A population-based approach to integrated healthcare delivery: a scoping review of clinical care and public health collaboration.

BACKGROUND: A population-based approach to healthcare goes beyond the traditional biomedical model and addresses the importance of cross-sectoral collaboration in promoting health of communities. By establishing partnerships across primary care (PC) and public health (PH) sectors in particular, healthcare organizations can address local health needs of populations and improve health outcomes. The purpose of this study was to map a series of interventions from the empirical literature that facilitate PC-PH collaboration and develop a resource for healthcare organizations to self-evaluate their clinical practices and identify opportunities for collaboration with PH. METHODS: A scoping review was designed and studies from relevant peer-reviewed literature and reports between 1990 and 2017 were included if they met the following criteria: empirical study methodology (quantitative, qualitative, or mixed methods), based in US, Canada, Western Europe, Australia or New Zealand, describing an intervention involving PC-PH collaboration, and reporting on structures, processes, outcomes or markers of a PC-PH collaboration intervention. RESULTS: Out of 2962 reviewed articles, 45 studies with interventions leading to collaboration were classified into the following four synergy groups developed by Lasker's Committee on Medicine and Public Health: Coordinating healthcare services (n = 13); Applying a population perspective to clinical practice (n = 21); Identifying and addressing community health problems (n = 19), and Strengthening health promotion and health protection (n = 21). Furthermore, select empirical examples of interventions and their key features were highlighted to illustrate various approaches to implementing collaboration interventions in the field. CONCLUSIONS: The findings of our review can be utilized by a range of organizations in healthcare settings across the included countries. Furthermore, we developed a self-evaluation tool that can serve as a resource for clinical practices to identify opportunities for cross-sectoral collaboration and develop a range of interventions to address unmet health needs in communities; however, the generalizability of the findings depends on the evaluations conducted in individual studies in our review. From a health equity perspective, our findings also highlight interventions from the empirical literature that address inequities in care by targeting underserved, high-risk populations groups. Further research is needed to develop outcome measures for successful collaboration and determine which interventions are sustainable in the long term.

Out of sync: a Shared Mental Models perspective on policy implementation in healthcare.

The impact of policy ambiguity on implementation is a perennial concern in policy circles. The degree of ambiguity of policy goals and the means to achieve them influences the likelihood that a policy will be uniformly understood and implemented across implementation sites. We argue that the application of institutional and organisational theories to policy implementation must be supplemented by a socio-cognitive lens in which stakeholders' interpretations of policy are investigated and compared. We borrow the concept of 'Shared Mental Models' from the literature on industrial psychology to examine the microprocesses of policy implementation. Drawing from interviews with 45 key informants involved in the implementation of a hospital funding reform, known as Quality-Based Procedures in Ontario, Canada, we identify divergent mental models and explain how these divergences may have affected implementation and change management. We close with considerations for future research and practice.

Standardising costs or standardising care? Qualitative evaluation of the implementation and impact of a hospital funding reform in Ontario, Canada.

BACKGROUND: Since 2011, the Government of Ontario, Canada, has phased in hospital funding reforms hoping to encourage standardised, evidence-based clinical care processes to both improve patient outcomes and reduce system costs. One aspect of the reform - quality-based procedures (QBPs) - replaced some of each hospital's global budget with a pre-set price per episode of care for patients with specific diagnoses or procedures. The QBP initiative included publication and dissemination of a handbook for each of these diagnoses or procedures, developed by an expert technical group. Each handbook was intended to guide hospitals in reducing inappropriate variation in patient care and cost by specifying an evidence-based episode of care pathway. We explored whether, how and why hospitals implemented these episode of care pathways in response to this initiative. METHODS: We interviewed key informants at three levels in the healthcare system, namely individuals who conceived and designed the QBP policy, individuals and organisations supporting QBP adoption, and leaders in five case-study hospitals responsible for QBP implementation. Analysis involved an inductive approach, incorporating framework analysis to generate descriptive and explanatory themes from data. RESULTS: The 46 key informants described variable implementation of best practice episode of care pathways across QBPs and across hospitals. Handbooks outlining evidence-based clinical pathways did not address specific barriers to change for different QBPs nor differences in hospitals' capacity to manage change. Hospitals sometimes found it easier to focus on containing and standardising costs of care than on implementing standardised care processes that adhered to best clinical practices. CONCLUSION: Implementation of QBPs in Ontario's hospitals depended on the interplay between three factors, namely complexity of changes required, internal capacity for organisational change, and availability and appropriateness of targeted external facilitators and supports to manage change. Variation in these factors across QBPs and hospitals suggests the need for more tailored and flexible implementation supports designed to fit all elements of the policy, rather than one-size-fits-all handbooks alone. Without such supports, hospitals may enact quick fixes aimed mainly at preserving budgets, rather than pursue evidence- and value-based changes in care management. Overestimating hospitals' change management capacity increases the risk of implementation failure.

