Primary and secondary care service use and costs associated with frailty in an ageing population: longitudinal analysis of an English primary care cohort of adults aged 50 and over, 2006-2017.

BACKGROUND: Frailty becomes more prevalent and healthcare needs increase with age. Information on the impact of frailty on population level use of health services and associated costs is needed to plan for ageing populations. AIM: To describe primary and secondary care service use and associated costs by electronic Frailty Index (eFI) category. DESIGN AND SETTING: Retrospective cohort using electronic health records. Participants aged ≥50 registered in primary care practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre, 2006-2017. METHODS: Primary and secondary care use (totals and means) were stratified by eFI category and age group. Standardised 2017 costs were used to calculate primary, secondary and overall costs. Generalised linear models explored associations between frailty, sociodemographic characteristics. Adjusted mean costs and cost ratios were produced. RESULTS: Individual mean annual use of primary and secondary care services increased with increasing frailty severity. Overall cohort care costs for were highest in mild frailty in all 12 years, followed by moderate and severe, although the proportion of the population with severe frailty can be expected to increase over time. After adjusting for sociodemographic factors, compared to the fit category, individual annual costs doubled in mild frailty, tripled in moderate and quadrupled in severe. CONCLUSIONS: Increasing levels of frailty are associated with an additional burden of individual service use. However, individuals with mild and moderate frailty contribute to higher overall costs. Earlier intervention may have the most potential to reduce service use and costs at population level.

Identifying models of care to improve outcomes for older people with urgent care needs: a mixed methods approach to develop a system dynamics model.

Background: We aimed to understand urgent and emergency care pathways for older people and develop a decision support tool using a mixed methods study design. Objective(s), study design, settings and participants: Work package 1 identified best practice through a review of reviews, patient, carer and professional interviews. Work package 2 involved qualitative case studies of selected urgent and emergency care pathways in the Yorkshire and Humber region. Work package 3 analysed linked databases describing urgent and emergency care pathways identifying patient, provider and pathway factors that explain differences in outcomes and costs. Work package 4 developed a system dynamics tool to compare emergency interventions. Results: A total of 18 reviews summarising 128 primary studies found that integrated social and medical care, screening and assessment, follow-up and monitoring of service outcomes were important. Forty patient/carer participants described emergency department attendances; most reported a reluctance to attend. Participants emphasised the importance of being treated with dignity, timely and accurate information provision and involvement in decision-making. Receiving care in a calm environment with attention to personal comfort and basic physical needs were key. Patient goals included diagnosis and resolution, well-planned discharge home and retaining physical function. Participants perceived many of these goals of care were not attained. A total of 21 professional participants were interviewed and 23 participated in focus groups, largely confirming the review evidence. Implementation challenges identified included the urgent and emergency care environment, organisational approaches to service development, staff skills and resources. Work package 2 involved 45 interviews and 30 hours of observation in four contrasting emergency departments. Key themes relating to implementation included: intervention-related staff: frailty mindset and behaviours resources: workforce, space, and physical environment operational influences: referral criteria, frailty assessment, operating hours, transport. context-related links with community, social and primary care organisation and management support COVID-19 pandemic. approaches to implementation service/quality improvement networks engaging staff and building relationships education about frailty evidence. The linked databases in work package 3 comprised 359,945 older people and 1,035,045 observations. The most powerful predictors of four-hour wait and transfer to hospital were age, previous attendance, out-of-hours attendance and call handler designation of urgency. Drawing upon the previous work packages and working closely with a wide range of patient and professional stakeholders, we developed an system dynamics tool that modelled five evidence-based urgent and emergency care interventions and their impact on the whole system in terms of reducing admissions, readmissions, and hospital related mortality. Limitations: Across the reviews there was incomplete reporting of interventions. People living with severe frailty and from ethnic minorities were under-represented in the patient/carer interviews. The linked databases did not include patient reported outcomes. The system dynamics model was limited to evidence-based interventions, which could not be modelled conjointly. Conclusions: We have reaffirmed the poor outcomes frequently experienced by many older people living with urgent care needs. We have identified interventions that could improve patient and service outcomes, as well as implementation tools and strategies to help including clinicians, service managers and commissioners improve emergency care for older people. Future work: Future work will focus on refining the system dynamics model, specifically including patient-reported outcome measures and pre-hospital services for older people living with frailty who have urgent care needs. Study registrations: This study is registered as PROSPERO CRD42018111461. WP 1.2: University of Leicester ethics: 17525-spc3-ls:healthsciences, WP 2: IRAS 262143, CAG 19/CAG/0194, WP 3: IRAS 215818, REC 17/YH/0024, CAG 17/CAG/0024. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme [project number 17/05/96 (Emergency Care for Older People)] and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. 14. See the NIHR Journals Library website for further project information.

