Optimising cardiac services using routinely collected data and discrete event simulation

Background: The current practice of managing hospital resources, including beds, is very much driven by measuring past or expected utilisation of resources. This practice, however, doesn’t reflect variability among patients. Consequently, managers and clinicians cannot make fully informed decisions based upon these measures which are considered inadequate in planning and managing complex systems. Aim: to analyse how variation related to patient conditions and adverse events affect resource utilisation and operational performance. Methods: Data pertaining to cardiac patients (cardiothoracic and cardiology, n=2241) were collected from two major hospitals in Oman. Factors influential to resource utilisation were assessed using logistic regressions. Other analysis related to classifying patients based on their resource utilisation was carried out using decision tree to assist in predicting hospital stay. Finally, discrete event simulation modelling was used to evaluate how patient factors and postoperative complications are affecting operational performance. Results: 26.5% of the patients experienced prolonged Length of Stay (LOS) in intensive care units and 30% in the ward. Patients with prolonged postoperative LOS had 60% of the total patient days. Some of the factors that explained the largest amount of variance in resource use following cardiac procedure included body mass index, type of surgery, Cardiopulmonary Bypass (CPB) use, non-elective surgery, number of complications, blood transfusion, chronic heart failure, and previous angioplasty. Allocating resources based on patient expected LOS has resulted in a reduction of surgery cancellations and waiting times while overall throughput has increased. Complications had a significant effect on perioperative operational performance such as surgery cancellations. The effect was profound when complications occurred in the intensive care unit where a limited capacity was observed. Based on the simulation model, eliminating some complications can enlarge patient population. Conclusion: Integrating influential factors into resource planning through simulation modelling is an effective way to estimate and manage hospital capacity.Open Acces

Effects of Incorporating Patient Acuity into the RN Assignment Process

As the largest sector of healthcare, nurses are the primary providers of patient care. By 2025, it is estimated that there will be a shortage of over 250,000 registered nurses (RNs) (American Association of Colleges of Nursing, 2011). Factors contributing to the nursing shortage include increased complexity of patients and decreased staffing that leads to decreased job satisfaction (Fox & Abrahamson, 2009). Over half of neonatal intensive care nurses reported missing at least one nursing task per shift when staffing was inadequate or patient acuity was high (TubbsCooley, Pickler, Younger, & Mark, 2015). The purpose of this evidence-based practice (EBP) project was to evaluate the effects of incorporating patient acuity into nursing assignments on nursing satisfaction and workload measures over a 3-month period. Kanter’s (1996) theory of structural empowerment and the Iowa model (2015) were used to guide the project on two medical units at a large pediatric hospital. Assignments for RNs were made by charge nurses who considered total patient acuity and each nurse’s proficiency level when making assignments. Nurses were surveyed using the Nurse Workload Satisfaction Questionnaire (NWSQ) pre- and post-implementation. In addition, two workload measures – pain reassessment within 30 minutes and medication given within 1 hour of scheduled time – were monitored throughout the study. Using paired t-tests, NWSQ scores showed a statistically significant increase in overall RN satisfaction. The mean pre-intervention NWSQ scores (M = 35.14, SD = 8.245) were compared to the mean post intervention NWSQ scores (M = 29.23, SD = 6.195, t = 2.833, p = .014). Other statistically significant improvements were found in the relational portion of the NWSQ, which gauges colleague relationships. There were no changes in the success rate of the two workload measures. Findings from this project support the incorporation of patient acuity into the nursing assignment process

