Rugged landscapes: complexity and implementation science.

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 e...

Descripción completa

Detalles Bibliográficos
Publicado en:Implementation Science Vol. 15; no. 1
Autores principales: Ornstein, Joseph T., Hammond, Ross A., Padek, Margaret, Mazzucca, Stephanie, Brownson, Ross C.
Formato: research Journal Article
Publicado: BioMed Central 9/29/2020
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146149663&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 146149663
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        17485908
        38MN
      jtl: Implementation Science
      issn: 17485908
      maglogo: N
    pubinfo:
      dt: 9/29/2020
      vid: 15
      iid: 1
      pid: 24147
      pub: BioMed Central
    artinfo:
      ui:
        146149663
        146149663
        NLM32993756
        146149663
        10.1186/s13012-020-01028-5
        NLM32993756
        146149663
      ppct: 1
      formats:
      tig:
        atl: Rugged landscapes: complexity and implementation science.
      aug:
        au:
          Ornstein, Joseph T.
          Hammond, Ross A.
          Padek, Margaret
          Mazzucca, Stephanie
          Brownson, Ross C.
        affil: Brown School, Washington University in St. Louis, Brookings Drive, St. Louis, MO, USA
      sug:
        subj:
          Professional Practice, Evidence-Based
          Public Health
          Human
          Decision Making
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Validation Studies
          Ferrans and Powers Quality of Life Index
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N