Many older people attending emergency care have poor outcomes; this project aimed to: describe best practice in emergency care understand how best practice might be delivered describe outcomes from emergency care, and synthesise this information in a computer simulation tool that can help teams decide which interventions might work best in their setting. The existing literature showed that holistic interventions (caring for the whole person), spanning emergency and community care, designed with the needs of older people in mind, work best. We checked these findings with front line clinicians, who agreed, but identified that implementing best practice in the emergency department was challenging. Limitations included the emergency department environment itself and the lack of staff with the right skillset. We also asked older people and their carers who had recently received emergency care what mattered. They prioritised basic needs such as comfort, communication, and timely care. They also stated that getting better, maintaining their usual level of function, and getting home safely were important outcomes. We then analysed data that linked together ambulance, emergency department, and hospital care in Yorkshire and Humber from 2011­17 for over 1 million emergency department attendances and hospital admissions. We found a novel and accurate predictor of long emergency department waits and hospital admission: the level of urgency according to the ambulance call handler. Drawing upon all the above and guided by a wide range of patient and professionals, we developed a computer model which allows emergency care teams to simulate different best practice emergency department interventions and estimate the impact on reducing admissions, readmissions, and hospital mortality. In summary, we have reaffirmed the poor outcomes experienced by many older people with urgent care needs. We have identified interventions that could improve patient and service outcomes, as well as implementation tools to help including clinicians, hospital managers and funders transform emergency care for older people.

Frailty transitions and prevalence in an ageing population: longitudinal analysis of primary care data from an open cohort of adults aged 50 and over in England, 2006-2017.

INTRODUCTION: frailty is common in older adults and is associated with increased health and social care use. Longitudinal information is needed on population-level incidence, prevalence and frailty progression to plan services to meet future population needs. METHODS: retrospective open cohort study using electronic health records of adults aged ≥50 from primary care in England, 2006-2017. Frailty was calculated annually using the electronic Frailty Index (eFI). Multistate models estimated transition rates between each frailty category, adjusting for sociodemographic characteristics. Prevalence overall for each eFI category (fit, mild, moderate and severe) was calculated. RESULTS: the cohort included 2,171,497 patients and 15,514,734 person-years. Frailty prevalence increased from 26.5 (2006) to 38.9% (2017). The average age of frailty onset was 69; however, 10.8% of people aged 50-64 were already frail in 2006. Estimated transitions from fit to any level of frailty were 48/1,000 person-years aged 50-64, 130/1,000 person-years aged 65-74, 214/1,000 person-years aged 75-84 and 380/1,000 person-years aged ≥ 85. Transitions were independently associated with older age, higher deprivation, female sex, Asian ethnicity and urban dwelling. Mean time spent in each frailty category decreased with age, with the longest period spent in severe frailty at all ages. CONCLUSIONS: frailty is prevalent in adults aged ≥50 and time spent in successive frailty states is longer as frailty progresses, resulting in extended healthcare burden. Larger population numbers and fewer transitions in adults aged 50-64 present an opportunity for earlier identification and intervention. A large increase in frailty over 12 years highlights the urgency of informed service planning in ageing populations.

