This chapter discusses how the methods of systems science can help increase understanding about the complexity of community-based prevention intervention by disentangling important features and associated variables, clarifying whether and how each of the variables changes over time, identifying causal relationships among the variables, quantifying the variables and the causal relationships, and simulating how changes to the system affect the variables and causal relationships in the system. Domains of value (health, community well-being, and community process) and illustrative elements within each domain are discussed, as are issues in valuing resources and costs of community-based prevention.
As discussed in Chapter 2, community-based prevention interventions cover a broad spectrum of types, from those directed at a specific health condition (e.g., high blood pressure or diabetes) to those aimed at a much broader and more complex array of conditions, including the prevalence of chronic and infectious diseases; the social, economic, and environmental determinants of population health; and health disparities and inequities experienced by lower income, lower educational status, and racial and ethnic minority populations. Chapter 2 also discussed the ecological model and pointed out the existence of multiple determinants of health at multiple levels that interact and link with each other. However, prevailing approaches to funding, research, and practice associated with community-based prevention interventions often fail to recognize their inherent complexity. For instance, categorical funding programs promote a one-disease-at-a-time
vision (with an accompanying set of interventions) for improving population health behaviors and health outcomes. Similarly, many research and evaluation questions seek to identify the best intervention or to examine interventions in the context of a single behavioral or health outcome. And, in the field, approaches to policy and practice change often reflect the interests of the institutions or organizations leading the efforts (e.g., government agencies, community-based organizations, or advocacy groups).
Current approaches tend to focus on individual rather than comprehensive interventions, to attribute changes in health behaviors and health outcomes to specific interventions instead of multiple or synergistic efforts, to not assess effectiveness and costs in terms of the collective value of multi-component intervention approaches, and to guide decisions about priorities and allocate resources intervention by intervention in line with these types of evidence. As such, prevailing approaches fall short in depicting the collective impact of community-based prevention efforts (Hanleybrown et al., 2012; Kania and Kramer, 2011).
However, there has been a growing amount of attention paid to new approaches to address these dynamic and complex systems (Homer and Hirsch, 2006; Luke and Stamatakis, 2012; Mabry et al., 2008; Madon et al., 2007). Examples include the community transformation grants from the Centers for Disease Control and Prevention (CDC); intervention and applied research efforts such as community-based participatory research; the dissemination and implementation research supported by the NIH National Heart, Lung, and Blood Institute and the Office of Behavioral and Social Sciences Research; and cross-sector and multidisciplinary interventions, such as the CDC Communities Putting Prevention to Work program and the Healthy Kids Healthy Communities program (BSSR/NIH, 2012; CDC, 2012a,b; Horowitz et al., 2009; NHLBI/NIH, 2012; RWJF, 2012).
Systems science methods have the potential for overcoming some of the problems with current approaches. Systems science is the study of “dynamic interrelationships of variables at multiple levels of analysis (e.g., from cells to society) simultaneously (often through causal feedback processes), while also studying the impact on the behavior of the system as a whole over time.”1 For purposes of this report, a system will refer to the interrelationships of relevant elements, resources, and processes that characterize community-based prevention. Systems science approaches excel at identifying nonlinear relationships, bidirectional feedback loops, time-delayed effects, emergent properties of systems, and oscillating system behavior (Mabry et al., 2010).
1 As defined by the Office of Behavioral and Social Sciences Research at the National Institutes of Health: http://obssr.od.nih.gov/scientific_areas/methodology/systems_science/index.aspx (accessed July 5, 2012).
Systems thinking is increasingly associated with community-based prevention, notably in obesity control. Of major importance from a systems science perspective is the context in which those interventions take place, that is, the social systems that are imbedded in and interacting with other social systems. Second, there is a growing literature that uses the system metaphor to describe the structure and functioning of the intervention itself (IOM, 2010; Livingood et al., 2011; Trickett, 2009). Because of the complexity, comprehensiveness, and intersectoral, and context-responsive nature of the broader community-based prevention efforts, a systems perspective is well equipped to provide needed analytical descriptions and evaluations of the multiple transformations targeted by such programs, policies, and strategies.
Using a systems science approach to think about community-based prevention can help people think through all the links that may be involved in and affected by a change in the community, whether that change comes from a deliberate intervention or a trend, (such as more smoking or less exercise) caused by forces that may lie outside the community. Furthermore, systems science can help further elucidate
- the pathways through which policy, system, and environmental changes operate to affect population health.
- important ingredients that are needed to implement effective community-based prevention interventions as well as the implementation fidelity and “dose” of these activities (Carroll et al., 2007; Glasgow et al., 1999; Linnan and Steckler, 2002).
