Rogers A

Bio: Rogers A is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.

Manual Handling Workload and Musculoskeletal Discomfort in Nursing Personnel

Abstract: iv Chapter 1: Introduction 1 Scope and Cost of Back Pain 2 Relationship of Musculoskeletal Pain to Workers’ Compensation Claims 3 Association with Strenuous Tasks 3 Chapter 2: Review of the Literature 6 Causes of Musculoskeletal Disorders 6 Body Parts Affected by WMSDs in Nursing 6 WMSD Risk Factors 6 Patient Handling and Movement Risk Factor Assessment 10 Patient Weight As Risk Factor 12 Assessing Risk 12 Exposure Assessment 16 Nursing Workload Measurement Systems 17 Risk Reduction Factors 19 Characteristics of James A. Haley VAMC High-Risk Patient Care Units 19 Screening for Musculoskeletal Disorders 20 Null Hypotheses 22 Definition of Terms 22 Chapter 3: Methods 27 Study Design 27 Sample and Sampling Procedures 27 Data Collection Procedures 28 Chapter 4: Results 30 Sample Size/Power Analysis 30 Data Analysis 30 Sample 30 Data Coding 32 Independent Variables 32

Triage codes: a predictor of nursing care time in the emergency department

Abstract: .....................................................................................................xi Chapter One Introduction .........................................................................1 Quality Patient Care..................................................................................2 Optimality .................................................................................................4 Benefits of Nursing to Patient Health.......................................................5 Cost of Nurse Staffing ..............................................................................8 Optimising Nurse Staffing......................................................................13 Summary.................................................................................................14 Chapter 2 Literature Review...................................................................15 Emergency Nursing Work ......................................................................16 Measuring Emergency Nurses Workload...............................................17 A Conceptual Framework for Nursing Work .........................................20 iii Patient Nursing Complexity................................................................24 Medical Condition and Severity .........................................................26 Nurse Characteristics .........................................................................35 Environmental Complexity .................................................................37 Summary.................................................................................................46 Chapter 3 Methods ...................................................................................49 Purpose ...................................................................................................49 Study Questions ......................................................................................49 Methodology...........................................................................................50 Study Design...........................................................................................51 Methods ..................................................................................................52 Setting .................................................................................................52 Sample ................................................................................................54 Variables of Interest ...........................................................................56 Procedure ...........................................................................................61 Ethical and Cultural Considerations .......................................................64 Data Management and Analysis .............................................................66 Summary.................................................................................................68 Chapter 4 Results......................................................................................69 Sampling.................................................................................................69 Sample Characteristics ...........................................................................70 Direct Nursing Care Time ......................................................................75 Associations with Direct Nursing Care Time.........................................77 Direct Nursing Care Time vs. Triage .................................................78

Nursing Unit Staffing: An Innovative Model Incorporating Patient Acuity and Patient Turnover: A Dissertation

Abstract: Changes in reimbursement make it imperative for nurse managers to develop tools and methods to assist them to stay within budget. Disparity between planned staffing and required staffing often requires supplemental staffing and overtime. In addition, many states are now mandating staffing committees to demonstrate effective staff planning. This retrospective quantitative study developed an empirical method for building nursing unit staffing plans through the incorporation of patient acuity and patient turnover as adjustments towards planning nursing workload. The theoretical framework used to guide this study was structural contingency theory (SCT). Patient turnover was measured by Unit Activity Index (UAI). Patient acuity was measured using case mix index (CMI). Nursing workload was measured as hours per patient day (HPPD). The adjustment to HPPD was made through the derivation of a weight factor based on UAI and CMI. The study consisted of fourteen medical, surgical, and mixed medical-surgical units within a large academic healthcare center. Data from 3 fiscal years were used. This study found that there were significant, but generally weak correlations between UAI and CMI and HPPD. The method of deriving a weight factor for adjusting HPPD was not as important as the decision-making relative to when to adjust planned HPPD. In addition, the measure of unit activity index was simplified which will assist researchers to more easily calculate patient turnover. As a result of this study, nurse managers and will be better able to adjust and predict HPPD in cases where benchmarking has been problematic. Data-driven adjustments to HPPD based on UAI and CMI will assist the nurse manager to plan and budget resources more effectively.

Nursing intensity and nurse staffing in perioperative settings

Abstract: Satu Rauta NURSING INTENSITY AND NURSE STAFFING IN PERIOPERATIVE SETTINGS University of Turku, Faculty of Medicine, Department of Nursing Science Annales Universitatis Turkuensis, Turku, 2018 The goal of this study was to design and test a nursing intensity (NI) instrument in perioperative settings to produce information concerning patients’ care needs. This information is intended to be used for knowledge-based management purposes when applying optimal nurse staffing. In Phase I, a Delphi method with two rounds (n=55) was used to define the core elements of perioperative nursing. Then those core elements were tested to evaluate NI during the pre-, intra-, and postoperative phases of the surgical patient’s care process (n=308 patients). In Phase II, the core elements were implemented in an instrument, and further testing was carried out in different perioperative settings (n=876 patients). In Phase III, an integrative review was conducted to find out how nurse staffing had been executed in perioperative settings. According to the results, the core elements of perioperative nursing describing patient’s safety or patient’s physiological needs were seen as the most crucial. A principal component analysis revealed that a patient’s care needs vary from the intraoperative to postoperative phases of perioperative nursing. Patients in a high ASA class more frequently had high intraoperative NI points, but patients in a low ASA class did not automatically have fewer intraoperative care needs. The length of stay in the post-anesthesia care unit (PACU) and the type of follow-up unit could be predicted with intraoperative NI. Scant evidence was found concerning nurse staffing in perioperative settings. The need to take into account patients’ care needs showed up in some papers, but these were not expressed in an assessable form. Staffing models in relation to perioperative nursing-sensitive outcomes were not found. This study offers an instrument for evaluating NI in perioperative settings. This information produced can be utilized for nurse staffing and nurse staff allocation purposes. More research is needed that focuses more on the detailed use of information based on NI. Its potential to serve as a knowledge-based management tool also needs clarifying in future studies.

The Hierarchical Condition Category Model - an Improved Comorbidity Adjustment Tool for Predicting Mortality in Medicare Populations?

Abstract: 14 INTRODUCTION 17 I. Explanation of the Problem 17 II. Aims and Hypothesis 22 III. Role of the Author in Research 27 IV. Dissertation Format 27 V. Review of the Literature 28 A. The Need for Risk Adjustment of Comorbidity 29 B. Confounding by Indication as Confounding by Comorbidity 30 C. Comorbidity and Cancer 30 D. Comorbidity and Ischemic Heart Disease 32 E. Comorbidity and All-Cause Mortality 33 F. Comorbidity Models 33 G. Measuring the Validity of a Comorbidity Model 34