Abstract
Health systems globally are exploring new models of care to address the increasing demand for palliative, hospice, and end-of-life care. Yet few tools exist at the population level to explore “what if” scenarios and test, in a “cost avoidance environment,” the impact of these new care models on policy, workforce, technology, and funding. This article introduces the application of scenario-based “what if” thinking and discrete event simulation in strategic planning for a not-for-profit hospice organization. It will describe how a set of conceptual models was designed to frame discussions between strategic partners about the implications and alternatives in implementing a new, integrated service model for palliative and end-of-life care.
Introduction
Delivering palliative and end-of-life services is a complex problem for Canada’s health system, complicated by: a growing populace of seniors, living longer with increasing rates of chronic disease and requiring more health services; a delivery system that has long had a lack of coordination, variability in access to services, and an absence of choice of place to die; and a failure to link costs to quality and outcomes.
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Despite numerous studies and programs, an increasing number of people—living with multiple chronic conditions, life-limiting or terminal illnesses, or who are frail—are falling through the cracks. 2
These issues have significant implications for system capacity, resource utilization, and workforce skill and education requirements, ultimately impacting the effectiveness and quality of care for people at the end of their lives.
In July 2017, a not-for-profit hospice organization sought to explore plausible solutions to address these issues and to predict the expected costs and capacity requirements needed to sustain a new delivery model for end-of-life care. As the organization explores new ways to improve end-of-life care services in their local area, they wanted a strategic planning approach that had the potential to inform local partners and funders. Scenario-based “what if” thinking and discrete event simulation in strategic planning were selected to identify and assess options. Based on a review of evidence-based research, a set of conceptual models were designed to frame discussions between strategic partners about the implications and alternatives in implementing a new, integrated service model for palliative and end-of-life care.
This new planning approach would have to consider the ever-changing political and social environment, along with ongoing fiscal and bed constraints and a delivery system facing resource shortages as a result of an ageing workforce.
Background and significance
A much-quoted statement in the literature is “everyone wants to die at home”. Patient surveys suggest that 73% would prefer to die at home. 3 The review of the literature supports that most people want to remain at home as long as possible, but this does not mean that every patient has the desire to remain in their own home, and the choice to remain at home is not always stable as physical and psychological challenges increase.
The data suggests that 58% (5 out 9 daily deaths) of patients die in a hospital setting on Vancouver Island; this percentage includes deaths in acute care beds, emergency departments and intensive care units. End-of-life scenarios and simulation models employed in this process are aimed at avoiding the costs associated with a hospital death by integrating services to enable more people to live and die in their preferred care setting. 4 Research shows it costs the healthcare system about $39,947 to treat a patient with organ failure near the end-of-life, $36,652 for a terminal illness, and $31,881 for frailty. Sudden death is the least costly at $10,223. 5 The projection data suggest a significant increase in the number of organ system failure deaths between 2020 and 2035, yet 78% of patients who receive palliative and hospice services today have a diagnosis of cancer, presenting opportunities to explore “what if” scenarios for new ways of working. 6
As people age, the likelihood they will have at least one chronic disease rises dramatically, resulting in more people with complex care needs. With British Columbia’s growing and ageing population, it is projected that the prevalence of chronic conditions may increase by 58% over the next 25 years. 7,8 BC Stats estimates that the percentage of seniors aged 80+ in BC will grow from 4.4% of the population in 2012 to 7.4% of the population by 2036. 7 This has significant implications for health service use in British Columbia, especially access to end-of-life care services in the community.
Scenario thinking, planning, and conceptual end-of-life care modelling
Predicting future demand for palliative and end-of-life care requires creating systematic plausible “what if” scenarios and simulation models that provide insight into: how to improve delivery models that leverage and optimize resources; how resources can be leveraged and optimized; the associated delivery costs; and the impact of policy changes on population needs for end-of-life care.
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Scenario planning or scenario thinking provides a method for learning about the future by understanding the nature and impact of the most uncertain and important driving forces affecting our world. Developing alternative scenarios helps to bridge organizational strategy, environmental analysis, and forecasting 10 by shaping “what if” solutions, while assessing the risks and benefits of alternative decisions.
