presents the total primary care scores for 18 members of the OECD for three decades: the 1970s, the 1980s, and the 1990s. Countries were scored based on each of the 10 criteria listed in . Scores reported reflect those at the midpoint of each decade. Statistical analyses were performed using scores calculated every year from 1970 to 1998. Appendix A
contains the score for each component used to calculate the total primary care score for each country.
Primary Care System and Practice Scores for OECD Countries
Several trends are apparent from an examination of . First, the average primary care score has improved by nearly one point over the three-decade period, although this difference was not statistically significant. Second, countries that were high performers in the 1970s remained high performers in each subsequent decade. If countries are divided into high and low performers (above or below the mean for each decade), then no country crossed the threshold from low to high or from high to low.
Certain system characteristics also appear to be associated with high primary care scores. For example, those countries with tax-based health financing also tend to score higher on other primary care components. One exception to this is the Netherlands. Although it does not have a purely tax-based health financing system, the Netherlands does share other features of primary care (such as few barriers to access, geographic regulation of primary care, use of family practitioners as gatekeepers, and a family-orientation) with its Scandinavian neighbors, all of which have high primary care scores.
Within the two groups of high and low performers there were significant movements over time. In general, these changes reflected improvements in primary care. For example, in the late 1980s and early 1990s Spain experienced reorganization and strengthening of primary care by improving health system features (moving to a tax-based financing system, improving geographic allocation of funds, and increasing the supply of family physicians) as well as practice features (improved integration, family orientation, coordination, and health promotion) (Larizgoitia and Starfield 1997
). Although the reform has not achieved all of its aims in every region (Larizgoitia and Starfield 1997
), there is some evidence that health outcomes have improved in regions where reform has been fully implemented (Villalbi et al. 1999
). The United States also showed a slight improvement over time. This improvement comes almost entirely from increased participation of Americans in health maintenance organizations (HMOs), which have tended, on average, to use a higher percentage of primary care providers who act as gatekeepers to higher levels of care, and which had (at least among the not-for-profit HMOs) a tradition of community involvement. This trend may reverse itself with the decrease in not-for-profit HMOs in the United States that was seen in the late 1990s.
presents descriptive data on independent and dependent variables used in multivariate analyses. Physicians per one thousand population, doctor visits per capita, and the percentage of population older than age 65 all showed increases in mean values at each decade. Tobacco consumption showed a statistically significant decrease each decade, from an average of 2,661 grams per capita in the 1970s to 1,970 grams per capita in 1990s. Even while controlling for inflation, both GDP and income per capita showed statistically significant increases over time. From the 1970s to the 1990s, income per capita nearly tripled, and average GDP per capita nearly quadrupled.
Descriptive Statistics of Variables Used in the Study
shows overall improvement in dependent (health outcome) variables over three decades. Age and sex-standardized all-cause mortality (as well as male- and female-specific all-cause mortality and cause-specific mortality) showed statistically significant declines each decade. All-cause mortality for both genders declined from an average of 943 per 100,000 in the 1970s to 695 per 100,000 in the 1990s, a statistically significant decrease of 26 percent. All-cause and cause specific premature mortality (Potential Years of Life Lost—PYLL) declined significantly over the period. Average all-cause PYLL declined from 6,933 years in 1970s to 4,495 years in the 1990s, a decline of approximately 35 percent.
Regression results are found in . Fixed effects regression analyses are presented in separate tables for each health outcome measure. In each of the tables presented, three nested models are compared. The first model (model 1) contains only primary care. The second model (model 2) contains primary care in addition to macro-level factors (physician supply, GDP per capita, and whether or not a country had a high proportion of elderly). The third model (model 3) contains primary care, macro-level factors, and aggregated individual measures expressed on a per capita basis (number of doctor visits, liters of alcohol consumed, grams of tobacco smoked, and the log of income earned adjusted for purchasing power parities). An F-test was performed to test the hypothesis that additional variables improved each model.
