Population Health Model Research Articles

Developing a Population Health Framework for Studying Problem Gambling

Research has shown that the expansion of gambling is an important public health concern and a public health approach should be applied to study problem gambling (Canadian Public Health Association, 2000; Korn, 2000; Korn & Shaffer, 1999). However, such an approach is underutilized. Therefore, a conceptual framework was developed to study problem gambling (or pathological gambling) based on Evans and Stoddart's (1990) popular population health model. This framework can be used to identify psychosocial/social, genetic, and environmental correlates of problem gambling and important relationships between problem gambling and health and functioning, mental and physical health conditions, and help-seeking behaviours.

IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy

Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills. To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers. The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data. The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data. We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

The Relation between Types and Frequency of Gambling Activities and Problem Gambling among Women in Canada

Canada experienced large-scale growth of the gambling industry during the 1990s. Clinical data have indicated that substantial proportions of people seeking help for gambling problems in Canada are women. A population health model was used to understand the relation between types and frequency of gambling activities and problem gambling among women in Canada. Data used for the analysis were from the nationally representative Canadian Community Health Survey: Mental Health and Well-Being (CCHS 1.2; n = 10,056, women aged 15 years and older; data collected in 2002). The types of gambling associated with the highest odds of problem gambling among women in Canada were video lottery terminals (VLTs) outside the casino (OR 2.37 to 53.73; P < 0.01), VLTs inside the casino (OR 2.84 to 36.19; P < 0.001), and other casino games (OR 4.01 to 24.15; P < 0.001). These observations further our understanding of problem gambling among women in Canada and confirm that problem gambling among women is an important public health concern. Frequent VLT gambling, both outside and inside casinos, and other casino games are associated with the largest odds of problem gambling, which highlights an area of gambling in Canada that needs to be reassessed if problem gambling is to be prevented or reduced. Evidence-based research is necessary to inform healthy public policies on gambling in Canada. Findings from the current research have important research and policy implications.

Development of a population-based microsimulation model of osteoarthritis in Canada

The purpose of the study was to develop a population-based simulation model of osteoarthritis (OA) in Canada that can be used to quantify the future health and economic burden of OA under a range of scenarios for changes in the OA risk factors and treatments. In this article we describe the overall structure of the model, sources of data, derivation of key input parameters for the epidemiological component of the model, and preliminary validation studies. We used the Population Health Model (POHEM) platform to develop a stochastic continuous-time microsimulation model of physician-diagnosed OA. Incidence rates were calibrated to agree with administrative data for the province of British Columbia, Canada. The effect of obesity on OA incidence and the impact of OA on health-related quality of life (HRQL) were modeled using Canadian national surveys. Incidence rates of OA in the model increase approximately linearly with age in both sexes between the ages of 50 and 80 and plateau in the very old. In those aged 50+, the rates are substantially higher in women. At baseline, the prevalence of OA is 11.5%, 13.6% in women and 9.3% in men. The OA hazard ratios for obesity are 2.0 in women and 1.7 in men. The effect of OA diagnosis on HRQL, as measured by the Health Utilities Index Mark 3 (HUI3), is to reduce it by 0.10 in women and 0.14 in men. We describe the development of the first population-based microsimulation model of OA. Strengths of this model include the use of large population databases to derive the key parameters and the application of modern microsimulation technology. Limitations of the model reflect the limitations of administrative and survey data and gaps in the epidemiological and HRQL literature.

Spatiotemporal modelling of ozone distribution in the State of California

This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone ( O 3) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O 3 component that may change significantly from site to site. O 3 seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space–time maps of the seasonal O 3 patterns are generated across space and time. During the summer and winter months the seasonal O 3 concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O 3 patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space–time O 3 concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.

KidsMatter: A Population Health Model to Support Student Mental Health and Well-being in Primary Schools

This article provides an overview of a new schoolbased mental health initiative currently being trialed in 101 primary schools in Australia. KidsMatter: the Australian Primary School Mental Health Initiative is a population model for supporting student mental health and well-being. Using a whole-school implementation model, it provides schools with a framework, a guided process and key resources to develop and implement a co-ordinated set of mental health promotion, prevention and early intervention (PPEI) strategies for the specific mental health and well-being needs of their students. Through KidsMatter primary schools are engaged in building their capacities for PPEI by promoting a positive school community, teaching social and emotional skills, providing parenting support and education, and facilitating early intervention for students experiencing mental health difficulties. The article describes the rationale and theoretical underpinnings of KidsMatter, outlines key features of the framework, impleme...

