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Patient Ratio (patient + ratio)
Selected AbstractsEffect of Mandated Nurse,Patient Ratios on Patient Wait Time and Care Time in the Emergency DepartmentACADEMIC EMERGENCY MEDICINE, Issue 5 2010Theodore C. Chan MD Abstract Objectives:, The objective was to evaluate the effect of mandated nurse,patient ratios (NPRs) on emergency department (ED) patient flow. Methods:, Two institutions implemented an electronic tracking system embedded within the electronic medical record (EMR) of two EDs (an academic urban, teaching medical center,Hospital A; and a suburban community hospital,Hospital B), with a combined census of 60,000/year, to monitor real-time NPRs and patient acuity, such that compliance with state-mandated ratios could be prospectively monitored. Data were queried for a 1-year period after implementation and included patient wait times (WTs), ED care time (EDCT), patient acuity, ED census, and NPR status for each nurse, patient, and the ED overall. Median WT and EDCT with interquartile ranges (IQRs) were analyzed to determine the effect of NPR status of each patient, nurse, and the ED overall. To control for factors that could affect the "within the mandated ratio" and the "outside of the mandated ratio" status, including patient volume and acuity, log-linear regression models were used controlling for specified factors for each hospital facility and combined. Results:, There were a total of 30,404 (50.9%) patients who waited in the waiting room prior to being placed in an ED bed (53.8% at Hospital A and 46.4% at Hospital B). Patients who waited at Hospital A waited a median duration of 55 minutes (IQR = 15,128 minutes), compared with 32 minutes (IQR = 12,67 minutes) at Hospital B with a combined median WT of 44 minutes (IQR = 13,101 minutes). In the log-linear regression analysis, WTs were 17% (95% confidence interval [CI] = 10% to 25%, p < 0.001) longer at Hospital A and 13% (95% CI = 3% to 24%, p = 0.008) longer at Hospital B (combined 16% [95% CI = 10% to 22%, p < 0.001] longer at both sites) when the ED overall was out-of-ratio compared to in-ratio. There were a total of 45,660 patients discharged from both EDs during the study period, from which EDCT data were collected (26,894 in Hospital A and 18,766 in Hospital B). Median EDCT was 184 minutes (IQR = 97,311 minutes) at Hospital A, compared to 120 minutes (IQR = 63,208 minutes) at Hospital B, for a combined median EDCT of 153 minutes (IQR = 81,269 minutes). In the log-linear regression analysis, the EDCT for patients whose nurse was out-of-ratio were 34% (95% CI = 30% to 38%, p < 0.001) longer at Hospital A and 42% (95% CI = 37% to 48%, p < 0.001) longer at Hospital B (combined 37% [95% CI = 34% to 41%, p < 0.001] longer at both sites) when compared to patients whose nurse was in-ratio. Conclusions:, In these two EDs, throughput measures of WT and EDCT were shorter when the ED nurse staffing were within state-mandated levels, after controlling for ED census and patient acuity. ACADEMIC EMERGENCY MEDICINE 2010; 17:545,552 © 2010 by the Society for Academic Emergency Medicine [source] THE AUSTRALIAN AND NEW ZEALAND DIALYSIS WORKFORCE STUDY IN THE INTERNATIONAL CONTEXTJOURNAL OF RENAL CARE, Issue 4 2009Nick Polaschek RN SUMMARY Background: Given increasing demand for renal replacement therapy, this study sought to identify of key workforce issues facing dialysis units, based on a "snapshot" of the current workforce. Methods: A web-based survey of all dialysis unit managers in Australia and New Zealand, in October 2008, about their workforce. Results: A significant minority of dialysis staff in most regions were not registered nurses. Many renal registered nurses worked part-time. Staff/patient ratios in dialysis units varied significantly by region, reflecting the relative prevalence of home therapies. Most dialysis units were generally adequately staffed. The proportion of registered nurses with specific renal qualifications varied significantly by region. Conclusion: The changing character of the workforce in the dialysis unit in the future will require clarification of the relationships between different categories of dialysis staff. Specialty education for nurses needs to be oriented to equipping staff to be effective in their changing work environment. [source] Assessing patient category/dependence systems for determining the nurse/patient ratio in ICU and HDU: a review of approachesJOURNAL OF NURSING MANAGEMENT, Issue 5 2004PG Dip., Renee Adomat BA (Hons) Background, A huge range of patient classification systems/tools are used in critical care units to inform workforce planning, however, they are not always applied appropriately. Many of these systems/tools were not originally developed for the purposes of workforce planning and so their use in determining the nurse:patient ratio required in critical care settings raises a number of issues for the organisation and