Adoption of high technology medical imaging and hospital quality and efficiency: Towards a conceptual framework.

Measuring the value of medical imaging is challenging, in part, due to the lack of conceptual frameworks underlying potential mechanisms where value may be assessed. To address this gap, this article proposes a framework that builds on the large body of literature on quality of hospital care and the classic structure-process-outcome paradigm. The framework was also informed by the literature on adoption of technological innovations and introduces 2 distinct though related aspects of imaging technology not previously addressed specifically in the literature on quality of hospital care: adoption (a structural hospital characteristic) and use (an attribute of the process of care). The framework hypothesizes a 2-part causality where adoption is proposed to be a central, linking factor between hospital structural characteristics, market factors, and hospital outcomes (ie, quality and efficiency). The first part indicates that hospital structural characteristics and market factors influence or facilitate the adoption of high technology medical imaging within an institution. The presence of this technology, in turn, is hypothesized to improve the ability of the hospital to deliver high quality and efficient care. The second part describes this ability throughout 3 main mechanisms pointing to the importance of imaging use on patients, to the presence of staff and qualified care providers, and to some elements of organizational capacity capturing an enhanced clinical environment. The framework has the potential to assist empirical investigations of the value of adoption and use of medical imaging, and to advance understanding of the mechanisms that produce quality and efficiency in hospitals.

Understanding relevance of health research: considerations in the context of research impact assessment.

BACKGROUND: With massive investment in health-related research, above and beyond investments in the management and delivery of healthcare and public health services, there has been increasing focus on the impact of health research to explore and explain the consequences of these investments and inform strategic planning. Relevance is reflected by increased attention to the usability and impact of health research, with research funders increasingly engaging in relevance assessment as an input to decision processes. Yet, it is unclear whether relevance is a synonym for or predictor of impact, a necessary condition or stage in achieving it, or a distinct aim of the research enterprise. The main aim of this paper is to improve our understanding of research relevance, with specific objectives to (1) unpack research relevance from both theoretical and practical perspectives, and (2) outline key considerations for its assessment. APPROACH: Our approach involved the scholarly strategy of review and reflection. We prepared a draft paper based on an exploratory review of literature from various fields, and gained from detailed and insightful analysis and critique at a roundtable discussion with a group of key health research stakeholders. We also solicited review and feedback from a small sample of expert reviewers. CONCLUSIONS: Research relevance seems increasingly important in justifying research investments and guiding strategic research planning. However, consideration of relevance has been largely tacit in the health research community, often depending on unexplained interpretations of value, fit and potential for impact. While research relevance seems a necessary condition for impact - a process or component of efforts to make rigorous research usable - ultimately, relevance stands apart from research impact. Careful and explicit consideration of research relevance is vital to gauge the overall value and impact of a wide range of individual and collective research efforts and investments. To improve understanding, this paper outlines four key considerations, including how research relevance assessments (1) orientate to, capture and compare research versus non-research sources, (2) consider both instrumental versus non-instrumental uses of research, (3) accommodate dynamic temporal-shifting perspectives on research, and (4) align with an intersubjective understanding of relevance.

Using decision trees for measuring gender equity in the timing of angiography in patients with acute coronary syndrome: a novel approach to equity analysis.