Who is at Risk for Special Health Care Needs: Findings From the National Survey of Children's Health

A conceptual model of risk factors for special health care needs in childhood was presented previously. This article uses that conceptual model to identify candidate variables for an exploratory empirical examination of the effects of factors that may increase or decrease the risk of developing a special health care need. The National Survey of Children's Health was used for our analysis (N = 102 353). We used multilevel and multivariate analysis methods. We examined risk factors for special health care needs generally and for specific physical, developmental, behavioral, and emotional conditions cooccurring with special health care needs. Risk factors were grouped into 6 major domains, namely, predisposing characteristics, genetic endowment, physical environment, social environment, health-influencing behavior, and health care system characteristics. We examined preschool-aged and school-aged children separately. Significant associations were found in 5 of 6 domains studied (no variables in the health care systems characteristics were significant). Individual variables found to decrease or to increase significantly the odds of experiencing special health care needs were expressed at the child level (eg, age and gender), family level (eg, family structure and family conflict), and neighborhood level (eg, perception of supportiveness of the neighborhood). This analysis is the first to consider empirically a range of risk factors for special health care needs, using a population health model. Although provisional, the results of our analysis can help us to begin thinking about which characteristics of the child, family, and community are worthy of further exploration. Some of the variables we found to be significantly associated with special health care needs, such as age and ethnicity, are immutable. However, we found a number of significant correlates (ie, possible risk factors) that may be amenable to public health interventions, including breastfeeding practices, exposure to secondhand smoke, family closeness, and neighborhood cohesion.

Factor analytic investigation of Canadians' population health risk perceptions: the role of locus of control over health risks

To better understand how health risks are conceptualised by the Canadian public, exploratory and confirmatory factor analytic techniques were applied to data from a recent national telephone survey on health risk perception (N = 1503). Hazards assessed comprised an array of 30 items selected a priori by a panel of experts to represent the following five determinants of population health: the physical environment, biology, lifestyle, the social environment and healthcare. Respondents in the survey rated each hazard in terms of perceived risk to the health of Canadians. Rather than the hypothesised five-factor model, findings supported a three-factor model, with biochemical, lifestyle and social health risk perceptions emerging as key factors explaining the public's health risk perceptions. Although the observed model differed from expectations, it maintained some elements of current population health models. Further analyses revealed that biochemical, lifestyle and social health risk perceptions were differentially associated with beliefs about the locus of control over health risks. Findings are contrasted with those of a similar analysis of data from a comparable national survey conducted in Canada in 1992, and are discussed in relation to trends in discourse on health risk over the past decade.

A population health model for integrated assessment models

In this paper we present the initial results from a project to develop a population health model so we can extend the scenarios included in the IPCC’s Special Report on Emission Scenarios to include population health status. Our initial hypothesis was that some climatic variable, particularly temperature, would have a significant impact on health outcomes. After experiments – using the Global Burden of Disease (GBD) data on Years of Life Lost (YLL) and Years Lived with disability (YLD) both by WHO region and by five degree latitude band as outcome variables – failed, we settled on life expectancy (LE) as the best measure of health status. We discovered that there is a solid relationship between LE and the GBD data from our first experiments, allowing us to extend the results from the LE model. The LE model used cross section data on LE for 91 countries and included temperature, per capita income, access to clean water and sanitation, literacy, simple medical attention, nutrition, per capita medical expenditure, electricity use per capita, and automobiles per capita as independent variables. While all were individually associated with LE, our model of choice included literacy, access to clean water and sanitation, simple medical attention, an indictor variable for Sub-Saharan Africa and purchasing-power parity per capita income. Note that neither temperature nor calories enter into this model. The fit between life expectancy, as predicted by this model, and actual life expectancy was quite good (R2 =0.90), except for Rwanda, Uganda, and Madagascar; these countries accounted for one half of the unexplained variation in the model. The LE model was then used to develop trajectories of life expectancy in India for the four IPCC SRES storylines, where values for the independent variables were extrapolated based on the story line content. YLL and YLD estimates were created using the current cross relationship of these outcomes to LE. Given the lack of a general role for climate in our LE model, future work is planned to explore how to add detailed climate related impacts, to explore alternative nutritional variables, as well as extend the data set to allow a cross-section time-series approach.