- methods needed to capture multi-component and dynamic community trends and to triangulate different qualitative and quantitative data sources (Patton, 2002; Rossi et al., 2004; Teddlie and Tashakkori, 2009; Ulin et al., 2005).
- the extent to which scale-up and spread of evidence-based interventions may be limited by the need to customize these strategies to local political or environmental circumstances, resource constraints, populations (e.g., race and ethnicity, poverty, urban versus rural, youth versus adult), and settings (e.g., home, child care, school, work, community).
- the challenges posed by political, social, and economic forces to the structures (e.g., partners, resources) and processes (e.g., participation, decision making) associated with collaborative community approaches to planning, implementing, enforcing, evaluating, and sustaining these prevention interventions.
Systems science methods are designed to deal with complexity and could prove particularly useful in analyzing community-based prevention
interventions and their impacts (Hammond, 2009; Huang et al., 2009). Results of the application of systems science methods could prove useful in valuing community-based prevention because they can provide information about not only the intervention programs, policies, and associated outcomes but also the contextual conditions, the multi-cause nature of change, and the dynamic interactions among all of the factors.
Systems science methods can be used to explore the various pathways leading from community-based prevention interventions to improvements in population behavioral and health outcomes, such as the influence of a sugar-sweetened beverage tax on the purchase and consumption of foods and beverages. Such methods can also capture the variation in these pathways associated with contextual factors (such as population characteristics, concentration of fast food restaurants, employment opportunities, and living wages) and detect changes in the overall system as new interventions surface.
Systems science methods can address both detail and dynamic complexity. With respect to detail complexity, these methods can clarify assumptions about public health problems, local community context, and change strategies and processes by identifying the variables and the underlying causal relationships among the variables. At the same time these methods are designed to examine how causal structures change over time, including the effect of changes in the type or number of interventions implemented, changes in social norms and community practices, changes in leadership or staff, and so on. Examining these causal structures can help identify the system leverage points that have the greatest potential for affecting behavioral and health outcomes, can increase understanding about intended effects and unintended consequences of the interventions implemented, and can identify facilitating factors and challenges influencing community change processes (Meadows, 1999; Sterman, 2000; Ulrich, 2000).
For examples of systems science approaches to valuing community-based prevention interventions, see Appendix B.
Policy makers, funders, and relevant stakeholders make decisions about the value of community-based interventions. Traditional approaches to assess value tend to focus solely on health impacts, to value interventions in isolation, to overlook community processes, and to fail to monitor
pathways toward progress. The committee was asked to develop a framework for assessing the value of community-based prevention. Because of the way in which community-based prevention is designed and developed (e.g., often to address the social and environmental determinants of health), the committee concluded that impacts of these interventions go beyond health effects. Therefore, a framework for valuing community-based prevention needs to take into account not only the outcomes in the domain of health, but also the outcomes in areas other than health. A framework that does not take into account and value non-health outcomes would be counting all the costs but not all the benefits, thereby providing an inaccurate and inadequate picture of the value of community-based prevention. To assess the true value of community-based prevention, therefore, decision makers, funders, and stakeholders would benefit from an approach that looks not just at health impacts, but at other impacts as well.
A major task facing the committee, then, was determining what domains should be included in a framework to value community-based prevention interventions. As a first step, each committee member was asked to list the outcomes he or she thought could result from community-based prevention interventions. The list generated included more than 100 items and all acknowledged that not everything that could be valued appeared on the list. As a next step, the committee decided to group the items into major categories. Clearly, a major outcome of community-based prevention is its impact on health. Therefore, health was identified as a major domain of interest.
However, there were a number of other items on the list that did not fall neatly into a health domain, for example, education, income, green space, crime, social support, and workplace safety. Initially, the committee identified six major categories under which these other items could be grouped: social environment, physical environment, economics, equity, employment, and education. Yet, as the committee discussed these items and reviewed the literature, it became clear that these elements were all elements related to well-being. Therefore, the committee identified a second major domain as the domain of community well-being.
There were a number of items that did not fit readily into either the health category or the well-being category but which the committee identified as important items of value, including such things as leadership, skill building, and civic participation. An examination of the history of community health efforts demonstrates that various process elements (such as skill building, leadership, and participation) are features that account for the relative success of community-based programs. Early efforts in the first half of the 20th century involved engaging stakeholder organizations and affected populations in first, the support of planned programs, then
in actually planning programs, then in evaluating programs, and finally in community-based participatory research (CBPR) (Green, 1986).
Based on the literature of CBPR (e.g., Minkler and Wallerstein, 2008) the committee deliberately decided to identify community process as a specific area of valued outcomes for community-based prevention.