Effects of Incorporating Patient Acuity into the RN Assignment Process

As the largest sector of healthcare, nurses are the primary providers of patient care. By 2025, it is estimated that there will be a shortage of over 250,000 registered nurses (RNs) (American Association of Colleges of Nursing, 2011). Factors contributing to the nursing shortage include increased complexity of patients and decreased staffing that leads to decreased job satisfaction (Fox & Abrahamson, 2009). Over half of neonatal intensive care nurses reported missing at least one nursing task per shift when staffing was inadequate or patient acuity was high (TubbsCooley, Pickler, Younger, & Mark, 2015). The purpose of this evidence-based practice (EBP) project was to evaluate the effects of incorporating patient acuity into nursing assignments on nursing satisfaction and workload measures over a 3-month period. Kanter’s (1996) theory of structural empowerment and the Iowa model (2015) were used to guide the project on two medical units at a large pediatric hospital. Assignments for RNs were made by charge nurses who considered total patient acuity and each nurse’s proficiency level when making assignments. Nurses were surveyed using the Nurse Workload Satisfaction Questionnaire (NWSQ) pre- and post-implementation. In addition, two workload measures – pain reassessment within 30 minutes and medication given within 1 hour of scheduled time – were monitored throughout the study. Using paired t-tests, NWSQ scores showed a statistically significant increase in overall RN satisfaction. The mean pre-intervention NWSQ scores (M = 35.14, SD = 8.245) were compared to the mean post intervention NWSQ scores (M = 29.23, SD = 6.195, t = 2.833, p = .014). Other statistically significant improvements were found in the relational portion of the NWSQ, which gauges colleague relationships. There were no changes in the success rate of the two workload measures. Findings from this project support the incorporation of patient acuity into the nursing assignment process

Triage Nursing Practice in Australian Emergency Departments 2002-2004: An Ethnography

This ethnographic study provides insight and understanding, which is needed to educate and support the Triage Nursing role in Australian Emergency Departments (EDs). The triage role has emerged to address issues in providing efficient emergency care. However, Triage Nurses and educators have found the role challenging and not well understood. Method: Sampling was done first by developing a profile of 900 nurses who undertake the triage role in 50 NSW EDs through survey techniques. Purposive sampling was then done with data collected from participant observation in four metropolitan EDs (Level 4 and 6), observations and interviews with 10 Triage Nurses and the maintenance of a record of secondary data sources. Analysis used standard content and thematic analysis techniques. Findings: An ED culture is reflected in a standard geography of care and embedded beliefs and rituals that sustain a cadence of care. Triage Nurses to accomplish their role and maintain this rhythm of care used three processes: gatekeeping, timekeeping and decision-making. When patient overcrowding occurred the three processes enabled Triage Nurses to implement a range of practices to restore the cadence of care to which they were culturally oriented. Conclusion: The findings provide a framework that offers new ways of considering triage nursing practice, educational programs, policy development and future research

Improving Nursing Staffing Methodology and Nursing Sensitive Outcomes with the Addition of a Patient Centered Acuity Measure

Background: Assigning the correct nursing resources to hospitalized patients positively impacts patient outcomes. The current process for matching nurses to patients is highly variable and involves a combination of simple ratios, historical workload data, and expert opinion but lacks objective measurement of the patient’s condition. Objectives: This project evaluated change in selected quality indicators and the daily unit-level management of nursing resources after implementing the Troubled Outcome Risk (TOR) into existing nursing staffing methodology in a Department of Veterans Affairs hospital. Methods: TOR provides objective measurement of individual patient allostatic load. Daily calculation of TOR scores for each patient on the study unit and nursing staffing methodology were used by charge nurses to determine assignments. Nursing sensitive indicators including length of stay, transfers to intensive care unit, hospital acquired pressure ulcer (HAPU), 30-day readmissions, and nursing surveillance indicators including rapid response team activation and cardiac arrests were compared before and after implementing TOR. Results: There was a reduction of HAPU rates that exceeded the stated goal after implementation of TOR. Other indicators did not meet project goals. Prior to implementation of TOR, nurse assignments clustered in specific locations; after implementation 16.7% were without regard to location. None of the results were statistically significant; yet we observed a small-medium effect size between intervention and assignment change. Conclusions: The implementation of TOR did not result in significant differences in nursing sensitive outcomes, however charge nurses appear to have changed staff nurse assignments using TOR as an addition to existing methodology. Future study with a larger sample over a longer period of time may yield different results

