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Nguyen, Abby. "Acuity-based staffing." Nursing Management (Springhouse) 46, no. 1 (January 2015): 35–39. http://dx.doi.org/10.1097/01.numa.0000459555.94452.e2.
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Dent, Robert L., and Pamela Bradshaw. "Building the Business Case for Acuity-Based Staffing." Nurse Leader 10, no. 2 (April 2012): 26–28. http://dx.doi.org/10.1016/j.mnl.2011.12.008.
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Barton, Nancy. "Acuity-Based Staffing: Balance Cost, Satisfaction, Quality, and Outcomes." Nurse Leader 11, no. 6 (December 2013): 47–64. http://dx.doi.org/10.1016/j.mnl.2013.08.005.
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Harrington, Charlene, Mary Ellen Dellefield, Elizabeth Halifax, Mary Louise Fleming, and Debra Bakerjian. "Appropriate Nurse Staffing Levels for U.S. Nursing Homes." Health Services Insights 13 (January 2020): 117863292093478. http://dx.doi.org/10.1177/1178632920934785.
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US nursing homes are required to have sufficient nursing staff with the appropriate competencies to assure resident safety and attain or maintain the highest practicable level of physical, mental, and psychosocial well-being of each resident. Minimum nurse staffing levels have been identified in research studies and recommended by experts. Beyond the minimum levels, nursing homes must take into account the resident acuity to assure they have adequate staffing levels to meet the needs of residents. This paper presents a guide for determining whether a nursing home has adequate and appropriate nurse staffing. We propose five basic steps to: (1) determine the collective resident acuity and care needs, (2) determine the actual nurse staffing levels, (3) identify appropriate nurse staffing levels to meet residents care needs, (4) examine evidence regarding the adequacy of staffing, and (5) identify gaps between the actual staffing and the appropriate nursing staffing levels based on resident acuity. Data sources and specific methodologies are analyzed, compared, and recommended. The goal is to assist nursing home nurses and administrators to ensure adequate nursing home staffing levels that protect resident health, safety, and well-being.
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Sobaski, Tanya. "Addressing Patient Acuity and Nurse Staffing Issues in the Acute Care Setting: A Review of the Literature." International Journal of Studies in Nursing 3, no. 3 (July 30, 2018): 1. http://dx.doi.org/10.20849/ijsn.v3i3.431.
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Background: Many times there is a misalignment on medical-surgical units nursing assignments that do not provide equitable distribution of the patient needs for the unit.Purpose: The purpose of the literature review was to identify resources that address patient acuity and nurse staffing issues in the acute care setting.Method: A literature review using the EBSCOhost health search engine, which included databases from Cumulative Index to Nursing and Allied Health Literature (CINAHL), Google Scholar, and ProQuest.Results: The future of nursing is moving toward staffing based on patient acuity. Chiulli, Thompson, and Reguin-Hartman (2014) developed an acuity tool because it was discovered that there was no appropriate “assessment tool…for [the] medical-surgical patient population” (p. 10). However, nurses are not guaranteed adequate staffing based on acuity regardless of what is determined by use of the tool. Recommended is that further studies need to be conducted using the Chiulli et al. tool.
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Fullam, Charlene. "Acuity-based ED nurse staffing: A successful 5-year experience." Journal of Emergency Nursing 28, no. 2 (April 2002): 138–40. http://dx.doi.org/10.1067/men.2002.122219.
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Vortherms, Jane, Brenda Spoden, and Jill Wilcken. "From Evidence to Practice: Developing an Outpatient Acuity-Based Staffing Model." Clinical Journal of Oncology Nursing 19, no. 3 (June 1, 2015): 332–37. http://dx.doi.org/10.1188/15.cjon.332-337.
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Redfern, Oliver C., Peter Griffiths, Antonello Maruotti, Alejandra Recio Saucedo, and Gary B. Smith. "The association between nurse staffing levels and the timeliness of vital signs monitoring: a retrospective observational study in the UK." BMJ Open 9, no. 9 (September 2019): e032157. http://dx.doi.org/10.1136/bmjopen-2019-032157.
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ObjectivesOmissions and delays in delivering nursing care are widely reported consequences of staffing shortages, with potentially serious impacts on patients. However, studies so far have relied almost exclusively on nurse self-reporting. Monitoring vital signs is a key part of nursing work and electronic recording provides an opportunity to objectively measure delays in care. This study aimed to determine the association between registered nurse (RN) and nursing assistant (NA) staffing levels and adherence to a vital signs monitoring protocol.DesignRetrospective observational study.Setting32 medical and surgical wards in an acute general hospital in England.Participants538 238 nursing shifts taken over 30 982 ward days.Primary and secondary outcome measuresVital signs observations were scheduled according to a protocol based on the National Early Warning Score (NEWS). The primary outcome was the daily rate of missed vital signs (overdue by ≥67% of the expected time to next observation). The secondary outcome was the daily rate of late vital signs observations (overdue by ≥33%). We undertook subgroup analysis by stratifying observations into low, medium and high acuity using NEWS.ResultsLate and missed observations were frequent, particularly in high acuity patients (median=44%). Higher levels of RN staffing, measured in hours per patient per day (HPPD), were associated with a lower rate of missed observations in all (IRR 0.983, 95% CI 0.979 to 0.987) and high acuity patients (0.982, 95% CI 0.972 to 0.992). However, levels of NA staffing were only associated with the daily rate (0.954, CI 0.949 to 0.958) of all missed observations.ConclusionsAdherence to vital signs monitoring protocols is sensitive to levels of nurse and NA staffing, although high acuity observations appeared unaffected by levels of NAs. We demonstrate that objectively measured omissions in care are related to nurse staffing levels, although the absolute effects are small.Study registrationThe data and analyses presented here were part of the larger Missed Care study (ISRCTN registration: 17930973).
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Weber, Shani Michelle, and Cheryl A. Steele. "Prospectively measuring the acuity of outpatient chemotherapy treatment regimens for staffing allocation." Journal of Clinical Oncology 34, no. 7_suppl (March 1, 2016): 48. http://dx.doi.org/10.1200/jco.2016.34.7_suppl.48.
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48 Background: UPMC CancerCenter is a large outpatient medical oncology network of 25 locations, located within a 200 mile radius of Pittsburgh, PA. Covering all of these centers with a limited pool of float nurses was a daily challenge. The literature describes many attempts to quantify nursing workload retrospectively based upon complexity, hours of nursing time, etc. The ability to schedule staff equitability in advance is critical to managing staff. New targeted therapies and complicated treatment regimens which impact patient acuity bring to light the need for accurate acuity measurement. Methods: The first step in designing an acuity model was to determine the level of complexity of each treatment regimen based on standardized criteria. The model is a five point system encompassing route, teaching, reaction potential, etc. designed by frontline nurses. A designated nurse at each site calculates the acuity and enters it into an online system prospectively. Nursing Administration can view the staffing and acuity rating across the entire network. This enables the assignment of float nurses to the location with the greatest need. Results: A stoplight report using the database was developed to highlight the sites that are outside of 0.5 standard deviation (SD) range for both the acuity and patient ratios. It was determined that the average nurse to acuity ratio was 11.92 (within SD range 10.69-13.16). The average nurse to patient ratio was 6.31 (within SD range 5.6-7.03). This enables Nursing Administration to identify sites that typically operate below or above the average range in order to better allocate nursing resources. This report is shared among all sites to provide transparency which has improved understanding by the staff of nursing resource allocation. Conclusions: The development of this prospective acuity system has helped to quantify treatment complexity to better allocate daily staffing resources. Further evaluation is necessary to determine the optimal ratios that are the most economical while still providing safe patient care. There are future plans to link the acuity levels to treatment regimens within the Electronic Medical Record to reduce the manual workload.
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Brennan, Caitlin W., Frank Meng, Mark M. Meterko, and Leonard W. D’Avolio. "Feasibility of Automating Patient Acuity Measurement Using a Machine Learning Algorithm." Journal of Nursing Measurement 24, no. 3 (2016): 419–27. http://dx.doi.org/10.1891/1061-3749.24.3.419.