Elements in the community process domain inherently affect outcomes upstream (e.g., civic participation) that, in turn, affect outcomes downstream (e.g., policy adoption and implementation), further downstream (e.g., equitable access to environments or resources to support health), further downstream (e.g., healthy behaviors of citizens in these environments or use of these resources), further downstream (e.g., healthy lifestyle choices of citizens), and, ultimately, health (although health feeds back to greater capacity for civic participation). Therefore, the committee concludes community process should be identified as a separate domain because in many cases, community empowerment and community capacity have been shown to be valued by communities in their own right (Sandoval et al., 2011). Also, because process elements are intermediary outcomes that increase well-being and health interventions (Minkler et al., 2008; Viswanathan et al., 2004), failing to recognize the increase of such potential as a valued outcome will further disadvantage those communities whose structural and population characteristics put them at increased risk of health and well-being deficit. It is important to note that without a solid grounding in science, community process, as is the case with any democratic process, could lead to worse outcomes with respect to health and well-being.
This section of Chapter 3 describes in more detail the wide array of effects that community-based prevention can have, grouping them under the three distinct but interrelated categories of outcomes, or domains of value: health, community well-being, and community process. The committee is aware that health is a component of well-being but for purposes of this report the health component is separated from other elements of community well-being because health is a particular outcome of interest. The goal in valuing these domains is to account for all of the potential harms and benefits of community-based interventions as well as the possible savings and costs associated with the interventions. This section introduces the domains of value as well as associated elements.
It is important to note that the list of elements included in each domain below is meant to be illustrative. The actual elements selected for valuing will depend on the particular intervention and its implementation. It is unlikely that any given intervention will have value in all elements listed, and there may well be other elements not listed here that should be included. The committee has identified one element, equity, that crosses all domains.
Physical health includes mortality, morbidity, and functional capability. Mental health includes cognition, individual resilience or emotional reserves, mortality due to such causes as suicide, morbidity (e.g., depression), and socio-emotional health-related quality of life (e.g., stress, behaviors, injuries, and perceptions of health). The promotion of mental and physical health includes several elements, in particular, reductions in the incidence and prevalence of disease, declines in mortality, and increases in health-related quality of life. Equity is another important element in the health domain. It is well documented that significant health disparities exist by race, ethnicity, and socioeconomic status (SES) (AHRQ, 2012; APHA, no date; IOM, 2003). Health inequalities across demographic groups (e.g., by race, ethnicity, gender, and SES) may be caused by inequalities in access to health care, by the unequal effect of public measures aimed at risk reduction, or by the unequal distribution of various social determinants of health (e.g., education, income and wealth, opportunity and liberty) (AHRQ, 2012; IOM, 2003, 2009). It may be, however, that the two goals of health policy—improving population health in the aggregate and distributing health fairly—are in tension. For example, some efforts that improve population health in the aggregate may increase health inequalities between groups, for example, a campaign to improve prenatal care that primarily reaches middle to higher income women and is not effective among lower income women may well increase health disparities. Reasonable people may disagree about when to give priority to one goal over the other. However, when assessing value, health inequalities are one element to consider.
The charge to the committee specified a focus on the prevention of long-term chronic diseases. As noted throughout the report, long-term chronic illnesses are often the result of a complex, extended interaction between genetics, individual behaviors, and environments. This complexity can make the task of valuing more difficult. For example, behaviors, such as eating foods with minimal nutritional value and participating in sedentary activities that can lead to obesity and related chronic diseases, are generally the result of lifestyles shaped in part by an individual’s environment. Lifestyle interventions aimed at preventing certain diseases, such as cardiovascular disease (CVD) and diabetes, have been shown to be effective (Saha et al., 2010). However, lowering the prevalence of CVD and diabetes is an outcome that takes a long time to realize. Interventions aimed at such outcomes can produce intermediate markers, such as decreased insulin resistance or lower blood pressure. For long-term outcomes such as the prevention of chronic disease, it will be important to identify intermediate or proximal outcomes as part of the valuation and determination of progress.
Community well-being is a valued outcome in and of itself. Independent of the health of individuals in a community, the concept of community well-being has been used to account for elements associated with community context, or the social, economic, and physical environments characterizing the community (IOM, 2009). Elements of community well-being include wealth and income, education, employment, safety, transportation, housing, worksites, food, health care, and recreational spaces, among others. These elements are produced, reproduced, and transformed by the practice of individuals in the community. Their benefits accrue to both individuals and the community as a whole.
Frumkin (2003) writes of the “atmosphere of a place, the quality of its environment” and the effect that it can have on both health and well-being. He identified four aspects of the built environment that may have an impact on human health and community well-being: nature contact, buildings, public spaces, and urban form. The built environment includes how land is used, the quality of housing and other buildings, transportation, and other design features “that together provide opportunities for travel and physical activity” and, more broadly, an environment that “is designed and constructed by humans” (IOM, 2001; TRB/IOM, 2005).