management of these services. Aim, The aim of this paper is to review the three main assessment systems that are commonly used in critical care settings in the UK and evaluate their effectiveness in accurately determining nurse : patient ratios. If the application of these systems/tools is to enhance care, a thorough understanding of their origins and purpose is necessary. If this is lacking, then decisions relating to workload planning, particularly when calculating nurse : patient ratios, may be flawed. Conclusions, Patient dependency/classification systems and patient dependency scoring systems for severity of illness are robust measures for predicting morbidity and mortality. However, they are not accurate if used to calculate nurse : patient ratios because they are not designed to measure nursing input. Nursing intensity measures provide a useful framework for calculating the cost of providing a nursing service in critical care and can serve as a measure of nursing input, albeit a fairly basic one. However, many components of the nursing role are not ,accounted' for in these measures. Implications, The implications of these findings for the organization and management of critical care services are discussed. Careful consideration of these areas is vital if a cost efficient and cost-effective critical care service is to be delivered. [source] Evidence-based human resource management: a study of nurse leaders' resource allocationJOURNAL OF NURSING MANAGEMENT, Issue 4 2009LISBETH FAGERSTRÖM RN Aims, The aims were to illustrate how the RAFAELA system can be used to facilitate evidence-based human resource management. Background, The theoretical framework of the RAFAELA system is based on a holistic view of humankind and a view of leadership founded on human resource management. Methods, Nine wards from three central hospitals in Finland participated in the study. The data, stemming from 2006,2007, were taken from the critical indicators (ward-related and nursing intensity information) for national benchmarking used in the RAFAELA system. The data were analysed descriptively. Results, The daily nursing resources per classified patient ratio is a more specific method of measurement than the nurse-to-patient ratio. For four wards, the nursing intensity per nurse surpassed the optimal level 34% to 62.2% of days. Resource allocation was clearly improved in that a better balance between patients' care needs and available nursing resources was maintained. Conclusions, The RAFAELA system provides a rational, systematic and objective foundation for evidence-based human resource management. Implications for nursing management, Data from a systematic use of the RAFAELA system offer objective facts and motives for evidence-based decision making in human resource management, and will therefore enhance the nurse leaders' evidence and scientific based way of working. [source] Assessing patient category/dependence systems for determining the nurse/patient ratio in ICU and HDU: a review of approachesJOURNAL OF NURSING MANAGEMENT, Issue 5 2004PG Dip., Renee Adomat BA (Hons) Background, A huge range of patient classification systems/tools are used in critical care units to inform workforce planning, however, they are not always applied appropriately. Many of these systems/tools were not originally developed for the purposes of workforce planning and so their use in determining the nurse:patient ratio required in critical care settings raises a number of issues for the organisation and management of these services. Aim, The aim of this paper is to review the three main assessment systems that are commonly used in critical care settings in the UK and evaluate their effectiveness in accurately determining nurse : patient ratios. If the application of these systems/tools is to enhance care, a thorough understanding of their origins and purpose is necessary. If this is lacking, then decisions relating to workload planning, particularly when calculating nurse : patient ratios, may be flawed. Conclusions, Patient dependency/classification systems and patient dependency scoring systems for severity of illness are robust measures for predicting morbidity and mortality. However, they are not accurate if used to calculate nurse : patient ratios because they are not designed to measure nursing input. Nursing intensity measures provide a useful framework for calculating the cost of providing a nursing service in critical care and can serve as a measure of nursing input, albeit a fairly basic one. However, many components of the nursing role are not ,accounted' for in these measures. Implications, The implications of these findings for the organization and management of critical care services are discussed. Careful consideration of these areas is vital if a cost efficient and cost-effective critical care service is to be delivered. [source] Effect of Mandated Nurse,Patient Ratios on Patient Wait Time and Care Time