BACKGROUND: Methods to measure or quantify equity in health care remain scarce, if not difficult to interpret. A novel method to measure health equity is presented, applied to gender health equity, and illustrated with an example of timing of angiography in patients following a hospital admission for an acute coronary syndrome. METHODS: Linked administrative hospital discharge and survey data was used to identify a retrospective cohort of patients hospitalized with Acute Coronary Syndrome (ACS) between 2002 and 2008 who also responded to the Canadian Community Health Survey (CCHS), was analyzed using decision trees to determine whether gender impacted the delay to angiography following an ACS. RESULTS: Defining a delay to angiography as 1 day or more, resulted in a non-significant difference in an equity score of 0.14 for women and 0.12 for men, where 0 and 1 represents perfect equity and inequity respectively. Using 2 and 3 day delays as a secondary outcome resulted in women and men producing scores of 0.19 and 0.17 for a 2 day delay and 0.22 and 0.23 for a 3 day delay. CONCLUSIONS: A technique developed expressly for measuring equity suggests that men and women in Ontario receive equitable care in access to angiography with respect to timeliness following an ACS.

Consumer e-health solutions: the cure for Baumol's disease?

Baumol's disease is the fact that costs in persistently labour-intensive sectors such as healthcare do not drop, despite increased use of technology. The idea of consumer e-health solutions is seductive, because it provides one option for treating Baumol's disease. However, barriers to the implementation of these solutions exist, and the successful treatment of Baumol's disease with consumer e-health solutions rests on more than their removal. In this introduction, the editor-in-chief adds to the conversation four shifts that are critical to reaping the benefits of consumer e-health solutions: moving the focus from privacy to protection; from mere access to the use of information in decision-making; from the patient-provider dyad to one that includes a full formal and informal care team; and from structural solutions in healthcare to ones designed around the goals we have for our health system.

Public health and primary care: competition or collaboration?

In this commentary, the authors summarize and discuss some of the concerns presented in the papers herein, including issues of funding, skill sets and education. They present two key steps we could take across this country to ensure the long-term viability of public health within our healthcare system and ensure that public health and population goals are shared widely across our health systems.

Institutional boundaries and the challenges of aligning science advice and policy dynamics: the UK and Canada in the time of COVID-19.

This comparison of institutions of science advice during COVID-19 between the Westminster systems of England/UK and Ontario/Canada focuses on the role of science in informing public policy in two central components of the response to the pandemic: the adoption of non-pharmaceutical interventions (NPIs) and the procuring of vaccines. It compares and contrasts established and purpose-built bodies with varying degrees of independence from the political executive, and shows how each attempted to manage the tensions between scientific and governmental logics of accountability as they negotiated the boundary between science and policy. It uses the comparison to suggest potential lessons about the relative merits and drawbacks of different institutional arrangements for science advice to governments in an emergency.

Playing to our strengths in evidence and policy.

Lindstrom, MacLeod and Levy provide an interesting and challenging perspective on collaborative policy making. In this commentary, we argue that effective policy making will require playing to our strengths as policy makers and researchers, rather than the creation of new roles and vehicles. We also argue that we need greater value placed on evidence and intellectual capital across all institutions in our health system.

Ontario's COVID-19 Modelling Consensus Table: mobilizing scientific expertise to support pandemic response.

SETTING: COVID-19 has highlighted the need for credible epidemiological models to inform pandemic policy. Traditional mechanisms of commissioning research are ill-suited to guide policy during a rapidly evolving pandemic. At the same time, contracting with a single centre of expertise has been criticized for failing to reflect challenges inherent in specific modelling approaches. INTERVENTION: This report describes an alternative approach to mobilizing scientific expertise. Ontario's COVID-19 Modelling Consensus Table (MCT) was created in March 2020 to enable rapid communication of credible estimates of the impact of COVID-19 and to accelerate learning on how the disease is spreading and what could slow its transmission. The MCT is a partnership between the province and academic modellers and consists of multiple groups of experts, health system leaders, and senior decision-makers. Armed with Ministry of Health data, the MCT meets once per week to share results from modelling exercises, generate consensus judgements of the likely future impact of COVID-19, and discuss decision-makers' priorities. OUTCOMES: The MCT has enabled swift access to data for participants, a structure for developing consensus estimates and communicating these to decision-makers, credible models to inform health system planning, and increased transparency in public reporting of COVID-19 data. It has also facilitated the rapid publication of research findings and its incorporation into government policy. IMPLICATIONS: The MCT approach is one way to quickly draw on scientific advice outside of government and public health agencies. Beyond speed, this approach allows for nimbleness as experts from different organizations can be added as needed. It also shows how universities and research institutes have a role to play in crisis situations, and how this expertise can be marshalled to inform policy while respecting academic freedom and confidentiality.