Land use, urban form, and green space The composition of the built environment, Frumkin’s “urban form,” has been associated with a number of health effects. For example, physical characteristics of neighborhoods have been found to be associated with lower levels of physical exercise and an increased risk of obesity (Ewing et al., 2006; Lopez, 2004; Nelson et al., 2006). The presence or absence of amenities, particularly the opportunities to buy healthy affordable food, can also have an effect on health (Bodor et al., 2010; Leung et al., 2011; Michimi and Wimberly, 2010; Morland et al., 2006; Powell et al., 2007). Access to—or even the presence of—green space is associated with increased physical activity, better perceived general health, mitigation of the effects of stressful life events, and lower prevalence of some illnesses (Ellaway, 2005; Maas et al., 2006, 2009; Ulrich, 1984; Van Den Berg et al., 2010).
Urban form also has effects beyond those on health. For example, areas with a high degree of “walkability” are perceived to be more aesthetically pleasing and are associated with more unplanned interactions with others and a greater sense of community (Wood et al., 2010). Trees in cities allow
for greater energy conservation and lower heating and cooling costs for buildings (McPherson et al., 1997).
Transportation Numerous studies have found that using public transit increases physical activity (Besser and Dannenberg, 2005; Lachapelle and Frank, 2009; Weinstein and Schimek, 2005; Wener and Evans, 2007). MacDonald and colleagues (2010) found that commuting to work by light rail was associated with a reduction in body mass index and reduced odds of becoming obese. Active travel, such as walking and cycling, along with increasing physical activity can also lead to a decrease in vehicle emissions, thereby improving air quality (de Nazelle, 2011). Investment in public transportation has other benefits as well—for example, bringing jobs and economic activity to communities (Weisbrod and Reno, 2009).
Building quality (indoor air) Housing is another area that has effects on both health and community well-being. People spend most of their time indoors, making buildings a component of the built environment that can have a significant impact on an individual’s health. Indoor air can contain radon, environmental tobacco smoke, and thousands of other chemicals and biological contaminants that pose serious risks to health (EPA, 2001). Children, in particular, are at risk of harm from indoor and outdoor air pollution, and the impact can be lifelong (Barakat-Haddad et al., 2012; EPA, 2001). A 2011 IOM committee found that “poor indoor environmental quality is creating health problems today and impairs the ability of occupants to work and learn” (IOM, 2011a, p. 7). In addition to its health benefits, providing quality housing also brings benefits to the community in the form of such things as improved educational outcomes and reduced crime (Carlson et al., 2011).
Social and Economic Environments
Education Extensive research has demonstrated the link between education and health outcomes throughout the life course (IOM, 2006a; Lleras-Muney, 2005). Researchers have also documented the relationship of education and well-being (i.e., higher earnings, higher percentages of home ownership and second-car ownership, reduced crime, reduced welfare, reduced unemployment and reduced poverty (Barnett, 1985, 1996; Gorey, 2001; Schweinhart et al., 1993).
Employment/unemployment Unemployment is positively associated with mortality from all causes, with both physical and mental illness, and with the increased use of health care services (Haan and Myck, 2009; Jin et al.,
1995; Rueda et al., 2012; Strully, 2009; Wilkinson and Marmot, 2003). Employment also has numerous non-health effects. For example, it is associated with more marriage, less divorce, more marital happiness, and greater child well-being (White and Rogers, 2000). Decreases in the unemployment rate have been found to be associated with declines in property crime rates (Raphael and Winter-Ebmer, 2001). Rising unemployment increases the incidence of foster home placement (Catalano et al., 1999).
Crime/safety Research has associated increased physical activity with increased feelings of neighborhood safety (Harrison et al., 2007). Conversely, those living in high crime areas were more likely to smoke and to report poorer health, poor sleep habits, and less exercise (Johnson et al., 2009; Shareck and Ellaway, 2011). In terms of non-health effects, crime and the fear of violence can interfere with social interaction and trust among community members. For example, crime or the fear of crime has been found to limit women’s movement around their environment and to increase levels of mistrust and fear, (Keane, 1998; Ross and Jang, 2000). Milam and colleagues (2010) found that math and reading achievement in schools decreased significantly with increasing neighborhood violence.
Social support and social networks Social networks are defined as webs of person-centered ties (Berkman and Glass, 2000). Numerous research studies have shown the relationship of social support and social networks to both physical and mental health (Berkman and Glass, 2000; Berkman and Kawachi, 2000; Cohen et al., 2000; Cornwell and Waite, 2009; Kawachi and Berkman, 2003; Marmot and Wilkinson, 1999; Maulik et al., 2009; Stansfeld et al., 1999). However, in addition to their relationship to health, social networks and social support are important in and of themselves. For example, Skogan (1989) found that neighborhoods in which residents have organizations and social support resources upon which to draw have more opportunity for action in “defense of their community.” Research has also shown that positive academic outcomes are promoted by social support (Garnefski and Diekstra, 1996; Malecki and Demaray, 2007).
