Health Policy and Management

The COVID-19 pandemic - as a massive disruption - has significantly increased the need for medical services putting an unprecedented strain on health systems. This study presents a robust location-allocation model under uncertainty to increase the resiliency of health systems by applying alternative resources, such as backup and field hospitals and student nurses. A multi-objective optimization model is developed to minimize the system's costs and maximize the satisfaction rate among medical staff and COVID-19 patients. A robust approach is provided to face the data uncertainty, and a new mathematical model is extended to linearize a nonlinear constraint. The ICU beds, ward beds, ventilators, and nurses are considered the four main capacity limitations of hospitals for admitting different types of COVID-19 patients. The sensitivity analysis is performed on a real-world case study to investigate the applicability of the proposed model. The results demonstrate the contribution of student nurses and backup and field hospitals in treating COVID-19 patients and provide more flexible decisions with lower risks in the system by managing the fluctuations in both the number of patients and available nurses. The results showed that a reduction in the number of available nurses incurs higher costs for the system and lower satisfaction among patients and nurses. Moreover, the backup and field hospitals and the medical staff elevated the system's resiliency. By allocating backup hospitals to COVID-19 patients, only 37% of severe patients were lost, and this rate fell to less than 5% after establishing field hospitals. Moreover, medical students and field hospitals curbed the costs and increased the satisfaction rate of nurses by 75%. Finally, the system was protected from failure by increasing the conservatism level. With a 2% growth in the price of robustness, the system saved 13%.

Background: Health systems are increasingly implementing policy-driven programs to incentivize performance using contracts, scorecards, rankings, rewards, and penalties. Studies of these “Performance Management” (PM) programs have identified unintended negative consequences. However, no single comprehensive typology of the negative and positive unintended consequences of PM in healthcare exists and most studies of unintended consequences were conducted in England or the United States. The aims of this study were: (1) To develop a comprehensive typology of unintended consequences of PM in healthcare, and (2) To describe multiple stakeholder perspectives of the unintended consequences of PM in cancer and renal care in Ontario, Canada. Methods: We conducted a rapid review of unintended consequences of PM in healthcare (n = 41 papers) to develop a typology of unintended consequences. We then conducted a secondary analysis of data from a qualitative study involving semi-structured interviews with 147 participants involved with or impacted by a PM system used to oversee 40 care delivery networks in Ontario, Canada. Participants included administrators and clinical leads from the networks and the government agency managing the PM system. We undertook a hybrid inductive and deductive coding approach using the typology we developed from the rapid review. Results: We present a comprehensive typology of 48 negative and positive unintended consequences of PM in healthcare, including five novel unintended consequences not previously identified or well-described in the literature. The typology is organized into two broad categories: unintended consequences on (1) organizations and providers and on (2) patients and patient care. The most common unintended consequences of PM identified in the literature were measure fixation, tunnel vision, and misrepresentation or gaming, while those most prominent in the qualitative data were administrative burden, insensitivity, reduced morale, and systemic dysfunction. We also found that unintended consequences of PM are often mutually reinforcing. Conclusions: Our comprehensive typology provides a common language for discourse on unintended consequences and supports systematic, comparable analyses of unintended consequences across PM regimes and healthcare systems. Healthcare policymakers and managers can use the results of this study to inform the (re-)design and implementation of evidence-informed PM programs.