Emergency care workload units: A novel tool to compare emergency department activity

INTRODUCTION: Funding bodies have traditionally used attendance figures as a way of determining the allocation of funding for resources in the EDs. Using attendance figures only might not accurately reflect the funding and resources required. The need to create an easily implemented tool to compare workload and resources required was identified. Using the Australasian Triage Scale, a tool was developed to estimate staffing requirements and resource use within each ED. This, although currently not validated, provides a promising start in finding a way to accurately determine ED workload. METHODS: Existing data on patient acuity, disposition, numbers of patients and the individual costing of each presentation was used to estimate and define the workload of an ED in emergency care workload units (ECWU). The tool is applied to six de-identified hospitals within Queensland to demonstrate its potential use for equitable budget and staffing allocation. RESULTS: The tool was applied to a selection of de-identified EDs within Queensland hospitals. An increased number of ECWU is generated for a patient with a more urgent triage category reflecting a higher resource consumption and workload. DISCUSSION: Although a few studies have been completed in Canada linking workload, resource consumption and cost to triage category, this tool will need to be validated before its use can be fully appreciated. CONCLUSION: This tool provides a simple method to calculate equitable distribution of staffing and budget allocation based on workload across the different EDs within Australia.No Full Tex

Nurses and midwives perceptions of missed nursing care – A South Australian study

Author version made available in accordance with the publisher's policy for non-mandated open access submission. Under Elsevier's copyright, non-mandated authors are permitted to make work available in an institutional repository. NOTICE: this is the author’s version of a work that was accepted for publication in Collegian. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in COLLEGIAN, [2014] DOI:10.1016/ j.colegn.2014.09.001Background Budgetary restrictions and shorter hospital admission times have increased demands upon nursing time leading to nurses missing or rationing care. Previous research studies involving perceptions of missed care have predominantly occurred outside of Australia. This paper reports findings from the first South Australian study to explore missed nursing care. Aim To determine and explore nurses’ perceptions of reasons for missed care within the South Australian context and across a variety of healthcare settings. Method The survey was a collaborative venture between the Flinders University of South Australia, After Hours Nurse Staffing Work Intensity and Quality of Care project team and the Australian Nursing and Midwifery Federation, SA Branch. Electronic invitations using Survey Monkey were sent to randomly selected nurses and midwives and available online for two months. Three hundred and fifty four nurses and midwives responded. Recurring issues were identified from qualitative data within the survey and three main reasons for missed care emerged. Findings Three main reasons for missed care were determined as: competing demands that reduce time for patient care; ineffective methods for determining staffing levels; and skill mix including inadequate staff numbers. These broad issues represented respondents’ perceptions of missed care. Conclusion Issues around staffing levels, skill mix and the ability to predict workload play a major role in the delivery of care. This study identified the increasing work demands on nurses/midwifes. Solutions to the rationing of care need further exploration

A decision support system for surgery sequencing at UZ Leuven's day-care department.

In this paper, we test the applicability of a decision support system (DSS) that is developed to optimize the sequence of surgeries in the day-care center of the UZ Leuven Campus Gasthuisberg (Belgium). We introduce a multi-objective function in which children and prioritized patients are scheduled as early as possible on the day of surgery, recovery overtime is minimized and recovery workload is leveled throughout the day. This combinatorial optimization problem is solved by applying a pre-processed mixed integer linear programming model. We report on a 10-day case study to illustrate the performance of the DSS. In particular, we compare the schedules provided by the hospital with those that are suggested by the DSS. The results indicate that the DSS leads to both an increased probability of obtaining feasible schedules and an improved quality of the schedules in terms of the objective function value. We further highlight some of the major advantages of the application, such as its visualization and algorithmic performance, but also report on the difficulties that were encountered during the study and the shortcomings that currently delay its implementation in practice, as this information may contribute to the success rate of future software applications in hospitals.Decision support system; Optimization; Visualization; Health care application;