Toward a Population Health Model of Segmented Assimilation: The Case of Low Birth Weight in Los Angeles

The authors adapt the segmented assimilation theory to a model of population health, which posits that assimilation is actually harmful to migrants' health. The authors also specify models of individual and contextual factors to indirectly test the theory of segmented assimilation— a theory that posits interactions between individual and residential circumstances. Using Year 2000 vital statistics data merged with 2000 U.S. census data from Los Angeles County, the authors model the probability of being born low birth weight among the native and foreign born. Results confirm an immigrant advantage at the individual level and protective effects of immigrant coresidence at the neighborhood level.

Indonesia’s social capacity for population health: the educational gap in active life expectancy

In this paper, we lay the initial groundwork for anticipating Indonesia’s future burden of disease by developing a demographic model of population health. We develop this model within the analytic framework of a Markov-based multistate life table model to calculate an important indicator of the burden of disease, the expected years of active life of elderly Indonesians. The magnitude of the gap points to the potential consequences of improvements in the nation’s educational level for the future burden of disease. The results show that having some education increases life expectancy but it also expands the expected years with a major functional problem. Overall educational attainment levels, however, are very low, indicating that Indonesia’s elderly are at the leading edge of improvements in the nation’s social capacity for health. The life tables suggest that at the early stages of development, longer life is accompanied by an expansion of morbidity.

Forecasting Acidification Effects Using a Bayesian Calibration and Uncertainty Propagation Approach

We present a statistical framework for model calibration and uncertainty estimation for complex deterministic models. A Bayesian approach is used to combine data from observations, the deterministic model, and prior parameter distributions to obtain forecast distributions. A case study is presented in which the statistical framework is applied using the hydrogeochemical model (MAGIC) for an assessment of recovery from acidification of soils and surface waters at a long-term study site in Norway under different future acid deposition conditions. The water quality parameters are coupled with a simple dose-response model for trout population health. Uncertainties in model output parameters are estimated and forecast results are presented as probability distributions for future water chemistry and as probability distributions of future healthy trout populations. The forecast results are examined for three different scenarios of future acid deposition corresponding to three different emissions control strategies for Europe. Despite the explicit consideration of uncertainties propagated into the future forecasts, there are clear differences among the scenarios. The case study illustrates how inclusion of uncertainties in model predictions can strengthen the inferences drawn from model results in support of decision making and assessments.

Race, Incarceration, and Health

Significant racial disparities in health outcomes have been consistently documented in the United States. Life-course and population-health models are often used to explain these disparities, but they generally do not take incarceration effects into account. Incarceration may have direct effects on health, but it is more likely to indirectly affect health by shaping employment, income, and marital trajectories. The authors contend that the failure of health researchers to take incarceration effects into account is problematic given the large increase in the incarceration of Black men over the past few decades. Moreover, because large numbers of incarcerated Black men are not present in research samples, racial disparities in health outcomes may be underestimated. Incarceration effects should be included in life-course and population-health models, study designs, and policy development processes.

Anastrozole is cost-effective vs tamoxifen as initial adjuvant therapy in early breast cancer: Canadian perspectives on the ATAC completed-treatment analysis