Purpose: Understanding how patients and families experience, respond to, and cope with the financial burden associated with cancer could assist in identifying future research priorities and developing relevant interventions to assist patients and families facing financial hardship. This systematic review offers a synthesis of the qualitative evidence on cancer-related financial toxicity from the perspective of patients and/or informal caregivers in publicly funded healthcare systems where it might be expected that financial protection would be strongest. Methods: Articles published between January 1, 2005, and March 7, 2019, describing financial burden experienced by cancer patients and/or informal caregivers were identified using OVID MEDLINE Embase and PsychInfo, CINAHL, Business Source Complete, and EconLit databases. English language, peer-reviewed qualitative papers describing studies conducted in countries with predominantly publicly funded healthcare systems were eligible. Quality appraisal was conducted using CASP Quality Appraisal Checklist. Narrative synthesis was completed with extracted data and themes identified inductively by all team members. Results: Twelve articles were identified as eligible. Articles reported on 10 studies conducted in Australia (n = 2), Canada (n = 2), England (n = 3), and Ireland (n = 3). The papers illustrate the complexity and multifaceted nature of experiencing financial hardship following a cancer diagnosis. Each contributes to the whole picture, providing different viewpoints regarding various and diverse forms of financial hardship, the process of confronting financial challenges, working to overcome difficulties, and coping with the resulting impacts. Synthesis of the studies suggested five themes: household and medical costs are increased, financial resources are reduced, financial change and financial hardship vary, financial hardship has many consequences, various mitigation strategies are used. Conclusion: Cancer patients and their families can experience a broad range of impacts when they are facing and coping with financial toxicity. Consistent gaps in support highlight that strategies to mitigate financial effects related to travel, accommodation, medications, family support, and income replacement are needed for many patients and families even in the context of publicly funded healthcare systems. Implications for Cancer Survivors: Survivors need to be informed early in their cancer experience about the potential financial burden associated with cancer treatment and its impact on survivors and their family members.

Objective: To assess the impacts of multiple chronic conditions (MCC) and frailty on 30-day post-discharge readmission and mortality among older patients with delayed discharge. Data source/extraction: We used a retrospective cohort of older patients in the Discharge Abstract Database (DAD) between 2004 and 2017 in Ontario, Canada. We extracted data on patients aged ? 65 who experienced delayed discharge during hospitalization (N = 353,106). Study design: We measured MCC and frailty using the Elixhauser Comorbidity Index (ECI) and the Hospital Frailty Risk Score (HFRS), respectively. We used multinomial logistic regression to model the main and interactive effects of MCC and frailty on the adverse outcomes. Principal findings: After adjusting for sex, discharge destination, urban/rural residency, wait time for alternative care, and socioeconomic status, the coexistence of MCC and high frailty increased the relative risk of 30-day mortality and readmission when compared to the references group, i.e., non-MCC patients with low-to-moderate frailty. Conclusions: Multimorbidity and frailty each provide unique information about adverse outcomes among older patients with delayed discharge but are most informative when examined in unison. Implications for health policy: To minimize the risk of adverse outcomes among older delayed discharge patients, discharge planning must be tailored to their concurrent multimorbidity and frailty status.

How do formal time allocations in teams affect team learning trajectories and performance? We argue that allocating more time for transition phases induces steeper learning trajectories that engender a positive group atmosphere, which in turn improves team performance by improving coordination quality. We tested our hypotheses in a laboratory experiment in which teams worked on a creative design task over multiple iterations. Using a latent growth modeling approach, we found that teams with shorter action and longer transition phases during prototyping had lower initial performance but steeper learning trajectories, which indirectly led to better final team performance.

Objective: Health care organizations monitor hundreds of performance indicators. It is unclear what processes and criteria organizations use to identify the indicators they use, who is involved in these processes, how performance targets are set, and what the impacts of these processes are. The purpose of this study is to synthesize international approaches to indicator selection and develop a standardized process framework. Methods: Using the PubMed and Web of Science search engines, a scoping review of peer reviewed and grey literature following PRISMA-ScR guidelines was conducted to identify documents describing indicator selection processes used by health systems. English-language papers from 11 countries published from 2010 to 2020 were included. Papers were thematically analyzed to develop a standardized process framework. Results: The review included 33 peer-reviewed papers and 11 grey-literature documents. While there are common practices used in health care to select indicators, no single standardized process framework for indicator selection exists. Arbitrary or incomplete indicator selection processes risk over-measurement, lack of alignment with strategic and operational goals, lack of support by endusers, and paralyzed decision-making ability. By consolidating international practices, we developed the 5-P indicator selection process framework to mitigate process risks and support high-quality indicator selection processes. Conclusion: The 5-P indicator selection process framework consists of five domains and 17 elements, and offers health care agencies a practical structure they can use to design indicator selection processes. The framework also provides researchers with a basis by which the implementation of these processes may be evaluated.