Seven key questions were identified to guide development of a simulation model and alternative scenarios to design a future state end-of-life care model that would inform the organization's resource use and strategic planning: What is the unmet need for palliative and end-of-life care in the aged 65 and older population; and given the changing patterns of complexity, how is it predicted to change over time? Who can benefit the most from palliative and end-of-life care, and how are these needs predicted to change over time given the changing therapies/technology interventions? What are the resource implications of adopting an early identification community-based palliative and end-of-life care model? What is the system-wide impact on hospital resources (beds and the workforce) when alternatives to dying in a hospital-care setting are provided? How does expanding palliative and end-of-life care to different trajectories of illness (e.g. cancer, organ failure, frailty, dementia and mental health) inform current and future service demand in a community? What are the combined effects of shifting services from acute care to a community-based model? What are the implications of these changes on academic institutions?
The scenarios and simulation model were developed through a process of internal and external engagement, demographic analysis, and research into the global evidence on innovative models of care, technology-enabled solutions, and performance outcomes. The “what if” model incorporated regional and local population demographics, social determinants of health, prevalence of disease using International Classification of Diseases, Tenth Revision CA, and findings from process maps, time and activity studies, information and document analysis, and review of patient charts. The model was based on published research 6,11 –14 and leveraged the evidence from the functional decline model 15 on trajectories of functional illness that illustrate the different patterns of decline depending on the disease type and/or cause of death (see Figure 1).
Key trajectories at end-of-life.
The team used the functional decline model 15 to develop the “what if” scenarios and undertook an analysis of the regional and provincial demographic data and prevalence of disease data, BC mortality database, Stats Canada, and other data sources to create the model’s illness trajectories (ie, cancer, organ failure, frailty, dementia, and mental health). 5 A number of access trajectory pathways were designed for patients, primary caregivers, and palliative care physicians. It was assumed that many patients would continue receiving primary care from their family physician or General Practitioner (GP), and there would be a number of people living in communities who are not attached to a GP or a practice. These factors were considered and incorporated into the simulation model (see Figure 2).
High-level pathway design forms the basis of the model from a conceptual standpoint.
The key question of “what if” was to understand the possible impact of changing health services for patients dying in the hospital and the impact of this model on the need for primary and community resources. It was assumed that if more people died at home, then more resources including nursing support might be required for community-based services. The model was extended to include these factors and to test the impact on policy and the workforce.
Development of the scenarios also included an analysis of aims and drivers of change, basic trends, key uncertainties, and scopes of practice. The following three scenarios were identified: doing the same—status quo; doing the bare minimum (eg, an expansion of community-based care); and the preferred option, a regional integrated palliative and end-of-life care model (e.g. inclusive all people 65+ with a life limiting or terminal illness diagnosis and regardless of location).
Designing the change with “what if?” and modelling
The scenarios and simulation model were designed to support the need to capture patient preferences for location of care and location of death, recognizing that these are not always the same thing and that preferences could change over time. 4 Incorporating these two key factors (location of care and place of death) reflects most government policy on inclusion of this information during goal planning with patients and their families in completing the advance care directive. 2
The simulation model considered the number of people aged 65 and older entering what will be their last year of life and followed the trajectory of illness (eg, organ failure, cancer, dementia, frailty) and care requirements through different stages of need (advanced, declining, and end-of-life). At each stage, there was the opportunity to recognize triggers as the basis for optimizing early identification and early intervention for people on the palliative and end-of-life care pathway.
These data were used to create the simulation, as illustrated in Figure 3. The simulation model demonstrates the complexity for end-of-life care incorporating the five trajectories and the “what if” questions set out below. These “what if” questions were developed to address government policy and strategic targets.
Palliative and end-of-life care simulation model.
What if?—Hospital in the Home (HITH) and Home-Based Hospice Care (HBHC), with 24/7 access to palliative care physicians and other specialists, were available to provide palliative and end-of-life care, wound care, and primary care to residents living in residential care facilities, structurally vulnerable populations, and Indigenous peoples? What if?— Hospice palliative care physicians and community palliative response teams collaborated with local partners to extend palliative and end-of-life care services into the community and residential care facilities for patients during the last year of life? What if?—Local partners agreed to joint e-referral and e-admission criteria and standardized assessments? What if?—Palliative care physicians worked collaboratively with primary and specialist groups to divert referrals from acute care to the community-based palliative care program? What if?—Technology-based surveillance tools were available to home and community care service providers? Would this solution result in earlier identification and intervention, reducing hospitalizations and deaths in a hospital setting? What if?—Current palliative and end-of-life care benefit programs for treatment and support services were designed using the trajectories of need model, expanding services to patients in their home during the last twelve (12) months of life? Would this potentially release acute hospital bed days and give people the choice to die at home? What if?—A mobile palliative care unit or a modified paramedic service was available to serve the rural and remote communities?
