Evaluating Costs, Quality and Performance within a Market Economy Framework for the Nations of the Organization for Economic Cooperation and Development (OECD)

Abstract

Title of Dissertation: Evaluating Costs, Quality and Performance within a Market Economy Framework for the Nations of the Organization for Economic Cooperation and Development (OECD) Joshua Winer, MPH, MBA, Doctor of Philosophy, 2024 Dissertation Directed By: Jie Chen, PhD Department of Health Policy Management Background: National healthcare delivery systems and social determinants of a population coexist within the confines of capitalism. But not all capitalist economies behave the same way. Two poles exist that demarcate the degree to which that national economy engages in coordination or liberal competition. The 38 member nations of the Organization for Economic Cooperation and Development (OECD) represent democratic governments with market-based economies. COVID-19 demonstrated that nations with Coordinated Market Economies (CME) fared better in both economic (national GDP and labor productivity measures) and health outcomes (case positivity rates and deaths) than Liberal Market Economies (LMEs). The distinguishing trait of the CME is the degree to which protection is afforded to the individual via social policy and normative values. Social and welfare markets are critical and more prevalent within CMEs. Creation of a CME order is predicated on growth of human capital stock whereas LMEs coordinate via hierarchies, competitive markets and market incentives. The current practice of evaluating differences in healthcare costs across nations utilizes the GINI coefficient and market income (i.e., total national income before debts and taxes) as independent variables. . This new approach will endeavor to create a Coordination Index across values of economic equality, education, political institutions, market concentration and employment stability. This new approach evaluates whether the OECD nations based on their level of coordination (i.e. CME vs. LME traits) produce significant differences via the Triple Aim framework: cost, care quality, and system performance by using the Coordination Index to assess cost on a total per capita expenditures basis; quality through life expectancy of the total population, and system performance via avoidable mortality.Data and Methods: A conceptual framework was first designed to explain the synergies across Andersen’s Behavioral Model, Lorenzoni and Belloni’s Reciprocal Domains, Hall and Soskice’s Coordinated Markets, and with support from Esping-Andersen and Gunnar Myrdal’s analyses on welfare states and Keynesian programs. A comprehensive literature review was conducted to make the case for inclusion of these frameworks and the differing traits they offer if collated into a novel data index. Finally, I tested the model and hypotheses empirically. Data comes from the 38 OECD nations for the period of 2008 to 2018. Measures used to create the index included: GINI coefficient of the market income; Index of Economic Freedom; Freedom in the World Score; Labor Market Institutions Index; Strictness of Employment Protection; Social Progress Index; World Integrated Trade Solutions Market Concentration; and the OECD Database. I created the coordination index using the average measures of the aforementioned multidimension aspects of coordination using the datasets presented above. After which, I applied linear regression analyses to examine the association between Coordination Index and cost, quality, and system performance. Results: I established a conceptual model delineating the components of market and national coordination that would in theory serve as material influences on healthcare cost, quality and system performance. The empirical findings were consistent with this theory. Coordination plays a significant part in healthcare cost, quality and system performance. The empirical findings were consistent with the theory. The new Coordination index further surpassed the benchmark of an Alpha score range of 0.65 to 0.7 indicating reliability of the measure. The Creation of a new Coordination Index on a z-scale (mean: 0, median: 0.133, minimum: -4.602, maximum: 2.531) explained a higher degree of variance and association in univariate regression with Total Health Expenditure: (coeff. 0.275, 0.263 adjusted R-squared, Standard Error 0.023, Root MSE 0.460, p < 0.001) compared to using GINI alone (coeff: -3.917, 0.131 adjusted R-squared, Standard Error 0.498, Root MSE 0.500, p<0.001). I further find that Coordination had a positive association and was significantly associated with higher total cost in a baseline model and when adjusted for insignificant findings and collinearity was still significant (coeff. 0.036, p<0.05). I also find that Results showed first that the mean difference between higher quartile rankings and lower quartiles of Coordination in regard to Total Health Expenditure is significant (p<0.01), and secondly that a statistically significant (p<0.01) difference exists amongst Total Health Expenditure by quartiles of Coordination. The findings indicate that changes in Market Coordination towards the mean distribution of the OECD are associated with a higher total expenditure of 0.036 on a natural log basis, or approximately $1.036 (in thousands) per year higher Total Expenditure. I also find that Coordination did have a positive association but not a statistically significant association with a natural log of Life Expectancy in a baseline model nor when adjusted for insignificant findings and collinearity (coeff. 0.002, p<0.05) in regression. I conclude however though first that the mean difference between quartile rankings of Coordination is significant for quartiles 1 and 4 (p<0.01) and quartiles 2 and 3 (p<0.01) in regard to Life Expectancy. Secondly, that a statistically significant (p<0.01) difference exists amongst variances by quartiles of Coordination for Life Expectancy. The findings indicate that changes in Market Coordination towards the mean distribution of the OECD is associated with an increase in mean Life Expectancy of 0.002 on a natural log scale, or nearly 1 year when converted. I use the metric of Avoidable Mortality as a measure for system performance and find that Coordination was negatively associated and statistically insignificant on an Avoidable Mortality per 10 000 scale in a baseline model nor when adjusted for insignificant findings and collinearity (coeff. 0.275, p<0.05) in regression. However, I do conclude first that the mean difference between higher quartile rankings and lower quartile rankings of Coordination with is significant (p-value: 0.000, p<0.01) for quartiles 2 and 3 as well as quartiles 1 and 4 (p-value: 0.000, p<0.01). Secondly, that a statistically significant (p<0.01) difference exists among variances by quartiles of Coordination for Avoidable Mortality. This finding indicates that changes in Market Coordination towards the mean distribution of the OECD are associated with a decrease in Avoidable Mortality of approximately 3 deaths per 100 000. Conclusion: Within the OECD nations, changes in market Coordination towards the mean distribution of the OECD are significantly associated with, and have increases in healthcare cost, quality, and system performance. Quartile levels of Coordination are also shown to produce statistically significant differences in cost, quality and system performance as well, with higher levels of Coordination having lower cost, higher quality and better performance. Though slightly imperfect in its pursuits, Coordination as a concept advances the notion that the pursuit of a welfare state which places the values of economic equality, education, political institutions, market concentration and employment stability as priorities has a relationship to healthcare as an institution. Changes to these institutions and values should be made in harmonization with all other policy measures to achieve substantive gains. Failure to improve healthcare in conjunction with these other values risks enfeebled outcomes to the former.