Purpose: Internationally, there has been a move towards more recovery-oriented mental health policies for people living with mental illness, and some countries have included well-being as a population-level objective. In practice, these policy objectives can be difficult to achieve because of deeply rooted policy legacies, including a biomedical approach to care and the stigma associated with mental illness. The purpose of this paper is to investigate how interventions that operate outside the formal mental health system, such as recovery colleges (RCs), may advance these policy objectives more easily than efforts at broader system reform. Design/methodology/approach: This study conducted a scoping review to explore the features and context of RCs that make the model an attractive and feasible opportunity to advance a recovery and well-being agenda. Our research is motivated by the initial and growing adoption of RCs by the Canadian Mental Health Association. This paper applies the consolidated framework for implementation research to analyse features of the model and the context of its implementation in Canada. Findings: The RC’s educational approach, adaptability, coproduced nature and positioning outside the formal mental health system are key features that facilitate implementation without disrupting deeply entrenched policy legacies. Other facilitators in the Canadian context include the implementing organisation’s independence from government, its federated structure and the model’s alignment with national policy objectives. Originality/value: This paper highlights how interventions outside the formal mental healthcare system can promote stated recovery and well-being policy goals.

Designing within complex service systems implies navigating across a plurality of norms and beliefs that multiple stakeholder groups uphold, designers included. Transformational processes may be challenged by minimum, moderate, or extensive conflict depending on the centrality or compatibility of competing logics. This article reflects on how the complexity inherent in higher level institutional orders of society can support or inhibit the potential of co-design in complex systems, particularly in the public sector. Using the context of public mental healthcare transformation as a backdrop, we identified and reflected on four predominant logics: the logic of state; the logic of market; the logic of profession; and the logic of community. We then developed a set of tools to support reflexivity—the excel Logic Multiplicity Workbook and the Layers of Logics Map—that can be used to take project logics snapshots to represent the perceived strength of project stakeholder logics at the micro, meso, and macro levels and their centrality and compatibility. Three co-design project examples were used to retrospectively develop and refine these tools, and support the process of making explicit the role of competing logics in project challenges or triumphs. While we acknowledge that logics are often highly institutionalized and difficult to become aware of, we value as fundamental the creation of tools to better enable designers to consciously adopt adequate strategies to navigate this complexity.

Background: Co-design is an approach to engaging stakeholders in health and social system change that is rapidly gaining traction, yet there are also questions about the extent to which there is meaningful engagement of structurally vulnerable communities and whether co-design leads to lasting system change. The McMaster University Co-Design Hub with Vulnerable Populations Hub ('the Hub') is a three-year interdisciplinary project with the goal of facilitating partnerships, advancing methods of co-design with vulnerable populations, and mobilising knowledge. Aims and objectives: A developmental evaluation approach inspired by experience-based co-design was used to co-produce a theory of change to understand how the co-design process could be used to creatively co-design a co-design hub with structurally vulnerable populations. Methods: Twelve community stakeholders with experience participating in a co-design project were invited to participate in two online visioning events to co-develop the goals, priorities, and objectives of the Hub. Qualitative data were analysed using a thematic content analysis approach. Findings: A theory of change framework was co-developed that outlines a future vision for the Hub and strategies to achieve this, and a visual graphic is presented. Discussion and conclusions: Through critical reflection on the work of the Hub, we focus on the co-creative methods that were applied when co-designing the Hub's theory of change. Moreover, we illustrate how co-creative processes can be applied to embrace the complexity and vulnerability of all stakeholders and plan for system change with structurally vulnerable populations.

