Health and health care are dominant economic and political issues in the United States and many other countries. This dissertation contains two essays addressing different subjects within the field of health economics. The first essay is labor market oriented: An Economic Analysis of the Effects of Obesity on Wages. It examines the effects of overweight and obesity on the wages of men and women. The second essay, An Economic Analysis of the Impact on Health Care of Certain Medicare Provisions of the Balanced Budget Act of 1997 examines changes in the treatment of Medicare patients in light of reimbursement changes brought about by the Balanced Budget Act of 1997. This analysis contained in An Economic Analysis of Obesity on Wages improves on previous work by using a dataset that can allow health effects to be better examined. Three series of regressions are performed, where log wage income is regressed on a series of variables including categorical variables based on body mass index. In contrast to some previous research, this analysis finds that the wages of obese individuals are not depressed by excess weight. It is possible that, because of the increasing prevalence of overweight and obesity over the last 20 years, any associated stigma has dwindled. An Economic Analysis of the Impact on Health Care of the Balanced Budget Act of 1997 examines the effects of one of the provisions of the Balanced Budget Act of 1997. Specifically, the analysis examines the implementation of the Post Acute Care Transfer policy, a change to Medicare Part A, caused the length of stay for patients grouped in certain targeted diagnosis related groups (DRGs) to increase, keeping with the goal of the policy change. In analyzing the short-stay patients, the data show that patients who were grouped into the pilot DRGs and were transferred after 10/01/98 (the effective date of the policy) were not in the hospital longer than before 10/01/98, implying that hospitals might not have been exploiting a financial loophole, as thought by the Health Care Financing Administration, now the Centers for Medicare and Medicaid Services.

This dissertation is a collection of three essays that use economic tools to address policy-relevant issues related to ageing, population health, and education. The use of economic modelling and econometric analyses has the potential to provide information on the consequences and effectiveness of policy interventions in these areas and enables policymakers to make better informed decisions. Chapter 1 provides an introduction to these topics and is followed by the three essays. In Chapter 2, I analyze how providing informal care to an elderly parent affects the caregiver's labour market outcomes, cognitive ability, and health; and study the influence of the institutional background on the caregiving decision and the effects of caregiving. My results show that negative effects on labour market outcomes can be avoided by the provision of formal care alternatives, but negative effects for caregivers' mental health persist. These findings give useful insights into the optimal provision of formal care in today's ageing societies. Self-reported health measures are commonly collected in numerous surveys but might be influenced by respondents' definitions and frames of reference of health. In Chapter 3, I address the issue of response bias in population surveys by constructing an objective measure of health. I find that using a common definition of health nearly eliminates the reported health differences between the U.S. and Canada. Socioeconomic differences in health are stronger in the U.S., but remain an issue in Canada. Chapter 4 studies the effect of post-secondary education on the continued development of reading proficiency during adolescence and young adulthood. Reading proficiency is essential for labour market success in a knowledge-based economy, but little is known about how advanced reading skills such as text interpretation and text evaluation are developed. The results show that university graduation increases students' reading proficiency relative to high school graduation, which demonstrates the importance of cognitive skill investments later in the life cycle. / Thesis (Ph.D, Economics) -- Queen's University, 2014-06-19 14:07:17.682

Background: Uncertainty in parameters is present in many risk assessment and decision making problems and leads to uncertainty in model predictions. Therefore an analysis of the degree of uncertainty around the model inputs is often needed. Importance analysis involves use of quantitative methods aiming at identifying the contribution of uncertain input model parameters to output uncertainty. Expected value of partial perfect information (EVPPI) measure is a current gold- standard technique for measuring parameters importance in health economics models. The current standard approach of estimating EVPPI through performing double Monte Carlo simulation (MCS) can be associated with a long run time. Objective: To investigate different importance analysis techniques with an aim to find alternative technique with shorter run time that will identify parameters with greatest contribution to uncertainty in model output. Methods: A health economics model was updated and served as a tool to implement various importance analysis techniques. Twelve alternative techniques were applied: rank correlation analysis, contribution to variance analysis, mutual information analysis, dominance analysis, regression analysis, analysis of elasticity, ANCOVA, maximum separation distances analysis, sequential bifurcation, double MCS EVPPI,EVPPI-quadrature and EVPPI- single method. Results: Among all these techniques, the dominance measure resulted with the closest correlated calibrated scores when compared with EVPPI calibrated scores. Performing a dominance analysis as a screening method to identify subgroup of parameters as candidates for being most important parameters and subsequently only performing EVPPI analysis on the selected parameters will reduce the overall run time.

