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.

Modelling lung cancer diagnostic pathways using discrete event simulation.

The United Kingdom has one of the poorest lung cancer survival rates in Europe. In this study, to help design and evaluate a single lung cancer pathway (SCP) for Wales, existing diagnostic pathways and processes have been mapped and then modelled with a discrete event simulation. The validated models have been used to provide key performance indicators and to examine different diagnostic testing strategies. Under the current diagnostic pathways, the mean time to treatment was 72 days for surgery patients, 56 days for chemotherapy patients, and 61 days for radiotherapy patients. Our research demonstrated that by ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 11 days from the current lung cancer pathway resulting in a 21% increase in patients receiving treatment within the Welsh Government set target of 62 days.

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.

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 empirical investigation of forecasting methods for ambulance calls - a case study.

A primary goal of emergency services is to minimise the response times to emergencies whilst managing operational costs. This paper is motivated by real data from the Welsh Ambulance Service which in recent years has been criticised for not meeting its eight-minute response target. In this study, four forecasting approaches (ARIMA, Holt Winters, Multiple Regression and Singular Spectrum Analysis (SSA)) are considered to investigate whether they can provide more accurate predictions to the call volume demand (total and by category) than the current approach on a selection of planning horizons (weekly, monthly and 3-monthly). Each method is applied to a training and test set and root mean square error (RMSE) and mean absolute percentage error (MAPE) error statistics are determined. Results showed that ARIMA is the best forecasting method for weekly and monthly prediction of demand and the long-term demand is best predicted using the SSA method.

Examining the diagnostic pathway for lung cancer patients in Wales using discrete event simulation.

BACKGROUND: UK's National Health Service (NHS) has one of the poorest lung cancer survival rates in Europe. To improve patient outcomes, a single cancer pathway was introduced in the NHS. In this study, a Discrete Event Simulation was developed to understand bottlenecks during lung cancer treatment. METHODS: This study focused on the lung cancer diagnostic pathways at two Welsh hospitals. Discrete Event Simulation is a computer-based method that has been effectively used in demand and capacity planning. In this study, simulation models were developed for the current and proposed single cancer pathways. The validated models were used to provide Key Performance Indicators. Several "what-if" scenarios were considered for the current and proposed pathways. RESULTS: Under the current diagnostic pathway, the mean time to treatment for a surgery patient was 68 days at the Royal Glamorgan Hospital and 79 days at Prince Charles Hospital. For chemotherapy patients, the mean time to treatment was 52 days at the Royal Glamorgan Hospital and 57 days at Prince Charles Hospital. For radiotherapy patients, the mean time to treatment was 44 days at Royal Glamorgan Hospital and 54 days at Prince Charles Hospital. Ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 20 days from the current lung cancer pathway resulting in a 20-25% increase of patients receiving treatment within 62 days. Ensuring that patients begin their treatment within 21 days of diagnosis sees almost all patients comply with the 62-day target. CONCLUSIONS: Discrete Event Simulation coupled with a detailed statistical analysis provides a useful decision support tool which can be used to examine the current and proposed lung cancer pathways in terms of time spent on the pathway.

Factors influencing the delivery of cancer pathways: a summary of the literature.

PURPOSE: The study aims to summarise the literature on cancer care pathways at the diagnostic and treatment phases. The objectives are to find factors influencing the delivery of cancer care pathways; to highlight any interrelating factors; to find gaps in the literature concerning areas of research; to summarise the strategies and recommendations implemented in the studies. DESIGN/METHODOLOGY/APPROACH: The study used a qualitative approach and developed a causal loop diagram to summarise the current literature on cancer care pathways, from screening and diagnosis to treatment. A total of 46 papers was finally included in the analysis, which highlights the recurring themes in the literature. FINDINGS: The study highlights the myriad areas of research applied to cancer care pathways. Factors influencing the delivery of cancer care pathways were classified into different albeit interrelated themes. These include access barriers to care, hospital emergency admissions, fast track diagnostics, delay in diagnosis, waiting time to treatment and strategies to increase system efficiency. ORIGINALITY/VALUE: As far as the authors know, this is the first study to present a visual representation of the complex relationship between factors influencing the delivery of cancer care pathways.

Resource optimization for cancer pathways with aggregate diagnostic demand: a perishable inventory approach.

This work proposes a novel framework for planning the capacity of diagnostic tests in cancer pathways that considers the aggregate demand of referrals from multiple cancer specialties (sites). The framework includes an analytic tool that recursively assesses the overall daily demand for each diagnostic test and considers general distributions for both the incoming cancer referrals and the number of required specific tests for any given patient. By disaggregating the problem with respect to each diagnostic test, we are able to model the system as a perishable inventory problem that can be solved by means of generalized G/D/C queuing models, where the capacity [Formula: see text] is allowed to vary and can be seen as a random variable that is adjusted according to prescribed performance measures. The approach aims to provide public health and cancer services with recommendations to align capacity and demand for cancer diagnostic tests effectively and efficiently. Our case study illustrates the applicability of our methods on lung cancer referrals from UK's National Health Service.

Modelling for the proposed roll-out of the '111' service in Wales: a case study.

NHS Direct Wales provides a single point of access where members of the public can telephone and seek medical support and/or advice. The service is provided for all the Health Boards in Wales by a single virtual call centre run from a main location in Swansea with 2 satellite locations. Patients in Wales can also access a local General Practitioner service during the evenings and at weekends, by phoning their Out of Hours service. The introduction of a '111' service is intended to combine these two operations on a pan-Wales basis using the existing NHS Direct Wales call centre and staff, with the existing Health Board Out of Hours 'hubs'. The merger of the two services is intended to improve the overall performance of both services. This paper focuses on the planned introduction of '111' in Cwm Taf and Hywel Dda University Health Boards. The purpose of the case study was to support the merger of the two telephony systems from both an organisational and service delivery perspective, by developing a Discrete Event Simulation to model the impact on service levels and staffing. In particular, to examine the percentage increase / decrease in the staffing requirements needed under partial or full integration of the two services. The results from the scenario analysis highlight that extra staffing resources would be required in certain groups (nurses and call handlers) whilst savings could be achieved in others, provided that there wasn't an increase in call volume after implementation of the new service.

A quantitative assessment of the risks from illegally imported meat contaminated with foot and mouth disease virus to Great Britain.

Foot and mouth disease (FMD) is considered by many as the most important animal disease in the world. FMD is highly contagious and outbreaks incur significant costs as affected countries are severely limited in their ability to trade. A number of trade commodities may be contaminated with FMD virus (FMDV) including animal products, for example, meat. As a member of the European Union, Great Britain (GB) has put in place a number of regulations to prevent the importation of pathogens in imported meat products. However, the illegal importation of meat provides a route by which safety controls may be circumvented and meat from FMD affected areas may be imported. This study assesses the FMD infection risk posed to the livestock population of GB from the illegal importation of meat, and estimates the major contributors to this overall risk, through the development of a quantitative risk assessment model. From model results, the total amount of illegal meat entering GB each year is estimated on average to be 11,875 tonnes. with 90% certainty that this is between 4,398 and 28,626 tonnes per year; of which between 64.5 and 565 kg are contaminated with FMDV. This flow of illegal meat results in an estimate of a frequency of FMD infection in GB livestock of 0.015 cases of infected animals per year, with 90% certainty it is between 0.0017 and 0.053. Imports from the region Near and Middle East account for 47% of this risk, and 68% of the risk is attributed to bone-in and dried de-boned products.