Andrew Milat

Amédé Gogovor and colleagues explain how scaling studies differ from implementation studies and present 33 recommendations for how to report scaling studies with maximum accuracy and usefulness.

Background: Scaling primary care innovations to benefit broader populations is a key priority for decision-makers. While the science of effective scaling evolves, little is known about innovations that scale spontaneously , i.e., without deliberate guidance. Objectives: To assess the spontaneous scaling process of STAT-C, a training workshop supporting management of sick leave related to common mental health disorders, and its perceived effects on primary care services and beneficiaries. Methods: We conducted a mixed-methods descriptive single-case study using an Integrated Knowledge Translation (iKT) approach involving patient users. The case was defined as the spontaneous scaling of STAT-C, presented at the Quebec College of Family Physicians’ Innovation Symposium and assessed using a selection criteria checklist. Over one year, we observed the scaling process through monthly meetings with the innovation team and collected documents to retrace key steps. We conducted interviews with decision-makers, healthcare professionals, and end-users, along with a focus group with the innovation team. Data were analyzed thematically using documents, interviews, and meetings. The scaling process was examined using the Scaling Impact principles: justification, optimal scale, coordination, and dynamic evaluation. Results: STAT-C met 71% of selection criteria. Fourteen participants were interviewed: innovation team (n = 2), healthcare professionals (n = 5), decision-makers (n = 4), and end-users (n = 3). Technical justifications included the need to standardize information across professionals (n = 10), while moral ones emphasized alignment with patient values (n = 8). Interviews revealed limited awareness of dynamic evaluation and a lack of indicators supporting further scaling. Ethical rationales reflected goal-oriented and duty-based reasoning. Preliminary data suggested improvements in healthcare professionals’ self-reported competence in managing CMHD-related sick leave, offering early indications of the innovation’s relevance. Conclusion: This study highlights strategies, challenges, and outcomes of spontaneous scaling under real-world conditions, showing how pathways emerge, strategies evolve, and ethical dimensions shape decision-making.

Scale-up guidance is valuable to guiding efforts to increase the reach and impact of public health innovations. Health equity, that is, ‘the absence of systematic disparities in health between groups’ is often a motivator for scale-up though it is unclear how ‘equity’ is considered within existing scale-up guidance. This scoping review aimed to identify the equity considerations articulated within existing scale-up models. Five databases and grey literature were systematically searched. Articles were included if they explicitly developed a model/framework to guide the process of scaling-up public health innovations. Search results were screened, and content analysis was undertaken. Of the 29 scale-up models identified, 24 included mention of equity terms or equity-related characteristics, however there was variation in how equity was conceptualized and the extent to which it was incorporated. Seven domains were developed to describe how equity was considered: (1) Equity acknowledged in the supporting text as an important factor when scaling-up; (2) Equity positioned as a guiding principle or cross-cutting theme; (3) Equity considered in scalable innovation design or intended population; (4) Equity incorporated into scale-up planning and strategy development; (5) Equity assessed within context and environment assessments; (6) Equity factored into resource allocation and workforce planning; (7) Equity considered in stakeholder engagement. There was considerable variation in how equity was considered which offers opportunities for enhancements. Existing and future scale-up models can be strengthened by applying a more consistent equity focus, and providing more comprehensive, actionable guidance for undertaking equitable scaling of public health innovations.

Quality health communication is fundamental to safe, patient-centered healthcare (Grover et al., 2022) and a core strategy to address health literacy (Nutbeam & Muscat, 2021). When communication be...

Background: Scaling effective primary care innovations to benefit more people is of interest to decision makers. However, we know little about how promising innovations are being scaled “spontaneously,” that is, without deliberate guidance. Objective: We aim to observe, document, and analyze how, in real-life conditions, 1 primary care innovation spontaneously scales up across Quebec, Canada. Methods: We will conduct a participative study using a descriptive single-case study. It will be guided by the McLean and Gargani principles for scaling and reported according to the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines. Informed by an integrated knowledge translation approach, our steering committee will include patient users throughout the project. Inspired by the Quebec College of Family Physician’s “Dragons’ Den” primary care program, we will identify a promising primary care innovation that is being or will be scaled spontaneously. We will interview the innovation team about their scaling experiences every month for 1 year. We will conduct interviews and focus groups with decision makers, health care providers, and end users in the innovation team and the target site about their experience of both scaling and receiving the scaled innovation and document meetings as nonparticipant observers. Interview transcripts and documentary data will be analyzed to (1) compare the spontaneous scaling plan and implementation with the McLean and Gargani principles for scaling and (2) determine how it was consistent with or diverged from the 4 McLean and Gargani guiding principles: justification, optimal scale, coordination, and dynamic evaluation. Results: This study was funded in March 2020 by the Canadian Institutes of Health Research. Recruitment began in November 2023 and data collection began in December 2023. Results are expected to be published in the first quarter of 2024. Conclusions: Our study will advance the science of scaling by providing practical evidence–based material about scaling health and social care innovations in real-world settings using the 4 guiding principles of McLean and Gargani. International Registered Report Identifier (IRRID): PRR1-10.2196/54855