To conduct an economic analysis comparing tamoxifen and anastrozole (Arimidex) in the adjuvant treatment of hormone receptor-positive (HR+), post-menopausal early breast cancer patients. An economic model examined typical patients (64 years of age, HR+, 64% node negative) from the Arimidex, tamoxifen alone, or in combination (ATAC) trial over a lifetime horizon. Rates of events were derived from ATAC trial results. Post-trial event rates were drawn from the literature for tamoxifen; event rates for anastrozole were modified by the relative risks observed in the ATAC trial. Resource utilization was drawn from Statistics Canada's Population Health Model for breast cancer, supplemented by an expert panel. A public health care system perspective, 2004 Canadian prices and a 5% discount rate were employed. Anastrozole-taking patients incurred additional hormonal treatment costs compared to tamoxifen-taking patients (incremental lifetime cost, 6,974 Canadian dollars per patient), partially offset by reduced downstream recurrences of breast cancer (1,143 Canadian dollars lifetime savings per patient) for a net incremental cost of 5,796 Canadian dollars per patient on anastrozole. The anastrozole-treated patients were projected to experience a 5.6% absolute risk reduction of first breast cancer recurrence and a 2.8% absolute risk reduction in breast cancer death. This corresponded to 30,000 Canadian dollars per life year gained and 28,000 Canadian dollars per quality-adjusted life year gained (95% confidence interval, 17,428 to 54,605 Canadian dollars). The results were affected by the duration and extent of anastrozole benefit under sensitivity analysis but remained cost-effective. Compared to tamoxifen, anastrozole therapy is effective and cost-effective as initial adjuvant therapy in post-menopausal, HR+ early breast cancer patients.

Chapter 14: Fairview Alive—An Integrated Strategy for Enhancing the Health and Well-Being of Employees

This article describes the successful integration between EAP and wellness programs at Fairview Health Services-a program called Fairview Alive.A brief history of integration between EAP and wellness at Fairview is provided including the shared mission these two programs serve at Fairview. Next, this article outlines the Population Health Model on which Fairview Alivewas built, and the specific programs and services provided under each segment of this model. This article then focuses on how Fairview addresses depressionone of their largest cost drivers-in a coordinated effort. Finally, preliminary outcomes from a comprehensive program evaluation, including the impact on medical costs, workers compensation costs and absenteeism costs, are discussed.

1 FECS Award Worldwide meta-analyses of breast cancer treatment - EBCTCG 2005 — an update

This paper describes the Population Health Model (POHEM) developed by Statistics Canada and shows its usefulness in the evaluation of cancer control interventions and policy decision-making. Models of the costs of diagnosis and treatment of lung and breast cancer were developed and incorporated into POHEM. Then, POHEM was used to evaluate the economic impact of chemotherapy for advanced non-small cell lung cancer; reduced length of hospital stay following breast cancer surgery; and the provision of preventive tamoxifen to women at high risk of breast cancer. A lung cancer chemotherapy treatment decision framework was developed to rank order currently available chemotherapy regimens according to relative cost-effectiveness and cost-utility. Reducing post-surgical breast cancer hospitalisation with optimal home care support could produce major healthcare savings. However, the provision of preventive tamoxifen was estimated to have no population health benefit. This paper demonstrates that POHEM is an effective tool for performing economic evaluations of cancer control interventions and to inform healthcare policy decisions.

A model of underlying socioeconomic vulnerability in human populations: evidence from variability in population health and implications for public health

Drawing from insights into the variability of complex biologic systems we propose that the health of human populations reflects the interrelationship between underlying vulnerabilities (determined by population-level social and economic factors; e.g., income distribution) and capacities (determined by population-level salutary resources, e.g., social capital) and how populations, shaped by these vulnerabilities and capacities, respond to intermittent stressors (e.g., economic downturns) and protective events (e.g., introduction of a school). Monitoring this dynamic at the population-level can be accomplished by examining not only rates of illness and mortality, but variability in rates, either between populations or within populations over time. We used mortality data from New York City neighborhoods between 1990 and 2001 to test two related hypotheses consistent with this model of population health: (a) There is greater variability in mortality rates at a point in time between neighborhoods that are characterized by socioeconomic vulnerability; and (b) there is greater variability in mortality rates over time within neighborhoods that are characterized by socioeconomic vulnerability. We found that neighborhoods characterized by social and economic vulnerability displayed substantial variability in particular mortality rates. Mortality rates displaying the greatest variability were from causes that may be sensitive to social conditions (e.g., homicide or HIV/AIDS rates). Variability in population health existed both between neighborhoods with underlying vulnerability at one point in time and within vulnerable neighborhoods over time. The results of this analysis are consistent with a theory of underlying socioeconomic vulnerabilities of human populations and suggest that variability in population health may be an important consideration in population health assessment.

Residence, income and cancer hospitalizations in British Columbia during a decade of policy change.

