Nursing Home Staffing and Quality of Care
- Presenter:
Chair: Sally Stearns; Discussant: Sally C. Stearns Tue June 6, 2006 13:45-15:15 Room 325
Most studies have found that higher nursing home staffing leads to higher quality of care. The implications of previous findings for an association between staffing and quality of care, however, may not reflect the true relationship. Existing estimates of the magnitude of the effect may be biased because most of these analyses were based on limited model specifications and did not control for the potential endogeneity of staffing. This study attempts to remove bias in estimates of the relationship between staffing and quality of care by controlling for endogeneity in staffing choices made by the facilities using fixed effects (FE) or fixed effects with instrumental variables (FE-IV). The analyses are conducted using facility-level data from the Online Survey and Certification Reporting (OSCAR) system from 1998 to 2003. OSCAR data are linked to data on specific market conditions and state policies. Quality is measured by facility-level total survey deficiencies, the incidence of contractures and pressure sores. Staffing level is measured by hours per resident day. Staffing mix is measured by the proportion of RNs hours compared to total staff hours. State policies, market (county) level nurse supply and demand variables are chosen as instruments to predict the staffing changes over time. Instrumental variables are incorporated in the model in order to (a) identify how nursing homes respond to the changes in the exogenous state policy shocks (i.e., state minimum staffing standards, Medicaid payment rates, a wage pass-through legislation), the relative competitiveness of the market and local resource constraints, and (b) investigate how these changes interact with staffing to yield changes in quality of care. The results from the study will be useful for understanding the contributions of staffing level and mix to the quality of nursing home care. The analysis also has two other dimensions of assessment. First, the estimation will allow an assessment of the effect of policies including state minimum staffing standards and wage pass-through provisions. Second, the magnitude and direction of the effect of staffing on quality of care is hypothesized to differ, contingent upon variations in facility characteristics (e.g., payer mix, case mix, size) and market environments (e.g., market competition, excess demand). Structural differences in the relationship between staffing and quality of care for different types of facilities may suggest different policy implications.