BACKGROUND: Currently, the Centers for Medicare and Medicaid Services report on 15 Quality Measures (QMs) on the Nursing Home Compare (NHC) website. It is assumed that nursing homes are able to make improvements on these QMs, and in doing so they will attract more residents. In this investigation, we examine changes in QM scores, and whether competition and/or excess demand have influenced these change scores over a period of 1 year. METHODS: Data come from NHC and the On-line Survey Certification And Recording (OSCAR) system. QM change scores are calculated using values from January 2003 to January 2004. A series of regression analyses are used to examine the association of competition and excess demand on QM scores. RESULTS: Eight QMs show an average decrease in scores (ie, better quality) and six QMs show an average increase in scores (ie, worse quality). However, for 13 of the 14 QMs these average changes averaged less than 1%. The regression analyses show an association between higher competition and improving QM scores and an association between lower occupancy and improving QM scores. CONCLUSION: As would be predicted based on the market-driven mechanism underlying quality improvements using report cards, we show that it is in the most competitive markets and those with the lowest average occupancy rates that improvements in the QM scores are more likely.
BACKGROUND: Currently, the Centers for Medicare and Medicaid Services report on 15 Quality Measures (QMs) on the Nursing Home Compare (NHC) website. It is assumed that nursing homes are able to make improvements on these QMs, and in doing so they will attract more residents. In this investigation, we examine changes in QM scores, and whether competition and/or excess demand have influenced these change scores over a period of 1 year. METHODS: Data come from NHC and the On-line Survey Certification And Recording (OSCAR) system. QM change scores are calculated using values from January 2003 to January 2004. A series of regression analyses are used to examine the association of competition and excess demand on QM scores. RESULTS: Eight QMs show an average decrease in scores (ie, better quality) and six QMs show an average increase in scores (ie, worse quality). However, for 13 of the 14 QMs these average changes averaged less than 1%. The regression analyses show an association between higher competition and improving QM scores and an association between lower occupancy and improving QM scores. CONCLUSION: As would be predicted based on the market-driven mechanism underlying quality improvements using report cards, we show that it is in the most competitive markets and those with the lowest average occupancy rates that improvements in the QM scores are more likely.
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