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Background and Purpose: One method of determining nurse staffing is to match patient demand for nursing care (patient acuity) with available nursing staff. This pilot study explored the feasibility of automating acuity measurement using a machine learning algorithm. Methods: Natural language processing combined with a machine learning algorithm was used to predict acuity levels based on electronic health record data. Results: The algorithm was able to predict acuity relatively well. A main challenge was discordance among nurse raters of acuity in generating a gold standard of acuity before applying the machine learning algorithm. Conclusions: This pilot study tested applying machine learning techniques to acuity measurement and yielded a moderate level of performance. Higher agreement among the gold standard may yield higher performance in future studies.
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Ricards, June E. "Proactive evaluation of staffing patterns supports need for extra staff based on patient acuity." AORN Journal 42, no. 1 (July 1985): 100–104. http://dx.doi.org/10.1016/s0001-2092(07)65018-2.
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DeRienzo, Christopher M., Ryan J. Shaw, Phillip Meanor, Emily Lada, Jeffrey Ferranti, and David Tanaka. "A discrete event simulation tool to support and predict hospital and clinic staffing." Health Informatics Journal 23, no. 2 (February 29, 2016): 124–33. http://dx.doi.org/10.1177/1460458216628314.
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We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit’s staffing, referral patterns, or patient mix would affect a unit in a future state.
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Gross, Jan C., Elizabeth A. Faulkner, Stacey W. Goodrich, and Mary E. Kain. "A Patient Acuity and Staffing Tool for Stroke Rehabilitation Inpatients Based on the FIM™ Instrument." Rehabilitation Nursing 26, no. 3 (May 6, 2001): 108–13. http://dx.doi.org/10.1002/j.2048-7940.2001.tb02214.x.
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Young, Judith, Mikyoung Lee, Laura Prouty Sands, and Sara McComb. "Nursing activities and factors influential to nurse staffing decision-making." Journal of Hospital Administration 4, no. 4 (May 6, 2015): 24. http://dx.doi.org/10.5430/jha.v4n4p24.
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Objective: There is limited published research supporting the effectiveness of nursing workload measurement to comprehensively measure nursing workload and to formulate nurse resource need. Predictive accuracy is impaired due to variation in direct and indirect care-related activities across measurement instruments. This study aimed to (1) identify common nursing activities considered by nurse managers for staffing decision-making, (2) systematically review such nursing activities in relation to existing nursing workload instruments and Nursing Intervention Classification taxonomy, and (3) describe challenges perceived by managers in staffing decision-making.Methods: A survey was developed from an inclusive review of 20 nursing workload instruments collectively measuring 502 nursing activities. Nurse managers in 13 medical-surgical and two intensive care units at a Midwest healthcare organization identified nursing activities considered daily for staffing decision-making.Results: Twenty-one activities were commonly considered by at least 90 percent of managers (n = 13) for daily staffing decisionmaking, although none of the instruments reviewed included all 21 activities.Conclusions: Lack of a standardized framework for nursing workload measurement might have led to nurse managers’ different perceptions about appropriate determinants of these measurements. A standardized approach for measuring nursing workload would facilitate benchmarking for estimating nurse resource need. Further research is needed to design a systematic infrastructure that ensures staffing to meet patient care need. A process is also needed to alleviate the challenges in staffing decision-making that nurse managers face, such as fluctuations in census and patient acuity, nurse competency-based patient assignments, and limited information resources for staffing estimation.
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Shah, Hirsh, Shelley A. Knowlson, Audrey Roberson, Emily Godbout, Michael Stevens, Gonzalo Bearman, and Michelle Elizabeth Doll. "Changes in Nursing Team Composition and Risk of Device Associated Infection in Intensive Care Units." Infection Control & Hospital Epidemiology 41, S1 (October 2020): s465. http://dx.doi.org/10.1017/ice.2020.1139.
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Background: The relationship between nursing staffing and healthcare-associated infections (HAIs) has been explored previously, with conflicting results. Intensive care units increasingly struggle to maintain trained staff. In May 2019, clinical coordinator (CC) roles changed to include 50% of time in direct patient care rather than supportive roles. In this study, we used shift records to explore the impact of staffing on HAI risk. Methods: Daily staffing records from December 2018 August 2019 for the medical-respiratory unit (MRICU) and the cardiac surgery unit (CSICU) were reviewed. Both units staff a fixed 2:1 patient:nurse ratio (1:1 for specific cardiac surgeries). Staff deficiency was defined as assignments filled by nurses pulled from other units/supplemental/or CC roles. Staff support comprised nursing assistants and unit secretaries. Census, admissions, and complexity score for number of devices were used to estimate care acuity. In CSICU, additional points were added for continuous renal replacement therapy, extracorporeal membrane oxygenation, ventricular assist devices, transplant, operative cases. NHSN definitions were used for central-line–associated bloodstream infections (CLABSIs) and catheter-associated urinary tract infections (CAUTIs). The Spearman correlation coefficient was used to determine relationship between staffing, acuity, and risk window for HAI (days 1–10 preinfection). Linear regression was used to determine whether staffing deficiencies and/or support associate with the risk window prior to HAI. The final model included census and complexity score as control variables. The statistical analysis was performed using SAS version 9.4 software (Cary, NC). Results: Overall, 8 HAIs occurred in the study period: medical-respiratory intensive care unit (MRICU: 3 CAUTIs and 1 CLABSI) and cardiac surgery intensive care unit (CSICU: 1 CAUTI and 3 CLABSIs). Staffing and census fluctuated daily (Table 1). Total number of nurses correlated with complexity scores (r = 0.35; P < .0001) and daily census (r = 0.31; P < .0001) in the CSICU, and the census (r = 0.12; P = .04) in the MRICU. Nursing deficiencies correlated with days 1–10 before infection (r = 0.20; P = .0013) in the CSICU. In the regression model for the CSICU, nursing deficiencies increased in the time prior to HAI (P = .004), and support staff decreased in the time prior to HAI (P = .034) while controlling for census and complexity. These relationships were not significant in the MRICU. Conclusion: The lack of core nurses to support the staffing structure in CSICU correlated with periods prior to CLABSI or CAUTI in this small, unit-based study. Failure to recruit and retain highly skilled core staff may produce HAI risks, particularly for CLABSI in specialized units.Funding: NoneDisclosures: Michelle Doll, Research Grant from Molnlycke Healthcare
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Brennan, Caitlin W., Michael Krumlauf, Kathryn Feigenbaum, Kyungsook Gartrell, and Georgie Cusack. "Patient Acuity Related to Clinical Research: Concept Clarification and Literature Review." Western Journal of Nursing Research 41, no. 9 (October 14, 2018): 1306–31. http://dx.doi.org/10.1177/0193945918804545.
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In research settings, clinical and research requirements contribute to nursing workload, staffing decisions, and resource allocation. The aim of this article is to define patient acuity in the context of clinical research, or research intensity, and report available instruments to measure it. The design was based on Centre for Reviews and Dissemination recommendations, including defining search terms, developing inclusion and exclusion criteria, followed by abstract review by three members of the team, thorough reading of each article by two team members, and data extraction procedures, including a quality appraisal of each article. Few instruments were available to measure research intensity. Findings provide foundational work for conceptual clarity and tool development, both of which are necessary before workforce allocation based on research intensity can occur.
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Sobaski, Tanya, Karen Allen, and Samuel P. Abraham. "The Results of Implementation of an Acuity Tool to Decrease the Number of Resuscitation Events on an Orthopedic-Neurology Unit." International Journal of Studies in Nursing 4, no. 1 (January 7, 2019): 1. http://dx.doi.org/10.20849/ijsn.v4i1.535.
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Background: Patients on medical-surgical units such as orthopedic-neurology are vulnerable for delayed recognition of physiological deterioration. Therefore, they are at increased risk of incurring a resuscitation event. Volume-based nurse staffing does not consider the necessity of nursing care that is individualized to the patient needs. Purpose: The purpose of this study was to implement an acuity tool to evaluate the number of resuscitation event occurrences on an Orthopedic-Neurology Unit. Method: A quasi-experimental, non-randomized, quality improvement project was implemented on a 32-bed Orthopedic/Neurology Unit over a three-month period, comparing resuscitation event occurrences with the use of the acuity tool and the group’s performance without the acuity tool. Analysis: For data analysis, a Chi-square test-for-independence was used with a 2x2 contingency table, for variance of the number of patient resuscitation event occurrences with and without the use of the tool. Data were examined and combined for the three months before and after the use of the tool. When compared to the three months that the tool was employed, it yielded a 1% difference, with a 33% relative risk reduction. Results: Results indicated support for clinical significance. The use of the acuity tool demonstrated a significant decrease in the number of occurrences from 9 to 2 to 0 for each successive month of the project on the Orthopedic/Neurology Unit.
