The Relationship Between Local Public Health Agency Administrative Variables and County Health Status Rankings in Kentucky

Harris, April L.; Scutchfield, F. Douglas; Heise, Georgia; Ingram, Rick E.

doi:10.1097/phh.0b013e3182a5c2f8

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…EBDM which is an approach to decision-making that combines the appropriate research evidence, practitioner expertise, and the characteristics, needs, and preferences of the community, can have a significant impact on health-related outcomes [ 1 , 17 ]. Specifically, leadership support in applying EBDM frameworks can enhance an organization’s capacity for improved public health practices [ 1 , 18 , 19 ]. Concurrently, contextual factors, cost burden and characteristics of early adopters are also factors in mis- implementation outcomes [ 16 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Patterns and correlates of mis-implementation in state chronic disease public health practice in the United States

et al. 2021

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Background Much of the disease burden in the United States is preventable through application of existing knowledge. State-level public health practitioners are in ideal positions to affect programs and policies related to chronic disease, but the extent to which mis-implementation occurring with these programs is largely unknown. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Methods A 2018 comprehensive survey assessing the extent of mis-implementation and multi-level influences on mis-implementation was reported by state health departments (SHDs). Questions were developed from previous literature. Surveys were emailed to randomly selected SHD employees across the Unites States. Spearman’s correlation and multinomial logistic regression were used to assess factors in mis-implementation. Results Half (50.7%) of respondents were chronic disease program managers or unit directors. Forty nine percent reported that programs their SHD oversees sometimes, often or always continued ineffective programs. Over 50% also reported that their SHD sometimes or often ended effective programs. The data suggest the strongest correlates and predictors of mis-implementation were at the organizational level. For example, the number of organizational layers impeded decision-making was significant for both continuing ineffective programs (OR=4.70; 95% CI=2.20, 10.04) and ending effective programs (OR=3.23; 95% CI=1.61, 7.40). Conclusion The data suggest that changing certain agency practices may help in minimizing the occurrence of mis-implementation. Further research should focus on adding context to these issues and helping agencies engage in appropriate decision-making. Greater attention to mis-implementation should lead to greater use of effective interventions and more efficient expenditure of resources, ultimately to improve health outcomes.

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Section: Introductionmentioning

confidence: 99%

Patterns and correlates of mis-implementation in state chronic disease public health practice in the United States

et al. 2021

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“…In delivery of mental health services, Massatti and colleagues made several key points regarding mis-implementation: (1) the right mix of contextual factors (e.g., organizational support) is needed for the continuation of effective programs in real-world settings; (2) there is a significant cost burden of the programs to the agency; and (3) understanding the nuances of early adopters promotes efficient dissemination of effective interventions [ 32 ]. Management support for EBDM in public health agencies are associated with improved public health performance [ 18 , 33 ], but little is known about the processes and factors that affect mis-implementation specifically. Pilot data indicate that organizational supports for EBDM may be protective against mis-implementation (e.g., leadership support for EBDM, having a work unit with the necessary EBDM skills) [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Toward optimal implementation of cancer prevention and control programs in public health: a study protocol on mis-implementation

et al. 2018

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BackgroundMuch of the cancer burden in the USA is preventable, through application of existing knowledge. State-level funders and public health practitioners are in ideal positions to affect programs and policies related to cancer control. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Greater attention to mis-implementation should lead to use of effective interventions and more efficient expenditure of resources, which in the long term, will lead to more positive cancer outcomes.MethodsThis is a three-phase study that takes a comprehensive approach, leading to the elucidation of tactics for addressing mis-implementation. Phase 1: We assess the extent to which mis-implementation is occurring among state cancer control programs in public health. This initial phase will involve a survey of 800 practitioners representing all states. The programs represented will span the full continuum of cancer control, from primary prevention to survivorship. Phase 2: Using data from phase 1 to identify organizations in which mis-implementation is particularly high or low, the team will conduct eight comparative case studies to get a richer understanding of mis-implementation and to understand contextual differences. These case studies will highlight lessons learned about mis-implementation and identify hypothesized drivers. Phase 3: Agent-based modeling will be used to identify dynamic interactions between individual capacity, organizational capacity, use of evidence, funding, and external factors driving mis-implementation. The team will then translate and disseminate findings from phases 1 to 3 to practitioners and practice-related stakeholders to support the reduction of mis-implementation.DiscussionThis study is innovative and significant because it will (1) be the first to refine and further develop reliable and valid measures of mis-implementation of public health programs; (2) bring together a strong, transdisciplinary team with significant expertise in practice-based research; (3) use agent-based modeling to address cancer control implementation; and (4) use a participatory, evidence-based, stakeholder-driven approach that will identify key leverage points for addressing mis-implementation among state public health programs. This research is expected to provide replicable computational simulation models that can identify leverage points and public health system dynamics to reduce mis-implementation in cancer control and may be of interest to other health areas.

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“…In a related setting (mental health), Massatti and colleagues made several key points regarding mis-implementation: (1) the right mix of contextual factors (e.g., organizational support) is needed for continuation of effective programs in real-world settings, (2) there is a significant cost burden of the programs to the agency, and (3) understanding the nuances of early adopters promotes efficient dissemination of effective interventions [ 36 ]. Management support for EBDM in public health agencies is associated with improved public health performance [ 37 , 38 ]. In a cross-country comparison of mis-implementation, leadership support and political contexts were all common factors in whether programs continued or ended [ 2 ].…”

Section: Discussionmentioning

confidence: 99%

Rugged landscapes: complexity and implementation science

et al. 2020

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Background Mis-implementation—defined as failure to successfully implement and continue evidence-based programs—is widespread in public health practice. Yet the causes of this phenomenon are poorly understood. Methods We develop an agent-based computational model to explore how complexity hinders effective implementation. The model is adapted from the evolutionary biology literature and incorporates three distinct complexities faced in public health practice: dimensionality, ruggedness, and context-specificity. Agents in the model attempt to solve problems using one of three approaches—Plan-Do-Study-Act (PDSA), evidence-based interventions (EBIs), and evidence-based decision-making (EBDM). Results The model demonstrates that the most effective approach to implementation and quality improvement depends on the underlying nature of the problem. Rugged problems are best approached with a combination of PDSA and EBI. Context-specific problems are best approached with EBDM. Conclusions The model’s results emphasize the importance of adapting one’s approach to the characteristics of the problem at hand. Evidence-based decision-making (EBDM), which combines evidence from multiple independent sources with on-the-ground local knowledge, is a particularly potent strategy for implementation and quality improvement.

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The Relationship Between Local Public Health Agency Administrative Variables and County Health Status Rankings in Kentucky

Cited by 5 publications

References 18 publications

Patterns and correlates of mis-implementation in state chronic disease public health practice in the United States

Patterns and correlates of mis-implementation in state chronic disease public health practice in the United States

Toward optimal implementation of cancer prevention and control programs in public health: a study protocol on mis-implementation

Rugged landscapes: complexity and implementation science

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