Objectives: To estimate the incremental cost per QALY in patients with Parkinson’s Disease (PD) with varying disease severity and to ascertain which patient subgroup would accrue the greatest net monetary benefits to Ontario’s public health perspective as a result of Deep Brain Stimulation (DBS). Design: A cost-utility study and a net monetary benefit framework approach were applied to 37 PD patients with varying disease stages who underwent DBS treatment. Results: DBS resulted in cost savings of $2,686.3, $2,752.4, and $7348.4 and QALY gains of 0.33, 0.09 and 0.04 in patients with mild, moderate and severe PD. The ICER was $16,076.2/QALY. At $50,000/QALY, the greatest net monetary benefits accrued to Ontario’s MOHLTC were from treating patients with mild PD with DBS. Conclusions: DBS surgery was found to be a cost-effective PD treatment compared to pharmacotherapy. The greatest net monetary benefits were from treating patients with mild PD severity.

Objectives: To estimate the incremental cost per QALY in patients with Parkinson’s Disease (PD) with varying disease severity and to ascertain which patient subgroup would accrue the greatest net monetary benefits to Ontario’s public health perspective as a result of Deep Brain Stimulation (DBS). Design: A cost-utility study and a net monetary benefit framework approach were applied to 37 PD patients with varying disease stages who underwent DBS treatment. Results: DBS resulted in cost savings of $2,686.3, $2,752.4, and $7348.4 and QALY gains of 0.33, 0.09 and 0.04 in patients with mild, moderate and severe PD. The ICER was $16,076.2/QALY. At $50,000/QALY, the greatest net monetary benefits accrued to Ontario’s MOHLTC were from treating patients with mild PD with DBS. Conclusions: DBS surgery was found to be a cost-effective PD treatment compared to pharmacotherapy. The greatest net monetary benefits were from treating patients with mild PD severity.

Introduction: Beta-Blocker Evaluation Survival Trial (BEST) sub-analyses indicated a likely interaction between bucindolol and race disadvantaging black heart failure (HF) patients (Domanski J Cardiac Fail 2003); Arg389 homozygotes having adjusted reductions of 38% in mortality and 34% in mortality/hospitalization over other genotypes (Liggett PNAS 2006). Bucindolol is being evaluated in Arg389 genotype patients in the GENETIC-AF trial (NCT01970501). Objective: To conduct parallel (using Domanski et al and Liggett et al) ex ante economic evaluations of Arg389 genetic testing in stage III/IV HF to support bucindolol treatment decisions (if Arg389-positive) and carvedilol (if Arg389-negative) treatment versus no such testing and empirical bucindolol; using Domanski et al and Liggett et al BEST sub-analyses. Methods: In both Domanski et al and Liggett et al analyses, we used a decision tree model with time horizon of 18 months divided into 3 six-month cycles to estimate the cost-effectiveness and cost-utility of Arg389 genetic testing, considering overall survival (OS) from Domanski et al and Liggett et al BEST sub-analyses. Costs and utilities were retrieved from literature except for assumed cost for bucindolol treatment (1.5x cost of carvedilol) and genetic testing ($250). Discount rate was set at 3%/yr. Weibull distributions were fitted to OS data. Life-years (LY) and quality-adjusted life-years (QALY) were used to estimate incremental cost-effectiveness (ICER) and cost-utility ratios (ICUR), and results were validated using probabilistic sensitivity analyses (PSA). Results: In the Domanski et-based analysis, Arg389 genetic testing versus no testing was associated with incremental gains of 0.29LYs and 0.27QALYs at incremental cost of $726; yielding ICER of US$2,503/LY and ICUR of US$2,688/QALY gained. In the Liggett et al-based analysis, Arg-389 genetic testing versus no testing was associated with incremental gains of 0.35LYs and 0.32QALYs at savings of -$1.081; for ICER of -US$3,089/LY and ICUR of -US$3,378/QALY gained. Both analyses were confirmed in PSAs. Conclusion: Arg389 genetic testing to support bucindolol treatment in stage III/IV HF patients prevails economically over bucindolol treatment without genetic testing due to superior OS. If bucindolol is priced at 1.5x the cost of carvedilol. this economic benefit is likely to disappear if bucindolol and/ or genetic testing are priced higher. The clinical and economic benefits of bucindolol treatment with versus without Arg389 genetic testing versus empiric carvedilol remains to be assessed.

Background: Uncertainty in parameters is present in many risk assessment and decision making problems and leads to uncertainty in model predictions. Therefore an analysis of the degree of uncertainty around the model inputs is often needed. Importance analysis involves use of quantitative methods aiming at identifying the contribution of uncertain input model parameters to output uncertainty. Expected value of partial perfect information (EVPPI) measure is a current gold- standard technique for measuring parameters importance in health economics models. The current standard approach of estimating EVPPI through performing double Monte Carlo simulation (MCS) can be associated with a long run time. Objective: To investigate different importance analysis techniques with an aim to find alternative technique with shorter run time that will identify parameters with greatest contribution to uncertainty in model output. Methods: A health economics model was updated and served as a tool to implement various importance analysis techniques. Twelve alternative techniques were applied: rank correlation analysis, contribution to variance analysis, mutual information analysis, dominance analysis, regression analysis, analysis of elasticity, ANCOVA, maximum separation distances analysis, sequential bifurcation, double MCS EVPPI,EVPPI-quadrature and EVPPI- single method. Results: Among all these techniques, the dominance measure resulted with the closest correlated calibrated scores when compared with EVPPI calibrated scores. Performing a dominance analysis as a screening method to identify subgroup of parameters as candidates for being most important parameters and subsequently only performing EVPPI analysis on the selected parameters will reduce the overall run time.