Social cohesion Social cohesion has been characterized by Marmot and Wilkinson (1999) as including “mutual trust and respect between different sections of society.” Social cohesion has been shown to be positively associated with health and levels of physical activity (Cradock et al., 2009; Kim et al., 2008; Lindén-Boström et al., 2010; Marmot and Wilkinson, 1999). But social cohesion also has important effects beyond those on health. For example, areas with higher levels of social cohesion are associated with lower levels of crime, with increasing contributions to group goals, and
with economic prosperity (Hirschfield and Bowers, 1997; Shimizu, 2011; Stanley, 2003).
Equity As mentioned previously, equity is an important element that crosses all three domains. Elements of community well-being are often not equitably distributed in a community. For example, both education and wealth, which are elements of the social environment, are often distributed unequally by race, and considerable attention has been given in recent literature to growing inequalities in income and wealth. The same point may be made for social trust: Levels may vary across various groups in a society, and some practices may weaken trust across groups. The built environment in a society may also be inequitable in its impact on different groups—neighborhoods may vary in the quality of housing, green space, transportation, or even access to fresh food. It is important in valuing community well-being to focus not only on aggregate measures, but also on how community well-being is distributed. Inequity in the distribution of these aspects of community well-being may lead to inequities in the distribution of health and may also contribute to inequities in community processes.
Community-based prevention involves decisions among groups of people about how to live in society, how cities are built, what food is served in schools, and so on. Therefore, it is important that the process by which an intervention is adopted and undertaken be treated as a valued outcome. With a vaccination, effectiveness does not depend on whether the patient trusts the doctor. In contrast, the success of a healthful eating campaign may hinge on the level of trust in the process.
Community processes refer to several elements that have a distinctive influence on community participation in the decision making as well as in the design and implementation associated with community-based interventions. These elements include civic engagement, local leadership development, community participation, trust, skill building, transparency, and inclusiveness. Community processes typically have a sequence of activities that incorporate learning about various options available for health improvement, deliberations associated with the selection of one or more options, consideration of the appropriate methods to implement the health improvement initiatives, and critical reflection on the entire process. The way that decisions are made and carried out not only can be important to the success of a strategy or policy—and thus to community well-being—but also can have a direct impact on well-being through benefits of broad participation and buy-in to decisions (Minkler and Wallerstein, 2008; Wallerstein and Duran, 2010). Community processes also support local adaptation and
implementation of community-based interventions through feedback on the successes and failures of these health improvement initiatives.
Leadership development According to Goodman and colleagues (1998), a healthy community needs diverse leadership that includes “a strong base of actively involved residents.” A diverse leadership will include elected or appointed leaders (e.g., mayor or councilman) and informal leaders (e.g., opinion leaders and community activists). Cook and colleagues (2009) report that strong local leaders have been found to positively influence community vitality by, for example, securing funding to produce change in the quantity of housing. Ricketts and Ladewig (2008, p. 137), in a study of how sense of community and social capital work with leadership to encourage change, found that “community leaders assisted in developing important relationships, establishing communication and imparting community direction, thereby providing the needed link between variables.”
Skill-building The skills related to community processes include those associated with the process of community organizing. A model based on work by Wechsler and Schnepp (1993) included the principles of listening, relationships, challenge, action, reflection, evaluation, and celebration in a cyclical framework that provides a map for how to build an engaged community that promotes ongoing participation in decision making related to those actions that affect the community as a whole. Individuals who have the ability to clearly communicate their values, interests, and motivations are key to this cyclical framework. They possess the essential qualities of inclusion, trustworthiness, leadership development, and self-reflection (Chavez et al., 2010).
Civic engagement or participation Active volunteers and people with high and medium civic participation (defined as belonging to one [medium] or two or more [high] clubs or organizations) report higher levels of well-being than those who are not active, and all-cause mortality rates were found to be lower in communities with high levels of civic engagement (Morrow-Howell et al., 2003; Poortinga, 2006) and “a strong institutional infrastructure for civic participation” (Lee, 2010, p. 1840). Neighborhood residents can play an important role in maintaining order in their neighborhoods when they participate in local organizations that make collective efforts possible (Skogan, 1989). Furthermore, a wide array of participation from community stakeholders can impact local government actions (Burby, 2003) and “institutions that promote participation and public discussion help citizens to make informed choices on many aspects that impinge on the QoL [quality of life]” (Stiglitz et al., 2009, p. 177).
