Does it Matter What You Measure? Neighbourhood Effects in a Canadian Setting
In: Healthcare Policy, Band 6, Heft 1, S. 47
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In: Healthcare Policy, Band 6, Heft 1, S. 47
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In: Journal of applied research in intellectual disabilities: JARID, Band 34, Heft 6, S. 1582-1591
ISSN: 1468-3148
AbstractBackgroundComplete physical examinations (CPE) can identify health disparities in persons with intellectual or developmental disabilities. The objective of this study was to determine and compare rates of CPE among Manitoba adults with and without intellectual or developmental disabilities over time and to identify factors that were associated with receiving a CPE.MethodA retrospective cohort study using linked administrative health and non‐health data from 1995 to 2015 was conducted. Poisson and logistic regression were used to calculate CPE rates and examine factors associated with CPE.ResultsThe rates of CPE are decreasing over time and are higher among Manitobans with an intellectual or developmental disability. Characteristics such as being male, living rurally, low socioeconomic status, and high continuity of care led to lower odds of receiving a CPE.ConclusionsThe current state of CPE provision to adults with intellectual or developmental disabilities in Manitoba is encouraging but needs improvement.
In: International journal of population data science: (IJPDS), Band 4, Heft 3
ISSN: 2399-4908
BackgroundUnder the National Housing Strategy, the Canadian government will make historic investments in housing over the next decade. The Canadian Mortgage and Housing Corporation is leading a research strategy to evaluate the impact of these investments. As part of this initiative, the Manitoba Center for Health Policy is conducting a pilot study to determine whether administrative data can be used to assess impacts, specifically looking at health, education and involvement in the justice system.
ApproachUsing administrative data we tested for changes in healthcare use and justice involvement in the two years before and after a cohort of individuals moved into public housing. Additionally, to determine if changes in the outcomes over time were unique to public housing, we included a matched comparison group of individuals who did not reside in public housing. GLM with generalized estimating equations tested for differences over time and between cohorts in the number of hospitalizations, inpatient days, emergency department visits, and contacts with the criminal justice system. The data were modeled using a Poisson distribution (rate ratio, RR).
Results Compared to the matched cohort, individuals accepted into public housing showed a significant decline in number of hospitalizations (pre RR=1.58 (1.53, 1.63), post RR=1.23 (1.19, 1.27), days in hospital (pre RR=1.66 (1.64, 1.68), post RR=1.24 (1.23, 1.26) and visits to the emergency department (pre RR=1.57 (1.52, 1.62), post RR=1.42 (1.38, 1.47). A trend towards fewer involvements with the criminal justice system was also observed (pre RR=1.37 (1.32, 1.43), post RR=1.28 (1.22, 1.34). No significant differences were noted for total respiratory morbidity or high school grades.
ConclusionAdministrative data show good potential to be used for the evaluation of public housing impacts on a wide range of health and social outcomes. Additional indicator comparisons will be reported at the conference.
In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACTObjectivesTo determine the relationship between known social complexity and model of primary care service deliveryApproachThe impacts of the social determinants of health are well described. To understand the contribution of specific factors on primary care service use we linked social data in the Population Health Research Data Repository at the Manitoba Centre for Health Policy to health system data. We included all patients visiting a Winnipeg clinic at least three times between 2010 and 2013. We allocated each participant to the primary care provider providing the majority of their care; and each provider was assigned to the model of care where they provided the majority of their clinical care. We developed eleven new indicators to describe social complexity such as: children in care, low income quintile, income assistance (welfare), high residential mobility, and involvement with the justice system. Results The cohort included 626,264 unique individuals of whom 53.1% were female. The majority of participants received their care from the fee for service (FFS) model (511,763) followed by 76,261 assigned to "reformed FFS". 16,536 and 12,178 were assigned to the 2 team-based care alternative funded models and 9,526 to the teaching clinic model. Patients with social complexities, except for newcomers, were more likely to attend the alternative funded clinics. The patients these clinics served were generally very complex with over 15% having more than 5 complexities compared to less than 5% of those attending the FFS models. Twice as many patients in the FFS models (60%) had no complexities compared to the alternative funded models.ConclusionThe availability of social data in population health repositories provides new opportunities to understand the distribution of these social factors amongst care providers and the impact of each on the health of populations. This new understanding can support focused interventions to address specific social risk factors and provide the evidence to support different models of primary care service delivery.
