Nurse staffing and skill mix and association with cost in the Veterans Health Administration
- Presenter:
Chair: TBA; Discussant: TBA Tue June 6, 2006 10:45-12:15 Room 225
Rationale: Several large scale studies have found associations between nurse staffing and mortality outcomes for hospitalized patients, aggregated to the facility level. In this study, we provide the first large-scale analysis using nursing unit-level data to examine staffing levels, skill mix, and costs of care.
Objective: To examine the association between nurse staffing, skill mix, and costs of care at the unit and facility levels. We define skill mix as the mix between different types of nursing provider, with different levels of training and receiving different wage rates.
Methodology: Data came from several sources: DSS nursing labor input files (ALBCC); VA National Patient Care Databases for demographic, comorbidity, complication and utilization data on all patients admitted to VHA inpatient acute care between 2/03-6/03; Decision Support System (DSS) TRTIPD files, a DSS extract file linking inpatients to nursing units; and DSS cost extracts for patient level costs of care for each admission. We estimate costs of inpatient care for each admission by regressing on patient risk of complications (estimated in a prior analysis), and staffing hours by type of nurse provider (registered nurse- RN, licensed practical nurse- LPN, nurse aide- NA), divided into tertiles, and including interaction terms among staffing level tertiles of different types of nurse providers. We stratify the analysis by whether the first inpatient unit was intensive care or non-intensive acute care, and will conduct sensitivity analyses varying patient cohort definition, for example, by stratifying by whether or not the patient received any intensive care vs. those who have no intensive care. We will use GLM as our primary estimator, controlling for clustering at the unit and facility level, as well as multilevel modeling using Stata’s recently added xtmixed procedures with two levels of clustering, and controlling for market variation in wages using real dollars. We will accomplish this last piece by controlling for the Medicare/Medicaid wage index, which is specific to local markets in the United States.
Results: The analyses includes 126,382 patients from 463 nursing units in 119 VAMCs, admitted between February and June 2003. 184 units are intensive care, and 279 non-intensive acute care units. In prior analyses, we have found that skill mix and staffing have a non-linear, U-shaped association with mortality risk in both ICU and non-intensive care patients, and that multi-level modeling, adequate patient risk adjustment, and careful modeling of non-linear relationships are critical. One major finding in the analyses to date, which are ongoing, is that the curvilinear relationship in skill mix between different types of nurse provider has a significant impact on risk service utilization, including length of stay. As we complete our analyses, we anticipate that this difference will result in major differences in cost of care in nursing units using different skill mixes, controlling for quality of care. Differences in wage rates between RN and NA in the United States can be as high as five times greater wages for RNs than NAs. Analyses are ongoing, and we anticipate completion of these cost analyses by February 2006.