Community mobilization Community mobilization, sometimes referred to as community organization, is the “organization and activation of a community to address local problems” (Shults et al., 2009, p. 362). Communities are complex social systems, and the process used to determine whether or not to implement potential prevention policies or strategies can, in its own right, be important to the successful implementation of the programs or policies. Shults and colleagues (2009) found that community mobilization efforts advance the problem-solving capacity and empowerment of both individuals and communities which, they said, can promote other beneficial effects. In terms of health, for example, “community mobilization is a promising approach to addressing health disparities” (Collie-Akers et al., 2009, p. 118S).
Equity Equity is an important element of community process. Being inclusive of various stakeholders contributes to equity, but inclusiveness can vary in important dimensions that may leave significant inequities in a process. A problematic inequality in community process, for example, is that some people may have more influence on decisions than others. Some stakeholders need support that improves their access to relevant evidence, but including them without support may leave important inequalities in their ability to contribute to a decision. Inequalities in the development of leadership across various groups may lead to inequalities in influence of the process of decision making about community-based interventions. More generally, even if the process is inclusive, power relationships may vary significantly and affect the way that interventions are valued, designed, and adopted.
The Problem of Double Counting
In a valuation framework with several domains such as those discussed above, the values captured in one domain should not be included again in one of the other domains—that is, they should not be double counted. Consider, for example, a case in which an intervention improves some aspect of a person’s health (such as a reduction in obesity) and this improvement in turn leads the person to return to school and gain more education. It is important that the valuation of the health gain be kept independent of the valuation of the increased education. One way to approach this is for the valuation of the health gain to be done comprehensively, such that the induced effect on education (and its value) is captured in the gains attributed to the improvement in health and captured in the health domain. In this case, the education gain should not be recorded independently and included in the community well-being domain. To do so would be double counting. A second approach would be to do the valuation of the health gain narrowly, so that it is limited to direct improvements in the person’s
health. In this case, the induced education gain would have to be valued separately with the value included in the overall assessment as a gain in community well-being.
The following section explores the issue of assessing the resource use or costs of a community-based prevention intervention.
Community-based prevention is a collaborative effort among three sets of actors: funders, community partners, and participants. Typically all of these actors contribute resources to the implementation of community-based interventions. As a result of an implementation, various effects are experienced by the actors as benefits, harms, savings, or costs (Drummond et al., 2005; Luce et al., 1996; Parasuraman et al., 2006). To ensure that the full range of resources used by the intervention is identified and counted, a broad net should be cast.
The funders of an intervention are those government agencies (international, federal, state, or local), private foundations, corporations, and individual philanthropists and donors that provide financial resources to the community partners to implement interventions. These funds are typically used to pay for salaries, wages, and benefits of staff, the cost of outside professionals and consultants, facilities costs (e.g., overhead, space, and equipment), program materials (e.g., devices and printed materials) and supplies. Funders provide other resources as well, such as professional expertise, consultants, training, and program materials to support community partners.
Community partners, such as local government agencies, nonprofit agencies like the YMCA or United Way, local employers, schools, churches, and physicians, are typically responsible for implementing the intervention. They provide staff, facilities, supplies, equipment, and program-related materials. Some of these resources are paid for by grants from funders. However, community partners themselves may donate additional staff time, facilities, equipment, and materials. The community partners may also use volunteer time. Volunteer time includes the unpaid services of individuals who are not employed by the community partners but who participate in the development, production, and delivery of the intervention. Community partners sometimes also incur intangible costs, such as costs associated with building coalitions and collaborations among community organizations. It is not unusual for community partners to have different organizational cultures, missions, and values. Each community partner may have to change or compromise its brand, reputation, and goals in order to participate in the community-based prevention program with a broader coalition of community partners.
Community-based prevention also requires the time and resources of participants. Participating in an intervention may reduce the time that participants can spend on work or leisure. These time costs need to be considered lest the intervention appear less costly than it really is compared to interventions that rely on participants purchasing goods or services. Some interventions may require participants to make various purchases items, such as of devices, equipment, transportation, and childcare expenses. Also, a participant’s family members may have to use their time and resources to accommodate his or her participating in the intervention. Participation may also have intangible costs. The intervention may require participants to do things that they feel are unpleasant or to stop doing things that they enjoy. Sometimes these opinions about the intervention are temporary and after participants adopt the lifestyle change they prefer the new behaviors to the old ones. However, feelings about the intervention sometimes do not change.
Nonparticipants can also be impacted by the implementation of community-based prevention. The committee prefers to treat these impacts as benefits and harms rather than as savings and costs.