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Rodgers, Georgina T. "Development of an infusion nurse staffing model for outpatient chemotherapy centers." Journal of Clinical Oncology 34, no. 7_suppl (March 1, 2016): 103. http://dx.doi.org/10.1200/jco.2016.34.7_suppl.103.
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103 Background: Nursing roles and responsibilities within ambulatory oncology infusion suites across our health system are not clearly defined and it is not understood what the appropriate staffing ratio should be per site. It is not clear if employees are working to the highest level of their licensure or skill, and if the appropriate activities are performed by the correct department. A standard staffing model to provide efficiency of clinical services and patient safety does not exist, and nursing roles are variable between the sites. Similar patient populations are being treated at each site and the variability of the roles introduces unnecessary costs to the system as a whole. The purpose of this project was to define roles of the infusion nurse to insure performance to the highest level of licensure, create efficiencies within the clinical setting, potentially reduce RN staffing requirements, achieve a cost savings, and develop a target nurse to patient ratio while maintaining quality care. Methods: Daily patient volume and hours of operation were compiled for each outpatient site and three methodologies were used to determine nurse to patient ratio. We utilized an acuity based ratio tool, hours per unit (HPU) method using billed charges for technical procedures and finally a simple 1:6 ratio based upon patient volume. Each methodology showed similar results and a final target ratio of 1:6 was chosen. Results: A staffing template was created to predict the number of RN’s necessary for treatment and an analysis of infusion sites was also completed to observe workflows and determine potential staffing adjustments. Our pilot site was initially staffed with 14 RN FTE’s and analysis showed many non-clinical, non-nursing duties were being performed by RN’s. Through process improvement we have created clear role delineation and the site currently functions with 5 RN FTE’s. We have maximized the efficiency of the nursing team, reduced costs, and there has been no decline or compromise in quality or patient safety. Conclusions: The implications of establishing this standard for infusion nursing has allowed us to duplicate the methodology across the health system and achieve a level of staffing that matches well with patient care needs.
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Shukla, Ramesh K. "Factors and Perspectives Affecting Nursing Resource Consumption in Community Hospitals." Health Services Management Research 5, no. 3 (November 1992): 174–85. http://dx.doi.org/10.1177/095148489200500302.
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The consumption of professional and non-professional nursing resources on medical/surgical nursing units varies sharply among community hospitals. In an effort to explain the variation, this study examines several factors: socio-economic characteristics of the population; supply of registered nurses; hospital characteristics such as size, complexity and diversity of services; patient characteristics such as case mix index and nursing care acuity index; and production system characteristics such as efficiency of technical support systems and the structure of nursing care delivery. Nursing skill mix varies more than the staffing levels among hospitals. The research suggests that factors associated with a clinical-rational model such as nursing acuity index and the efficiency of clinical/support systems explains little, whereas factors associated with economic-rational model of hospital revenues – like case mix, number of hospital services, poverty (through Medicaid program) and age distribution (through Medicare program) – do significantly affect nursing resource consumption. The results point to the presence of resource allocation to nursing based on hospital revenues rather than patient care needs.
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Brugler, L., and L. Bernstein. "An Acuity Based Clinical Nutrition Staffing Model Improves Acute Care Clinical Effectiveness and Maintains Program Viability in a Managed Care Environment." Journal of the American Dietetic Association 98, no. 9 (September 1998): A23. http://dx.doi.org/10.1016/s0002-8223(98)00384-8.
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Garth, Alyssa, Susan Schreiner, and Dawn Jourdan. "Operational efficiencies in the infusion center: Improving nursing efficiencies and patient wait times while decreasing costs." Journal of Clinical Oncology 31, no. 31_suppl (November 1, 2013): 56. http://dx.doi.org/10.1200/jco.2013.31.31_suppl.56.
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56 Background: Decreased nursing efficiency and patient assignments has increased patient wait times and has significant implications on overall patient flow in the infusion center and labor dollars. Historically, staff nurses signed up for their patients, and took an average of 2 patients at one time. This created disparity in patient/staffing ratios, high number of labor dollars per worked infusion and an overall atmosphere of inequity among the nurses. Methods: Patient flow and labor cost were examined. Analysis of the nursing staffing matrix led to the creation of a patient placement nurse, taken from the daily staff allocation, assigning patients based on current patient assignment and acuity of patients. Nurses were identified to learn the patient placement nurse role based on critical thinking and organizational skills. With the assistance of a patient locator system, the patient placement nurse is able to identify when a patient’s wait begins and which nurse is the best choice to be assigned. A system was implemented in which a staff nurse was assigned a patient every 30-40 minutes with a maximum patient assignment of 4 concurrently. A standard 1:3 nurse to patient ratio was established unless a patient’s acuity prohibited this ratio. Results: Nursing ratios stabilized at 1:3. Staff became more efficient and work was reorganized for less subjectivity in patient assignments, producing more equitable workloads. This resulted in an increase in patients seen within 15 minutes improving from 69.8% to 85.3%. In addition, it allowed for the elimination of one nurse per day shift, resulting in a cost savings of approximately a 1.0 FTE/week or average annual salary of $62,129. Conclusions: Development of a standardized patient placement process can increase infusion center efficiencies and stabilize nursing workload, as well as decrease patient wait time and reduce the cost per infusion. This supports a delivery of patient-centered care while utilizing staff efficiently and appropriately and decreasing cost.
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Griffiths, Peter, Christina Saville, Jane E. Ball, Rosemary Chable, Andrew Dimech, Jeremy Jones, Yvonne Jeffrey, et al. "The Safer Nursing Care Tool as a guide to nurse staffing requirements on hospital wards: observational and modelling study." Health Services and Delivery Research 8, no. 16 (March 2020): 1–162. http://dx.doi.org/10.3310/hsdr08160.
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Background The Safer Nursing Care Tool is a system designed to guide decisions about nurse staffing requirements on hospital wards, in particular the number of nurses to employ (establishment). The Safer Nursing Care Tool is widely used in English hospitals but there is a lack of evidence about how effective and cost-effective nurse staffing tools are at providing the staffing levels needed for safe and quality patient care. Objectives To determine whether or not the Safer Nursing Care Tool corresponds to professional judgement, to assess a range of options for using the Safer Nursing Care Tool and to model the costs and consequences of various ward staffing policies based on Safer Nursing Care Tool acuity/dependency measure. Design This was an observational study on medical/surgical wards in four NHS hospital trusts using regression, computer simulations and economic modelling. We compared the effects and costs of a ‘high’ establishment (set to meet demand on 90% of days), the ‘standard’ (mean-based) establishment and a ‘flexible (low)’ establishment (80% of the mean) providing a core staff group that would be sufficient on days of low demand, with flexible staff re-deployed/hired to meet fluctuations in demand. Setting Medical/surgical wards in four NHS hospital trusts. Main outcome measures The main outcome measures were professional judgement of staffing adequacy and reports of omissions in care, shifts staffed more than 15% below the measured requirement, cost per patient-day and cost per life saved. Data sources The data sources were hospital administrative systems, staff reports and national reference costs. Results In total, 81 wards participated (85% response rate), with data linking Safer Nursing Care Tool ratings and staffing levels for 26,362 wards × days (96% response rate). According to Safer Nursing Care Tool measures, 26% of all ward-days were understaffed by ≥ 15%. Nurses reported that they had enough staff to provide quality care on 78% of shifts. When using the Safer Nursing Care Tool to set establishments, on average 60 days of observation would be needed for a 95% confidence interval spanning 1 whole-time equivalent either side of the mean. Staffing levels below the daily requirement estimated using the Safer Nursing Care Tool were associated with lower odds of nurses reporting ‘enough staff for quality’ and more reports of missed nursing care. However, the relationship was effectively linear, with staffing above the recommended level associated with further improvements. In simulation experiments, ‘flexible (low)’ establishments led to high rates of understaffing and adverse outcomes, even when temporary staff were readily available. Cost savings were small when high temporary staff availability was assumed. ‘High’ establishments were associated with substantial reductions in understaffing and improved outcomes but higher costs, although, under most assumptions, the cost per life saved was considerably less than £30,000. Limitations This was an observational study. Outcomes of staffing establishments are simulated. Conclusions Understanding the effect on wards of variability of workload is important when planning staffing levels. The Safer Nursing Care Tool correlates with professional judgement but does not identify optimal staffing levels. Employing more permanent staff than recommended by the Safer Nursing Care Tool guidelines, meeting demand most days, could be cost-effective. Apparent cost savings from ‘flexible (low)’ establishments are achieved largely by below-adequate staffing. Cost savings are eroded under the conditions of high temporary staff availability that are required to make such policies function. Future work Research is needed to identify cut-off points for required staffing. Prospective studies measuring patient outcomes and comparing the results of different systems are feasible. Trial registration Current Controlled Trials ISRCTN12307968. Funding This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 16. See the NIHR Journals Library website for further project information.