RéSUMé: LIEU: La COVID-19 a mis en évidence le besoin de modèles épidémiologiques crédibles pour éclairer la politique pandémique. Les mécanismes habituels pour commander des travaux de recherche sont peu propices à orienter les politiques lors d'une pandémie qui évolue rapidement. En même temps, la passation de contrats avec un seul centre d'expertise est critiquée, car elle ne tient pas compte des difficultés inhérentes de certaines approches de modélisation. INTERVENTION: Le présent rapport décrit une approche de rechange pour mobiliser le savoir scientifique. L'Ontario a créé en mars 2020 une Table de concertation sur la modélisation (TCM) qui permet de communiquer de façon rapide et fiable les estimations des effets de la COVID-19 et d'apprendre plus vite comment la maladie se propage et ce qui pourrait en ralentir la transmission. La TCM, un partenariat entre les modélisateurs de la province et des milieux universitaires, est composée de plusieurs groupes d'experts, de dirigeants du système de santé et de décideurs de haut niveau. Armée des données du ministère de la Santé, la TCM se réunit une fois par semaine pour partager les résultats d'exercices de modélisation, générer des jugements consensuels sur les futurs effets probables de la COVID-19 et discuter des priorités des décideurs. RéSULTATS: La TCM rend possible un accès rapide aux données pour les participants, une structure pour élaborer des estimations consensuelles et les communiquer aux décideurs, des modèles fiables pour éclairer la planification du système de santé, ainsi qu'une transparence accrue dans la communication des données sur la COVID-19 au public. Elle facilite aussi la publication rapide des résultats de recherche et leur intégration dans la politique gouvernementale. CONSéQUENCES: L'approche de la TCM est un moyen d'obtenir rapidement des conseils scientifiques à l'extérieur du gouvernement et des organismes de santé publique. Au-delà de sa rapidité, cette approche offre une grande souplesse, car des experts de différents organismes peuvent être ajoutés au besoin. Elle montre aussi que les universités et les établissements de recherche ont un rôle à jouer dans les situations de crise, et qu'il est possible de mobiliser leurs compétences pour éclairer les politiques tout en respectant la liberté et la confidentialité des milieux de la recherche et de l'enseignement.

Research and advice giving: a functional view of evidence-informed policy advice in a Canadian Ministry of Health.

CONTEXT: As evidence-based medicine grows in influence and scope, its applicability to health policy prompts two questions: Can the principles and, more specifically, the tools used to bring research into the clinical world apply to civil servants offering advice to politicians? If not, what approach should the evidence-oriented health policy organization take to improve the use of research? METHODS: This article reviews evidence-based medicine and models of research use in policy. Then it reports the results of interviews with civil servants in the Ontario Ministry of Health, which recently adopted a stewardship rather than an operational role, incorporating many evidence-oriented strategies. The interviews focused on functional roles for research-based evidence in policy advice. FINDINGS: The clinical context and tools for evidence-based medicine can rarely be generalized to policy. Most current models of research use offer lessons to researchers wishing to apply their work to policy but little help for civil servants wishing to become more evidence oriented. The interviews revealed functional roles for research in setting agendas (noting upcoming issues and screening interest groups' claims), developing new policies (reducing uncertainty, helping speak truth to power, and preventing repetition and duplication), and monitoring or modifying existing policies (continuously improving programs and creating a culture of inquiry). Each area requires different tools to help filter the push of evidence from researchers and set agendas, to facilitate the urgent pull on relevant research by civil servants developing new policy, and to support ongoing linkage and exchange between civil servants and researchers for monitoring and modifying existing policy. CONCLUSIONS: A functional framework for evidence-informed policy advice is useful for distinguishing the activity from evidence-based medicine and "auditing" the balance of efforts across the different functional roles of research in policy.

The relationship between hospital adoption and use of high technology medical imaging and in-patient mortality and length of stay.