To determine the cost of a community-based prevention program one must first decide from whose perspective the determination is being made. Funders may consider only their program costs, while community partners may want to consider only the costs that they bear. However, a comprehensive perspective considers the costs of all of the resources expended, including those of the participants. This perspective eliminates the possibility of double counting because it looks at the resources used to provide the intervention. This perspective assumes that resources have alternative uses and therefore opportunity costs. If a resource is traded in a market place, then its opportunity costs can be estimated as its market prices, i.e., wages and salaries for personnel, rental rates for facilities, and purchase prices for equipment, services, and material. Sometimes, however, market prices may not represent the true resource costs—for example, if those prices are too high because they include excess profits or too low because of government subsidies.
The opportunity costs of non-market items such as volunteer and participant time can be estimated at an appropriate wage rate (Luce et al., 1996). The choice of a wage is left to the judgment of the analysts. Examples are actual, average, or overtime wage rates of volunteers and participants. In the case of non-working participants, the disabled, and children, using wage data is an imperfect solution, but there are no good alternatives in economic evaluation literature. Some analysts use zero in these cases, implying that there is no alternative use for volunteers’ and participants’ time. This assumption is unreasonable, however, given that volunteers and participants do have other uses for their time, uses that they value. Not
counting volunteer and participant time misleads decision makers on the true costs of an intervention, much in the same way as overlooking the community wellness and community process aspects of community-based prevention misleads decision makers on the true benefits and harms.
As another example, the occupation of a building by a program means that the building cannot be used in another activity—the intervention has eliminated this alternative use. From an economic perspective, the cost of using the building is the value of the services that the building would have generated in this alternative use. Even if the program pays no rent, there is still a cost, and that cost can be approximated by the rents paid for similar buildings.
The valuation of an intervention is based on the changes in outcomes and in resources used that were caused by an intervention, as compared to an alternative. The alternative can be the existing situation (sometimes called the status quo) or another intervention. If an intervention uses less of some resources than the alternative, it yields savings for those items of cost. Sometimes the total costs of an intervention may be less than those of the alternative, yielding an overall saving. The crucial point is that savings become apparent only when two alternatives are compared and that the savings depend on the specific comparison. An intervention that yields savings, i.e., uses fewer resources, compared to one alternative may not yield savings when compared to a different alternative.
For example, in addition to the costs of implementing an intervention, community-based prevention may reduce costs in health care and other social service sectors of the community. For example, a community health workers program that helps residents with chronic health conditions improve their self-care and medication use could result in lower emergency room use and rates of preventable hospitalizations. This lowers the residents’ hospital care costs, thus generating savings for them and their health plans. Another example is community-based prevention targeting at-risk youth who have a dual diagnosis of mental illness and substance abuse. In addition to helping youth maintain their mental health and staying drug free, such a program could reduce costs in the juvenile justice system through lower arrest and incarceration rates. These types of cost offsets should be considered when computing the costs of community-based prevention. The cost offsets should not be confused with the benefits of the programs, which are improvements in health, community well-being, and community process.
Table 3-1 provides a hypothetical example of a total costs computation for an illustrative community-based renovation of a derelict park undertaken to promote physical activity among the town’s citizens. Donated resources are valued according to the closest market rates for time, space, and other goods and services. The total net costs are $10,000.
TABLE 3-1 Hypothetical Community-Based Renovation of a Park: Cost Computation
|Type of Costs||Park Left as Is, No Exercise Facilities||Park Renovated with Exercise Facilities||Difference|
|Donated time and space for meetings to plan renovation||0||$50,000||$50,000|
|Purchased plants, equipment||0||$100,000||$100,000|
|Park renovation and maintenance paid by town (includes state grant)||$10,000||$50,000||$40,000|
|Donated time for park renovation and maintenance||0||$10,000||$10,000|
|Donated time to lead exercise activities||0||$10,000||$10,000|
|Town citizens’ health care costs||$1,000,000||$850,000||–$150,000|
|Town juvenile justice costs||$200,000||$150,000||–$50,000|
|TOTAL COSTS||$1,210,000||1, 220,000||$10,000|
Resource use and benefits occur over a period of time that may extend many years into the future. If that period is greater than 1 year, it is appropriate to discount, in order to capture two realities: people prefer benefits sooner rather than later; and resources are productive—if they are not consumed now but are invested instead, they will produce even more resources in the future. (It is important to note that the concept of a discount rate is net of and different from that of inflation.) In cost–benefit and cost-effectiveness analysis, the practice is to discount both costs and benefits and to discount them at the same rate (Lipscomb et al., 1996; OMB, 2003). When the time horizon is very long, it can lead to difficult questions regarding discounting. This is particularly true of prevention interventions where the costs accrue immediately but the benefits accrue much later. In theory this could lead to an undervaluation of the long-term benefits relative to the short-term costs. In this case it is important to value the long-term benefits adequately rather than attempt to adjust the discount rate (IOM, 2006b; Lipscomb et al., 1996).