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Dreyer, Jonathan F., Shelley L. McLeod, Chris K. Anderson, Michael W. Carter, and Gregory S. Zaric. "Physician workload and the Canadian Emergency Department Triage and Acuity Scale: the Predictors of Workload in the Emergency Room (POWER) Study." CJEM 11, no. 04 (July 2009): 321–29. http://dx.doi.org/10.1017/s1481803500011350.
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ABSTRACTIntroduction:The Canadian Emergency Department Triage and Acuity Scale (CTAS) is a 5-level triage tool used to determine the priority by which patients should be treated in Canadian emergency departments (EDs). To determine emergency physician (EP) workload and staffing needs, many hospitals in Ontario use a case-mix formula based solely on patient volume at each triage level. The purpose of our study was to describe the distribution of EP time by activity during a shift in order to estimate the amount of time required by an EP to assess and treat patients in each triage category and to determine the variability in the distribution of CTAS scoring between hospital sites.Methods:Research assistants directly observed EPs for 592 shifts and electronically recorded their activities on a moment-by-moment basis. The duration of all activities associated with a given patient were summed to derive a directly observed estimate of the amount of EP time required to treat the patient.Results:We observed treatment times for 11 716 patients in 11 hospital-based EDs. The mean time for physicians to treat patients was 73.6 minutes (95% confidence interval [CI] 63.6–83.7) for CTAS level 1, 38.9 minutes (95% CI 36.0–41.8) for CTAS-2, 26.3 minutes (95% CI 25.4–27.2) for CTAS-3, 15.0 minutes (95% CI 14.6–15.4) for CTAS-4 and 10.9 minutes (95% CI 10.1–11.6) for CTAS-5. Physician time related to patient care activities accounted for 84.2% of physicians' ED shifts.Conclusion:In our study, EPs had very limited downtime. There was significant variability in the distribution of CTAS scores between sites and also marked variation in EP time related to each triage category. This brings into question the appropriateness of using CTAS alone to determine physician staffing levels in EDs.
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Goh, Mien Li, Emily N. K. Ang, Yiong-Huak Chan, Hong-Gu He, and Katri Vehviläinen-Julkunen. "Patient Satisfaction Is Linked to Nursing Workload in a Singapore Hospital." Clinical Nursing Research 27, no. 6 (June 13, 2017): 692–713. http://dx.doi.org/10.1177/1054773817708933.
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No studies have examined the association between patient satisfaction and the allocation of nursing care hours using a workload management system. The aim of this study is to examine the correlation between inpatients’ perceived satisfaction with nursing care and nursing workload management in a Singapore hospital. A secondary data analysis was performed based on the results of 270 patients’ perceived satisfaction measured by the Revised Humane Caring Scale and nursing workload management data extracted from the TrendCare Patient Acuity System. Data were collected from March to October 2013. There were weak positive ( rs = .212 to rs = .120) and negative ( rs = −.120 to rs = −.196) correlations between patient satisfaction and nursing workload. Nursing leaders should build positive work environment through maximizing efficient resource allocation and adequate staffing to deliver safe patient care. Future studies could involve other patient outcomes such as incidences of fall and pressure ulcer.
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Stys, Dana, Kerri Landry, Tatum Mitra, and Vincent Grant. "A provincial assessment of readiness for paediatric emergencies: What are the existing resource gaps in Alberta?" Paediatrics & Child Health 25, no. 8 (October 9, 2019): 498–504. http://dx.doi.org/10.1093/pch/pxz111.
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Abstract Objectives A large proportion of all emergency visits for paediatric patients across Canada are to general emergency departments (EDs). These centres may not be adequately equipped to provide optimal care for high acuity paediatric emergencies. The objective of this study was to determine paediatric readiness for general EDs and urgent care centres (UCCs) across Alberta and provide each centre with an overall weighted Paediatric Readiness Score (WPRS). Methods A paediatric readiness assessment consisting of 55-questions normalized on a 100-point scale was used to survey 107 general EDs, UCCs, and tertiary paediatric EDs in Alberta, Canada. It addresses six primary categories, including Coordination of Patient Care, Physician/Nurse Staffing and Training, Quality Improvement Activities, Patient Safety Initiatives, Policies and Procedures, and Equipment and Supplies. Descriptive statistics were used to present the WPRS score among different groups. Linear regression models were used to explore factors associated with the score. Results The overall response rate was 59.8%. The median overall WPRS (/100) for all general EDs and UCCs was 48.4 ([interquartile range {IQR}] 17.6). Factors that were correlated with overall score included high paediatric patient volume (24.28, 95% confidence interval [CI]: 10.52 to 38.04) and involvement in a simulation education outreach program (9.38, 95% CI: 1.11 to 17.66). Conclusion Based on this survey, the WPRS of EDs and UCCs across Alberta suggest a need to improve readiness to respond to high acuity paediatric emergencies in these settings.
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Innes, Grant D., Robert Stenstrom, Eric Grafstein, and James M. Christenson. "Prospective time study derivation of emergency physician workload predictors." CJEM 7, no. 05 (September 2005): 299–308. http://dx.doi.org/10.1017/s1481803500014482.
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ABSTRACT Background: A reliable emergency department (ED) workload measurement tool would provide a method of quantifying clinical productivity for performance evaluation and physician incentive programs; it would enable health administrators to measure ED outputs; and it could provide the basis for an equitable formula to estimate ED physician staffing requirements. Our objectives were to identify predictors that correlate with physician time needed to treat patients and to develop a multivariable model to predict physician workload. Methods: During 31 day, evening, night and weekend shifts, a research assistant (RA) shadowed 20 emergency physicians, documenting time spent performing clinical and non-clinical functions for 585 patient visits. The RA recorded key predictors including patient gender, age, vital signs and Glasgow Coma Scale (GCS) score, and the mode of arrival, triage level assigned, comorbidity and procedures performed. Multiple linear regression was used to describe the associations between predictor variables and total physician time per patient visit (TPPV), and to derive an equation for physician workload. Model derivation was based on 16 shifts and 314 patient visits; model validation was based on 15 shifts and 271 additional patient visits. Results: The strongest predictor variables were: procedure required, triage level, arrival by ambulance, GCS, age, any comorbidity, and number of prior visits. The derived regression equation is: TPPV = 29.7 + 8.6 (procedure required [Yes]) – 3.8 (triage level [1–5]) + 7.1 (ambulance arrival) – 1.1 (GCS [3–15]) + 0.1 (age in years) – 0.05 (n of previous visits) + 3.1 (any comorbidity). This model predicted 31.3% of the variance in physician TPPV (F [12, 29] = 13.2; p < 0.0001). Conclusions: This study clarifies important determinants of emergency physician workload. If validated in other settings, the predictive formula derived and internally validated here is a potential alternative to current simplistic models based solely on patient volume and perceived acuity. An evidence-based workload estimation tool like that described here could facilitate ED productivity measurement, benchmarking, physician performance evaluation, and provide the substrate for an equitable formula to estimate ED physician staffing requirements.