BACKGROUND Scaling effective primary care innovations to benefit more people is of interest to decision makers. However, we know little about how promising innovations are being scaled “spontaneously,” that is, without deliberate guidance. OBJECTIVE We aim to observe, document, and analyze how, in real-life conditions, 1 primary care innovation spontaneously scales up across Quebec, Canada. METHODS We will conduct a participative study using a descriptive single-case study. It will be guided by the McLean and Gargani principles for scaling and reported according to the COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines. Informed by an integrated knowledge translation approach, our steering committee will include patient users throughout the project. Inspired by the Quebec College of Family Physician’s “Dragons’ Den” primary care program, we will identify a promising primary care innovation that is being or will be scaled spontaneously. We will interview the innovation team about their scaling experiences every month for 1 year. We will conduct interviews and focus groups with decision makers, health care providers, and end users in the innovation team and the target site about their experience of both scaling and receiving the scaled innovation and document meetings as nonparticipant observers. Interview transcripts and documentary data will be analyzed to (1) compare the spontaneous scaling plan and implementation with the McLean and Gargani principles for scaling and (2) determine how it was consistent with or diverged from the 4 McLean and Gargani guiding principles: justification, optimal scale, coordination, and dynamic evaluation. RESULTS This study was funded in March 2020 by the Canadian Institutes of Health Research. Recruitment began in November 2023 and data collection began in December 2023. Results are expected to be published in the first quarter of 2024. CONCLUSIONS Our study will advance the science of scaling by providing practical evidence–based material about scaling health and social care innovations in real-world settings using the 4 guiding principles of McLean and Gargani. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/54855

Background: Tobacco smoking during pregnancy is the most important preventable risk factor for pregnancy complications and adverse birth outcomes and can have lifelong consequences for infants. Smoking during pregnancy is associated with higher healthcare costs related to birth complications and during childhood. Psychosocial interventions to support pregnant women to quit are effective, yet provision of smoking cessation support has been inconsistent. The Midwives and Obstetricians Helping Mothers to Quit Smoking (MOHMQuit) intervention provides systems change, and leadership and clinician elements, to support clinicians to help women stop smoking in pregnancy. There have been few long-term analyses conducted of the cost-effectiveness of smoking cessation interventions for pregnant women that target healthcare providers. This protocol describes the economic evaluation of the MOHMQuit trial, a pragmatic stepped-wedge cluster-randomised controlled implementation trial in nine public maternity services in New South Wales (NSW), Australia, to ascertain whether MOHMQuit is cost-effective in supporting clinicians to help women quit smoking in pregnancy compared to usual care. Methods: Two primary analyses will be carried out comparing MOHMQuit with usual care from an Australian health care system perspective: i) a within-trial cost-effectiveness analysis with results presented as the incremental cost per additional quitter; and ii) a lifetime cost-utility analysis using a published probabilistic decision analytic Markov model with results presented as incremental cost per quality-adjusted life-year (QALY) gained for mother and child. Patient-level data on resource use and outcomes will be used in the within-trial analysis and extrapolated and supplemented with national population statistics and published data from the literature for the lifetime analysis. Discussion: There is increasing demand for information on the cost-effectiveness of implementing healthcare interventions to provide policy makers with critical information for the best value for money within finite budgets. Economic evaluation of the MOHMQuit trial will provide essential, policy-relevant information for decision makers on the value of evidence-based implementation of support for healthcare providers delivering services for pregnant women. Trial registrations: ACTRN12622000167763, registered 2 February 2022.

Scaling up effective interventions in public health is complex and comprehensive, and published accounts of the scale-up process are scarce. Key aspects of the scale-up experience need to be more comprehensively captured. This study describes the development of a guide for reflecting on and documenting the scale-up of public health interventions, to increase the depth of practice-based information of scaling up. Reviews of relevant scale-up frameworks along with expert input informed the development of the guide. We evaluated its acceptability with potential end-users and applied it to two real-world case studies. The Scale-up Reflection Guide (SRG) provides a structure and process for reflecting on and documenting key aspects of the scale-up process of public health interventions. The SRG is comprised of eight sections: context of completion; intervention delivery, history/background; intervention components; costs/funding strategies and partnership arrangements; the scale-up setting and delivery; scale-up process; and evidence of effectiveness and long-term outcomes. Utilization of the SRG may improve the consistency and reporting for the scale-up of public health interventions and facilitate knowledge sharing. The SRG can be used by a variety of stakeholders including researchers, policymakers or practitioners to more comprehensively reflect on and document scale-up experiences and inform future practice.