Regular and Off-Shift Nursing: Impacts on Patient Outcomes and Cost of Care
Project Number1I01HX000361-01A2
Contact PI/Project LeaderPHIBBS, CIARAN S.
Awardee OrganizationVETERANS ADMIN PALO ALTO HEALTH CARE SYS
Description
Abstract Text
Anticipated Impact on Veterans Health Care: The knowledge gained from this study will help to inform
hospital staffing practices, nursing delivery and patient outcomes across the VA healthcare system. To ensure
dissemination and translation of our findings into effective VA policies, we have recruited a high-level advisory
group representing important stakeholders and thought leaders including the Chief Nursing Officer from the
VA, and representatives from both the Joint Commission, and the Institute of Healthcare Improvement.
Project Background: Although there is increasing evidence that establishes the positive relationship
between the level of RN staffing and quality patient outcomes in general acute care settings, there are still
significant scientific knowledge gaps. For example, hospitals provide 24-hour, 7-day a week service and there is
evidence that patients admitted on off-shifts (nights, weekends, and holidays) have worse outcomes. However,
there is almost no research that has been conducted examining relationships between off-shifts nurse staffing
and patient outcomes. Due to limitations in previous datasets, researchers have not been able to account for
variation in patient needs at the unit-level, nor have they been able to consider other important workforce
characteristics such as education and tenure. Furthermore, most nurse staffing studies have been cross-
sectional, which limits the ability to infer causality. Finally, very few studies have explored the economic
considerations related to nurse staffing. We are just completing a project that has exploited the detailed VA
data systems to address some of these limitations. Specifically, we used a 4-year panel of monthly, unit-level
data for all VA acute care units to examine the effects of nurse staffing on adverse patient events and length of
stay (LOS). By integrating VA payroll data, we were able to move beyond just staffing levels to examine the
effects of contract nurses, the characteristics of the nursing staff (education, VA tenure, etc.), and the stability
of the nursing teams.
Project Objectives: The purpose of this project is to expand on our current research to examine how the
differences in nurse staffing between regular and off-shifts affect patient outcomes, and to conduct a detailed
examination of the trade-offs between the costs and benefits of increased nurse staffing. The existing dataset
we have created integrates patient, accounting, and payroll data from all VA acute care hospitals across the
nation for FY 03-06. We propose to expand this through FY11, to pull DSS cost of care data, and to develop
indicators related to off-shift nurse staffing to create the most comprehensive picture of nurse human capital
and patient outcomes available in the United States. We will also extend the model to control for treating
physician. Using this dataset, in the next two years our aims are 1) examine how the differences between
regular shifts and off-shifts in nursing inputs (staffing levels, skill mix, contract nurses, and general, facility-
specific, unit/team-specific human capital) effect nursing-sensitive patient outcomes and 2) analyze efficiency
in nursing services by studying the trade-offs between nursing personnel costs and cost savings from a
reduction in nursing-sensitive adverse events and LOS.
Project Methods: We will use fixed effects models to obtain the most current and comprehensive
examination of nurse staffing strategies and the impact on important nursing sensitive patient outcomes (e.g.,
decubitus ulcers, failure-to-rescue) and LOS. Staffing will be controlled separately for unit type (ICUs vs. other
acute care units). In addition to controlling for nurse staffing and the characteristics of the nursing team, we
will include variables to capture how the nurse staffing on the off-shifts differs from regular shifts. To compute
the cost of various staffing strategies, we will use the estimates of the effects of the human capital variables
from the previous aim 1 and link these data to associated wage data. We will re-run models using the cost of
patient encounters as the dependent variable to estimate the potential cost savings.
Public Health Relevance Statement
Nursing personnel are the largest workforce in hospitals. The overall goal of the study is to better
understand how to best provide high quality nursing care to veterans on all shifts efficiently. This
study will use detailed data from nine years on nurse staffing and patient outcomes. These data are
only available within the VA. Results from this study should inform hospital staffing practices across
the VA healthcare system, as well as have implications for non-VA hospitals. To ensure our findings
are translated into effective VA policies, we have recruited a high-level advisory group representing
important stakeholders and thought leaders including the Chief Nursing Officer from the VA.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AccountingAcuteAddressAdverse eventAffectBudgetsCaringCharacteristicsContractsCost SavingsCosts and BenefitsCross-Sectional StudiesDataData CollectionData SetDecubitus ulcerDiscipline of NursingEconomicsEducationEnsureEtiologyEventFailureFoundationsFundingGoalsHealthcareHealthcare SystemsHolidaysHospitalsHourInformation SystemsInpatientsInstitutesIntensive Care UnitsJointsKnowledgeLength of StayLicensureLinkLong-Term CareLongitudinal StudiesManuscriptsMedicalMethodsModelingNursesNursing ServicesNursing StaffOperative Surgical ProceduresOutcomePatientsPeer ReviewPhysiciansPoliciesRecruitment ActivityRegistered nurseResearchResearch PersonnelRiskRunningServicesSeverity of illnessTeam NursingTimeTranslatingTranslationsUnited StatesUnited States Department of Veterans AffairsVariantVeteransWagesWood materialWorkcosteconomic implicationexperiencehuman capitalimprovedinnovationnursing care qualitypatient safetyshift workskillssymposiumtheories
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