Objective: Although vaccines are one of the most cost-effective, low-risk healthcare approaches that save thousands of lives every year, paradoxical fear about vaccine safety is a major roadblock for achieving widespread vaccination coverage. The objective of this study is to change public perception of vaccine safety by presenting real-world incidence of adverse events following immunization (AEFIs). Methods: In this study, we used Canadian post-market adverse events data to estimate the real-world risk of AEFI and benchmarked them against five commonly used drug types—ACE inhibitors, beta2 adrenergic receptors, penicillins, proton pump inhibitors, and HMG-CoA reductase inhibitors. Results: Our analysis shows that post-market AEFIs are rare, and vaccination generally carries a significantly lower risk compared to some commonly used medicinal product types. Conclusion: Despite some limitations with using post-trial adverse events data, we believe that the evidence presented in this study, especially the comparative risk analysis between vaccines and medicinal products, when communicated through proper channels, can help vaccine-hesitant individuals overcome their perceived safety concerns with regard to vaccines.

Purpose: The number of older cancer survivors is growing rapidly and expected to double through the next decade. Survivors can face challenges from treatment as well as other co-morbid conditions which may influence quality of living and generate distress. Understanding more about factors influencing whether older cancer survivors receive the help they desire is important for cancer program planning. The purpose of this analysis was to understand relationships between income and emotional/practical concerns, help-seeking experiences and unmet needs of adults 65+ years one to three years following cancer treatment. Materials and Methods: A survey was conducted with randomly selected Canadian cancer survivors about their survivorship care. Drawing from these publicly available data, this secondary analysis examines prevalence of concerns, help-seeking, receipt of help, reasons for not seeking help, responses to information questions, and overall unmet needs for trends across income groups. Results: 7975 respondents 65+ years responded, of which the 5891 (73.9%) indicating annual household income were analyzed. Over 80% responded to questions regarding emotional/practical concerns following treatment with the largest proportions reporting emotional concerns for anxiety/fear of cancer returning (63%) and depression (49%), and practical concerns regarding transportation for appointments (33%) and paying healthcare bills (31%). Individuals with household incomes <$25,000 reported higher levels of concern than other income groups and higher proportions sought assistance for their concerns. Across income levels, 20% reported difficulty finding assistance to address their concerns. Discussion: Older cancer survivors across all income categories reported emotional/practical concerns, lack of information about these issues, and unmet needs regarding both emotional and practical concerns. Many encountered challenges obtaining help with those in lower income categories more severely affected despite Canada's universal health care system. Financial burden ought to be assessed with older survivors on an on-going basis to ensure relevant intervention.

Traditionally, economic evaluations are based on clinical trials with well-defined patient populations that exclude many patient types. By contrast, studies that incorporate general patient populations end up including those in lower income categories, some of whom have significant financial burdens (often described as financial toxicity) related to their care. Consideration of these patient burdens when examining the incremental cost-effectiveness of newer treatments from a clinical trial perspective can result in differing conclusions regarding cost-effectiveness. The challenge is to reliably assess the link between financial toxicity, quality of life and potential decisions to forego or delay care. It is also well-documented that these financial effects are not evenly distributed across populations, with those with low income and of black or Latino decent being most affected. There is a paucity of literature in this space, but some of the early work has suggested that for lung, breast, colorectal and ovarian cancers there are poorer quality-of-life scores and/or shorter overall survival for those experiencing financial toxicity. Hence, we may see both a lower quality of life and a shorter duration of life for these populations. If this is the case, additional considerations include: are the benefits of newer, more-expensive treatment strategies muted by the lack of adherence to these newer treatments due to financial concerns, and, if true, can these effects be effectively quantified as “real-world” outcomes? This rapid review examines these possibilities and the steps that may be required to examine this reliably.

How does leadership emerge and function when multiple health care organizations come together to form a network? In this qualitative comparative case study, we draw on distributed leadership theory to examine the leadership practices that manifested during the implementation of three coordinated care networks. Thirty leaders and care providers participated in semistructured interviews. Interview data were inductively analyzed using thematic analysis. Although established in response to the same policy initiative, each case differed in its leadership approach and implementation strategy. We found that manifestation of distributed leadership was contingent on the presence of an individual leader who acted as a unifying force across their respective network. Our findings suggest that policies to encourage the development of interorganizational networks should include sufficient resources to support an individual leader who enables distributed leadership.