Results
From these broad “what if” questions, the simulation provided the following information: The number of people in the region (population of 755,000) whose end-of-life care needs will follow one of the five trajectories of illness—cancer, organ failure, frailty, dementia, and other terminal and sudden death, from 2020 to 2035; The impacts of changing demography, earlier recognition of end-of-life care needs and choice of place of death on community support, and the community palliative and end-of-life care workforce; A context within which local and regional partners can begin a discussion about strategy and working collaboratively toward an integrated approach to end-of-life care; and, A model that identifies the age 65+ palliative patient population groups. The data for the model incorporate clinical judgment about the needs of individuals in each of the selected trajectories that can be used for costing and workforce resource planning.
Linking scenario-based “what if”? simulation to healthcare operations management
Although operations research methods are used in industry and business operations to improve effectiveness and efficiency of processes, they are still relatively new in health and social care and across government services. 16,17 Yet, the feasibility and relevance of these methods to inform end-of-life care delivery system planning and decision-making for improving system efficiencies has been demonstrated. It is suggested that the issue is not the need for more research on palliative care practices, but rather the ability to implement what is already known to address large and growing unmet needs. 18
Based on a special report by the Economist Intelligence Unit, even if hospice palliative care improves quality and efficiencies, improving access will continue to be a challenge.
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The results from this project will help the organization’s management with: Costing—predicting future costs for the possible scenarios for each trajectory of illness; Capacity—predicting the necessary resources to manage each specific scenario, identification of potential services that can be shifted from acute care to the community (personnel and health professionals), and infrastructure costs; Operations—predicting day-to-day operations for each scenario including technology and documentation for management and reporting of outcomes; Management—developing detailed standard operating procedures and policies for all the activities and processes for each scenario and clinical pathway; and Strategic planning—optimizing resource utilization for delivering inpatient, community, and respite services for palliative and end-of-life care.
The next step for the hospice organization is to engage with service delivery and funding partners. This engagement will explore how the palliative and end-of-life care system should be redesigned in order to enhance capacity, improve resource utilization, address workforce skill and education requirements, and increase the effectiveness and quality of care for people at end-of-life. 20,21
Conclusion
Many organizations today are considering new models of care in their drive to reduce costs, save time, and increase safety. However, new models, particularly those that differ significantly from existing ones, can be risky to implement. Although there may be evidence of similar models working elsewhere, this is not always forthcoming, and these models may not be directly applicable to another setting, particularly when the model is novel and culturally based. Pilot projects to test out new services can be costly, disruptive, and time-consuming and they may not reveal the real impact of the service on the rest of the healthcare economy.
Utilizing “what if” visual and animated aspects of simulation can be invaluable in translating evidence-based practices into implementation. “What if” conversations and simulation modelling enable decision-makers to understand the factors that may impact system and patient outcomes while redesigning palliative and end-of-life care models that address cost, time, and safety issues.
Scenario-based “what if” and simulation modelling approaches can also inform the strategic planning process by taking into consideration future events based on population ageing, health status, and community resources to predict demand. Using this approach allows governments, funders, providers and clinical groups to plan preventive measures ahead of implementation to mitigate the impact of any possible unknown risks for each scenario.
Exploring new service and delivery models for palliative and end-of-life care means managing the complex relationships among stakeholders. “What if” conversations and simulations can also be used as a collaboration tool to generate discussions in order to uncover new insights that will further enhance the patient and family end-of-life experience and support after death. For this project, the approach and tools were used in combination with a comprehensive local assessment of end-of-life care services involving all key partners (Vancouver Island hospice facilities, private and publicly funded providers, and local health authorities), informed by best practice and provincial policy documents and intelligence related to geography based end-of-life strategies. The impact has been increased engagement and confidence, and buy-in to new ways of working.
In moving forward, the hospice organization is working with its key stakeholders to scope out plausible opportunities and develop a plan to implement the required system changes. A collaborative outcome mapping process 22 will be used to translate the strategic intentions derived from the “what if” scenarios and simulations into concrete outcomes and to gain agreement on the priority initiatives and the implementation rollout.