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Key Performance Indicators for program scale-up and divergent practice styles: a study from NSW, Australia.
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- المؤلفون: Grøn, Sisse1,2 ; Loblay, Victoria3; Conte, Kathleen P4; Green, Amanda5; Innes-Hughes, Christine5; Milat, Andrew6; Mitchell, Jo7; Persson, Lina6; Thackway, Sarah6; Williams, Mandy8; Hawe, Penelope3
- المصدر:
Health Promotion International. Dec2020, Vol. 35 Issue 6, p1415-1426. 12p.
- الموضوع:
- معلومة اضافية
- الموضوع:
- نبذة مختصرة :
Implementing programs at scale has become a vital part of the government response to the continuing childhood obesity epidemic. We are studying the largest ever scale-up of school and child care obesity prevention programs in Australia. Health promotion teams support primary schools and early childhood services in their area to achieve a number of specified, evidence-based practices aimed at organizational changes to improve healthy eating and physical activity. Key performance indicators (KPIs) were devised to track program uptake across different areas—measuring both the proportion of schools and early childhood services reached and the proportion of practices achieved in each setting (i.e. the proportion of sites implementing programs as planned). Using a 'tight–loose–tight' model, all local health districts receive funding and are held accountable to reaching KPI implementation targets. However, local teams have independent discretion over how to best use funds to reach targets. Based on 12 months of ethnographic fieldwork and interviews across all districts, this study examines variations in the decision making and strategizing processes of the health promotion teams. We identified three distinct styles of practice: KPI-driven practice (strategic, focussed on targets); relationship-driven practice (focussed on long-term goals); and equity-driven practice (directing resources to sites most in need). In adapting to KPIs, teams make trade-offs and choices. Some teams struggled to balance a moral imperative to attend to equity issues, with a practical need to meet implementation targets. We discuss how models of program scale-up and tracking could possibly evolve to recognize this complexity. [ABSTRACT FROM AUTHOR]
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