Background: Out-of-pocket costs (OOPC) associated with treatment have significant implications on quality of life and survival in cancer patients. Head and neck cancer patients face unique treatment-related challenges, but to date OOPC have been understudied in this population. Aims: This study aims to identify and measure OOPC for patients with head and neck cancer (HNC) in Ontario. Methods: HNC patients between 2015 and 2018 at Princess Margaret Cancer Centre in Toronto were recruited. Participants completed OOPC questionnaires and lost income questions during radiation, post-surgery, and 3, 6, 12, and 24 months after completion of treatment. Associations between OOPC and treatment modality and disease site were tested with multivariable hurdle regression. Results: A total of 1545 questionnaires were completed by 657 patients. Median estimated OOPC for the total duration of treatment for participants undergoing chemoradiation was $1452 [$0–14 616], for surgery with adjuvant radiation or chemoradiation (C/RT) was $1626, for radiation therapy alone was $635, and for surgery alone was $360. The major expenses for participants at the mid-treatment time-point was travel (mean $424, standard error of the mean [SEM] $34) and meals, parking, and accommodations (mean $617, SEM $67). In multivariable analysis, chemoradiation, surgery with C/RT, and radiation were associated with significantly higher OOPC than surgery alone during treatment (791% higher, p <.001; 539% higher, p <.001; 370% higher, p <.001 respectively) among patients with non-zero OOPC. Participants with non-zero OOPC in the laryngeal cancer group paid 49% lower OOPC than those with oropharyngeal cancers in adjusted analysis (p =.025). Conclusions: Patients undergoing treatment for HNC pay significant OOPC. These costs are highest during treatment and gradually decrease over time. OOPC vary by patient demographics, clinical factors, and, in particular, treatment modality.

The objective of this study was to explore the relationship among income and emotional/practical concerns, help-seeking and unmet needs for cancer survivors aged 18 to 64 years one to three years after treatment. A cross-sectional survey was mailed in 2016 to 40,790 survivors randomly selected from 10 Canadian provincial cancer registries. Thirty-three percent responded. A trend analysis was conducted for survivors most likely to be in the workforce exploring the relationship across four income levels and emotional/practical concerns, whether help was sought for identified concerns, and whether help was received. A total of 4,264 respondents, aged 18–64, provided useable data with breast (34.4%) and colo-rectal (15.0%) accounting for the primary cancer type and 32.0% reporting annual household incomes of <$50,000. More than 94% of respondents indicated having emotional or practical concerns. Between one-third and one-half of the respondents sought help for their concerns and, of those, between one-third and one-half experienced difficulty finding help or did not obtain assistance. Significant trends across income categories indicated greater percentages of those in lower income categories experienced emotional and practical concerns, rated their concerns as ‘big’, sought help, and had difficulty finding help to address their concerns. Clearly adult cancer survivors experience emotional and practical concerns. Healthcare professionals have important roles monitoring these concerns and connecting those who desire help to relevant services. Opportunities should be given to individuals, regardless of income level, to indicate if they have concerns and if they would like assistance.

Perspectives of cancer survivors, caregivers, and social workers as key stakeholders on the clinical management of financial toxicity (FT) are critical to identify opportunities for better FT management. Semi-structured interviews (cancer survivors, caregivers) and a focus group (social workers) were undertaken using purposive sampling at a quaternary public hospital in Australia. People with any cancer diagnosis attending the hospital were eligible. Data were analysed using inductive-deductive content analysis techniques. Twenty-two stakeholders (n = 10 cancer survivors of mixed-cancer types, n = 5 caregivers, and n = 7 social workers) participated. Key findings included: (i) genuine concern for FT of cancer survivors and caregivers shown through practical support by health care and social workers; (ii) need for clarity of role and services; (iii) importance of timely information flow; and (iv) proactive navigation as a priority. While cancer survivors and caregivers received financial assistance and support from the hospital, the lack of synchronised, shared understanding of roles and services in relation to finance between cancer survivors, caregivers, and health professionals undermined the effectiveness and consistency of these services. A proactive approach to anticipate cancer survivors’ and caregivers’ needs is recommended. Future research may develop and evaluate initiatives to manage cancer survivors and families FT experiences and outcomes.

