Patient Acuity

Topics: Health care, Nursing, Electronic health record Pages: 20 (2618 words) Published: April 15, 2015

Nurse Leader Perceptions and Experiences with Workload Acuity Tools: Survey of United States Health Systems

Kanetia Stepney

HSM 5003.30 Management of Health Service Organizations
Spring 2015
Texas Woman’s University
School of Management
Professor Patricia Driscoll, JD, RN
March 31, 2015

Table of Contents
Types of Acuity Level Determination4
Literature Review5
Discussion and Recommendations9
Appendix A: Survey Tool11
Appendix B: Survey Invitation Message14
Appendix C: Graph Results of Data Collection15

The purpose of this paper is to examine the role and importance of using computer-based tools to determine patient acuity as it relates to hospital staff satisfaction and improved patient care. Patient acuity is defined as the severity of illness of the patient, in terms of the physical and psychological status of the patient, and the nursing intensity of the patient’s status, in terms of the nursing care needs and corresponding workload and complexity of care required by a patient (Brennan & Daly, 2009). This examination will consist of a review of pertinent literature as well as a presentation of formal survey results on the topic. The value of using triage to initially prioritize care based on the seriousness and extent of patients’ needs has long been established. The use of an acuity system to further prioritize levels and amounts of care exhibits the same logic and justification. Since hospitals must strike a balance between cost and the need to provide safe and quality inpatient care (Needleman, et. al, 2011), and since nurses are the most expensive labor resource in a hospital (Buerhaus, 2010), this suggests the possibility of reducing costs and improving patient care by more efficiently assigning nurses on the basis of the type and seriousness of patient condition. Basing the level and amount of nursing care on the type and seriousness of patients’ medical problems might also improve job satisfaction. Job dissatisfaction among hospital nurses is four times greater than the average for all U.S. workers, and one in five hospital nurses report that they intend to leave their current job within a year (Choi, et al., 2012). The ability to match nursing assignments to patient acuity has critical implications for providing safe, effective, and efficient care (Brennan, et al., 2012). Using Brennan’s definition of patient acuity, a patient acuity tool can then be defined as a tool which will indicate the optimum staffing requirements in order to deliver safe and effective patient care based on the acuity measurements. This measure of nursing workload, using the patients’ acuity scores, can also be used to assist with determining numbers of nurses needed each shift on specific units as well as with unit-level hiring decisions (Brennan, et al., 2012). This data can help justify and allocate nursing resources in an objective, meaningful fashion. To calculate specific acuity, the system reviews patients’ critical indicators, which differentiates patients and determines the workload or measurement of each patient’s need for care (Barton, 2013). Types of Acuity Level Determination

There are basically two types of acuity evaluation. In one, the patient’s electronic chart is reviewed by charge and supervising nurses, and a subjective evaluation using training and experience is made. In the other, all available data on the patient is fed into a preprogrammed computer module and the module determines the acuity level. Patient classification can be determined by methods and processes that are used to identify, validate and monitor the needs of an individual patient (Kontio, et al., 2014). The major companies providing electronic acuity systems are: Clairvia, API, Kronos and McKesson. Unfortunately, their claims towards positive satisfaction impacts are not substantiated by references on their...

References: Barton, N. (2013). Acuity-Based Staffing: Balance Cost, Satisfaction, Quality, and Outcomes.
Buerhaus, P. I. (2010). It’s time to stop the regulation of hospital nurse staffing dead in its tracks. Nursing Economic$, 28(2), 110-113. 
Choi J., Choi J
Duffield C., Diers D., O’Brien-Pallas L., et al. Nursing staffing, nursing workload, the work environment and patient outcomes. Appl Nurs Res. 2011;24(4):244-55.
Salantera, S., (2014). Predicting patient acuity from electronic patient records.
Journal of Biomedical Informatics, 51, 35-40.
Needleman, J., Buerhaus, P., Pankratz, V. S., Leibson, C. L., Stevens, S. R., & Harris, M. (2011). Nurse staffing and inpatient hospital mortality. New England Journal of Medicine, 364, 1037–1045.
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