Optimisation: defining and exploring a concept to enhance the impact of public health initiatives

Abstract

Background: Repeated, data-driven optimisation processes have been applied in many fields to rapidly transform the performance of products, processes and interventions. While such processes may similarly be employed to enhance the impact of public health initiatives, optimisation has not been defined in the context of public health and there has been little exploration of its key concepts. Methods: We used a modified, three-round Delphi study with an international group of researchers, public health policy-makers and practitioners to (1) generate a consensus-based definition of optimisation in the context of public health and (2i) describe key considerations for optimisation in that context. A pre-workshop literature review and elicitation of participant views regarding optimisation in public health (round 1) were followed by a daylong workshop and facilitated face-to-face group discussions to refine the definition and generate key considerations (round 2); finally, post-workshop discussions were undertaken to refine and finalise the findings (round 3). A thematic analysis was performed at each round. Study findings reflect an iterative consultation process with study participants. Results: Thirty of 33 invited individuals (91%) participated in the study. Participants reached consensus on the following definition of optimisation in public health: "A deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints". A range of optimisation considerations were explored. Optimisation was considered most suitable when existing public health initiatives are not sufficiently effective, meaningful improvements from an optimisation process are anticipated, quality data to assess impacts are routinely available, and there are stable and ongoing resources to support it. Participants believed optimisation could be applied to improve the impacts of an intervention, an implementation strategy or both, on outcomes valued by stakeholders or end users. While optimisation processes were thought to be facilitated by an understanding of the mechanisms of an intervention or implementation strategy, no agreement was reached regarding the best approach to inform decisions about modifications to improve impact.

Process Evaluation of a School-Based High-Intensity Interval Training Program for Older Adolescents: The Burn 2 Learn Cluster Randomised Controlled Trial

“…The deviation in implementation (i.e., program drift) that occurs as interventions move from the pilot/efficacy phase to the effectiveness/replication phase typically results in decreasing benefits for participants [ 22 ]. Comprehensive process evaluations can help to explain the process of implementation and guide intervention optimisation, defined by Wolfenden and colleagues [ 23 ] (pg. 5) as, “a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints”.…”

How to optimise public health interventions: a scoping review of guidance from optimisation process frameworks

“…The predominant focus on optimising intervention effectiveness is unsurprising given that the main goal of public health interventions are to produce positive health outcomes for the population. However, a recent qualitative study examining optimisation of health care innovations in public health found that it was important for outcomes of the optimisation process to be determined by key stakeholders and end-users of the intervention to generate the greatest impact [13]. Previous studies have reported that stakeholders, typically agencies and organisations that fund the implementation or delivery of interventions, often consider many outcomes in addition to effectiveness, including cost, appropriateness to context and reach, when determining whether an intervention is suitable for translation or scaling up at a population level [13].…”

“…1. They report a framework describing a process of optimisation defined as a "deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholderdefined public health impacts within resource constraints" [13]. 2.…”

“…In the field of public health, optimisation has been defined as a "deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints" [13]. While it is a relatively new concept in public health there are a number of examples where optimisation processes have been employed.…”

“…Given the potential and interest in the application of optimisation for public health improvement [13], the systematic identification of frameworks relevant to optimisation in public health and medicine, and the characterisation of commonly recommended processes inherent in these frameworks may represent an important resource to guide future optimisation research and practice. As such we sought to conduct a scoping review to:…”