Embedding OR modelling as decision support in health capacity planning: insights from an evaluation.

Literature reviews over five decades have reported the paucity of examples of OR methods being routinely used to support decision-making in health and social care. This paper presents insights from an independent evaluation of a project intended to overcome some of the barriers to implementation by establishing a "community of practice" in Kent (England). The project itself was undertaken by practitioners, and had two main aims: providing training in system dynamics modelling to analysts, and making senior managers aware of the benefits of modelling. The findings largely confirmed previous studies, but also raised issues about style of training delivery and selection of problems to be modelled. Project leaders fully understood the barriers to embedding OR modelling skills, and made considerable efforts to avoid them, but nevertheless the main barrier, pressures on people's time, remained an obstacle. The paper concludes with general reflections and advice.

Examining the effect of interventions in emergency care for older people using a system dynamics decision support tool.

BACKGROUND: Rising demand for Emergency and Urgent Care is a major international issue and outcomes for older people remain sub-optimal. Embarking upon large-scale service development is costly in terms of time, energy and resources with no guarantee of improved outcomes; computer simulation modelling offers an alternative, low risk and lower cost approach to explore possible interventions. METHOD: A system dynamics computer simulation model was developed as a decision support tool for service planners. The model represents patient flow through the emergency care process from the point of calling for help through ED attendance, possible admission, and discharge or death. The model was validated against five different evidence-based interventions (geriatric emergency medicine, front door frailty, hospital at home, proactive care and acute frailty units) on patient outcomes such as hospital-related mortality, readmission and length of stay. RESULTS: The model output estimations are consistent with empirical evidence. Each intervention has different levels of effect on patient outcomes. Most of the interventions show potential reductions in hospital admissions, readmissions and hospital-related deaths. CONCLUSIONS: System dynamics modelling can be used to support decisions on which emergency care interventions to implement to improve outcomes for older people.

Closing the Implementation Gap Comment on "Insights Gained From a Re-analysis of Five Improvement Cases in Healthcare Integrating System Dynamics Into Action Research".

Holmström et al provide an interesting and thought-provoking contribution to a perennial problem: why, despite a vast number of applications of simulation modelling in healthcare over the past 70 years, there is still remarkably little evidence of successful implementation of model results. Their paper is a retrospective analysis of five case studies, all undertaken as consultancy, that used a blend of system dynamics (SD) modelling and action research (AR). This commentary assesses the effectiveness of this approach in achieving implementation, based on the evidence presented, and discusses some of the issues raised. These issues include a comparison of Holmström's approach with group model building (GMB) in SD, the differences between healthcare modelling projects undertaken by (a) business consultants and (b) academics, and the challenges of undertaking 'systematic' reviews of the grey literature.

Understanding no-show behaviour for cervical cancer screening appointments among hard-to-reach women in Bogotá, Colombia: A mixed-methods approach.

The global burden of cervical cancer remains a concern and higher early mortality rates are associated with poverty and limited health education. However, screening programs continue to face implementation challenges, especially in developing country contexts. In this study, we use a mixed-methods approach to understand the reasons for no-show behaviour for cervical cancer screening appointments among hard-to-reach low-income women in Bogotá, Colombia. In the quantitative phase, individual attendance probabilities are predicted using administrative records from an outreach program (N = 23384) using both LASSO regression and Random Forest methods. In the qualitative phase, semi-structured interviews are analysed to understand patient perspectives (N = 60). Both inductive and deductive coding are used to identify first-order categories and content analysis is facilitated using the Framework method. Quantitative analysis shows that younger patients and those living in zones of poverty are more likely to miss their appointments. Likewise, appointments scheduled on Saturdays, during the school vacation periods or with lead times longer than 10 days have higher no-show risk. Qualitative data shows that patients find it hard to navigate the service delivery process, face barriers accessing the health system and hold negative beliefs about cervical cytology.

