Marketplace Plans With Narrow Physician Networks Feature Lower Monthly Premiums Than Plans With Larger Networks

Research Brief

Marketplace Plans With Narrow Physician Networks Feature Lower Monthly Premiums Than Plans With Larger Networks

Confirms trade-off between lower premiums and a more restricted choice of providers

Daniel Polsky, Zuleyha Cidav, and Ashley Swanson, Health Affairs October 2016


Key Findings: Narrow network plans on the health insurance marketplaces allow consumers to trade-off lower premiums for a more restricted choice of providers. This study finds that, all else being equal, an individual consumer is saving 6.7 percent of premiums, or between $212 and $339 a year, on a typical plan. 


The Question

Insurers offering plans on the Affordable Care Act’s health insurance marketplaces have used a strategy of restricted, or narrow, provider networks to limit costs. Narrow network plans are thought to be less expensive for consumers, but how much are they actually saving in premiums by choosing such plans? This study uses data from all ‘silver’ plans offered on the marketplaces in 2014 in all 50 states and the District of Columbia to categorize networks into “t-shirt sizes” and to estimate the association between the breadth of a provider network and plan premiums.

The Findings

The authors, building on previous work, categorized network size into five groups, based on the percentage of physicians in a service area participating in the network:   x-small (less than 10%), small (10%-25%), medium (25%-40%), large (40%-60%), and x-large (more than 60%). The average network included 30 percent of physicians in the service area. Slightly fewer than half of the plans had small or extra-small networks, while fewer than one-third had large or extra-large ones.

Adjusting for plan types, market features, and other insurer characteristics, a plan with an extra-small network had a monthly premium that was 6.7 percent less than a plan with a large network. These premium differences translate to a savings of $212 annually for a 27-year-old single individual, $339 for a 50-year-old, and $692 for a young family of four. The authors did not find a significant difference in premiums among x-small, small, and medium-size networks, suggesting that very restrictive plans do not tend to be cheaper than moderately restrictive plans. 

 

 

 

The Implications

This is the first study to investigate the relationship between physician network size and premiums for all 50 states and the District of Columbia. This rich dataset allows the authors to analyze the full variation across states with varying uninsurance rates, uptake of plans, and competitive environments.

The finding of a 6.7 percent reduction may not seem substantial, but it is based on the full premium, rather than the premium consumers pay after subsidies. For example, the average net premium after subsidy for a 27-year-old was $984 in 2014.  Based on that amount, a $212 annual reduction in premiums translates to a 22 percent reduction. Thus, subsidies are likely to magnify consumers’ sensitivity to premium differences between plans with different size networks.

Narrow networks have been criticized over concerns that consumers prioritize premium costs and are unaware of the network restrictions of the plans they select. If consumers in the Marketplace were fully informed about the networks tied to the plans in the Marketplace, many would still prefer the restrictions of a narrow network plan for the premiums they would save. This study advances our understanding of the trade-offs tied to network size by quantifying the premium trade-off, but more research is needed to understand the trade-off between quality of care and network size.

Offering plans with more restricted networks provides a way for insurance companies to offer lower-cost plans on the marketplaces. The success of these marketplaces, and further health coverage expansion, may be tied to the successful implementation of narrow networks that are transparent, adequate, and cost-saving.

The Study

The authors used the Health Insurance Exchange (HIX) Compare data set for 2014, which includes information on key plan features, such as premiums by rating area, deductibles, and cost-sharing requirements. They used publicly available provider directories from insurance company websites to add information on the size of provider networks for 341 unique provider networks identified.

To compare premiums, the authors used a plan’s rating area, since that is the level at which premiums vary. They assumed all types of physicians to be equally important to network breadth and did not differentiate between types of physicians.

The authors looked at silver plans, which have an actuarial value of 70 percent and are the most popular plans on the exchanges. Part of this popularity is because the government’s cost-sharing subsidies for lower-income consumers are only available for silver plans.  

The authors looked primarily at the premium offered to a 27-year-old single, nonsmoking policyholder, although they also considered premiums for a 50-year-old and a young family of four. They controlled for plan characteristics that might influence premium variation, such as plan type and primary care physician copayment, as well as market attributes that might drive prices, such as the level of competition, geographic variation in the cost of health care and population needs. They also controlled for variation in strategy, market power, or brand-name recognition among insurance companies.  

Lead Author: Dr. Daniel Polsky

Daniel Polsky, PhD is the Executive Director of LDI, Professor of Medicine in the School of Medicine and a Professor of Health Care Management in the Wharton School at the University of Pennsylvania. His research interests include access to health care, economics of the physician workforce, and economic evaluation of medical and behavioral health interventions. He serves on the Congressional Budget Office’s Panel of Health Advisers. 

 

LDI Research Briefs are produced by LDI's policy team. For more information please contact Janet Weiner at weinerja@med.upenn.edu