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Fasoli, DiJon R., and Kathlyn Sue Haddock. "Results of an Integrative Review of Patient Classi cation Systems." Annual Review of Nursing Research 28, no. 1 (December 2010): 295–316. http://dx.doi.org/10.1891/0739-6686.28.295.
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This chapter presents the findings of an integrative review of the literature to identify current practices related to patient classification systems (PCSs). We sought to determine if there was a “gold standard” PCS that could be adopted or adapted for use by nurse leaders in practice. Sixty-three articles reporting studies related to PCS, Patient Acuity Systems or Workload Management Systems from 1983 to 2010 and applicable for inpatient medical/surgical settings were reviewed. Generally, we found that many of the criticisms of earlier PCSs are still evident: (1) difficulties with measuring workload remain an overarching theme throughout the literature; (2) definitions and descriptions of nursing work continue to be deemed inadequate; (3) there is insufficient evidence of reliability and validity testing of PCSs; and (4) there is still a need to identify nursing sensitive performance indicators and outcomes. We identified characteristics of promising PCSs, but concluded that no consensus exists about PCSs. We suggest that any approach to predicting staffing should seek to be parsimonious, minimize additional workload, be based on expert nurse judgment, be a true reflection of nursing work, and include indicators that measure patient complexity, required nursing care, available resources, and relevant organizational attributes.
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Asamani, James Avoka, Christmal Dela Christmals, and Gerda Marie Reitsma. "Health Service Activity Standards and Standard Workloads for Primary Healthcare in Ghana: A Cross-Sectional Survey of Health Professionals." Healthcare 9, no. 3 (March 16, 2021): 332. http://dx.doi.org/10.3390/healthcare9030332.
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The attainment of health system goals is largely hinged on the health workforce availability and performance; hence, health workforce planning is central to the health policy agenda. This study sought to estimate health service activity standards and standard workloads at the primary health care level in Ghana and explore any differences across health facility types. A nationally representative cross-sectional survey was conducted among 503 health professionals across eight health professions who provided estimates of health service activity standards in Ghana’s Primary Health Care (PHC) settings. Outpatient consultation time was 16 min, translating into an annual standard workload of 6030 consultations per year for General Practitioners. Routine nursing care activities take an average of 40 min (95% CI: 38–42 min) for low acuity patients; and 135 min (95% CI: 127–144 min) for high dependency patients per inpatient day. Availability of tools/equipment correlated with reduced time on clinical procedure. Physician Assistants in health centres spend more time with patients than in district hospitals. Midwives spend 78 min more during vaginal delivery in health centres/polyclinics than in district/primary hospital settings. We identified 18.9% (12 out of 67) of health service activities performed across eight health professional groups to differ between health centres/polyclinics and district/primary hospitals settings. The workload in the health facilities was rated 78.2%, but as the workload increased, and without a commensurate increase in staffing, health professionals reduced the time spent on individual patient care, which could have consequences for the quality of care and patient safety. Availability of tools and equipment at PHC was rated 56.6%, which suggests the need to retool these health facilities. The estimated standard workloads lay a foundation for evidence-based planning for the optimal number of health professionals needed in Ghana’s PHC system and the consequent adjustments necessary in both health professions education and the budgetary allocation for their employment. Finally, given similarity in results with Workload Indicators of Staffing Need (WISN) methodology used in Ghana, this study demonstrates that cross-sectional surveys can estimate health service activity standards that is suitable for health workforce planning just as the consensus-based estimates advocated in WISN.
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Leopardi, Marco, and Marco Sommacampagna. "Emergency Nursing Staff Dispatch: Sensitivity and Specificity in Detecting Prehospital Need for Physician Interventions During Ambulance Transport in Rovigo Emergency Ambulance Service, Italy." Prehospital and Disaster Medicine 28, no. 5 (August 15, 2013): 523–28. http://dx.doi.org/10.1017/s1049023x13008790.
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AbstractIntroductionIn Italy, administration of medications or advanced procedures dictates the prehospital presence of a physician to initiate treatment. Nursing staff is often used as dispatchers in Italian emergency medical ambulance services. There is little data about nursing dispatch performance in detecting high-acuity patients who need prehospital medications and procedures.ObjectiveTo determine the ability of a dispatch center staffed by emergency ambulance nurses to detect prehospital need for physician interventions in the context of a semi-rural area Emergency Medical Services system.MethodsA retrospective analysis of 53,606 calls from the Rovigo Emergency Ambulance Services’ database was undertaken. Physician prehospital interventions were defined as the administration of medications or procedures (advanced airway management and ventilation, pneumothorax decompression, fluid replacement therapy, external defibrillation, cardioversion and pacing). The dispatch codes (assigned by a subjective decision-making process as Red, Yellow, or Green) of all transported prehospital patient calls were matched with an out-of-hospital triage system staffed by clinicians to determine the number of correctly identified prehospital need of physician interventions. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated.ResultsThe sensitivity of subjective experience-based nursing dispatch in detecting the need for physician interventions was 78.0% (95% CI, 76.9%-79.1%), with a PPV of 36.6% (95% CI, 35.8%-37.5%). Specificity was 83.8% (95% CI: 83.4%-84.1%), with an NPV of 96.9% (95% CI, 96.8%-97.1%).ConclusionA dispatch center staffed by nurses with six years of experience and three months of training correctly identified when not to send a doctor to the scene in the absence of need for physician interventions, using a subjective decision-making process. The nurses staffing the dispatch center also worked in the field. Dispatch center staff were not able to predict when there was no need for physician interventions in high-acuity dispatch code patients, resulting in an over-triage and use of emergency physicians on scene.LeopardiM, SommacampagnaM.Emergency nursing staff dispatch: sensitivity and specificity in detecting prehospital need for physician interventions during ambulance transport in Rovigo Emergency Ambulance Service, Italy. Prehosp Disaster Med. 2013;28(5):1-6.
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Tyler, Denise, Cleanthe Kordomenos, and Melvin Ingber. "Stakeholder Perspectives on Reducing Hospitalizations Among Nursing Home Residents." Innovation in Aging 4, Supplement_1 (December 1, 2020): 85. http://dx.doi.org/10.1093/geroni/igaa057.280.
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Abstract Organizations in seven states have been participating in the Center for Medicare and Medicaid Innovation (CMMI) initiative aimed at reducing potentially avoidable hospitalizations among long-stay nursing home (NH) residents. The purpose of this study was to identify market and policy factors that may have affected the initiative in those states. Forty-seven interviews were conducted with key stakeholders in the seven states (e.g., representatives from state departments of health, state Medicaid offices, and nursing, hospital and nursing home associations) and qualitatively analyzed to identify themes across states. Few policies or programs were found that may have affected the initiative; only New York (NY) was found to have state policies or programs specifically aimed at reducing hospitalizations. Market pressures reported in most states were similar. For example, stakeholders reported that the increased availability of home and community-based services and the growing presence of managed care are contributing to higher acuity among both long and short stay residents and that reimbursement rates and staffing have not kept up. Stakeholders suggested greater presence of physicians and nurse practitioners in NHs, better training around behavioral health issues for frontline staff, and more advance care planning and education of families about end of life may help further reduce NH hospitalizations. We also found that all states, except NY, had regional coalitions of health care related organizations focused on improving some aspect of care, such as reducing hospital readmissions. These coalitions may suggest ways that organizations can work together to reduce hospitalizations among NH residents.
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Nelsen, Greg, Heidi Pigott, Caleb Hopkinson, and Christine M. Formea. "Considerations for development of pharmacy support models for COVID-19 alternate care sites." American Journal of Health-System Pharmacy 77, no. 19 (July 23, 2020): 1592–97. http://dx.doi.org/10.1093/ajhp/zxaa214.