Improving intervention design to promote cervical cancer screening among hard-to-reach women: assessing beliefs and predicting individual attendance probabilities in Bogotá, Colombia.

BACKGROUND: Despite being a preventable disease, cervical cancer continues to be a public health concern, affecting mainly lower and middle-income countries. Therefore, in Bogotá a home-visit based program was instituted to increase screening uptake. However, around 40% of the visited women fail to attend their Pap smear test appointments. Using this program as a case study, this paper presents a methodology that combines machine learning methods, using routinely collected administrative data, with Champion's Health Belief Model to assess women's beliefs about cervical cancer screening. The aim is to improve the cost-effectiveness of behavioural interventions aiming to increase attendance for screening. The results presented here relate specifically to the case study, but the methodology is generic and can be applied in all low-income settings. METHODS: This is a cross-sectional study using two different datasets from the same population and a sequential modelling approach. To assess beliefs, we used a 37-item questionnaire to measure the constructs of the CHBM towards cervical cancer screening. Data were collected through a face-to-face survey (N = 1699). We examined instrument reliability using Cronbach's coefficient and performed a principal component analysis to assess construct validity. Then, Kruskal-Wallis and Dunn tests were conducted to analyse differences on the HBM scores, among patients with different poverty levels. Next, we used data retrieved from administrative health records (N = 23,370) to fit a LASSO regression model to predict individual no-show probabilities. Finally, we used the results of the CHBM in the LASSO model to improve its accuracy. RESULTS: Nine components were identified accounting for 57.7% of the variability of our data. Lower income patients were found to have a lower Health motivation score (p-value < 0.001), a higher Severity score (p-value < 0.001) and a higher Barriers score (p-value < 0.001). Additionally, patients between 25 and 30 years old and with higher poverty levels are less likely to attend their appointments (O.R 0.93 (CI: 0.83-0.98) and 0.74 (CI: 0.66-0.85), respectively). We also found a relationship between the CHBM scores and the patient attendance probability. Average AUROC score for our prediction model is 0.9. CONCLUSION: In the case of Bogotá, our results highlight the need to develop education campaigns to address misconceptions about the disease mortality and treatment (aiming at decreasing perceived severity), particularly among younger patients living in extreme poverty. Additionally, it is important to conduct an economic evaluation of screening options to strengthen the cervical cancer screening program (to reduce perceived barriers). More widely, our prediction approach has the potential to improve the cost-effectiveness of behavioural interventions to increase attendance for screening in developing countries where funding is limited.

The dynamics of frailty development and progression in older adults in primary care in England (2006-2017): a retrospective cohort profile.

BACKGROUND: Frailty is a common condition in older adults and has a major impact on patient outcomes and service use. Information on the prevalence in middle-aged adults and the patterns of progression of frailty at an individual and population level is scarce. To address this, a cohort was defined from a large primary care database in England to describe the epidemiology of frailty and understand the dynamics of frailty within individuals and across the population. This article describes the structure of the dataset, cohort characteristics and planned analyses. METHODS: Retrospective cohort study using electronic health records. Participants were aged ≥50 years registered in practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre between 2006 to 2017. Data include GP practice details, patient sociodemographic and clinical characteristics, twice-yearly electronic Frailty Index (eFI), deaths, medication use and primary and secondary care health service use. Participants in each cohort year by age group, GP and patient characteristics at cohort entry are described. RESULTS: The cohort includes 2,177,656 patients, contributing 15,552,946 person-years, registered at 419 primary care practices in England. The mean age was 61 years, 52.1% of the cohort was female, and 77.6% lived in urban environments. Frailty increased with age, affecting 10% of adults aged 50-64 and 43.7% of adults aged ≥65. The prevalence of long-term conditions and specific frailty deficits increased with age, as did the eFI and the severity of frailty categories. CONCLUSION: A comprehensive understanding of frailty dynamics will inform predictions of current and future care needs to facilitate timely planning of appropriate interventions, service configurations and workforce requirements. Analysis of this large, nationally representative cohort including participants aged ≥50 will capture earlier transitions to frailty and enable a detailed understanding of progression and impact. These results will inform novel simulation models which predict future health and service needs of older people living with frailty. STUDY REGISTRATION: Registered on www.clinicaltrials.gov October 25th 2019, NCT04139278 .