Importance: To our knowledge, there have been no studies that estimated the short-, mid-, and long-term effects on cancer survivors' labor market earnings using administrative data. Objective: To estimate the change in labor market earnings due to cancer diagnosis stratified by cancer type and age category. Design, Setting, and Participants: This population-based cohort study used a retrospective analysis of Statistics Canada's administrative linkage file, which includes microdata from the 1991 Census, the Canadian Cancer Registry, mortality records, and personal income tax files. Participants included patients newly diagnosed with cancer from 1992 to 2008. All statistical analyses were finished on September 30, 2020. Exposures: Cancer diagnosis using the International Classification of Diseases, Ninth Revision, and the International Classification of Diseases, Tenth Revision. Main Outcomes and Measures: Annual and percent change in labor market earnings. The empirical strategy used a combination of the Mahalanobis distance and propensity score matching method and the difference-in-difference regression method to select a control group similar to the cancer survivors in this study and assess the association of the cancer diagnosis with labor market earnings, respectively. Results: A total of 59532 patients with cancer and 243446 patients without cancer were included in the main analysis. The mean (SD) age was similar between the matched treatment and control cohort (49.70 [8.1] years vs 49.68 [7.2] years), as was the proportion of females (0.49 vs 0.49), and the individual reported income ($37 937 [$18 645] vs $37 396 [$16 876]). The results showed the negative associations of cancer with labor market earnings. Additionally, the severity of the cancer was associated with labor market earnings, where cancer survivors with a severe type of cancer in terms of the 5-year survival rate are shown to have a larger and more persistent earnings difference compared with the control group. Conclusions and Relevance: The findings of this cohort study suggest that labor market earnings losses are associated with a cancer diagnosis. A better understanding of the loss of labor market earnings following cancer diagnosis and by cancer type can play an important role in starting a dialogue in future policy initiatives to mitigate the financial burden faced by cancer survivors..

Goal-oriented care is an approach to care delivery that uses patient-identified goals to drive care planning. Implementing goal-oriented care requires team members to cognitively shift the focus from “what is the matter” to “what matters to patients,” and align their mental models of what it means to care for patients. Yet, no empirical studies of goal-oriented care apply evidence from the cognitive sciences, such as Shared Mental Model (SMM) theory. We conducted a qualitative case study of an interprofessional team that adopted goal-oriented care in Vermont, US (n = 18). Guided by SMM theory, we distinguished between task-related and team-related mental models. We used framework analysis and qualitative content analysis to determine mental model content and similarity. The most shared content areas were operationalizing goal-oriented care, engaging in formal and informal communication, taking a “whole-person” approach, taking a team approach, and building trusting relationships with patients and with other team members. Trust was the only construct that spanned both task and team mental model categories, highlighting the importance of both intra-team trust and provider-patient trust to the implementation of goal-oriented care. Team members developed SMMs through training, regular meetings, and interactions during care delivery. This study provides insight into the cognitive mechanisms that underlie team-based goal-oriented care delivery, which can be used to inform implementation, training content, and future research.

