The Growth and Geographical Variation of Nursing Home Self-Pay Prices

Published: 2019


Nursing home care is arguably the largest financial risk for the elderly without private or social insurance coverage. The annual out-of-pocket expenditure can easily exceed $70,000. Despite the substantial financial burdens on the elderly, the understanding of nursing home self-pay prices is rather sparse due to data limitation. To bridge the gap in the literature, we collected a unique and longitudinal price dataset from eight states, spanning from 2005 to 2010, to advance the understanding of the determinants and geographical variations of nursing home price and price growth. Overall, nursing home prices have consistently outpaced the inflation of consumer prices, particularly in California and Oregon. We also see faster price growth in markets where they face stricter capacity constraints and have higher for-profit market shares. Organizational structures are also significantly associated with price variations. We find that nonprofit nursing homes have higher prices than for-profit nursing homes and that chain-affiliated nursing homes charge higher prices than nonchains counterparts.

Key Findings

    • We provide empirical evidence of the association between nursing home private-pay prices and organization types and market structures. However, we find these determinants explain relatively little about price growth.
    • While we include resident characteristics to control for the differences in resident profiles, there can be unobservable and differential resident selection into different organization types which may bias our results. To account for this issue in future research, we suggest using resident-level data and the instrumental variables approach which theoretically can randomize the likelihood of a resident being admitted to a particular type of nursing homes.
    • We do not control for quality differences between nursing homes and the observed price variations to some extent can be related to underlying quality. Future work should consider adopting structural modeling techniques that can simultaneously account for price and quality differences between nursing homes. a more comprehensive price dataset including more markets and years will be useful to provide more market-level variations overtime.
    • We show that nursing home prices have consistently outpaced both the consumer and medical care inflations. While it may partly reflect better quality and more comprehensive services provided at nursing homes over the study period, private-pay residents still face greater financial burdens. Given the significant portion of the elderly’s wealth at stake, it is important to understand whether the escalating prices mostly reflect better quality, or to some extent, are the results of market inefficiencies.
    • We find statistically significant price differences between the FP and NFP as well as chain and nonchain nursing homes. The results suggest that when evaluating the value of nursing home care (quality over price), the priv


Huang, Sean Shenghsiu, Richard A. Hirth, Jane Banaszak-Holl, and Stephanie Yuan. 2019. “The Growth and Geographical Variation of Nursing Home Self-Pay Prices.” Ann Arbor, MI: University of Michigan Retirement Research Center (MRRC) Working Paper, WP 2019-397.