Implementation science is an emerging field of research with considerable penetration in physical medicine and less in the fields of mental health and social services. There remains a lack of consensus on methodological approaches to the study of implementation processes and tests of implementation strategies. This paper addresses the need for methods development through a structured review that describes design elements in nine studies testing implementation strategies for evidence-based interventions addressing mental health problems of children in child welfare and child mental health settings. Randomized trial designs were dominant with considerable use of mixed method designs in the nine studies published since 2005. The findings are discussed in reference to the limitations of randomized designs in implementation science and the potential for use of alternative designs.
Implementation science is a quickly growing discipline. Lessons learned from business and medical settings are being applied but it is unclear how well they translate to settings with different historical origins and customs (e.g., public mental health, social service, alcohol/drug sectors). The purpose of this paper is to propose a multi-level, four phase model of the implementation process (i.e., Exploration, Adoption/Preparation, Implementation, Sustainment), derived from extant literature, and apply it to public sector services. We highlight features of the model likely to be particularly important in each phase, while considering the outer and inner contexts (i.e., levels) of public sector service systems.
Despite a decade's worth of effort, patient safety has improved slowly, in part because of the limited evidence base for the development and widespread dissemination of successful patient safety practices. The Agency for Healthcare Research and Quality sponsored an international group of experts in patient safety and evaluation methods to develop criteria to improve the design, evaluation, and reporting of practice research in patient safety. This article reports the findings and recommendations of this group, which include greater use of theory and logic models, more detailed descriptions of interventions and their implementation, enhanced explanation of desired and unintended outcomes, and better description and measurement of context and of how context influences interventions. Using these criteria and measuring and reporting contexts will improve the science of patient safety.
Differences in contexts (eg, policies, healthcare organisation characteristics) may explain variations in the effects of patient safety practice (PSP) implementations. However, knowledge of which contextual features are important determinants of PSP effectiveness is limited and consensus is lacking on a taxonomy of which contexts matter.
Iterative, formal discussions were held with a 22-member technical expert panel composed of experts or leaders in patient safety, healthcare systems, and methods. First, potentially important contextual features were identified, focusing on five PSPs. Then, two surveys were conducted to determine the context likely to influence PSP implementations.
The panel reached a consensus on a taxonomy of four broad domains of contextual features important for PSP implementations: safety culture, teamwork and leadership involvement; structural organisational characteristics (eg, size, organisational complexity or financial status); external factors (eg, financial or performance incentives or PSP regulations); and availability of implementation and management tools (eg, training organisational incentives). Panelists also tended to rate specific patient safety culture, teamwork and leadership contexts as high priority for assessing their effects on PSP implementations, but tended to rate specific organisational characteristic contexts as high priority only for use in PSP evaluations. Panelists appeared split on whether specific external factors and implementation/management tools were important for assessment or only description.
This work can guide research commissioners and evaluators on the contextual features of PSP implementations that are important to report or evaluate. It represents a first step towards developing guidelines on contexts in PSP implementation evaluations. However, the science of context measurement needs maturing.
Many models of infectious disease ignore the underlying contact structure through which the disease spreads. However, in order to evaluate the efficacy of certain disease control interventions, it may be important to include this network structure. We present a network modeling framework of the spread of disease and a methodology for inferring important model parameters, such as those governing network structure and network dynamics, from readily available data sources. This is a general and flexible framework with wide applicability to modeling the spread of disease through sexual or close contact networks. To illustrate, we apply this modeling framework to evaluate HIV control programs in sub-Saharan Africa, including programs aimed at concurrent partnership reduction, reductions in risky sexual behavior, and scale up of HIV treatment.
There is a large literature on innovation and the importance of a node and a network as
important to creating an environment for such innovation. Most of the analysis of this
system has been in high technology industries, and in the products and technologies that
it creates. However, there is no reason why we can’t analyze innovation in less leading
edge industries and products, and in the development or organizational structures rather
than products. This paper tries to illustrate the potential of this type of innovation
institutions by looking at structures for business relationships as the innovation, and
consciously chooses two very low technology industries (Japanese trading company
relationships in textiles and steel) to illustrate the potential usefulness of innovation
system concepts in less conventional venues.
An excerpt from "Implementing Change: Organizational Challenges" (pp. 309-310):
Improving organizational performance is never easy. As sociologist Jim March has noted, success requires that organizations balance exploration the search for new ways of doing things with exploitation, the ability to harness new practices and jettison older, less effective ones (March, 1991). These challenges confront all organizations, but two factors make them more acute for intelligence agencies. The first is bounded rationality (Simon, 1976). In the theoretical world, individuals have the luxury of perfect rationality, seeing all of the relevant options, assessing trade-offs with clarity, and making the best decisions. The real world is not as nice. There, rationality is inherently limited or bounded by uncertainty, imperfect information, and cognitive constraints that lead individuals to make decisions that appear to be “good enough”—but may turn out to be nowhere close (Simon, 1976). Intelligence officials have the toughest time of all, confronting bounded rationality problems in spades. Their job is to give policy-making customers decision advantage amidst swirling uncertainty, missing information, enemy deception and denial, and fast-changing events that are often unforeseeable, even to the participants themselves.
The second acute intelligence challenge is secrecy. As I discuss below, the more specialized any organization becomes, the harder it is for any one part of the organization to understand or improve what another part is doing, a phenomenon that sociologists call “structural secrecy” (Vaughan, 1996). In the classified universe, of course, this structural secrecy is compounded by actual secrecy, which protects vital information from adversaries, but also compartmentalizes information, ideas, organizations, and practices to a much greater extent.
Despite the intelligence community’s (IC’s) unique challenges, the fields of organization theory and political science offer useful insights and cautionary warnings about the organizational side of improving intelligence analysis. The chapters in Part II (Analytic Methods) of this volume mine an array of relevant literature for the best analytic tools to improve intelligence analysis. Here, we turn to a different task: Examining a broad sweep of relevant social science research with an eye to identifying which organizational factors impede or facilitate effective analysis. Worth underscoring, though, is the fact that social science does not offer ready-made instructions about how to make intelligence analytic improvements stick. However, it does offer some useful generalizations that can illuminate the trade-offs and challenges involved to guide more effective implementation.
The four-volume Encyclopedia of Global Studies covers the field of global studies and subjects related to it, such as globalization, transnational activity and themes of global society. This encyclopedia is written for the educated general reader as well as students and professionals working in the field of global studies. It is the first encyclopedia of its kind, and aims to become the internationally-recognized reference work for academics, policymakers, and practitioners interested in the various dimensions of globalization. It provides succinct summaries of concepts and theories, definitions of terms, biographical entries, and organizational profiles; offers a guide to sources of information; and establishes an overview of Global Studies in different parts of the world and across cultures and historical periods. The wide range of subjects covered include the following:
- intellectual approaches, such as global sociology, political economy, world systems theory, peace and conflict studies, and communications;
- global and transnational topics, such as cross-border conflicts and terrorism, worldwide health crises and climate disruption, the planetary immigration patterns and new cultural diasporas, and the seemingly boundless global market, rapid communications, and transnational cyberspaces devised by technology and new media.