Fixed Effects Regression Estimates for Mortality Outcomes
In , fixed effects regression analyses are presented for all-cause standardized mortality for both genders, for women only, and for men only. Primary care is negatively associated with all-cause mortality rates independently (model 1), within a model of macro-level health determinants (model 2), and also in the full model (model 3) that includes aggregated individual determinants of health. In all models the primary care score is statistically significant (p<0.05), although the effect of primary care is partially reduced in the presence of environmental factors, and further reduced by the presence of aggregate individual health determinants. As expected, the numbers of physicians and GDP per capita are also negatively associated with all-cause mortality. In the full model, doctor visits and alcohol are not statistically significantly related with mortality, although income per capita (p<0.001) and tobacco (p<0.05) are. Model 2 and model 3 have unadjusted R2 values of 0.80 and 0.84, respectively.
The results are somewhat different for gender-specific all-cause mortality rates. For women, primary care is negatively associated with mortality in models 1 and 2, but it is not statistically significant in model 3. Macro-level factors have the expected effect, but alcohol, tobacco, and doctor visits per capita are not significant. All-cause mortality for men shows yet another pattern. Primary care is negatively associated with mortality in all three models, and both alcohol and tobacco are each positively associated with male mortality rates. Full models for female and male mortality both have unadjusted R2 values of 0.82.
presents results for all-cause Potential Years of Life Lost (PYLL)—a measure of premature mortality. Primary care is negatively associated with all-cause PYLL for both genders combined as well as for male-only and female-only PYLL, even in the presence of other known determinants of health (models 2 and 3). This is in keeping with the hypothesis that primary care would be most closely associated with health outcomes that represent preventable deaths. The number of physicians per one thousand population and income per capita were also found to be strongly and significantly negatively associated with PYLL in all models, and for both combined and separate gender-specific rates. In a pattern consistent with results for all-cause mortality, alcohol and tobacco use are positively associated with all-cause PYLL for men, but not for women. Finally, as expected, GDP per capita is negatively associated with PYLL, although in full models for both genders and for women only, it is not statistically significant. Unadjusted coefficients of determination for models 2 and 3 were between 0.69 and 0.79.
Fixed Effects Regression Estimates for Premature Mortality (PYLL)
presents results for four PYLL measures thought to be particularly sensitive to primary care. The first panel shows that primary care is negatively associated with premature mortality due to asthma, bronchitis, and emphysema, even in the presence of all other covariates, although, as in other models, the magnitude of the primary care coefficient was reduced with the introduction of other covariates. Total physician supply per one thousand population and income per capita were also negatively associated with premature deaths from these conditions. Somewhat surprisingly, GDP per capita was associated with a slightly increased prevalence of premature deaths. Coefficients of determination were only 0.43 and 0.49 for models 2 and 3, respectively. Because GDP per capita is positively associated with air pollution, it may be that the positive association between GDP and these respiratory conditions is actually due to increased air pollution.
Fixed Effects Regression Estimates for PYLL (Cause-Specific)
Premature deaths from pneumonia and influenza are negatively associated with primary care in all three models. Physician supply and income per capita were also associated with reduced premature deaths from pneumonia. As expected, there were higher numbers of pneumonia deaths in countries with a higher proportion of elderly. Two results are unexpected. The GDP per capita was associated with slightly higher premature pneumonia deaths, and alcohol use was associated with lower pneumonia deaths. Coefficients of determination were low for these models (0.35 and 0.36), indicating that there are likely to be other important determinants of pneumonia and influenza deaths that were not included in the models.
Primary care is significantly associated with reduced premature deaths from cerebrovascular diseases. In the presence of other covariates the relationship is reduced in magnitude, but remains statistically significant. Physicians, GDP, doctor visits, and income per capita were all negatively associated with cerebrovascular PYLL measures. Those countries with a high proportion of elderly also experienced greater potential years of life lost due to cerebrovascular disease. Alcohol and tobacco were not found to have a significant effect. Unadjusted R2 measures for the multivariate models were 0.68 and 0.72.
Ischemic heart disease is one of the most prevalent causes of death in OECD countries. It follows a pattern similar to that of cerebrovascular disease. Primary care is significantly and negatively associated with premature mortality from heart disease in all three models. Income and GDP per capita are also negatively associated with heart disease. Alcohol and tobacco use are positively associated with premature heart disease deaths. The unadjusted coefficient of determination was 0.64 for model 2 and 0.78 for model 3.