Background

Rankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data.

Methods

We primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors.

Results

The US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank.

Discussion

Our study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions.

Conclusions

Future international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency.

Objective

To predict changes in wage growth for health care workers based on projections of insurance enrollment from the Affordable Care Act (ACA).

Data sources

Enrollment data came from three large employers and a sampling of premiums from ehealthinsurance.com. Information on state Medicaid eligibility rules and costs were from the Kaiser Family Foundation. National predictions were based on the MEPS and Medicare Current Beneficiary surveys. Bureau of Labor Statistics data were used to estimate employment.

Study design

We projected health insurance enrollment by plan type using a health plan choice model. Using claims data, we measured the services demanded for each plan choice and year. Projections of labor demand were based on current output/input ratios. Changes in wages resulting from changes in labor demand from 2014 to 2021 were based on labor supply and demand elasticities.

Principal findings

Expenditures required to retain and grow the health care workforce will increase substantially. Wages will increase most for professions with the greatest training requirements (physicians and registered nurses). The largest impact will be felt in 2015.

Conclusions

Projected wage increases for health care workers may drive substantial growth in insurance premiums and reduce the affordability of health insurance.