Purpose: This paper examines how “quality” was framed in the design and implementation of a policy to reform hospital funding and associated care delivery. The aims of the study were: (1) To describe how government policy-makers who designed the policy and managers and clinicians who implemented the policy framed the concept of “quality” and (2) To explore how frames of quality and the framing process may have influenced policy implementation. Design/methodology/approach: The authors conducted a secondary analysis of data from a qualitative case study involving semi-structured interviews with 45 purposefully selected key informants involved in the design and implementation of the quality-based procedures policy in Ontario, Canada. The authors used framing theory to inform coding and analysis. Findings: The authors found that policy designers perpetuated a broader frame of quality than implementers who held more narrow frames of quality. Frame divergence was further characterized by how informants framed the relationship between clinical and financial domains of quality. Several environmental and organizational factors influenced how quality was framed by implementers. Originality/value: As health systems around the world increasingly implement new models of governance and financing to strengthen quality of care, there is a need to consider how “quality” is framed in the context of these policies and with what effect. This is the first framing analysis of “quality” in health policy.

Introduction Medical advancements are slow to reach the patient bedside due to issues with knowledge translation from preclinical studies. Multi-laboratory preclinical studies are a promising strategy for addressing the methodological deficiencies that weaken the translational impact of single laboratory findings. However, multi-laboratory preclinical studies are rare and difficult, requiring strong collaboration to plan and execute a shared protocol. In multiteam systems such as these, collaboration is enhanced when members have cohesive ways of thinking about their goals and how to achieve them-that is, when they have "shared mental models". In this research project, we will examine how members of Canada's first multi-laboratory preclinical study build shared mental models and collaborate in the execution of their study. Methods Six independent labs in Canada will conduct a preclinical study using a common protocol. To investigate mental models and collaboration in this multiteam system we will conduct a longitudinal qualitative study involving interviews at four time points, team observation, and document analysis. We will analyze interview transcripts using deductive coding to produce a matrix analysis of mental model content over time and inductive coding to produce a thematic analysis of members' experiences of collaboration over time. We will also triangulate data sources to "tell the story"of teamwork, capturing events and contextual information that explain changes in mental models and collaboration over time. Discussion This study will be one of the most comprehensive longitudinal analyses of a real-world multiteam system, and the first within a preclinical laboratory setting. The results will contribute to our understanding of collaboration in multiteam systems, an organizational form increasingly used to tackle complex scientific and social problems. The results will also inform the implementation of future multi-laboratory preclinical studies, enhancing the likelihood of effective collaboration and improved 'bench to bedside' translation.

Over the last 15 years, there has been a trend in Canada to centralise the provision of health services that were previously administratively and fiscally decentralised. Canadian policy rhetoric on centralisation often identifies improved innovation as an anticipated outcome. This paper challenges the assumed relationship between centralisation and innovation. We incorporate evidence from the management literature into the debate on the structure of health systems to explore the effects that centralisation is likely to have on innovation in health systems. The findings of this paper will be of interest to international policymakers, who are currently grappling with the prospect of maintaining a decentralised approach or adopting a more centralised health system structure in the future.

This study examines long-term care (LTC) discharge planning among older delayed discharge patients. While awaiting placements in alternate care such as LTC, these patients occupy hospital beds despite not requiring an intensive level of care. This study proposes a novel discharge decision model based on the Markov decision process (MDP) framework, which incorporates predictions regarding the patients' health trajectory and the associated hospital costs. Our machine learning (ML)-based predictive analytics allow for considering heterogeneous health transitions, hence personalized decision making, leading to valuable information for reducing hospital costs. We also develop data-driven cost functions using patient characteristics to estimate the person-level costs associated with the decisions in the optimization model, that is, whether or not to discharge a patient to LTC. The data analyses and cost estimations are based on large historical data collected over 13 years in Ontario, Canada. To solve the resulting high-dimensional MDP models, we develop an index policy, where each patient's index value is calculated using their health complexity (comorbidity), sex, age, and acute length of stay in the hospital. Using extensive numerical experiments, we illustrate the superior performance of the proposed index policy against some benchmarking policies and demonstrate the significance of predictive information in optimizing discharge decisions. Our results also indicate that the value of predictive information increases with LTC bed availability and decreases with hospital capacity. We also demonstrate that with the anticipated exacerbating mismatch between supply and demand, targeted prediction-driven discharge policies, such as the proposed index policy, become even more critical.