Moving Care to the Community: An International Perspective

Medical treatments that were once provided in hospital are being increasingly administered in the community. Within health systems, there is a renewed focus on delivering general health care in the community, freeing hospitals to provide more complex, specialised and emergency care. As the drive to shift specialised and non-specialised care out of hospital gathers momentum, there is a greater demand for a skilled and competent community nursing workforce to facilitate this shift at a local level. Nurses are essential in the delivery of continuous care as they often serve as an interface between acute and community care, focusing on prevention, self- management and providing support to transition patients smoothly across the health and social care services.Moving care to the community has been a UK-wide health and social care policy priority for more than a decade. However, progress has been slow and in some cases fragmented. In order to address the issue, it is important to first review where this shift has been implemented and which lessons can be learned from international experiences. The RCN is committed to working closely with its equivalent nursing organisations overseas to learn from international best practices and incorporate some of this learning to shape health and social care policy in the UK, and more specifically promote good nursing practice. This report will focus on system-wide or sector specific reforms in Australia, Canada, Sweden, Norway and Denmark as these countries have at one point or another addressed the need todeliver care outside of hospitals, either in patients' homes, GP clinics, community-basedcentres or care home settings

Staffing and job satisfaction: nurses and nursing assistants

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106848/1/jonm12012.pd

Flexible nurse staffing based on hourly bed census predictions

Workload on nursing wards depends highly on patient arrivals and patient lengths of stay, which are both inherently variable. Predicting this workload and staffing nurses accordingly is essential for guaranteeing quality of care in a cost effective manner. This paper introduces a stochastic method that uses hourly census predictions to derive efficient nurse staffing policies. The generic analytic approach minimizes staffing levels while satisfying so-called nurse-to-patient ratios. In particular, we explore the potential of flexible staffing policies which allow hospitals to dynamically respond to their fluctuating patient population by employing float nurses. The method is applied to a case study of the surgical inpatient clinic of the Academic Medical Center (AMC) Amsterdam. This case study demonstrates the method's potential to study the complex interaction between staffing requirements and several interrelated planning issues such as case mix, care unit partitioning and size, and surgical block planning. Inspired by the numerical results, the AMC decided that this flexible nurse staffing methodology will be incorporated in the redesign of the inpatient care operations during the upcoming years

Factors in the practice environment of nurses working in inpatient mental health: A partial least squares path modeling approach

Background: Developing a therapeutic relationship with consumers is considered as the central aspect of nursing work in mental health. The importance of this relationship stems from its association with enhanced patient care and improved patient outcomes. Factors within the practice environment may influence the nurse's ability to engage effectively in this relationship. Objective: This study explored a model that added characteristics of the individual and practice environment to a central framework incorporating therapeutic commitment: a nurse's ability and willingness to engage in a therapeutic relationship. Setting and participants: Data were collected at six mental health nursing units in five public general acute hospitals in New South Wales, Australia for 14 days per unit, between 2005 and 2006. All nurses in participating wards were invited to partake in the study. Seventy-six (51%) responses were analyzed. Method: The data were collected using a Nurse Survey inclusive of the Practice Environment Scale of the Nursing Work Index (NWI-PES), and the Mental Health Problems Perception Questionnaire (MHPPQ). A Unit Profile form was used concurrently to collect staffing, skill mix and patient turnover data. Partial least squares path modeling (PLS-PM) was chosen as the analytical method to test the model and identify the most influential factors. Results: Experienced nurses who perceived themselves to be competent and supported were more likely to express a willingness to engage therapeutically with patients. Environmental factors associated with these perceptions included foundations of quality nursing care, opportunities to participate in hospital affairs and clinical supervision. Not all elements in the proposed model were supported. Conclusion: Positive hospital practice environments can improve the capacity of nurses working in mental health to engage therapeutically with patients. Specific approaches may include access to preceptorship, continued education and career development opportunities, together with clinical supervision, improved continuity of care, and the involvement of mental health nurses in the governance of the hospital. © 2011 Elsevier Ltd

Developing a caseload model to reflect the complexity of district and community nursing

A study by the England Centre for Practice Development proposes to develop and evaluate an optimum caseload model for district and community nursing, building on two rounds of funded pilot research in the south east of England using the Cassandra MatrixTM. It addresses national calls for a strategic capacity-and-demand model to measure and reflect the multidimensional complexity of the community nursing workload, maximising the potential of the workforce to meet the needs of clients with increasingly complex comorbidities and interdependencies. It also addresses the ambitions of the NHS Five Year Forward View to enable planned growth of the workforce for the future

The Cassandra Project- building a sustainable workload activity model for future community and district nursing workforce capacity planning

Purpose This paper presents work in progress from a two year mixed methods study in the UK to evaluate the impact of a community nursing workload activity tool as a mechanism for modelling optimum caseloads to underpin decisions about safe staffing levels. Current methods of measuring workload and output in the community context are not robust enough to capture the complexity of care differences in rural and urban populations. Many teams have heavy caseloads, poor/inappropriate referrals, and an inability to state when capacity has been reached. . Research Aim To develop and evaluate a robust model to predict and plan for optimum community nursing caseload activity within a whole system. Research Objectives 1. To develop a taxonomy and associated database that provides a consistent language for describing community nursing interventions that can be used to provide reliable and comparable metrics. 2. To determine the utility of the Cassandra tool in capturing community nursing interventions. 3 To use the data collected to build an inter-relational model of community nursing practice that can be used to determine, case-load, activity and develop a predictive model. 4. To evaluate the usability of the model in assisting managers and local decision-makers in workforce planning. 5. To assess the effectiveness of the model in capturing community nursing care left undone or missed 6. To explore how the model interrelates community nursing caseload activity with other care provision in a whole system. Methods Informed by critical realism, which attempts to understand real world issues, the design is guided by optimum caseload modelling, and given the multivariate nature of the environment in which workload activity takes place, a multiple case study evaluation across six NHS Pilot sites in England. Full ethical approval is in place. Results Results from case study sites demonstrated we have created a robust tool that captures an accurate picture of the multidimensional complexity of community nursing intervention, context of care, users of care and care left undone and are beginning to mine the data to identify patterns and relationships to build and test more accurate predictive optimum caseload activity tools to support workforce planning around patient acuity and skill mix, and provide an economic analysis of the cost of care left undone. Application in international contexts will be considered. Conclusions The tool can accurately capture a representative picture of how community and district nurses spend their time by generating both individual and organisational level reports. This reporting is speedy and enables workforce planners to work with robust evidence to make decisions about commissioning education for nurses, identifying skills shortages to target recruitment and retention activities, and to underpin decision making about commissioning services and the workforce required to provide high quality care

The Future Health Workforce: Integrated Solutions and Models of Care

This edited collection brings together a diverse set of original research and review articles that contribute towards a unified objective of redesigning the future health workforce. Our fundamental premise is that the future health workforce needs to be more closely aligned to population needs and be able to address emerging challenges of the 21st century. • The collection includes 13 articles (11 original research; 2 review) from nine countries. • Original research articles that contributed to this special issue came from Australia, Brazil, Canada, China, Japan, South Korea, Sweden, the United Kingdom and the United States of America. • The collection features a range of health professionals including medical, dental, nursing, allied health, social work, and health management workforce. This unique piece of scholarship adds to ongoing global efforts on health workforce integration, universal health coverage, and creating sustainable and people-centric health system