An analytical framework for group simulation model building.

This paper presents a framework for understanding and improving the process of simulation model building involving a group of domain experts, classifying the different roles the model may play at various stages of its development. The framework consists of four different "object roles", defined along two dimensions: a functional dimension (boundary object vs. representational object) and a knowledge dimension (epistemic object vs. technical object). A model can take different roles during the development process, e.g. for facilitating communication, for gaining insight into the real-world system, or for experimentation and policy evaluation. The use of the framework is illustrated by two case studies in healthcare. Its relevance and applicability are examined through a survey on model use. The survey was conducted among a group of modelling consultants with experience of using both discrete-event simulation and system dynamics within the NHS, and indicated the potential usefulness of the framework.

Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand.

BACKGROUND: With the challenges that dengue fever (DF) presents to healthcare systems and societies, public health officials must determine where best to allocate scarce resources and restricted budgets. Constrained optimization (CO) helps to address some of the acknowledged limitations of conventional health economic analyses and has typically been used to identify the optimal allocation of resources across interventions subject to a variety of constraints. METHODS: A dynamic transmission model was developed to predict the number of dengue cases in Thailand at steady state. A CO was then applied to identify the optimal combination of interventions (release of Wolbachia-infected mosquitoes and paediatric vaccination) within the constraints of a fixed budget, set no higher than cost estimates of the current vector control programme, to minimize the number of dengue cases and disability-adjusted life years (DALYs) lost. Epidemiological, cost, and effectiveness data were informed by national data and the research literature. The time horizon was 10 years. Scenario analyses examined different disease management and intervention costs, budget constraints, vaccine efficacy, and optimization time horizon. RESULTS: Under base-case budget constraints, the optimal coverage of the two interventions to minimize dengue incidence was predicted to be nearly equal (Wolbachia 50%; paediatric vaccination 49%) with corresponding coverages under lower bound (Wolbachia 54%; paediatric vaccination 10%) and upper bound (Wolbachia 67%; paediatric vaccination 100%) budget ceilings. Scenario analyses indicated that the most impactful situations related to the costs of Wolbachia and paediatric vaccination with decreases/ increases in costs of interventions demonstrating a direct correlation with coverage (increases/ decreases) of the respective control strategies under examination. CONCLUSIONS: Determining the best investment strategy for dengue control requires the identification of the optimal mix of interventions to implement in order to maximize public health outcomes, often under fixed budget constraints. A CO model was developed with the objective of minimizing dengue cases (and DALYs lost) over a 10-year time horizon, within the constraints of the estimated budgets for vector control in the absence of vaccination and Wolbachia. The model provides a tool for developing estimates of optimal coverage of combined dengue control strategies that minimize dengue burden at the lowest budget.

The economic impact and cost-effectiveness of combined vector-control and dengue vaccination strategies in Thailand: results from a dynamic transmission model.