PURPOSE: The purpose of this paper is to investigate the relationship between hospital adoption and use of computed tomography (CT) scanners, and magnetic resonance imaging (MRI) machines and in-patient mortality and length of stay. DESIGN/METHODOLOGY/APPROACH: This study used panel data (2007-2010) from 124 hospital corporations operating in Ontario, Canada. Imaging use focused on medical patients accounting for 25 percent of hospital discharges. Main outcomes were in-hospital mortality rates and average length of stay. A model for each outcome-technology combination was built, and controlled for hospital structural characteristics, market factors and patient characteristics. FINDINGS: In 2010, 36 and 59 percent of hospitals had adopted MRI machines and CT scanners, respectively. Approximately 23.5 percent of patients received CT scans and 3.5 percent received MRI scans during the study period. Adoption of these technologies was associated with reductions of up to 1.1 percent in mortality rates and up to 4.5 percent in length of stay. The imaging use-mortality relationship was non-linear and varied by technology penetration within hospitals. For CT, imaging use reduced mortality until use reached 19 percent in hospitals with one scanner and 28 percent in hospitals with 2+ scanners. For MRI, imaging use was largely associated with decreased mortality. The use of CT scanners also increased length of stay linearly regardless of technology penetration (4.6 percent for every 10 percent increase in use). Adoption and use of MRI was not associated with length of stay. RESEARCH LIMITATIONS/IMPLICATIONS: These results suggest that there may be some unnecessary use of imaging, particularly in small hospitals where imaging is contracted out. In larger hospitals, the results highlight the need to further investigate the use of imaging beyond certain thresholds. Independent of the rate of imaging use, the results also indicate that the presence of CT and MRI devices within a hospital benefits quality and efficiency. ORIGINALITY/VALUE: To the authors' knowledge, this study is the first to investigate the combined effect of adoption and use of medical imaging on outcomes specific to CT scanners and MRI machines in the context of hospital in-patient care.

Are we prepared? The development of performance indicators for public health emergency preparedness using a modified Delphi approach.

BACKGROUND: Disasters and emergencies from infectious diseases, extreme weather and anthropogenic events are increasingly common. While risks vary for different communities, disaster and emergency preparedness is recognized as essential for all nation-states. Evidence to inform measurement of preparedness is lacking. The objective of this study was to identify and define a set of public health emergency preparedness (PHEP) indicators to advance performance measurement for local/regional public health agencies. METHODS: A three-round modified Delphi technique was employed to develop indicators for PHEP. The study was conducted in Canada with a national panel of 33 experts and completed in 2018. A list of indicators was derived from the literature. Indicators were rated by importance and actionability until achieving consensus. RESULTS: The scoping review resulted in 62 indicators being included for rating by the panel. Panel feedback provided refinements to indicators and suggestions for new indicators. In total, 76 indicators were proposed for rating across all three rounds; of these, 67 were considered to be important and actionable PHEP indicators. CONCLUSIONS: This study developed an indicator set of 67 PHEP indicators, aligned with a PHEP framework for resilience. The 67 indicators represent important and actionable dimensions of PHEP practice in Canada that can be used by local/regional public health agencies and validated in other jurisdictions to assess readiness and measure improvement in their critical role of protecting community health.

Barriers to patient involvement in health service planning and evaluation: an exploratory study.

OBJECTIVE: Patient involvement in health service planning and evaluation is considered important yet not widely practiced. This study explored stakeholder beliefs about patient participation in performance indicator selection to better understand hypothesized barriers. METHODS: Interviews with 30 cancer patients and health professionals from two teaching hospitals were analyzed qualitatively. RESULTS: All groups believed patients, not members of the public, should be involved in the selection of indicators. Ongoing, interactive methods such as committee involvement, rather than single, passive efforts such as surveys were preferred. Health professionals recommended patients assume a consultative, rather than decision-making role. Older patients agreed with this. CONCLUSION: Variable patient interest, health professional attitudes, and a lack of insight on appropriate methods may be limiting patient involvement in this, and other service planning and evaluation activities. More research is required to validate expressed views among the populations these stakeholders represent, and to establish effective methods for engaging patients. PRACTICE IMPLICATIONS: Efforts to encourage a change in health professional attitude may be required, along with dedicated organizational resources, coordinators and training. Methods to engage patients should involve deliberation, which can be achieved through modified Delphi panel or participatory research approaches.

