nursing home bankruptcies in California:
An Exploratory Study
Martin Kitchener, Ph.D.
Charlene Harrington, Ph.D.
Department of Social & Behavioral Sciences
University of California, San Francisco
This report was prepared pursuant to a request of California State Senator Deborah V. Ortiz and the Senate Rules Committee to the California Research Bureau to examine factors related to nursing home bankruptcies in California. The study was funded by a grant from the California Research Bureau’s Contract Research Fund. The views expressed here are those of the authors and not the California Research Bureau or the California State Senate.
Introduction and Study Aims
In 2000, an estimated 1,900 U.S. nursing homes were operating under the protection of Chapter 11 of the U.S. Bankruptcy Code. While Chapter 11 status allows nursing home corporations to restructure, stop payments to creditors and renegotiate loan schedules, most owners continue to operate their nursing homes. Despite this, widespread anxiety about nursing home bankruptcy arose in California after two widely publicized cases of sudden facility closure.
This first independent study of nursing home bankruptcy in California had two main goals: (1) To describe the nature and scope of nursing facility bankruptcy in the state, and (2) To examine the relationship between individual nursing home bankruptcy status and a range of facility-level factors.
Our sample of 955 California free standing (e.g., not hospital-based) nursing homes included all facilities except non-profit homes because they do not have the ability to enter into bankruptcy. Data provided by the state, Centers for Medicaid and Medicare Services (CMS) and an industry association allowed us to identify only bankrupt members of multi-facility organizations (chains). Bankruptcy data were not available for independent (non-chain) facilities. This means that our models predict only which individual California nursing homes were members of bankrupt chains in 2000, and not necessarily, the bankruptcy of a chain organization. We used the California licensing and certification division’s (ACLAIMS) database to identify the individual California facility members of chains in bankruptcy.
We followed standard practice in bankruptcy research to conduct a series of conditional logit regression analyses in which the independent (predictor) variables were lagged one year to estimate bankrupt homes in 2000. One model used 1999 data on all homes in the sample to predicted 25 percent of the individual facilities that were members of bankrupt chains in 2000. A second model used 1999 data on chain members only to 25 percent of the individual facilities that were members of bankrupt chains among all facilities in 2000. The predictive capacity of these models is strong when compared with models produced from bankruptcy studies in other sectors.