujet des flambées épidémiques entre celles rapportées en premier par des sources non gouvernementales comparées à celle déclarées en premier par des sources gouvernementales pour la période 1996-2009 (IRR=0.95, 95% CI [0.77, 1.18]). De plus, bien que les deux types de sources rapportent les flambées épidémiques plus rapidement, une amélioration statistiquement significative n'a été notée que pour les sources gouvernementales (IRR=0.94, 95% CI [0.91, 0.97]). Conclusion : À notre connaissance, il s'agit de la première étude à quantifier la rapidité des communications au sujet de flambées épidémiques provenant des sources gouvernementales et non gouvernementales, touchant une période étendue et une variété de maladies. Bien qu'aucune différence statistiquement significative n'a été démontrée entre ces deux types de sources, nos résultats sont limités à un petit échantillon de flambées épidémiques confirmées par l'OMS. D'autres études sont nécessaires pour confirmer ces résultats

A Probabilistic Case-finding Algorithm for Chronic Disease Surveillance

We developed and validated a multivariable probabilistic case-detection model to detect known cases of diabetes mellitus (DM) using clinical and demographic data. We applied our method to a cohort of older adult residents of the region of Sherbrooke, Quebec. Predictors were added to a logistic regression model and internally validated using a 2:1 split sample approach. Models were compared using measures goodness of fit, discrimination and accuracy. The best model incorporated all predictors into the model: male sex, age, at least one hospitalization, physician visit and drug dispensed for diabetes

A Probabilistic Case-finding Algorithm for Chronic Disease Surveillance

We developed and validated a multivariable probabilistic case-detection model to detect known cases of diabetes mellitus (DM) using clinical and demographic data. We applied our method to a cohort of older adult residents of the region of Sherbrooke, Quebec. Predictors were added to a logistic regression model and internally validated using a 2:1 split sample approach. Models were compared using measures goodness of fit, discrimination and accuracy. The best model incorporated all predictors into the model: male sex, age, at least one hospitalization, physician visit and drug dispensed for diabetes

Income inequalities in multimorbidity prevalence in Ontario, Canada: a decomposition analysis of linked survey and health administrative data

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

Association between continuity of care and subsequent diagnosis of multimorbidity in Ontario, Canada from 2001-2015: A retrospective cohort study.

BackgroundContinuity of care is a well-recognized principle of the primary care discipline owing to its medical, interpersonal, and cost-saving benefits. Relationship continuity or the ongoing therapeutic relationship between a patient and their physician is a particularly desirable goal, but its role in preventing the accumulation of chronic conditions diagnoses in individuals is unknown. The objective of this study was to investigate the effect of continuity of care with physicians on the rate of incident multimorbidity diagnoses in patients with existing conditions.MethodsThis was a population-based, retrospective cohort study from 2001 to 2015 that focused on patients aged 18 to 105 years with at least one chronic condition (n = 166,665). Our primary exposure was relationship continuity of care with general practitioners and specialists measured using the Bice-Boxerman Continuity of Care Index (COCI). COCI was specified as a time-dependent exposure prior to the observation period. Our outcomes of interest were the time to diagnosis of a second, third, and fourth chronic condition estimated using cause-specific hazard regressions accounting for death as a competing risk.FindingsWe observed that patients with a single chronic condition and high continuity of care (>0.50) were diagnosed with a second chronic condition or multimorbidity at an 8% lower rate compared to individuals with low continuity (cause-specific hazard ratio (HR) 0.92 (95% Confidence Interval 0.90-0.93; pConclusionsContinuity of care is a potentially modifiable health system factor that reduces the rate at which diagnoses of chronic conditions are made over time in patients with multimorbidity. Additional research is needed to explain the underlying mechanisms through which continuity is related to a protective effect and the clinical sequalae