Various governmental and nongovernmental groups recommend—or require—specific discount rates, but there is no general agreement among them on what the discount rate should be (Jawad and Ozbay, 2006). For example, the Office of Management and Budget recommends a real (adjusted for inflation) discount rate of 7 percent per year, with 3 percent as an alternative to test the sensitivity of an evaluation’s results to the discount rate (OMB, 2003). The Panel on Cost-Effectiveness in Health and Medicine recommends a real rate of 3 percent for cost-effectiveness analyses and the National Institute of Health and Clinical Excellence in the United Kingdom requires a real rate of 3.5 percent.
There are a variety of sources of data on health, including surveys (e.g., the National Health Interview Survey and the Behavioral Risk Factor Surveillance System), cohort studies (e.g., the Framingham Heart Study), registries, health services data, vital statistics, and data collected by state public health agencies. Unfortunately, there are several limitations on using these data for local, community-based measurement (IOM, 2011b). For example, national surveys are unable to provide the detailed data needed for local estimates without specifically designing local data collection. Registries and health services data provide information only about those who seek and receive health services, cohort studies are resource intensive, and vital statistics are subject to coding errors (IOM, 2011b). To collect information to measure baseline health and changes in health at the local level may require developing and implementing local surveys aimed at the specific health issues of interest.
Identifying measures and sources of information for community well-being and community process elements is even more challenging than collecting such information about health. Table 3-2 lists elements and indicators that could be used in the three domains of interest: health, community well-being, and community process. As stated before, these are examples only. The actual elements and indicators chosen will depend on the community-based prevention intervention being considered.
Applying methods from systems science to community-based prevention efforts can help increase our understanding of the complex interrelationships among factors important to building healthy populations and healthy communities. The following chapter discusses how a framework for valuing resides within a decision-making context, reviews eight frameworks currently used to assess community-based prevention, and discusses the strengths and limitations of each for addressing the special characteristics of community-based prevention.
TABLE 3-2 Domains and Examples of Elements and Indicators for Valuing Community-Based Prevention Interventions
|Value Component||Elements (examples)||Possible Measures (data sources)|
|1. Quality of life||1. Quality-adjusted life year (QALY) or health-adjusted life expectancy (HALE)|
|2. Perceived health||2. Self-reported health status|
|1. Mortality (overall and per cause)||1. Deaths|
|2. Morbidity||2. Rates of conditions or diseases of interest, unhealthy days|
|3. Functional capability||3. Level of activities of daily living, exercise|
|4. Injuries||4. Rates of injuries|
|Mental||Mental—Change in rates|
|1. Cognition||1. Cognitive Abilities Screening Instrument (Adult), Dementia Rating Scale (Adult), Differential Abilities Scale (Children)|
|2. Morbidity||2. Self-reported unhealthy days mental|
|3. Depression Anxiety Stress Perceived well-being||3. Self-reported healthy days mental|
|4. Suicide rates||4. Rates of suicides|
|Community||Built environment||Built environment|
|Well-Being||1. Land use||1. Number and quality of facilities—schools, libraries, housing|
|2. Transportation||2. Number of sidewalks for walking, bike paths, buses, metro/trains, automobiles.|
|3. Building quality (indoor air)||3. Levels of pollutants (e.g., radon, tobacco smoke, chemicals)|
|4. Food systems||4. Grocery stores with healthy choices, farmer’s markets|
|Value Component||Elements (examples)||Possible Measures (data sources)|
|Natural physical environment||Natural physical environment|
|Green space||Parks, preserved open spaces, beauty|
|Social and economic environments||Social and economic environments|
|1. Social support and social networks||1. Number, type, frequency of contact|
|2. Social cohesion||2. Trust, respect|
|3. Education||3. Number and quality of schools|
|a. Resources||a. Books, computers, play equipment, class size|
|b. Achievement||b. 3rd-grade reading level, high school and college graduation rates|
|c. Health literacy||c. Change in level of health literacy|
|4. Employment||4. Employment/unemployment rate|
|a. Safe work places||a. Physical environment and job effort|
|b. Stress||b. Job demand versus control, job effort versus rewards|
|c. Income||c. Wages, food stamp use|
|5. Crime/safety||5. Rates for various crimes|
|6. Access to health care and health insurance||6. Number and type of health care facilities, rate of uninsured|
|Community Process||1. Local leadership development||1. Elected leaders reflect community diversity, number and type of community activists|
|2. Skill building||2. Number and type of peer counselors and community organizers|
|3. Civic engagement or participation||3. Voting rates, volunteering, participation in clubs or other local organizations|
|4. Community mobilization||4. Involvement in civic activities (e.g., town hall meetings)|
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