BACKGROUND AND AIMS: Dengue fever is a major public health problem in tropical/subtropical regions. Prior economic analyses have predominantly evaluated either vaccination or vector-control programmes in isolation and do not really consider the incremental benefits and cost-effectiveness of mixed strategies and combination control. We estimated the cost-effectiveness of single and combined approaches in Thailand. METHODS: The impacts of different control interventions were analysed using a previously published mathematical model of dengue epidemiology and control incorporating seasonality, age structure, consecutive infection, cross protection, immune enhancement and combined vector-host transmission. An economic model was applied to simulation results to estimate the cost-effectiveness of 4 interventions and their various combinations (6 strategies): i) routine vaccination of 1-year olds; ii) chemical vector control strategies targeting adult and larval stages separately; iii) environmental management/ public health education and awareness [EM/ PHEA]). Payer and societal perspectives were considered. The health burden of dengue fever was assessed using disability-adjusted life-years (DALYs) lost. Costs and effects were assessed for 10 years. Costs were discounted at 3% annually and updated to 2013 United States Dollars. Incremental cost-effectiveness analysis was carried out after strategies were rank-ordered by cost, with results presented in a table of incremental analysis. Sensitivity and scenario analyses were undertaken; and the impact and cost-effectiveness of Wolbachia was evaluated in exploratory scenario analyses. RESULTS: From the payer and societal perspectives, 2 combination strategies were considered optimal, as all other control strategies were dominated. Vaccination plus adulticide plus EM/ PHEA was deemed cost-effective according to multiple cost-effectiveness criteria. From the societal perspective, incremental differences vs. adulticide and EM/ PHEA resulted in costs of $157.6 million and DALYs lost of 12,599, giving an expected ICER of $12,508 per DALY averted. Exploratory scenario analyses showed Wolbachia to be highly cost-effective ($343 per DALY averted) vs. other single control measures. CONCLUSIONS: Our model shows that individual interventions can be cost-effective, but that important epidemiological reductions and economic impacts are demonstrated when interventions are combined as part of an integrated approach to combating dengue fever. Exploratory scenario analyses demonstrated the potential epidemiological and cost-effective impact of Wolbachia when deployed at scale on a nationwide basis. Our findings were robust in the face of sensitivity analyses.

Designing the blood supply chain: how much, how and where?

BACKGROUND: The topology of the blood supply chain network can take different forms in different settings, depending on geography, politics, costs, etc. Many developed countries are moving towards centralized networks. The goal for all blood distribution networks, regardless of topology, remains the same: to satisfy demand at minimal cost and minimal wastage. STUDY DESIGN AND METHODS: Mathematically, the blood supply system design can be viewed as a location-allocation problem, where the aim is to find the optimal location of collection and production facilities and to assign hospitals to them to minimize total system cost. However, most location-allocation models in the blood supply chain literature omit several important aspects of the problem, such as selecting amongst differing methods of collection and production. In this paper, we present a location-allocation model that takes these factors into account to support strategic decision-making at different levels of centralization. RESULTS: Our approach is illustrated by a case study (Colombia) to redesign the national blood supply chain under a range of realistic travel time limitations. For each scenario, an optimal supply chain configuration is obtained, together with optimal collection and production strategies. We show that the total costs for the most centralized scenario are around 40% of the costs for the least centralized scenario. CONCLUSION: Centralized systems are more efficient than decentralized systems. However, the latter may be preferred for political or geographical reasons. Our model allows decision-makers to redesign the supply network per local circumstances and determine optimal collection and production strategies that minimize total costs.

Simulation-optimization model for production planning in the blood supply chain.

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

Impact of combined vector-control and vaccination strategies on transmission dynamics of dengue fever: a model-based analysis.

Dengue fever is a vector-borne disease prevalent in tropical and subtropical regions. It is an important public health problem with a considerable and often under-valued disease burden in terms of frequency, cost and quality-of-life. Recent literature reviews have documented the development of mathematical models of dengue fever both to identify important characteristics for future model development as well as to assess the impact of dengue control interventions. Such reviews highlight the importance of short-term cross-protection; antibody-dependent enhancement; and seasonality (in terms of both favourable and unfavourable conditions for mosquitoes). The compartmental model extends work by Bartley (2002) and combines the following factors: seasonality, age-structure, consecutive infection by all four serotypes, cross-protection and immune enhancement, as well as combined vector-host transmission. The model is used to represent dengue transmission dynamics using parameters appropriate for Thailand and to assess the potential impact of combined vector-control and vaccination strategies including routine and catch-up vaccination strategies on disease dynamics. When seasonality and temporary cross-protection between serotypes are included, the model is able to approximate the observed incidence of dengue fever in Thailand. We find vaccination to be the most effective single intervention, albeit with imperfect efficacy (30.2 %) and limited duration of protection. However, in combination, control interventions and vaccination exhibit a marked impact on dengue fever transmission. This study shows that an imperfect vaccine can be a useful weapon in reducing disease spread within the community, although it will be most effective when promoted as one of several strategies for combating dengue fever transmission.