In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACTObjectives To determine the relationships between five models of primary care service delivery and quality of care indicators in an urban population. Two fee-for-service (FFS) and three alternative-funded models of primary care service delivery were studiedApproach We allocated all Manitoba residents who had at least three visits to any primary care provider (PCP) at any Winnipeg clinic between 2010-2013 to the most responsible PCP (N = 626,264). We then allocated each PCP to a model of primary care service delivery. We created general linear mixed models to describe the relationship between each model of primary care and the dominant, traditional fee-for-service model for health services use, while controlling for a variety of PCP and patient factors, including patient social complexity.Results Patient social complexity was associated with poorer crude rates for many of the indicators. There were no differences among the models for hospital readmission within 30 days or specialist referral by the assigned PCP. Hospitalizations for ACSC were higher for one alternative funded model (1.98 OR, 1.38-2.83 95% CI), while non-indicated low back X-rays were lower for a different alternative funded model (0.14 OR, 0.03-0.59 95% CI). Ambulatory care visits to any PCP were lower for all three alternative funded models than the two FFS models. The family medicine academic teaching sites had lower rates of continuity of care (p< 0.5)Conclusion Overall, no model of primary care consistently outperformed the others. FFS models had higher rates of visits, but appeared to satisfy patient needs better because they had less use of telehealth services following visits. Teaching sites appeared to sacrifice continuity of care potentially to support other academic activities. Controlling for social complexity was associated with a reduction in the differences between models in indicator outcomes.
OBJECTIFS: À l'aide des données du Recensement du Canada, des chercheurs du Centre de la politique des soins de santé du Manitoba ont voulu créer un indicateur socioéconomique régional (ISR). Nous avons évalué le degré d'association entre cet ISR et la santé. MÉTHODE: Les valeurs de plusieurs variables du Recensement (revenu, instruction, emploi et structure familiale) ont été saisies à l'échelle des secteurs de dénombrement ou des aires de diffusion, puis soumises à une analyse factorielle en composantes principales afin de créer trois ISR: une version actualisée de l'indice des facteurs socioéconomiques (SEFI-2) et des versions modifiées des indices de défavorisation matérielle et sociale de Pampalon. Les scores factoriels de ces analyses ont ensuite été comparés à plusieurs indicateurs de santé des populations: le taux de mortalité prématurée (TMP), les années potentielles de vie perdues (APVP), l'espérance de vie et la santé autoévaluée. RÉSULTATS: Les scores du SEFI-2 étaient fortement liés non seulement aux autres ISR, mais à chaque indicateur d'état sanitaire. Les plus fortes corrélations entre un ISR et un indicateur de santé ont été observées entre le SEFI-2 et les APVP (r=0,85), et entre le SEFI-2 et le TMP (r=0,80). Les plus faibles corrélations ont été observées entre l'ISR de défavorisation sociale et la santé autoévaluée. CONCLUSION: Les ISR basés sur des indicateurs du Recensement du Canada sont une précieuse ressource pour les chercheurs en santé des populations. Il est important de noter que, tout dépendant de la question de recherche et de la raison de l'inclusion d'un ISR, les indicateurs composites peuvent donner de meilleurs résultats que l'indicateur de revenu à lui seul. La possibilité d'apporter des ajustements en fonction du statut socioéconomique, lorsqu'on évalue l'état sanitaire de populations ou des interventions en santé des populations, contribue à la validité des conclusions de ce type de recherche, et les ISR peuvent se substituer à l'état sanitaire de la population d'une région ...