Selecting effective incentive structures in health care: A decision framework to support health care purchasers in finding the right incentives to drive performance.

BACKGROUND: The Ontario health care system is devolving planning and funding authority to community based organizations and moving from steering through rules and regulations to steering on performance. As part of this transformation, the Ontario Ministry of Health and Long-Term Care (MOHLTC) are interested in using incentives as a strategy to ensure alignment - that is, health service providers' goals are in accord with the goals of the health system. The objective of the study was to develop a decision framework to assist policymakers in choosing and designing effective incentive systems. METHODS: The first part of the study was an extensive review of the literature to identify incentives models that are used in the various health care systems and their effectiveness. The second part was the development of policy principles to ensure that the used incentive models are congruent with the values of the Ontario health care system. The principles were developed by reviewing the Ontario policy documents and through discussions with policymakers. The validation of the principles and the suggested incentive models for use in Ontario took place at two meetings. The first meeting was with experts from the research and policy community, the second with senior policymakers from the MOHLTC. Based on the outcome of those two meetings, the researchers built a decision framework for incentives. The framework was send to the participants of both meetings and four additional experts for validation. RESULTS: We identified several models that have proven, with a varying degree of evidence, to be effective in changing or enabling a health provider's performance. Overall, the literature suggests that there is no single best approach to create incentives yet and the ability of financial and non-financial incentives to achieve results depends on a number of contextual elements. After assessing the initial set of incentive models on their congruence with the four policy principles we defined nine incentive models to be appropriate for use in Ontario and potentially other health care systems that want to introduce incentives to improve performance. Subsequently, the models were incorporated in the resulting decision framework. CONCLUSION: The design of an incentive must reflect the values and goals of the health care system, be well matched to the performance objectives and reflect a range of contextual factors that can influence the effectiveness of even well-designed incentives. As a consequence, a single policy recommendation around incentives is inappropriate. The decision framework provides health care policymakers and purchasers with a tool to support the selection of an incentive model that is the most appropriate to improve the targeted performance.

Response audit of an Internet survey of health care providers and administrators: implications for determination of response rates.

BACKGROUND: Internet survey modalities often compare unfavorably with traditional survey modalities, particularly with respect to response rates. Response to Internet surveys can be affected by the distribution options and response/collection features employed as well as the existence of automated (out-of-office) replies, automated forwarding, server rejection, and organizational or personal spam filters. However, Internet surveys also provide unparalleled opportunities to track study subjects and examine many of the factors influencing the determination of response rates. Tracking data available for Internet surveys provide detailed information and immediate feedback on a significant component of response that other survey modalities cannot match. This paper presents a response audit of a large Internet survey of more than 5000 cancer care providers and administrators in Ontario, Canada. OBJECTIVE: Building upon the CHEcklist for Reporting Results of Internet E-Surveys (CHERRIES), the main objectives of the paper are to (a) assess the impact of a range of factors on the determination of response rates for Internet surveys and (b) recommend steps for improving published descriptions of Internet survey methods. METHODS: We audited the survey response data, analyzing the factors that affected the numerator and denominator in the ultimate determination of response. We also conducted a sensitivity analysis to account for the inherent uncertainty associated with the impact of some of the factors on the response rates. RESULTS: The survey was initially sent out to 5636 health care providers and administrators. The determination of the numerator was influenced by duplicate/unattached responses and response completeness. The numerator varied from a maximum of 2031 crude (unadjusted) responses to 1849 unique views, 1769 participants, and 1616 complete responses. The determination of the denominator was influenced by forwarding of the invitation email to unknown individuals, server rejections, automated replies, spam filters, and 'opt out' options. Based on these factors, the denominator varied from a minimum of 5106 to a maximum of 5922. Considering the different assumptions for the numerator and the denominator, the sensitivity analysis resulted in a 12.5% variation in the response rate (from minimum of 27.3% to maximum of 39.8%) with a best estimate of 32.8%. CONCLUSIONS: Depending on how the numerator and denominator are chosen, the resulting response rates can vary widely. The CHERRIES statement was an important advance in identifying key characteristics of Internet surveys that can influence response rates. This response audit suggests the need to further clarify some of these factors when reporting on Internet surveys for health care providers and administrators, particularly when using commercially available Internet survey packages for specified, rather than convenience, samples.