Professional perspectives on systemic barriers to admission avoidance: learning from a system dynamics study of older people's admission pathways.

BACKGROUND: There is debate worldwide about the best way to manage increased healthcare demand within ageing populations, particularly rising rates of unplanned and avoidable hospital admissions. OBJECTIVES: To understand health and social care professionals' perspectives on barriers to admission avoidance throughout the admissions journey, in particular: the causes of avoidable admissions in older people; drivers of admission and barriers to use of admission avoidance strategies; and improvements to reduce unnecessary admissions. DESIGN: A qualitative framework analysis of interview data from a System dynamics (SD) modelling study. METHODS: Semi-structured interviews were conducted with twenty health and social care professionals with experience of older people's admissions. The interviews were used to build understanding of factors facilitating or hindering admission avoidance across the admissions system. Data were analysed using framework analysis. RESULTS: Three overarching themes emerged: understanding the needs of the patient group; understanding the whole system; and systemwide access to expertise in care of older people. There were diverse views on the underlying reasons for avoidable admissions and recognition of the need for whole-system approaches to service redesign. CONCLUSIONS: Participants recommended system redesign that recognises the specific needs of older people, but there was no consensus on underlying patient needs or specific service developments. Access to expertise in management of older and frailer patients was seen as a barrier to admission avoidance throughout the system. IMPLICATIONS FOR PRACTICE: Providing access to expertise and leadership in care of frail older people across the admissions system presents a challenge for service managers and nurse educators but is seen as a prerequisite for effective admission avoidance. System redesign to meet the needs of frail older people requires agreement on causes of avoidable admission and underlying patient needs.

Modelling of Hampshire Adult Services--gearing up for future demands.

This paper describes a study to investigate future demand from older people for social care services in Hampshire, UK. The study used system dynamics to explore the significant challenges of an ageing population in the context of budget limitations. The results show that as anticipated, the numbers requiring care will increase considerably over the next 5 years. The effects of two possible interventions to reduce the impact of this are explored.

Mapping care pathways for the elderly.

PURPOSE: Aims to describe a project carried out within Hampshire Social Services investigating potential care pathways for older people after discharge from hospital and to show the potential of the simulation methodology in such situations. DESIGN/METHODOLOGY/APPROACH: A discrete-event simulation was used to determine the system capacities and to estimate the likely associated reimbursement costs. FINDINGS: A prototype simulation model was developed showing the potential value of this approach. RESEARCH LIMITATIONS/IMPLICATIONS: Restrictions in data access shifted the focus from quantitative service mapping to a more descriptive approach. PRACTICAL IMPLICATIONS: Currently, many older patients experience delayed discharge from acute beds because of capacity limitations in Social Services' traditional post-acute care services. At the same time, new regulations require Local Authorities to reimburse NHS Acute Trusts if hospital discharge is delayed solely due to inadequate provision of social care assessments and services. In order to overcome the so-called "bed-blocking" problem, a new range of services termed "Intermediate Care" has been introduced to offer alternative options for older patients. These services are examined in terms of capacity and appropriateness. ORIGINALITY/VALUE: This paper fulfils an identified need to record and evaluate the new post-acute packages introduced by the Social Services and NHS and proposes simulation as one of the most suitable methodologies for such objectives.