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Development of an inpatient nursing master staffing model based on patient acuity levels

Posted on:2004-11-09Degree:Ph.DType:Dissertation
University:Capella UniversityCandidate:Roth, Theresa AnnFull Text:PDF
GTID:1454390011453930Subject:Health Sciences
Abstract/Summary:
For the nurse executive working in the hospital environment, achieving a balance between quality patient care and cost-effective staffing across patient specialty areas is a challenge. An objective, valid master staffing model can assist the nurse executive to operate their respective departments with staffing levels that fit within the budgetary parameters of the organization and provide quality patient care. This research study utilized trends in patient acuities as a foundation for validating master staffing levels for 11 inpatient-nursing units within an integrated healthcare system. The study used a descriptive design to examine data from reported trends in patient acuities for the calendar year 2001. This data was analyzed against the patient classification system's central tendency statistics to develop a master staffing model for each of the inpatient units. Results indicated that the reported patient acuity trends along with the patient classification system's central tendency statistics could be used to develop an inpatient/nursing staffing model in a variety of specialty nursing units. Correlational analysis was used to investigate the relationship between the dependent variable of master staffing levels with the independent variables of reported patient acuity levels and patient census. The study did not yield a statistically significant relationship between the analyzed variables. It is noteworthy, however, that other factors such as patient satisfaction, positive patient outcomes and nursing staff satisfaction support a relationship, although not statistical in nature, between the master staffing level and the reported trends in patient acuity.
Keywords/Search Tags:Patient, Master staffing, Health sciences, Nursing, Reported trends, Nurse executive, Central tendency statistics
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