BASE
In: International journal of population data science: (IJPDS), Band 5, Heft 5
ISSN: 2399-4908
IntroductionHigh dimensional propensity scores (HDPS) aim to account for unmeasured confounding. However, it is unclear to what extent HDPS are able to attain this.
Objectives and ApproachThis study aimed to test how well HDPS can account for confounding due to social determinants of health when using only health data. A retrospective cohort study was used to examine the effect of exposure to prescription opioids in utero on childhood outcomes (ADHD, school readiness, NICU admission, and hospitalization within the first year of life). Administrative health and social data were linked at the individual level and HDPS for each outcome were calculated using the mothers' health data. Exposed and unexposed mother-child dyads were then matched. Standardized differences of mothers' social factors (history of teen birth, lowest income quintile, ever received income assistance (i.e., welfare), ever lived in social housing, history with child protection services, residential mobility, and contact with the justice system) were compared before and after matching to determine to what degree the HDPS could account for differences in social determinants of health. Additional HDPS analyses were performed with social factors included in the HDPS with the health data.
ResultsBefore matching, standardized differences between exposed and unexposed groups for the social factors ranged between 0.40-0.75. Income assistance and lowest income quintile consistently had the greatest and smallest standardized difference for all outcomes, respectively. After matching, using health data only, standardized differences decreased considerably, ranging from 0.05-0.27. When including social factors into the HDPS, the addition of income assistance produced the smallest standardized differences with a range of 0.01-0.13 for all outcomes.
ConclusionsUsing the HDPS with health data only can reduce confounding due to social factors. If data are available, including income assistance in the HDPS may further reduce confounding for all social determinants of health.
In: International journal of population data science: (IJPDS), Band 3, Heft 4
ISSN: 2399-4908
IntroductionOn their 18th birthday children in custody of provincial Child and Family Services (CFS) age out, and are adults in control of their own care. An additional extended transitional services program was introduced several years ago to address gaps in the provicion of, and access to, adult social services during this change.
Objectives and ApproachUsing linked population based data from the Manitoba Population Research Data Repository, children in the custody of CFS who turned 18 during a 10 year study period were compared to children not in custody. For those in custody of CFS, we also compared individuals who participated in the extended transitional care services to those who opted out. Outcomes included use of health services and prescription drugs, social assistance, involvment with the justice system, living in social housing, and mental health outcomes. For most outcomes, the two year period prior to the 18th birthday and the two year period after were measured.
ResultsDuring the study period, 4656 children in care of CFS turned 18 while in custody. There were 2811 permanent wards, of which 1663 participated in the extended transitional services program. An additional 1845 non-permanent wards also turned 18 during the study period. Permanent wards were much more likely to be long term wards (greater than six years, ~65\%) compared non permanent wards (~17\%). Opioid prescription rates more than doubled in the two years after their 18th birthday and were about 6 times greater than prescription rates for those not in care of CFS. Criminal accusation rates did not change after their 18th birthday, were about equal for permanent and non-permanent wards. For the majority of outcomes, the transitional services program appeared to have little impact.
Conclusion/ImplicationsCompared to children not in care of CFS, rates of most outcomes were considerably higher for wards. Not all outcomes demonstrated a significant change over the transition period. By linking data from so many different government departments, extra attention can be focused on areas likely to have the greatest impact.
In: International journal of population data science: (IJPDS), Band 3, Heft 4
ISSN: 2399-4908
IntroductionSocioeconomic gradients in health exist in Canada. Although multiple Canadian area-based socioeconomic measures (ABSM) have been developed, none have been specifically validated against relevant pediatric outcomes. Our objective was to use key pediatric health outcomes and compare the strength of association with a number of ABSM, including income quintile.
Objectives and ApproachThis is a retrospective cross-sectional assessment of the association between socioeconomic status (SES) measured by ABSM and key pediatric health outcomes at the population level. Data from the Manitoba Population Research Data Repository was used for residents aged 0-19y. The timeframe was 2010-2015. Outcomes included preterm births, birth weight, mortality, vaccination rates and teen pregnancy. Regressions used each outcome against various ABSM (e.g. CAN-Marg, SEFI2, INSPQ) or income quintile. Best model for each outcome was assessed by goodness of fit measure (AIC). Measures of inequality included SII (Slope Index of Inequality) and RII (Relative Index of Inequality, both RIImean and RIIratio).
