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Brian C Quinn

Publications and source records attributed to Brian C Quinn.

2 recordsLinked to original sources

Do physicians always flee from HMOs? New results using dynamic panel estimation methods.

OBJECTIVE: To assess the impact of changes in relative health maintenance organization (HMO) penetration on changes in the physician-to-population ratio in California counties when changes in the economic conditions in California counties relative to the U.S. average are taken into account. DATA SOURCES: Data on physicians who practiced in California at any time from 1988 to 1998 were obtained from the AMA Masterfile. The analysis was restricted to active, patient care physicians, excluding medical residents. Data on other covariates in the model were obtained from the Bureau of Economic Analysis, InterStudy, the Area Resource File, and the California state government. Data were merged using county FIPS codes. STUDY DESIGN: Changes in the physician-to-population ratio in California counties include the effects of both intrastate migration and interstate migration. A reduced-form model was estimated using the Arellano-Bond dynamic panel estimator. Economic conditions in California relative to the U.S. were measured as the ratio of county-level real per capita income to national-level real per capita income. Relative HMO penetration in California was measured as the ratio of county-level HMO penetration to HMO penetration in the U.S. relative HMO penetration was instrumented using five identifying variables to address potential endogeneity. Omitted-variable bias was controlled for by first differencing the model. The model also incorporated eight other covariates that may be associated with the demand for physicians: the percentage of the population enrolled in Medicaid, beds in short-term hospitals per 100,000 population, the percentage of the population that is black, the percentage of the population that is Hispanic, the percentage of the population that is Asian, the percentage of the population that is below age 18, the percentage of the population that is aged 65 and older, and the percentage of the population that are new legal immigrants in a given year. All of the above variables were lagged one period. The lagged physician-to-population ratio was also included to control for the supply of physicians. Separate equations were estimated for primary care physicians and specialist physicians. PRINCIPAL FINDINGS: Changes in lagged relative HMO penetration are negatively associated with changes in specialist physicians per 100,000 population. However, this effect of HMO penetration is attenuated and at times reversed in areas where the magnitude of the difference in relative economic conditions is sufficiently large. We did not find any statistically significant effects for primary care physicians. CONCLUSIONS: Consistent with prior studies, we find that changes in physician supply are associated with changes in relative HMO penetration. Relative economic conditions are an important moderator of the effect of changes in relative HMO penetration on physician migration.

California↗

Estimating the effect of smoking cessation on weight gain: an instrumental variable approach.

OBJECTIVE: To propose and test a method that produces an unbiased estimate of the average effect of smoking cessation on weight gain. Previous estimates may be biased due to unobservable differences in attributes of quitters and continuing smokers. An accurate estimate of weight gain due to cessation is important for policymakers, health managers, clinicians, consumers, and developers of smoking cessation aids. STUDY SETTING: Our analysis consisted of an instrumental variables (IVs) approach in which treatment assignment in randomized smoking cessation trials served as a random source of variation in probability of quitting. DATA COLLECTION: We searched the medical literature for previously conducted smoking cessation trials that contained data suitable for our reanalysis. PRINCIPAL FINDINGS: We identified one trial for our reanalysis, the Lung Health Study, a randomized smoking cessation trial with 5,887 smokers aged 35-60 from 1986 to 1994 in several sites across the United States. In our IV reanalysis, we estimated a 9.7 kg weight gain over 5 years due to cessation, as compared with the conventional estimate of 5.3 kg. CONCLUSIONS: The true effect of smoking cessation on weight gain may be larger than previously estimated. This result indicates the importance of fully understanding the possible weight effects of cessation and underscores the need to accompany cessation programs with weight management interventions. The result, however, does not overturn the conclusion that the net health benefits of quitting are positive and very large. The application of the IV technique we propose is likely to be useful in a variety of contexts in which one is interested in the effect of one health condition on another.

Adult↗