BackgroundThrough the 1990s, governments across Canada shifted health care funding allocation and organizational foci toward a community-based population health model. Major concerns of reform based on this model include ensuring equitable access to health and health care, and enhancing preventive and community-based resources for care. Reforms may act differentially relative to specific conditions and services, including those geared to chronic versus acute conditions. The present study therefore focuses on health service utilization, specifically cancer hospitalizations, in British Columbia during a decade of health system reform.MethodsData were drawn from the British Columbia Linked Health Data resource; income measures were derived from Statistics Canada 1996 Census public use enumeration area income files. Records with a discharge (separation) date between 1 January 1991 and 31 December 1998 were selected. All hospitalizations with ICD-9 codes 140 through 208 (except skin cancer, code 173) as principal diagnosis were included. Specific cancers analyzed include lung; colorectal; female breast; and prostate. Hospitalizations were examined in total (all separations), and as divided into first and all other hospitalizations attributed to any given individual. Annual trends in age-sex adjusted rates were analyzed by joinpoint regression; longitudinal multivariate analyses assessing association of residence and income with hospitalizations utilized generalised estimating equations. Results are evaluated in relation to cancer incidence trends, health policy reform and access to care.ResultsAge-sex adjusted hospitalization rates for all separations for all cancers, and lung, breast and prostate cancers, decreased significantly over the study period; colorectal cancer separations did not change significantly. Rates for first and other hospitalizations remained stationary or gradually declined over the study period. Area of residence and income were not significantly associated with first hospitalizations; effects were less consistent for all and other hospitalizations. No interactions were observed for any category of separations.ConclusionsNo discontinuities were observed with respect to total hospitalizations that could be associated temporally with health policy reform; observed changes were primarily gradual. These results do not indicate whether equity was present prior to health care reform. However, findings concur with previous reports indicating no change in access to health care across income or residence consequent on health care reform.

Developing a national performance indicator framework for the Dutch health system.

To report on the first phase of the development of a national performance indicator framework for the Dutch health system. In January 2002, we initiated an informed interactive process with the intended users-policymakers at the Ministry of Health, Welfare and Sport-and academics to develop both the conceptual framework and its content. Decisions were based on consensus after discussing strategic goals of the health system, information needs of policy makers at the Ministry of Health, Welfare and Sport, and studying existing theory and international experiences with national performance indicator frameworks. We identified objectives and criteria for a framework at the national level, constructed a conceptual model, and selected indicator areas. As a starting point we chose a balanced scorecard reflecting four perspectives towards health system management information at the national level. These perspectives are consumer orientation, finances, delivery of high quality care, and the ability to learn and grow. We then linked the Lalonde model for population health to a balanced scorecard model. The constructed model makes the relationship between population health and health system management apparent, and facilitates the presentation of performance information from various perspectives. The model reflects the strategic goals of the Dutch health system, i.e. contributing to the production of health by providing necessary health care of good quality that is accessible for all Dutch citizens while simultaneously informing policy makers about the performance of the entire health system in all sectors (care, cure, prevention, and social services). The selected indicator areas for health system management information (20 in total) reflect the policy and management functions of the government and the defined public goals of the health system. The model was formally adopted by the Ministry of Health, Welfare and Sport in February 2003, and since then individual indicator areas have been operationalized by 30 representatives of various departments at the Ministry with continuous external research support. The merit of linking the balanced scorecard inspired model to public health data is that it facilitates the visualization of the contribution of the health system to the improvement of population health. The method of an intensive interactive indicator development process between policy makers and researchers has so far proven successful.

Understanding the barriers to cervical cancer screening among older women.

Despite the fact that 90% of cervical cancers can be prevented by regular Pap screening, many women are not screened regularly, particularly older women. To understand better the barriers to screening, the authors held five focus groups during April 2000 in Prince Edward Island (PEI), Canada. Of the 32% of women aged 45 to 70 who had not been screened over a 5-year period (1995-2000), 60 randomly selected women participated in this research. The authors analyzed discussions for themes using an inductive approach, with interpretation guided by the population health model. Women who have avoided a Pap test are falling between the cracks created by a complex interaction between personal experiences and the health system's approach to Pap screening.