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Abstract Purpose Guidance on alternate care site planning based on the experience of a health-system pharmacy department in preparing for an expected surge in coronavirus disease 2019 (COVID-19) cases is provided. Summary In disaster response situations such as the COVID-19 pandemic, healthcare institutions may be compelled to transition to a contingency care model in which staffing and supply levels are no longer consistent with daily practice norms and, while usual patient care practices are maintained, establishment of alternate care sites (eg, a convention center) may be necessitated by high patient volumes. Available resources to assist hospitals and health systems in alternate care site planning include online guidance posted within the COVID-19 resources section of the US Army Corps of Engineers website, which provides recommended medication and supply lists; and the Federal Healthcare Resilience Task Force’s alternate care site toolkit, a comprehensive resource for all aspects of alternate care site planning, including pharmacy services. Important pharmacy planning issues include security and storage of drugs, state board of pharmacy and Drug Enforcement Administration licensing considerations, and staff credentialing, education, and training. Key medication management issues to be addressed in alternate site care planning include logistical challenges of supply chain maintenance, optimal workflow for compounded sterile preparations (eg, on-site preparation vs off-site preparation and delivery from a nearby hospital), and infusion pump availability and suitability to patient acuity levels. Conclusion Planning for and operation of alternate care sites in disaster response situations should include involvement of pharmacists in key decision-making processes at the earliest planning stages.
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Molloy, Michael, Paul Kelly, and Gregory R. Ciottone. "Concerns for Small Hospitals in Rationalising Trauma Services: How Do We Ensure Enhanced Patient Services in Rural Areas?" Prehospital and Disaster Medicine 34, s1 (May 2019): s110—s111. http://dx.doi.org/10.1017/s1049023x19002334.
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Introduction:Trauma bypass has been introduced successfully worldwide with sustained reductions in mortality/morbidity. Analyzing structure, process, and outcome individually and collectively in systems has been found to focus improvement efforts in the audit cycle. The second Irish report on Major Trauma Audit (MTA) was published in December 2017. The median age of trauma patients in Ireland was 59, indicating an aging trauma population. 28% of patients required secondary transfer to complete their care. The mortality rate for 2016 was only 4%.Aim:To determine the ability of a road-based EMS system to bring patients from areas of Wexford County to proposed receiving centers within 60-90 minutes.Methods:Analysis took population centers in Wexford County, used Google Maps to estimate travel times at 3pm on a weekday, and proposed new trauma units and centers in Dublin, Cork, and Waterford.Results:In Wexford County urban centers, >95% of patients will not reach a trauma unit in less than 60 minutes with current prehospital medical service capabilities. This even excludes response/on-scene time by prehospital practitioners in land-based EMS vehicles.Discussion:The proposed introduction of trauma bypass systems in Ireland should not disenfranchise patients with respect to the standards they are currently receiving. Gap analysis suggests considerable work is required within the ambulance service to increase critical skill levels of paramedics to support critical patients in the golden hour of their transfer. An increase in vehicles/resources will be required to ensure adequate staffing to meet Health Information and Quality Authority (HIQA) targets of 8 and 19 minutes for response acuity, and for longer durations of transport allied to dynamic resource deployment model as used by National Emergency Operations Centre (NEOC). Unintended consequences of system changes will need to be monitored carefully to avoid further adversely impacting recruitment of staff to bypassed Model 3 hospitals.
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Weigl, Matthias, Joana Beck, Markus Wehler, and Anna Schneider. "Workflow interruptions and stress atwork: a mixed-methods study among physicians and nurses of a multidisciplinary emergency department." BMJ Open 7, no. 12 (December 2017): e019074. http://dx.doi.org/10.1136/bmjopen-2017-019074.
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ObjectivesDealing with multiple workflow interruptions is a major challenge in emergency department (ED) work. This study aimed to establish a taxonomy of workflow interruptions that takes into account the content and purpose of interruptive communication. It further aimed to identify associations of workflow interruptions with ED professionals’ work stress.DesignCombined data from expert observation sessions and concomitant self-evaluations of ED providers.SettingED of an academic community hospital in Germany.ParticipantsMultidisciplinary sample of ED physicians and nurses. 77 matched observation sessions of interruptions and self-evaluations of work stress were obtained on 20 randomly selected days.Outcome measuresED professionals’ stress evaluations were based on standardised measures. ED workload data on patient load, patient acuity and staffing were included as control variables in regression analyses.ResultsOverall mean rate was 7.51 interruptions/hour. Interruptions were most frequently caused by ED colleagues of another profession (27.1%; mean interruptions/hour rate: 2.04), by ED colleagues of the same profession (24.1%; 1.81) and by telephone/beeper (21%; 1.57). Concerning the contents of interruption events, interruptions most frequently occurred referring to a parallel case under care (30.3%, 2.07), concerning the current case (19.1%; 1.28), or related to coordination activities (18.2%, 1.24). Regression analyses revealed that interruptive communication related to parallel cases significantly increased ED providers’ stress levels (β=0.24, P=0.03). This association remained significant after controlling for ED workload.DiscussionInterruptions that refer to parallel cases under care were associated with increased stress among ED physicians and nurses. Our approach to distinguish between sources and contents of interruptions contributes to an improved understanding of potential benefits and risks of workflow interruptions in ED work environments. Despite some limitations, our findings add to future research on the implications of interruptions for effective and safe patient care and work in complex and dynamic care environments.
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Bell, Anthony, Ghasem-Sam Toloo, Julia Crilly, John Burke, Ged Williams, Bridie McCann, and Gerry FitzGerald. "Emergency department models of care in Queensland: a multisite cross-sectional study." Australian Health Review 43, no. 4 (2019): 363. http://dx.doi.org/10.1071/ah17233.
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Objective The acuity and number of presentations being made to emergency departments (EDs) is increasing. In an effort to safely and efficiently manage this increase and optimise patient outcomes, innovative models of care (MOC) have been implemented. What is not clear is how these MOC reflect the needs of patients or relate to each other or to ED performance. The aim of this study was to describe ED MOC in Queensland, Australia. Methods Situated within a larger mixed-methods study, the present study was a cross-sectional study. In early 2015, leaders (medical directors and nurse managers) from public hospital EDs in Queensland were invited to complete a survey detailing ED activity, staffing profiles, treatment space, MOC and National Emergency Access Target (NEAT) performance. Routinely collected ED information system data was also used. Results Twenty of the 27 EDs invited participated in the study (response rate 74%). An extensive array of MOC were identified that were categorised into those that facilitate input, throughput and output from the ED. There was no consistent evidence as to the relative effectiveness of these MOC in achieving ED performance benchmarks, such as NEAT performance. Conclusion There is considerable variability in the MOC used throughout EDs in Queensland. A more complete analysis of the relative effectiveness of different MOC either in isolation or as part of a comprehensive approach would help inform more consistent MOC in Queensland EDs. What is known about the topic? MOC in any given ED are implemented in response to factors such as the geographical location of the hospital, hospital-specific characteristics and service profile, staffing profile and patient demographic profile. In the era of time-based targets, they may also serve to address a particular aspect of flow in the face of rising ED demand. Although many of the MOC attempt to deal with flow in a linear fashion, target specific phases of the ED journey or address particular patient cohorts, what is clear is that not all EDs are shaped and formed the same. What does this paper add? The study provides a comprehensive description of the varied models of care operating within Queensland public hospital EDs and how they relate to ED performance. A basic taxonomy of contemporary ED MOC is necessary to allow comparison between departments and inform decisions regarding safety, efficiency and cost-effectiveness. What are the implications to practitioners? A contemporary understanding of the presence and profile of ED MOC that currently exist within a network of hospitals and health services is important for managers, clinicians and patients to inform decision-making regarding the safety, clinical effectiveness and cost-effectiveness of these models. This understanding can also inform where and how further improvements in care delivery can progress.
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Kirkland, S., L. Gaudet, D. Keto-Lambert, and B. Rowe. "P073: Consultations in the emergency department: a systematic review." CJEM 21, S1 (May 2019): S89. http://dx.doi.org/10.1017/cem.2019.264.