Cigarette smoking causes many chronic diseases that are costly and result in frequent hospitalization and re-hospitalization. Smoking cessation leads to improved morbidity and reduced risk of death. Hospital-initiated smoking cessation interventions increase the likelihood that patients will become smoke-free. Despite this, few Canadian hospitals have in place policies, protocols, and reminder systems that support the consistent and effective identification and treatment of tobacco users. The Ottawa Model for Smoking Cessation (OMSC), developed at the University of Ottawa Heart Institute (UOHI), is a systematic approach to identifying and treating smokers in the hospital setting. In order for health care funders and hospital administrators to begin supporting effective prevention interventions, like the OMSC, a compelling cost-effectiveness argument must be made. Few studies have looked at the downstream health, health care, and cost implications of such programs, particularly in the Canadian context and none using actual health care administrative data. In response to this gap, three studies were completed, applying theories and methodologies related to health services and population health research. Study 1: From the hospital payer’s perspective, what is the short-term (one year) and long-term (lifetime) cost-effectiveness of the OMSC intervention, as compared to a usual care condition, among high-risk smokers with chronic diseases? A cost-effectiveness analysis was completed based on a decision-analytic model to assess smokers hospitalized in Ontario, Canada for acute myocardial infarction, unstable angina, heart failure, and chronic obstructive pulmonary disease, their risk of continuing to smoke, and the effects of quitting on re-hospitalization and mortality over a one year period. Short- and long-term cost-effectiveness ratios were calculated. The primary outcome was one-year cost per quality-adjusted life year (QALY) gained. Study 2: What are the effects of the OMSC intervention on: 1) mortality, and 2) downstream health care utilization? An effectiveness study was completed comparing patients who received the OMSC intervention (n=726) to usual care controls (n=641). The study took place at 14 hospitals in Ontario. Baseline data was linked to Ontario health care administrative data. Unadjusted and adjusted competing-risks regression models were constructed, clustered by hospital, to compare the cumulative incidence of death, re-hospitalization, emergency department (ED) visits, and physician visits at 30 days, one, and two years following index hospitalization between groups. Study 3: From the health system perspective, what are the cumulative mean health care costs at 30-day, 1-year, and 2-year follow-up among smoker-patients that receive the OMSC compared to those that do not? What are the predictors of direct health care costs for patients that receive the OMSC compared to those who do not? Expanding on Study 2, a cost-analysis was completed to assess 30-day, 1-year, and 2-year health care costs between intervention and control groups. Costs were broken down by service type (e.g. inpatient, ED visits, laboratory, physician visits). To calculate cumulative mean costs, costs were grouped into the study’s 24 monthly intervals and weighted by the inverse probability of not being censored at the beginning of each month. Covariate-adjusted generalized linear models were performed for each of the 24 monthly intervals to determine the association between independent variables and health care costs.

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In strengthening health systems, the World Health Report 2000 indicates that health system improvement strategies must also cover private (for-profit and non-profit) health care provision and financing if progress towards Universal Health Coverage is to be achieved. Yet very little is known about the financing of non-profit providers in Africa - especially not faith-based health providers, who have often historically remained elusive in terms of financial transparency. This thesis reports on a multiple case study conducted with two non-profit faith-based health providers in Kenya, namely the Africa Inland Church Kijabe Hospital; and Nyumbani-Children of God Relief Institute in Nairobi (Nyumbani) - and situates these within the broader context of health systems financing and public-private partnership in Kenya. Data was collected from multiples sources including: secondary literature; secondary analysis of existing data (such as the Kenya Health Information System); financial data on projects and annual reports; routine facility and service data; previous research on both organizations; archival data; and supplemented by 6 in-depth interviews with key stakeholders. The study reveals a highly complex funding environment for non-profit (and faith-based) health providers in Kenya, which is a result of historic health system configurations, and current funding policy and focus (such as the influx of HIV-related funding). The HIV program in AIC Kijabe Hospital is solely funded by USAID; while Nyumbani is also funded by USAID (70%), but has other private sources. In both cases, funding from various sources is structured differently with varied financial flows and requirements. Faith-based health providers in Kenya are highly dependent on complex donor-funding arrangements, and lack financial resilience as a result. Donors need to better understand the nuance of engagement with such providers.