ResultsIn our regression models, the 4 Can-Marg subcomponents consistently had about 15% lower AICs (best fit) across all 16 key pediatric outcomes compared to INSPQ (Raymond-Pampalon), income quintile or SEFI2 (Socioeconomic Factor Index - Version 2). Sex differences were small and inconsequential. Whether ABSMs were treated as continuous or categorical predictors was of little statistical consequence. Of note, 15 of the 16 outcomes had socioeconomic gradients identified by SII or RII on at least one of the ABSMs. Income quintile detected 12 of 15, CAN-Marg material deprivation detected 9; the combination of CAN-Marg material deprivation and ethnicity detected 13 of 15. SEFI2 detected only 3 and the National INSPQ detected 6.
Conclusion/ImplicationsThere are significant health inequalities in pediatric outcomes in Manitoba (15 of 16 studied). Combining CAN-Marg measures of poverty (material deprivation) and ethnic concentration identified 13/15 cases of documented inequality and was the best ABSM for capturing pediatric health gradients; it was similar to income quintile alone.
In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACT
ObjectivesOur objective was to develop a comprehensive longitudinal data resource, which population health research scientists could use to study the social determinants of child health and health equity.
MethodsThe PATHS Resource was created from data holdings within the Manitoba Population Health Research Data Repository. The Manitoba Health Registry sits at the centre of the Repository and includes information – including a scrambled personal health identification number (PHIN) and date when coverage commenced and expired – on every individual registered with the province's universal healthcare system. The Repository also includes administrative data spanning several sectors including health, social services, justice, and education. We used individuals' scrambled PHINs to link children's administrative records across sectors to build a holistic picture of their health and development. We developed metadata, including routinized SAS algorithms and variable definitions, to ensure consistent operationalization of variables across studies. The longitudinal nature of these data allowed us to construct individual-level health and development trajectories from birth through adolescence for children born from 1984-2014. We used income data from the Canadian Census to develop both indicators of socioeconomic status (average neighbourhood level income) and provincial measures of income inequality (the Gini coefficient).
ResultsThe PATHS Resource includes data on the social determinants of health as well as health and development for children born 1984 to 2014 (n=608,007). We are able to follow children for a median observation period of 15.4 years. Income inequality – measured using the Gini coefficient – increased from 1984 to 2014: 0.16 to 0.21 (p<0.01). The proportion of children born to women from the bottom income quintile (i.e., the poorest 20% of families) also grew from 23.2% in 1984 to 27.2% in 2014 (p<0.01). When we followed children over their life course, we found that they were most likely to experience poverty (measured by family receipt of income assistance) at 2 years of age (p<0.01). Many studies from a variety of researchers have utilized the PATHS metadata to conduct child health and development research, ensuring consistent variable operationalization. These data have been used to identify policy levers for improving child health and reducing health inequalities.
ConclusionA resource such as the PATHS Resource can facilitate research into the health and development of children. Having data on the entire population allows investigators to both monitor trends in health inequities and identify strategies for improving health. Metadata ensure variable consistency and comparability across studies.
In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACT
ObjectivesThere is increased interest in identifying strategies the reduce health inequities. With this focus, population health scientists have applied equity measures first developed in other disciplines to health equity research. The objective of this study is to illustrate the application of these measures in research using linkable administrative databases. This presentation will provide a brief description of some commonly-used equity measures and issues investigators face when applying them in their own health equity research.