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Introduction: While consultation is a common and important aspect of emergency department (ED) care, a previous systematic review identified significant utilization and process variation across ED's. The aim of this review update was to examine the proportion of the patients undergoing consultation in the ED among recent studies. Methods: Eight primary literature databases and the grey literature were searched. Studies published from 2007 to 2018 focusing on all-comers to the ED and reporting a consultation-related outcome were included. Disease- and specialty-specific studies were not eligible. Two independent reviewers screened studies for relevance, inclusion, quality assessment, and data extraction. Disagreements were resolved through consensus. Means, medians and interquartile ranges are reported. Wilcoxon-rank sum test and one-way ANOVA were used to identify differences between groups, as appropriate. Results: A total of 2632 unique citations and 49 studies from the grey literature were screened, of which 29 primary studies were included. Fifteen studies reported on the proportion of ED patients undergoing consultation, involving EDs in the Middle East (n = 4), North America (n = 4), Asia (n = 4), and Europe (n = 3). Overall, the proportion of patients receiving consultation ranged from 7% to 78% (median: 26%; IQR: 20%, 38%). There were no differences in the proportions of consulted patients based on country of origin. Ten studies were conducted prior to 2013, while five studies recruited patients during and after 2013. The mean proportion of consulted patients was lower for post-2012 studies compared to pre-2012 studies (mean: 18% vs. 36%; p = 0.0048). The proportion of consulted patients admitted to hospital ranged considerably between the 14 reporting studies (median: 56%; IQR: 49%, 76%). No differences in the proportion of admitted patients undergoing a consult were identified based on country of origin or year of recruitment for the study. Conclusion: Although consultation utilization appears to be decreasing overall, there is considerable practice variation in EDs around the world. These differences may result from variation in patient acuity, case-load, staffing levels, institutional and health-system organization, and medical training and future research should explore reasons for these differences.
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Rusiecki, D., S. Hoffe, M. Walker, J. Reid, N. Rocca, H. White, L. McDonough, and T. Chaplin. "P112: In situ simulation: A team sport?" CJEM 21, S1 (May 2019): S104. http://dx.doi.org/10.1017/cem.2019.303.
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Introduction: Identification of latent safety threats (LSTs) in the emergency department is an important aspect of quality improvement that can lead to improved patient care. In situ simulation (ISS) takes place in the real clinical environment and multidisciplinary teams can participate in diverse high acuity scenarios to identify LSTs. The purpose of this study is to examine the influence that the profession of the participant (i.e. physician, registered nurse, or respiratory therapist) has on the identification of LSTs during ISS. Methods: Six resuscitation- based adult and pediatric simulated scenarios were developed and delivered to multidisciplinary teams in the Kingston General Hospital ED. Each ISS session consisted of a 10- minute scenario, followed by 3-minutes of individual survey completion and a 7- minute group debrief led by ISS facilitators. An objective assessor recorded LSTs identified during each debrief. Surveys were completed prior to debrief to reduce response bias. Data was collected on participant demographics and perceived LSTs classified in the following categories: medication; equipment; resources and staffing; teamwork and communication; or other. Two reviewers evaluated survey responses and debrief notes to formulate a list of unique LSTs across scenarios and professions. The overall number and type of LSTs from surveys was identified and stratified by health care provider. Results: Thirteen ISS sessions were conducted with a total of 59 participants. Thirty- four unique LSTs (8 medication, 15 equipment, 5 resource, 4 communication, and 2 miscellaneous issues) were identified from surveys and debrief notes. Overall, MDs (n = 12) reported 19 LSTss (n = 41) reported 77 LSTs, and RTs (n = 6) reported 4 LSTs based on individual survey data. The most commonly identified category of LSTs reported by MDs (36.8%) and RTs (75%) was equipment issues while RNs most commonly identified medication issues (36.4%). Participants with □5 years of experience in their profession, on average identified more LSTs in surveys than participants with >5 years experience (1.9 LSTs vs 1.5 LSTs respectively). Conclusion: Nursing staff identified the highest number of LSTs across all categories. There was fairly unanimous identification of major LSTs across professions, however each profession did identify unique perspectives on LSTs in survey responses. ISS programs with the purpose of LST identification would benefit from multidisciplinary participation.
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Savage, D., and D. Petrie. "LO77: Assessing the long-term emergency physician resource planning for Nova Scotia, Canada." CJEM 21, S1 (May 2019): S35—S36. http://dx.doi.org/10.1017/cem.2019.120.
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Introduction: Planning for the future emergency physician (EP) workforce will be a significant challenge for decision makers given the rise in emergency department (ED) visits and no concurrent increase in resident positions. EP workforce planning must incorporate physician supply, as well as current and forecasted patient demand. Nova Scotia has undertaken the process of developing a planning model to support policy decision making. We hypothesize that Nova Scotia will require increased resident positions and recruitment from other provinces to meet future patient demand. Methods: We have developed an age structured population model that tracks the number of clinical full-time equivalent (FTE) EPs by their age and shows the “variance” (i.e., supply – demand = variance) over a 30 year planning horizon. This model represents all Level 1, 2, 3, and 4 EDs in Nova Scotia. Current physician supply was calculated based on FTE staffing levels. The current patient demand was based on historical volume and acuity of patients and converted to an FTE demand estimate. Forecasted demand was predicted to increase at an average rate of 0.5% per year. We varied the number of residents trained and the number of EPs recruited from outside the province to examine the effect on the EP workforce. Our initial model will reflect the current training environment and will be referred to as the “current state”. In our 3 scenarios, we increased the number of residents and recruited physicians by 50%, individually and then together. Our outcome measure will be the variance in FTE. Results: The current state showed that the province will have a deficit of 51 FTE EPs over the next 30 years. In scenario 1, a 50% increase in both resident training streams eliminated all variance, while in scenario 2, the increase in recruitment reduced the FTE variance to 34 FTE positions unfilled. In scenario 3, the variance was 0. Conclusion: We feel that this CTAS weighted volumes perspective is important for clinical services planning but the siting, sizing, and synergizing of EDs in a region will involve other inputs. Its important to recognize that we have made the assumption that all physicians starting to work in Nova Scotia will be a 1 FTE. Future iterations will examine the effect of more realistic FTE definitions that account for administrative, teaching and research activities.
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Calder-Sprackman, S., G. Clapham, T. Kandiah, J. Choo-Foo, S. Aggarwal, J. Sweet, K. Abdulkarim, C. Price, V. Thiruganasambandamoorthy, and E. Kwok. "MP02: The impact of adoption of an electronic health record on emergency physician work: a time motion study." CJEM 22, S1 (May 2020): S42—S43. http://dx.doi.org/10.1017/cem.2020.150.
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Introduction: Adoption of a new Electronic Health Record (EHR) can introduce radical changes in task allocation, work processes, and efficiency for providers. In June 2019, The Ottawa Hospital transitioned from a primarily paper based EHR to a comprehensive EHR (Epic) using a “big bang” approach. The objective of this study was to assess the impact of the transition to Epic on Emergency Physician (EP) work activities in a tertiary care academic Emergency Department (ED). Methods: We conducted a time motion study of EPs on shift in low acuity areas of our ED (CTAS 3-5). Fifteen EPs representing a spectrum of pre-Epic baseline workflow efficiencies were directly observed in real-time during two 4-hour sessions prior to EHR implementation (May 2019) and again in go live (August 2019). Trained observers performed continuous observation and measured times for the following EP tasks: chart review, direct patient care, documentation, physical movement, communication, teaching, handover, and other (including breaks). We compared time spent on tasks pre Epic and during go live and report mean times for the EP tasks per patient and per shift using two tailed t-test for comparison. Results: All physicians had a 17% decrease in patients seen after Epic implementation (2.72/hr vs 2.24/hr, p < 0.01). EPs spent the same amount of time per patient on direct patient care and chart review (direct patient care: 9min06sec/pt pre vs 8min56sec/pt go live, p = 0.77; chart review: 2min47sec/pt pre vs 2min50sec/pt go live, p = 0.88), however, documentation time increased (5min28sec/pt pre vs 7min12sec/pt go live, p < 0.01). Time spent on shift teaching learners increased but did not reach statistical significance (31min26sec/shift pre vs 36min21sec/shift go live, p = 0.39), and time spent on non-patient-specific activities – physical movement, handover, team communication, and other – did not change (50min49sec/shift pre vs 50min53sec/shift go live, p = 0.99). Conclusion: Implementation of Epic did not affect EP time with individual patients - there was no change in direct patient care or chart review. Documentation time increased and EP efficiency (patients seen per hr on shift) decreased after go live. Patient volumes cannot be adjusted in the ED therefore anticipating the EHR impact on EP workflow is critical for successful implementation. EDs may consider up staffing 20% during go live. Findings from this study can inform how to best support EDs nationally through transition to EHR.
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Jackson Cullison, Stephanie Renae, Arda Celen, Nicole Adell Doudican, Mary Stevenson, and John A. Carucci. "Modified operations to permit safe and timely delivery of essential surgical care for high-risk skin cancer during a pandemic." Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021): e21565-e21565. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e21565.