in the Emergency DepartmentACADEMIC EMERGENCY MEDICINE, Issue 5 2010Theodore C. Chan MD Abstract Objectives:, The objective was to evaluate the effect of mandated nurse,patient ratios (NPRs) on emergency department (ED) patient flow. Methods:, Two institutions implemented an electronic tracking system embedded within the electronic medical record (EMR) of two EDs (an academic urban, teaching medical center,Hospital A; and a suburban community hospital,Hospital B), with a combined census of 60,000/year, to monitor real-time NPRs and patient acuity, such that compliance with state-mandated ratios could be prospectively monitored. Data were queried for a 1-year period after implementation and included patient wait times (WTs), ED care time (EDCT), patient acuity, ED census, and NPR status for each nurse, patient, and the ED overall. Median WT and EDCT with interquartile ranges (IQRs) were analyzed to determine the effect of NPR status of each patient, nurse, and the ED overall. To control for factors that could affect the "within the mandated ratio" and the "outside of the mandated ratio" status, including patient volume and acuity, log-linear regression models were used controlling for specified factors for each hospital facility and combined. Results:, There were a total of 30,404 (50.9%) patients who waited in the waiting room prior to being placed in an ED bed (53.8% at Hospital A and 46.4% at Hospital B). Patients who waited at Hospital A waited a median duration of 55 minutes (IQR = 15,128 minutes), compared with 32 minutes (IQR = 12,67 minutes) at Hospital B with a combined median WT of 44 minutes (IQR = 13,101 minutes). In the log-linear regression analysis, WTs were 17% (95% confidence interval [CI] = 10% to 25%, p < 0.001) longer at Hospital A and 13% (95% CI = 3% to 24%, p = 0.008) longer at Hospital B (combined 16% [95% CI = 10% to 22%, p < 0.001] longer at both sites) when the ED overall was out-of-ratio compared to in-ratio. There were a total of 45,660 patients discharged from both EDs during the study period, from which EDCT data were collected (26,894 in Hospital A and 18,766 in Hospital B). Median EDCT was 184 minutes (IQR = 97,311 minutes) at Hospital A, compared to 120 minutes (IQR = 63,208 minutes) at Hospital B, for a combined median EDCT of 153 minutes (IQR = 81,269 minutes). In the log-linear regression analysis, the EDCT for patients whose nurse was out-of-ratio were 34% (95% CI = 30% to 38%, p < 0.001) longer at Hospital A and 42% (95% CI = 37% to 48%, p < 0.001) longer at Hospital B (combined 37% [95% CI = 34% to 41%, p < 0.001] longer at both sites) when compared to patients whose nurse was in-ratio. Conclusions:, In these two EDs, throughput measures of WT and EDCT were shorter when the ED nurse staffing were within state-mandated levels, after controlling for ED census and patient acuity. ACADEMIC EMERGENCY MEDICINE 2010; 17:545,552 © 2010 by the Society for Academic Emergency Medicine [source] Assessing patient category/dependence systems for determining the nurse/patient ratio in ICU and HDU: a review of approachesJOURNAL OF NURSING MANAGEMENT, Issue 5 2004PG Dip., Renee Adomat BA (Hons) Background, A huge range of patient classification systems/tools are used in critical care units to inform workforce planning, however, they are not always applied appropriately. Many of these systems/tools were not originally developed for the purposes of workforce planning and so their use in determining the nurse:patient ratio required in critical care settings raises a number of issues for the organisation and management of these services. Aim, The aim of this paper is to review the three main assessment systems that are commonly used in critical care settings in the UK and evaluate their effectiveness in accurately determining nurse : patient ratios. If the application of these systems/tools is to enhance care, a thorough understanding of their origins and purpose is necessary. If this is lacking, then decisions relating to workload planning, particularly when calculating nurse : patient ratios, may be flawed. Conclusions, Patient dependency/classification systems and patient dependency scoring systems for severity of illness are robust measures for predicting morbidity and mortality. However, they are not accurate if used to calculate nurse : patient ratios because they are not designed to measure nursing input. Nursing intensity measures provide a useful framework for calculating the cost of providing a nursing service in critical care and can serve as a measure of nursing input, albeit a fairly basic one. However, many components of the nursing role are not ,accounted' for in these measures. Implications, The implications of these findings for the organization and management of critical care services are discussed. Careful consideration of these areas is vital if a cost efficient and cost-effective critical care service is to be delivered. [source] | ||||||||||