MethodsAnalyses focused on children born in Manitoba, 1984 to 2014. We used linkable administrative data from health, social services, and education to develop indicators of health and the social determinants of health. Income data from the Canadian Census were used to stratify children by socioeconomic status. Our study considered the distribution of several child outcomes: breastfeeding initiation, mortality, complete immunization rates at age 2, Grade 9 completion, and high school completion. We examined several measures often used to capture income-related health inequities: rate ratios and rate differences comparing children from high-income neighbourhoods with children from low-income neighbourhoods; the concentration index which quantifies the equity in the distribution of outcomes across the entire socioeconomic gradient; and the relative and absolute indices of inequality which compare the most advantaged individuals with the least advantaged individuals in the population while accounting for the distribution of health across the population.
ResultsWhen these measures are applied to health equity, they can be affected by factors not initially considered by investigators. The application of Concentration measures using health outcomes that are frequently dichotomized, and the prevalence of the health outcome can affect the degree of inequity that is possible, with highly prevalent outcomes showing very little divergence from the line of equity. Comparing concentration measures to the inequality indices can produce contradictory and seemingly incompatible results. Sample selection that alters the distribution of income from the population can also change the apparent equity of health outcomes. These matters are complicated when monitoring changes in health equity, over time.
ConclusionsSummary measures of equity can be useful but come with limitations that need to be considered when interpreting and applying study findings. We offer some suggestions to consider when applying these measures in health equity research.
In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACT
ObjectivesThe objective of this study was to identify whether breastfeeding inequalities have increased between 1984 and 2014 and to examine whether trends in income inequality are related to breastfeeding inequalities.
MethodsWe used linkable administrative data from the Population Health Research Data Repository. Our sample included all infants born in Manitoba, 1984 to 2014. We used area-level income – derived from the Canadian Census – to stratify infants into income quintiles. Canadian Census income data were also used to quantify provincial level income inequality for each fiscal year in our study period. Data from the hospital discharge abstract database were used to classify infants according to whether or not they had initiated breastfeeding. We linked infant data to maternal data using the Manitoba health insurance registry to capture maternal characteristics – including the mother's postal code of residence and her age at first birth. We used generalized linear models to calculate income quintile-specific breastfeeding rates for each fiscal year in our observation period for all of Manitoba. We also calculated age-adjusted breastfeeding rates to account for the changing age distribution in Manitoba mothers, over time. We measured breastfeeding inequities using the concentration index as well as the rate ratio and rate difference (comparing the breastfeeding rate between the highest and lowest income quintiles). We quantified income inequality using the Gini coefficient on income. Trend analyses and two-sided Z-tests tested for changes, over time. Time by income-quintile interactions tested whether breastfeeding rates were statistically significantly different, across socioeconomic groups.
ResultsBreastfeeding rates increased from 1985 to 2014, from 72% to 81% (p<0.01). The Gini coefficient increased from 0.16 to 0.21; a linear trend test of the Gini coefficient showed income inequality increased over the study period (p<0.05). Rate differences, rate ratios, and the Concentration index showed that significant breastfeeding inequalities existed throughout the study period. Trend tests revealed that breastfeeding inequalities did not increase, over time.
ConclusionsAggregate analyses may suggest overall improvement when inequality persists. Although there was improvement in breastfeeding initiation rates, children from lower socioeconomic status continue to lag behind their counterparts. Policy-focused health equity research needs to measure outcomes, overall, and inequity across time.
In: http://hdl.handle.net/10680/378
This project addresses the lack of neighbourhood statistical data and survey information on the quality of life in the inner city available to community groups. Many organizations and individuals in Winnipeg's inner city are working to enhance individual quality of life in the inner city and to raise the standard of living. However, there is no adequate way, at this time, to measure change occurring in neighbourhoods. Inner city organizations and larger governmental and non-governmental organizations collect data useful to measure outcomes of specific programs and general social trends; unfortunately these data and the survey instruments used are not standardized between organizations. It is difficult to use these data when measuring the community-wide impacts of programs, perceptions of residents, and the social or economic progress of neighbourhoods and communities.
BASE
In: Social science & medicine, Band 59, Heft 7, S. 1435-1447
ISSN: 1873-5347
In: Child abuse & neglect: the international journal ; official journal of the International Society for the Prevention of Child Abuse and Neglect, Band 76, S. 1-9
ISSN: 1873-7757