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e21565 Background: Many surgical practices closed at the onset of the COVID-19 pandemic raising concerns that delayed cancer care might impact patient outcomes. We implemented operational changes to safely remain open and treat tumors with potential to threaten life or function. We studied the impact of these changes on safety, access, and treatment. Methods: A single-center retrospective study was conducted in an academic office-based dermatologic surgery practice. All patients consented to research. “Pre-pandemic” (Nov. 2019 – March 21, 2020) consultations served as controls. Consultations during the “pause” (March 22 - June 8, 2020) and “reopening” (June 9 – Sept. 30, 2020) were evaluated for time to treatment, tumor area, and upstaging. One-way ANOVA or Fisher Exact analyses were performed with P < 0.05 significant. Operational changes included (1) modified scheduling, staffing, and rooming; (2) COVID-19 symptom screening; (3) N95 masks and shields for patient contact; (4) triage by tumor acuity; (5) same day or video consultation; and (6) increased utilization of same day biopsy and surgery for suspicious lesions. Results: Data from 698 patients (23-103 yrs of age, avg 71 yrs) yielded 876 tumors treated by Mohs surgery (n = 776), standard excision (n = 73), staged excision (n = 14) or electrodessication and curettage (n = 13). The average time from biopsy or consultation to treatment was faster during the pause and reopening relative to pre-pandemic (Table). More frozen section diagnostic biopsies were performed in the pause (n = 6) and reopening (n = 4) compared to pre-pandemic (n = 0). Post-operative defects were similar to pre-pandemic sizes (3.2 cm2) during the pause (3.9 cm2) and reopening (3.2 cm2) (p = 0.72). A reduction in treatment of basal cell carcinoma (BCC, Χ2= 0.04) and shift toward treatment of higher risk tumors such as cutaneous squamous cell carcinoma (SCC, 49% of tumors during pause vs 37% pre-pandemic) and melanoma (11% pause vs 4.7% pre-pandemic) was noted. The percentage of SCC upstaged after treatment increased during the pause (42%, Χ2= 0.02) vs pre-pandemic (18.5%) or reopening (17.4%). Conclusions: Time to treatment, tumor size, and SCC upstaging pre-pandemic and during the reopening fail to identify any significant access interruptions. This likely reflects practice modifications of increased same day surgery, frozen section diagnostic biopsy, and tumor triage. Lack of COVID-19 transmission attributable to maintained operations suggests that essential surgical care can be delivered safely to patients with high-risk skin cancers during a pandemic.[Table: see text]
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Lemaistre, Charles F., Ju-Hsien Chao, Tonya Cox, Jose Carlos Cruz, William B. Donnellan, Alireza Eghtedar, Jared Holder, et al. "Center Effects on Outcomes in the Treatment of Acute Myelogenous Leukemia (AML): A Multilevel, Community-Based, Case-Controlled Study." Blood 134, Supplement_1 (November 13, 2019): 4780. http://dx.doi.org/10.1182/blood-2019-130640.
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Background As with other complex therapies, treatment of AML varies among centers (ctrs) due to differences in patients (pts), infrastructure and care delivery models. Variation in ctrs practices, experience and resources may influence pt outcomes. Few studies have examined the association of ctr characteristics and survival in AML. Previous research offers conflicting results regarding outcomes of AML pts treated in National Cancer Institute Comprehensive Cancer Centers (NCICCC) versus community settings; neither study investigated ctr-level differences other than volume. We sought to compare AML outcomes in any of the HCA Healthcare (HCA) network of 131 community hospitals from 2011-18 with those reported in the Surveillance, Epidemiology, and End Results (SEER) database. We then examined pt, disease and center-related characteristics influencing outcomes in HCA hospitals. Methods We identified pts with AML (excluding APL) > 18 yrs treated between 10/31/11 and 10/31/18 in an HCA hospital (N = 4,882) and obtained pt level data from electronic medical records. A comparative population treated was developed from the most recent SEER database (2011-15; N = 19,349). We used coarsened exact matching to control for as many potential biases as possible. We compared mortality at 30, 90 and 120-days and overall survival curves between HCA and SEER . A Cox regression model was used to investigate differences in hazard rates among HCA facilities while simultaneously assessing the impact of patient characteristics and facility characteristics. Of the HCA patients, 1339 were treated in 6 hospitals that meet defined metrics of infrastructure, staffing, processes and volume as part of certification to participate in the Sarah Cannon Blood Cancer Network (SCBCN). Results Matching for age, gender and race, HCA pts were found to have significantly lower mortality than SEER at 30, 90 and 120 days (p<.001) as well as significantly better survival (p<0.001; fig.1). We next investigated how pt and facility characteristics interact to predict outcomes for HCA patients (table 1). Elevated White Count at diagnosis (HR=1.3), Charlson index (HR=1.1), older age (HR= 1.04), and receiving treatment at a hospital with larger bed count (HR=1.26) were associated with significantly worse survival. Commission on Cancer (COC) accreditation status, Socio-economic status (SES), distance to facility, and gender did not significantly impact risk. Being treated in the SCBCN (HR=0.68) and African American race (HR= 0.66) were associated with improved survival Conclusions Previous research utilizing registry data demonstrated better survival for pts with AML treated in higher volume centers but provides conflicting information about survival for pts treated in a NCICCC versus a community setting. Neither study examined center characteristics beyond NCI designation. This report examines a large pt cohort treated in community hospitals across the US. Pts treated in these hospitals had significantly better survival than a matched cohort from the SEER database. We validate the importance of age, acuity and Charlson index as adverse factors. Analysis of facility characteristics demonstrated that qualification as a member of SCBCN was associated with improved survival underscoring the importance of infrastructure, quality systems and volume in achieving improved outcomes. Disclosures Lemaistre: HCA: Employment. Chao:HCA: Employment. Cruz:1. Daiichi Sankyo advisory board: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Speakers Bureau. Eghtedar:Verastem Oncology: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; Jazz: Consultancy, Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Takeda: Honoraria, Speakers Bureau. Holder:Sarah Cannon: Employment. Malik:Kite Pharma: Honoraria. Rotta:Kadmon Corporation, LLC: Consultancy; Jazz: Speakers Bureau.
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"Acuity Based Staffing: Let’s Look at the Patient." Journal of the American Dietetic Association 91 (September 1991): A—152. http://dx.doi.org/10.1016/s0002-8223(21)07115-7.
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Stellman, Robert, Andrew Redfern, Sa'ad Lahri, Tonya Esterhuizen, and Baljit Cheema. "How much time do doctors spend providing care to each child in the ED? A time and motion study." Emergency Medicine Journal, April 15, 2021, emermed-2019-208903. http://dx.doi.org/10.1136/emermed-2019-208903.
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BackgroundThe total time per patient doctors spend providing care in emergency departments (EDs) has implications for the development of evidence-based ED staffing models. We sought to measure the total time taken by doctors to assess and manage individual paediatric patients presenting to two EDs in the Western Cape, South Africa and to compare these averages to the estimated benchmarks used regionally to calculate ED staffing allocations.MethodsWe conducted a cross-sectional, observational study applying time and motion methodology, using convenience sampling. Data were collected over a 5-week period from 11 December 2015 to 18 January 2016 at Khayelitsha District Hospital Emergency Centre and Tygerberg Hospital Paediatric Emergency and Ambulatory Unit. We assessed total doctor time for each patient stratified by acuity level using the South African Triage Scale.ResultsCare was observed for a total of 100 patients. Median age was 21 months (IQR 8–55). Median total doctor time per patient (95% CI) was 31 (22 to 38), 39 (31 to 63), 48 (32 to 63) and 96 (66 to 122) min for triage categories green, yellow, orange and red, respectively. Median timing was significantly higher than the estimated local benchmark for the lowest acuity ‘green’ triage category (31 min (22 to 38) vs 15 min; p=0.001) and the highest acuity ‘red’ category (96 min (66 to 122) vs 50 min; p=0.002).ConclusionDoctor time per patient increased with increasing acuity of triage category and exceeded estimated benchmarks for the highest and lowest acuities. The distinctive methodology can easily be extended to other settings and populations.